Noice rate
\r\n\tIn sum, the book presents a reflective analysis of the pedagogical hubs for a changing world, considering the most fundamental areas of the current contingencies in education.
",isbn:"978-1-83968-793-8",printIsbn:"978-1-83968-792-1",pdfIsbn:"978-1-83968-794-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"b01f9136149277b7e4cbc1e52bce78ec",bookSignature:"Dr. María Jose Hernandez-Serrano",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10229.jpg",keywords:"Teacher Digital Competences, Flipped Learning, Online Resources Design, Neuroscientific Literacy (Myths), Emotions and Learning, Multisensory Stimulation, Citizen Skills, Violence Prevention, Moral Development, Universal Design for Learning, Sensitizing on Diversity, Supportive Strategies",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 14th 2020",dateEndSecondStepPublish:"October 12th 2020",dateEndThirdStepPublish:"December 11th 2020",dateEndFourthStepPublish:"March 1st 2021",dateEndFifthStepPublish:"April 30th 2021",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Phil. Maria Jose Hernandez Serrano is a tenured lecturer in the Department of Theory and History of Education at the University of Salamanca, where she currently teaches on Teacher Education. She graduated in Social Education (2000) and Psycho-Pedagogy (2003) at the University of Salamanca. Then, she obtained her European Ph.D. in Education and Training in Virtual Environments by research with the University of Manchester, UK (2009).",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"187893",title:"Dr.",name:"María Jose",middleName:null,surname:"Hernandez-Serrano",slug:"maria-jose-hernandez-serrano",fullName:"María Jose Hernandez-Serrano",profilePictureURL:"https://mts.intechopen.com/storage/users/187893/images/system/187893.jpg",biography:"DPhil Maria Jose Hernandez Serrano is a tenured Lecturer in the Department of Theory and History of Education at the University of Salamanca (Spain), where she currently teaches on Teacher Education. She graduated in Social Education (2000) and Psycho-Pedagogy (2003) at the University of Salamanca. Then, she obtained her European Ph.D. on Education and Training in Virtual Environments by research with the University of Manchester, UK (2009). She obtained a Visiting Scholar Postdoctoral Grant (of the British Academy, UK) at the Oxford Internet Institute of the University of Oxford (2011) and was granted with a postdoctoral research (in 2021) at London Birbeck University.\n \nShe is author of more than 20 research papers, and more than 35 book chapters (H Index 10). She is interested in the study of the educational process and the analysis of cognitive and affective processes in the context of neuroeducation and neurotechnologies, along with the study of social contingencies affecting the educational institutions and requiring new skills for educators.\n\nHer publications are mainly of the educational process mediated by technologies and digital competences. Currently, her new research interests are: the transdisciplinary application of the brain-based research to the educational context and virtual environments, and the neuropedagogical implications of the technologies on the development of the brain in younger students. Also, she is interested in the promotion of creative and critical uses of digital technologies, the emerging uses of social media and transmedia, and the informal learning through technologies.\n\nShe is a member of several research Networks and Scientific Committees in international journals on Educational Technologies and Educommunication, and collaborates as a reviewer in several prestigious journals (see public profile in Publons).\n\nUntil March 2010 she was in charge of the Adult University of Salamanca, by coordinating teaching activities of more than a thousand adult students. She currently is, since 2014, the Secretary of the Department of Theory and History of Education. Since 2015 she collaborates with the Council Educational Program by training teachers and families in the translation of advances from educational neuroscience.",institutionString:"University of Salamanca",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Salamanca",institutionURL:null,country:{name:"Spain"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"23",title:"Social Sciences",slug:"social-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"301331",firstName:"Mia",lastName:"Vulovic",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/301331/images/8498_n.jpg",email:"mia.v@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"6942",title:"Global Social Work",subtitle:"Cutting Edge Issues and Critical Reflections",isOpenForSubmission:!1,hash:"222c8a66edfc7a4a6537af7565bcb3de",slug:"global-social-work-cutting-edge-issues-and-critical-reflections",bookSignature:"Bala Raju Nikku",coverURL:"https://cdn.intechopen.com/books/images_new/6942.jpg",editedByType:"Edited by",editors:[{id:"263576",title:"Dr.",name:"Bala",surname:"Nikku",slug:"bala-nikku",fullName:"Bala Nikku"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"17225",title:"Silicon Photo Multipliers Detectors Operating in Geiger Regime: an Unlimited Device for Future Applications",doi:"10.5772/21521",slug:"silicon-photo-multipliers-detectors-operating-in-geiger-regime-an-unlimited-device-for-future-applic",body:'Photon detectors are indispensable in many areas of fundamental physics research, particularly in the emerging fields of particle astrophysics, nuclear and particle physics, as well as in medical equipment (i.e. PET), in physical check-ups and diagnosis as in-vitro inspection (Radioimmunoassay and Enzyme immunoassay as luminescent, fluorescent, Chemiluminescent Immunoassay), biomedicine, industrial application, in environmental measurement equipment (like dust counters used to detect dust contained in air or liquids, and radiation survey monitors used in nuclear power plants). In astroparticle physics, photons detectors play a crucial role in the detection of fundamental physical processes:in particular, most of the future experiments which aimed at the study of very high-energy (GRB, AGN, SNR) or extremely rare phenomena (dark matter, proton decay, zero neutrinos-double beta decay, neutrinos from astrophysical sources)[3-7] are based on photons detection. The needs of very high sensitivity pushthe designing of detectors whose sizes should greatly exceed the dimensions of the largest current installations. In the construction of such large-scale detectors no other option remains as using natural media - atmosphere, deep packs of ice, water and liquefied gases at cryogenic temperatures [8-13]. In these (transparent) media, charged particles, originating from interaction or decays of primary particles, emit Cherenkov radiation or fluorescence light, detected by photosensitive devices. Hence, for the improvement in the quality of the experimental results a particular attention should be paid to the improvement of photon detectors performances. In underwater neutrino telescopes (but this is applicable also to other experiments) Cherenkov light, emitted by charged leptons stemming from neutrino interaction, hits photomultipliers (PMT) situated at different distances from the track. This implies, that the response of PMTs should be linear in a very wide range from high illumination to the single photon. Another area of interest is the direct searches of Dark Matter in form of WIMPs: in these experiments it is exploited the scintillation properties of double-phase (liquid-gas) detectors, where primary and secondary scintillation light signals are detected by high-efficiency PMTs, immersed in cryogenic liquids or low temperature gases (89 K for the liquid argon)[14-17]. The next generation of experiments requires further improvement in linearity, gain, and sensitivity (quantum efficiency and single photon counting capability) of PMTs.
To date, the photon detection capabilities of the Vacuum Photomultiplier Tube (VPMT) seem to be unrivalled. Nevertheless standard photomultiplier tubes suffer of the following drawbacks:
fluctuations in the first dynode gain make single photon counting difficult;
the linearity is strongly related to the gain and decreases as the latter increases;
the transit time spreads over large fluctuations;
the mechanical structure is complex and expensive;
they are sensitive to the magnetic fields;
the need of voltage dividers increases failure risks, complexity in the experiments designs and power consumption.
To overcome these limitations, alternatives to VPMT, mainly concentrated on solid-state detectors, are under study. After about one century of standard technology (photocathode and dynode electron multiplication chain), the recent strong developments of modern silicon devices have the potential to boost this technology towards a new generation of photodetectors, based on an innovative and simple inverse p–n junction, PN or PIN photodiodes, avalanche photodiodes—APD and avalanche photodiodes in linear Geiger-mode (GM-APD, SiPM from now on) [18-25]. These solid-state devices present important advantages over the vacuum ones, namely higher quantum efficiency, lower operation voltages, insensitivity to the magnetic fields, robustness and compactness. The step by-step evolution of solid-state photon detectors was mainly determined by their internal gain: a PIN has no gain, an APD can reach a gain of few hundreds, while the GM-APD 105–106, comparable with that of the vacuum photodetectors; this would allow the GM-APD to achieve single-photon sensitivity and to be used in low-level light applications. This silicon device has become commercially available in the recent years.
We will first discuss the detection of light by silicon devices and then move on to the description of the SiPM and its properties and possible applications.
The basis for detection of light in silicon photodiodes is the p-n junction described inFigure 1, where a depleted region is formed due to carriers diffusion [26].
A junction is formed by diffusing a donor impurity to a shallow depth into silicon which is originally high purity p-type, sometimes called π-type silicon. Thus the layer at the surface is highly doped n-type, often referred as n+ type with an high concentration of electrons, and the material inside is p type with a relatively low concentration of holes. A schematic view of the structure is shown in Figure 2. The resulting structure, referred to as an n+-p junction, presents a configuration n+pπp+, where π is a very slight p-type doping. In an analogous fashion a diffused p+n junction detector can be constructed. Since the density of acceptors in the p-type region is much lower relatively to that of donors in the n+-type region, the space charge region extends much further into the p region than into the n+ region. This space-charge region, characterized primarily by acceptor centres in the p-region and filled by donor electrons from the n+ region, is a charge depleted region of very high resistivity. If electron-hole pairs are produced in this region, the electric field will drive electrons toward the n and holes toward the p side producing a current through the device.
p-n junction with reversed bias. Energy band diagram is also shown.
Pairs can be produced by light if the energy of the photon is sufficient to bring the electron over the energy band gap.
Schematic view of a p+n junction.
The photon absorption process for photo generation, that is the creation of electron-hole pairs, requires the photon Energy to be at least equal to the band gap energy Egap of the semiconductor material to excite an electron from the valence to the conduction band, namely hν>Egap, corresponding to hc/λ>Egap:
The upper cut-off wavelength (or the threshold wavelength) λth is therefore determined by the bandgap energy Egap:
In some semiconductors, such as Si and Ge, the photon absorption process for photon energies near Egap requires the absorption and emission of lattice vibrations (vibrations of the Si atoms), namely phonons. The absorption process is said, in these cases, to be indirect as it depends on lattice vibrations which in turn depends on the temperature [27]. Since the interaction of a photon with a valence electron needs a third body, a lattice vibration, the probability of photon absorption is not as high as in a direct transition. As a consequence, the threshold wavelength is not as sharp as for direct bandgap semiconductors. During the absorption process, a phonon may be absorbed or emitted. If ξ is the frequency of the lattice vibrations, then the phonon energy is hξ and the photon energy should be hν> Egap± hξ.Actually, since hξ is small (<0.1 eV), the energy needed for absorption is very close to Egap.
In silicon, for which Egap=1.12 eV, the threshold wavelength as given by the Equation 1 is ≈1100 nm.
Incident photons with wavelengths shorter than λth become absorbed as they travel in the semiconductor and the light intensity, which is proportional to the number of photons, decays exponentially with distance into the semiconductor. The absorption coefficientαdetermines how far into a material the light of a particular wavelength can penetrate before absorption. In a material with a low absorption coefficient, light is only poorly absorbed, and if the material is thin enough, it will appear transparent to that wavelength.
The absorption coefficient, α, is related to the extinction coefficient, k, by the following formula:
where λ is the wavelength. Thus, defining the complex index of refraction as ñ= n – ik, the imaginary component k is related to the absorption, whereas the real component n= c/vphase is related to reflectivity. In Figure 3 the real and imaginary part of the refractive index of silicon is shown [28].
Real and (negative) imaginary components of the refractive index for silicon at 300 K.
As a consequence of the cut-off wavelength, direct bandgap semiconductor materials (as GaAs, InP) have a sharp edge in their absorption coefficient. Actually, even for those photons which have an energy above the band gap, the absorption coefficient is not constant, but still depends strongly on the wavelength. The probability of absorbing a photon depends on the probability that a photon and an electron interact in such a way as to move from one energy band to another. For photons which have an energy very close to that of the band gap, the absorption is relatively low since only those electrons directly at the valence band edge can interact with the photon to cause absorption. As the photon energy increases a larger number of electrons can interact with the photon, resulting in a higher absorption probability.
In indirect bandgap semiconductor materials, like silicon, there is a long tail in absorption out to long wavelengths. Figure 4 [27] shows the absorption coefficient α as a function of wavelength λ for various semiconductors: it is clear the different behaviour of α with the wavelength in the case of direct band gap semiconductors (e.g. GaAs, InP) with respect to indirect band gap semiconductors (e.g. Si, Ge). In Figure 5 [29], instead, the absorption length or penetration depth, defined as 1/α, as a function of wavelength for Si is shown.
Absorption coefficient α as a function of wavelength λ for various semiconductors.
To detect light by a photodiode, it first has to enter through the surface and then absorbed in the active volume of the device. Due to the high value of real part of the refractive index of silicon, which is above 3.5 for wavelengths below 1100 nm at 300 K as shown in Figure 3, an antireflective coating is needed to reduce the strong Fresnel reflection of light from the surface of the device.
Absorption length 1/α as a function of wavelength λ for Silicon.
Actually, not all the incident photons are absorbed to create pairs that can be collected and give rise to a photocurrent. The efficiency of the conversion process is measured by the quantum efficiency QEof the detector, defined as
which depends on the wavelength. In the evaluation of QE, the number of electrons collected per seconds is given by Iph/e, where Iph is the measured photocurrent, whereas the number of photons arriving per second is Po/hν, with Po the incident optical power.
Then the QE can be also defined as [27]
A typical photodiode QE is shown in Figure 6 [30].
If the semiconductor length is comparable with the penetration depth not all the photons will be absorbed, resulting in a low QE.
Therefore, to obtain an high quantum efficiency, the thickness of the depleted layer has to be larger than the absorption length. The absorption length shows strong variations from about 10 nm, for near UV light, to more than 1 mm, in the infrared region. To enhance the sensitivity in the range of blue light, the active region needs to be close to the surface and for the detection of longer wavelengths it has to be thick compared to the absorption length.
Typical photodiode QE as a function of wavelength.
The thickness of the layer can be increased by applying a reverse bias to the diode junction. To obtain a thick depletion layer with low reverse bias, a PIN photodiode is used with an intrinsic layer between the p and n faces of the diode. The photodiode does not present any internal amplification of the signal so the number of charges generated itis equal to the number of detected photons. It can be used for applications in which more than about 10,000 photons are simultaneously detected by the device. Taking into account that the capacitance per unit area C/A, expressed in picofarad per square centimetre, is C/A=1,061/x0 where x0 is the depletion layer thickness expressed in cm,millivolt ranged signal is expected using typical parameters [31].A typical application in high energy physics for such a device is the calorimetry, in which a large amount of photons has to be detected.
To detect weaker signals, instead, internal amplification is required. This can be obtained, as in gas based devices, by increasing the applied voltage. In fact, if the electric field in the silicon is high enough, primary carriers can produce new pairs by impact ionization. These generated electron-hole pairs are further accelerated by the electric field to a sufficiently high kinetic energy to cause new impact ionization, releasing more electron-hole pairs, which leads to an avalanche of impact ionization processes. Thus, with a single photon absorption, one can generate a large number of electron-hole pairs, all of which contribute to the observed photocurrent, leading an internal gain mechanism. Each absorbed photon creates in average a finite number M of electron–hole pairs exploiting the impact ionization process. The multiplication of carriers in the avalanche region depends on the probability of impact ionization which strongly depends on the reverse bias Vbias.
This mode of operation is called linear because the number of the collected carriers is proportional (by a factor M) to the number of absorbed photons.A photodiode with such an amplification region is called the avalanche photodiode (APD). The ionization rate is higher for electrons than for holes, so the amplification process for electrons starts at lower fields and the avalanche grows in the direction of the electrons movement. With the increase in the electric field also holes start to ionize. When the ionization probability is high enough, the amplification can no longer be controlled. This limits the amplification factor in APDs to about ~100. Due to the low amplification, these devices are still not appropriate for detection of signals of a few photonsonly. However, signals coming from about 100 photons can be detected.
To obtain the single photon sensitivity in a silicon device, one needs to operate the APD in the Geiger mode [32]. A diode working in a region near the breakdown voltage can be operated in two different ways depending on whether the bias voltage is below or above the breakdown point. In the first case the device is called avalanche photodiode (APD) described above. In the second case the device is referred to as Geiger-mode APD (GM-APD). In this bias condition, the electric field is so high that a single carrier injected into the depletion region can trigger a self-sustaining avalanche. The carrier initiating the discharge can be either thermally generated (noise source of the device) or photo-generated (useful signal).
In Figure 7the schematic view of the gain as a function of reverse bias is shown.
Schematic view of gain as a function of Vbias.
The main limitation of a single diode working in GM is that the output signal is the same regardless of the number of interacting photons. In order to overcome this limitation, the diode can be segmented in tiny micro-cells (each working in GM) connected in parallel to a single output. Each element, when activated by a photon, gives the same current response, so that the output signal is proportional to the number of cells hit by a photon and the output signal is the sum of the Geiger mode signals of microcells. The dynamic range is limited by the number of elements composing the device, and the probability that two or more photons hit the same micro-cell depends on the size of the micro-cell itself. This structure is called Silicon PhotoMultiplier (SiPM) [1].
All the microcells are identical, independent and operate in single photon counting mode. A quenching mechanism is implemented thanks to a specially resistive material technology. Together with the common electrode structure all this gives the possibility to act as a proportional detector for measurements of low intensity photons flux.
The typical density of microcells that can be produced is 1000–5000 per mm2 and the total number of microcells on our tested photodetectors with sensitive area of 1mm2 is of the order of 2000. This defines the dynamic range of the device. The noise conditions of the SiPM is defined by dark count rate, as in Geiger mode a single thermally generated electron or hole can initiate an avalanche, leading to an electrical pulse that is indistinguishable from the one of a single photon. This gives the main limitation of increasing the sensitive area of SiPM operated in single photon counting mode, but it is not so significant for low photon flux measurement when Nphot> 3.
Structure of the multi cell matrix of a SiPM.
The structure of the silicon photomultiplier is a combination of large number of avalanche microcells on a single substrate and with common quenching mechanism (resistive layer) and common electrodes.
The schematic structure of the avalanche microcell of a SiPM is shown in Figure 9 and presents a configuration n+-p-π-p+, where π represents very slight p-type doping.
Schematic structure of avalanche microcell of SiPM.
The n+ side is thin and is the onewhich receives light through a window. A thickness of about 1µm of depletion region between the thin n+ (thickness = 0.1–1.5 µm) and p layers is created thanks to the reverse electric field. There are three p-type layers of different doping levels next to the n+ layer to suitably modify the field distribution across the structure. The first is a thin p-type layer, the second is a thick lightly p-type doped (almost intrinsic) π-layer of ≈300 µm, and the third is a heavily doped p+ layer ≈ 3µm thick. On the surface of the avalanche microstructure a thin metal layer is placed (≈ 0.01 µm) with an antireflection coating. Above the n+ region, a resistive SiO2 layer (thickness ≈0.15 µm, ρ ≈ 105-107Ωcm) limits the Geiger breakdown propagation by a local reduction of the electric field.
The electric field is at a maximum at the n+p junction, then decreases slowly through the p-layer. The field vanishes at the end of the narrow depletion layer in the p+ side, as shown in Figure 10[33].
Configuration of the electric field. The high-field region (E≈5×105 V/cm) is built up in the highly doped n+p.
The absorption of photons ofλ≈400nmtakes place mainly in the π-layer. The nearly uniform field here separates the electron–hole pairs and drifts them at velocities near saturation towards the n+ and p+ sides, respectively. When the drifting electrons reach the p-layer it may be accelerated by the high fields to sufficiently large kinetic energies to further cause impact ionization and release more electron-hole pairs which leads to an avalanche of impact ionization processes. Thus, from a single electron entering the p-layer, one can generate a large number of electron-hole pairs all of which contribute to the observed photocurrent. In this mode, any electron event in the sensitive area will produce a very large current flow with amplification gain of up to 106.
As mentioned in the previous paragraph the SiPM is a matrix of GM-APDs connected in parallel. A schematic representation of the device is shown in Figure 11. The connection between the cells is made on one side by thelow-resistivity substrate and on the other side by a metal layer.The diodes (labelled as D) are asymmetric p–n junctions. Each GM-APD has in series a quenching resistor (RQ) which is needed to stop the avalanche current and, then, to restore the initial bias condition enabling the detection of a new incoming photon. A reverse bias voltage (Vbias) is applied to each junction through the common substrate electrode to deplete the n+–p junctions.
Equivalent electric scheme of the SiPM
The breakdown voltage (Vbreak) and the RQ values are determined thanks to the reverse and forward current–voltage (I–V) characteristics curves.
The MPPCs used for this workhave an active surface of 1 X 1mm2, divided into 1,600 pixels of 25μm x 25μm (Figure 12, Figure 13 and Figure 14), and of 3 X 3 mm2, divided in 14,400 pixels of 25μm x 25μm (Figure 15 and Figure 16 : from Hamamatsu data sheet) [34].
Aspect and external dimensions of the MPPC 1 X 1 mm2 under characterization.
Operating parameters of the MPPC 1 X 1 mm2 as delivered by the supplier.
a) A Photograph of the MPPC S10362-11-025U by Hamamatsu. b) Structure of a MPPC pixel.
Aspect and external dimensions of the MPPC 3 X 3 mm2 under characterization.
Operating parameters of the MPPC 3 X 3 mm2 as delivered by the supplier.
A Vbreak of 70.1 V has been obtained for S10362-11-025U 1 X 1 mm2 SiPM, thus demonstrating a good uniformity of the Vbreak for different SiPM’s. The value of the quenching resistor extracted from the forward characteristics is of ~145 Ω, giving for a single micro-cell a value of 230 kΩ (see Figure 17). In fact the global resistance measured is related as:
where Nmicro-cell = 1,600 for theS10362-11-025U model of 1 X 1mm2SiPM and Nmicro-cell = 14,400 for theS10931-025P model of 3X 3 mm2SiPM.
Forward characteristics of S10362-11-025U SIPM (1 x 1 mm2).
A similar measurement on the 3x3 mm2 SiPM led to a global resistance of 26 Ω, giving a single pixel quenching resistance of ~ 380 kΩ.
In the Figure 18, the reverse biased portion of the I-V curve is shown, for the 3x3 mm2 SiPM. This side of the curve is used to extrapolate from the fit, the most convenient bias voltage to apply to the device.
A circuit model, which emulates the evolution of the signal of a GM-APD was developed in the 1960s to describe the behaviour of micro-plasma instability in silicon [35, 36]. According to this model, the pre-breakdown state can be represented as a capacitance (junction capacitance, CD) in series with the quenching resistor.
Reverse side of the Current VS Voltage curve, this time for the 3x3 mm2 SiPM.
In steady state, the capacitance is charged at Vbias>Vbreak. When a carrier traverses the high-field region, (switch closed in Figure 11/b) there is a certain probability, to initiate an avalanche discharge. If this happens, the new state of the system can be modelled adding to the circuit a voltage source Vbreak with a series resistor RS in parallel to the diode capacitance. RS (≈ 1kΩ) includes both the resistance of the neutral regions inside the silicon as well as the space charge resistance. CD, originally charged at Vbias>Vbreak, discharges through the series resistance down to the breakdown voltage with a time constant τD given by the product RSCD. The discharge current of the avalanche process can take some hundreds of ps. As the voltage on CD decreases, the current flowing through the quenching resistance tends to the asymptotic value of (Vbias-Vbreak)/(RQ+RS). In this final phase, if RQ is high enough (some hundreds of kΩ), the diode current is so low that a statistical fluctuation brings the instantaneous number of carriers flowing through the high-field region to zero, quenching the avalanche.
When the avalanche process is terminated, the switch is again open and the circuit is in its initial configuration with the capacitance charged at Vbreak. At this point it starts recharging to the bias voltage with a time constant τR=CDRQ and the device becomes ready to detect the arrival of a new photon (Figure 19). The number of carriers created during an avalanche discharge is given by ncarriers=(Vbias–Vbreak)CD/e, where e is the electron charge.
The time evolution of the current into a cell, when a discharge occurs.
Than the gain of the SiPM (G) is determined by the charge (Q) that can be released from a micro-cell after the breakdown [19]:
where ΔV = (Vbias-Vbreak) is the overvoltage and ΔV/ RQ = Imax.
The time integration of the micro-cell dark pulse allowed the measurement of the gain.
Each diode composing the SiPM reacts independently in the above-described way. Thus, if n cells are activated at the same time, the charge measured at the SiPM output is n times the charge developed by a single GM-APD, giving information on the light intensity.
The basic performances of the MPPC’s are measured with light from a pulsed laser. All results shown in this section are for a Hamamatsu MPPC of 1x1mm2 and3x3mm2.
The general scheme of the experimental setup is shown in the Figure 20. The board accommodating the MPPC is placed inside of a dark chamber; the laser, pulsed at a typical frequency of 100 kHz, is connected via optical fiber with a custom connector as coupling device. Two beam splitters are installed along the fiber way in order to reduce the beam intensity and control, for very low intensities, the number of photons: the 1% outputs are used on both splitters, leading to a 10-4 reduction factor.
The optical power of the installation has been measured using a Newport mod. 815 power meter having a sensitivity of 1 nW obtaining a response of about 50 to 2350 photons per pulse.
Scheme of the bench test for the MPPC using laser source and beam splitters.
Figure 21shows the electric scheme of the board used to amplify the MPPC signals. The detector receives power from a polarization resistor RP~10 kΩ and its output is connected to the input of a current-to-voltage amplifier. The amplifier is a LMH6624 by National Semiconductor used in inverting configuration and powered by ±5 V. In this configuration the output of the operational amplifier is directly proportional to the current on the input flowing through the reaction resistance Rf, determining the amplification trans resistance gain and so giving:
Schematic diagram of the amplification board designed which accommodates the MPPC.
Figure 22 shows the raw signal and the output charge spectrum from an MPPC takenwith an oscilloscope. The MPPC is illuminated by pulsed lightfrom the laser at low intensity and the oscilloscope is triggeredin synch with the laser. The responses for multipletriggers are overlaid in the figure. The charge correspondingto different numbers of fired pixels shows well separated peaks.
This indicates that the gain of each micropixel is uniform, demonstrating the excellent photoncounting capability of the MPPC. For bias voltage under 69.8 V on the 1x1 mm2device (and 69.4 V on the 3x3 mm2device) we did not succeeded in observing any signal, since their amplitude is covered by electronic noise. At 69.8 V (69.4 V for the 3x3 mm2device) we observe clear signals of 1 photon equivalent (p.e.) of an amplitude of the order of 2 mV (2.7 mV for the 3x3 mm2device). As the bias voltage increases, higher signalsare obtained, so 1 p.e. and signals for 2 or 3 p.e. begin to be always observable. The latter are due to an increased probability of thermally generation and crosstalk events. Around 71.5 V signals for 2 or 3 p.e. become very frequent and it is clear that, in these conditions, it becomes difficult to distinguish between any actual signal and dark count.
Some samples of signal as observed at the oscilloscope at different operating voltages are shown in the Figure 23.
We remark that:
Rise time and fall time of signals are basically independent from the applied voltage. Rise time is around 1-2 ns; fall time is 2-3 ns and is sensitive to the transition capacitance of the pixels and the quenching resistor, since:
Optimal working voltage for this MPPC are around 70.5-71.2 V, values that are compatible with the ones suggested by the manufacturer.
Rise and fall time have been measured at 70.8 V reverse bias, by accumulating 10,000 values and obtaining, for the 1x1 mm2:
and 72.1 V reverse bias for the 3x3 mm2,obtaining:
A collection of pulse signals from MPPC as observed at the oscilloscope for the 3x3 mm2 MPPC.
A collection of pulse signals from MPPC as observed at the oscilloscope for the 1x1 mm2 MPPC.
From the number of ADC counts between awell-separated pedestal and the peak corresponding to a singlefired pixel, we derive the charge correspondingto a it, Q. The gain is defined as Q dividedby the charge of an electron:
Figure 25shows the gain measured as a function of the applied voltage for the 1x1 mm2 MPPC. The measurementis performed inside a temperature-controlled chamber and data at 22.5º C are shown. The measured gain depends linearly on the applied voltage as expected.
As a second method, the gain can be calculated by measuring the number of channels between two neighboring peaks. To calculate the gain with the second method we put the MPPC under very low illuminations conditions, allowing to clearly distinguish between peaks of 1, 2, 3 and 4 p.e..By changing the bias voltage between 71.5 and 74.1 V in 0.2V steps, we measured the difference in the amplitudes of signals of 2 – 1 p.e., 3 – 2p.e. and 4 – 3 p.e..Figure 22shows the measurements obtained for 1x1 mm2 MPPC whereas histograms on the left in Figure 24 show the results obtained with a 3x3 mm2 MPPC. Alternatively, the gain can also be evaluated by measuring the charge of the signal corresponding to the initial number of photoelectrons. The method is shown in the right histogram in theFigure 24, while inFigure 26 the two methods are compared.
Pulses from MPPC and gain measurement for the 3x3 mm2 MPPC (binning of left histograms is of 5 mV, and,of right one is 50.0 pVs. Signal shown with 5 mV/div-20ms/div).
Measured gain as a function of the applied voltage for the 1x1 mm2 MPPC.
Comparison between methods for gain evaluation for the 1x1 mm2 MPPC (Left) and the for the 3x3 mm2 MPPC (Right).
From the gain obtained it is possible to get an estimation of the junction capacitance CD. In the case of the 3x3 mm2 MPPC (1x1 mm2 MPPC), from the linear fit of Figure 26, the slope of the fitting line is
by multiplying this value for the electron charge we get:
From this we can get an estimation of the value of the quenching resistor:
Moreover, since
it is also possible to estimate the breakdown voltage of the device, by extrapolating from the gain line the voltage value corresponding to G=0. In the 3x3 mm2 MPPC we obtain
The Geiger-mode micro-cell detection of an event does not give intensity information. The output pulse produced by the detection of a photon is indistinguishable from that produced by the detection of many simultaneously absorbed ones. That means a single thermally generated electron or hole can initiate an avalanche. This gives the main limitation of increasing the sensitive area of Si avalanche structures operated in single photon-counting mode at room temperature. Reduction of the dark counting rate in Si avalanche can be obtained by limiting both the sensitive area1x1 - 3x3 mm2) and the thickness of depleted region.
Other improvements can be achieved by minimizing the number of generation-recombination centres, the impurities and crystal defect. In addition, the detector operation at low temperature and a good quality in the fabrication process further improve the single photon detection capability. The main effect to be taken into account is the production of after-pulses by charges from the avalanche process that are temporarily trapped, generating a new avalanche after their release (seeFigure 27).
After-pulses with short delay contribute little because the cells are not fully recharged, but have an effect on the recovery time. Operation at low temperatures elongate the delayed release by a factor of 3 when the temperature is reduced by 25º C [21].
Another effect to be taken into account is the optical cross talk due to photon travelling to a neighbouring cell which trigger an avalanche.
In fact, in an avalanche breakdown, there are 1–3 photons emitted in average per carriers, with a photon energy higher than the band gap of silicon. These photons may travel to another pixel of the matrix and initiate an avalanche breakdown there. A dedicated design, with grooves between the cells acting as an optical isolation, reduces the cross talk till two order of magnitude. Operation at a relatively low gain is advantageous in this case.
After pulse event as obtainable at the oscilloscope.
The origin of the cross-talk is presumed to be related tooptical photons emitted during avalanche [37] which enter neighboring micro pixels and trigger another Geiger discharge. The probability of causing cross-talk is estimated from the fraction of events with more than one p.e. to that with one p.e. in randomly triggered events without external light. We assume that the events with more than 1 p.e. are caused by the cross-talk from the original Geiger discharge in a single pixel. At low bias voltage, a dark count of 2 p.e. should be related to crosstalk phenomena only because of the low probability that both electrons generate a Geiger discharge.
In order to obtain a complete characterization of the device we have measured the dark counts rate as a function of the supply voltage. For every voltage applied we have performed three measures of rate using three different trigger thresholds: 0.5 p.e., 1.5 p.e. and 2.5 p.e. at 23º C.Results for these measurements are shown inFigure 28. The noise rate decreases as the temperature becomes lower. The temperaturecoefficient of noise rate at 0.5 p.e. threshold is −5 %/ºC. There is a factor 2 reduction of the dark count every 8º C [21, 38]. Theseobservations imply that the dominant component of the noiseis due to the discharge of single pixels induced by thermally generated carriers.
Dark counts rate generated by the MPPC as a function of the supply voltage.
The measurement of the event rate with 0.5 p.e. trigger gives an estimation of the global noise rate, including the thermal dark counts and the crosstalk events. At 1.5 p.e. of trigger and for low bias voltage, an estimation of the cross talk events only should be possible, since at room temperature we have a low probability that two pixels generate, at the same time, a couple just for thermal excitation.
From the Figure 28 we can remark that the high single rate of the SiPM (if we adopt a low photoelectron threshold) can be easily overcome in those experimental conditions where the time parameter takes a main role. A double coincidence or a gate signal of the right duration can reduce the single rate to acceptable or negligible levels. We have to remind, at this stage of the discussion, that the threshold is of the level of a single or few photoelectrons, a level which would be impossible for classical PMT.
In the following table it is shown the noise rate as a function of the threshold and duration of the coincidence:
gate duration | Treshold 0.5 p.e | Treshold 1,5 p.e | Treshold 2,5 p.e |
10 ns | 23 Hz | 1 Hz | ~10-10 Hz |
20 ns | 46 Hz | 0.5 Hz | ~10-10 Hz |
50 ns | 115 Hz | 0.2 Hz | ~10-10 Hz |
Noice rate
These rates are perfectly compatible with the random coincidences rate obtained from the relation N1xN2x2T. Under these conditions we can see that the dark noise is negligible with respect to the collected events. Moreover, even without artifices like the indicated coincidence technique, with a threshold greater than 3 p.e., the single rate becomes acceptable.
The efficiency of an SiPM is the product of several factors and depends on the QE, the geometrical efficiency (εgeom), the Geiger-triggering probability:
The geometrical efficiency εgeom represents the fraction of active area in a micropixel.
Actually, only part of the area, occupied by the micro-cell, is active and the rest is used for the quenching resistor and other connections (seeFigure 29).εgeom is defined as the ratio of sensitive to insensitive area, namely the fill factor, and thus depends on the design and layout of the pixels only.It is about 0.3 for a 25 μm pitch sample(as the considered ones) and about 0.7 for a 100 μm pitch sample [34, 39].
The quantum efficiency of the sensitive area isdefined by the intrinsic QE of Si(typical QE = 80–90%).The thickness oflayers on top of the structure and ofthe depletion area can be optimized forspecific applications.Efficient absorption of photons requires an increase of the thickness in order tomaximize photon conversion. On the other side, it is necessary tominimize the depletion area region inorder to reduce the dark count rate. Since the QE of the sensitive area is defined by absorption coefficient α in Si, taking into account the probability of reflection of photons on the device surface, photon detection efficiency can be written as:
where R is the reflection coefficient and x is the position in which the electron-hole pair is generated.The fraction of the light transmitted to the sensitivevolume is conditioned by the topmost layers and theresistive one. For short wavelengthin the UV region, the situation is more critical. To improve the sensitivity also in this region it is necessary to optimize the top contact technologie, depletion thickness and n-p configurations.The triggering probability Ptrigger depends on the position where the primary electron–hole pairs are generated and the over-voltage (ΔV).To enhance the triggering probability, we have to take into account that electrons have in silicon a better chance to trigger a breakdown with respect to holes, by about a factor of 2, and their difference decreases with increasing fields, as shown in Figure 30 [40].If one electron-hole pair is born at position x, then the probability that neither the electron nor the hole causes an avalanche is given by (1 - Pe ). (1- Ph) where the function Pe is the probability that an electron starting at position x in the depletion layer will trigger an avalanche and the function Ph is the analogous for holes.
Matrix of G-APD and evidence of the so called "Fill Factor".
Consequently, the probability Ptrigger that at x either the electron or the hole initiates an avalanche is given by
Thus, we can write:
In case of a photo-generation event, two carriers are created travelling in opposite directions at the absorption point. Thecontribution to the PDE can be calculated as a function of the generation position by solving two differential equations involving the carrier ionization rates. If conversion happens in the p depleted region, x is equal to the depleted region thickness (see Figure 2).
In a conventional structuren+-p-π-p+, when a pair is generated in the upper side of the high-field region (n+), the electron is directly collected at the n+ terminal (see Figure 31); thus, it does not contribute to the triggering. The hole is forced to pass the whole high-field triggering the avalanche. On the contrary, when the pair is generated in the bottom side (p), the situation is symmetrical and only electrons contribute to the triggering probability.So the triggering probability depends on the position where the primary electron–hole pair is generated and on the overvoltage. A high gain operation is favoured.
Avalanche region with width W and the position X which runs from 0 to W starting at the n-edge.
Thus, to maximize the triggering probability, the photon conversion should happen in the p side of the junction, in order to allow the electrons to cross the high-field zone and trigger the avalanche.
As an example for λ>450nm (green and red light) photons convert deep in p-silicon beyond the high-field region. Electrons drift back into the high-field region, triggering avalanches. Hence in thiswavelength range the efficiency is very high. For λ<400 nm photons are absorbed in the first microns of the n+ layer. Here the holes drift into the high-field region and trigger the avalanche. Under these conditions the QE is reduced in this wavelengths range. As a reference for λ = 400 nm (corresponding to photon energy = 3.10 eV) the absorption coefficient is 1.2x105cm-1 and the thickness required to absorb more than 99% of the light is ~1μm (see Figure 5,where the absorption length as a function of the wavelength is shown) [41-43]. Several solutions exist for increasing the sensitivity at short wavelengths:
an higher reverse bias voltage would increase the avalanche probability for holes, though the voltage has to be limited due to the increase of cross talk and dark rate
entrance windows has to be made as thin as possible [44, 45]
the n+ layer has to be as shallow as possible (for optimum QE); with standard equipment for detector fabrication, layers with a junction depth of 100 nm can be obtained. The high-field region should be as thin as possible in order to convert photos beyond it.
Triggering probability can be improved by maintaining the same doping profile configuration but reversing the types, i.e. having a p+-n-n--n+ structure, and making the junction deeper (> 0.4 µm). Hence the roles of electrons and holes are reversed, resulting in avalanches triggered by electrons at short wavelengths (Figure 31).
In conclusion, to maximize the triggering probability: (i) the photogeneration should happen in the p side of the junction in order for the electrons to pass the whole high field zone, and (ii) the bias voltage (Vbias) should be as high as possible.
A better scenario is obtained when electron bombardment is considered. In Figure 32a simulation for the range of electrons penetrating into the silicon is shown. The simulation has been computed by using Geant4 Simulation Toolkit [46, 47]. If ionizing particles, like electrons, are detected in a n+pp+ junction, the range - i.e. the energy - will determine where the carriers are generated. If the end of range is in the p region beyond the high-field area, both carriers created along the track will be travelling in the opposite directions, contributing to the avalanche-triggering probability. Electrons detection efficiency can be evaluated from the following:
where Pe and Phare the electron and hole breakdown initiation probabilities and Rback is the backscattering probability. When a pair is generated before the high field region, the electron is collected at the n+ terminal; thus, it does not contribute to the trigger. The hole is forced to pass through the full high-field region and so its triggering probability is given by Ph. For pairs generated beyond the high field region, the situation is reversedand only electrons contribute to the triggering probability Pe. These probabilities depend on the impact ionization rates of holes and electrons, respectively. As pointed out above, the electron has an ionization rate of about a factor 2 higher than the hole.
The reduction of the thickness in n+layer allows lowering the detectable electron energy. As an alternative, maintaining the same doping profile configuration but reversing the types, i.e. using a p+nn+ structure and making the junction deeper, can improve the triggering probability. In this case the electron range is completely contained inside the p+ region.
SiPMs produce a standard signal when any of the cells goes to breakdown. When many cells are fired at the same time, the output is the sum of the standard pulses. Single photonsproduce a signal of several millivolts on a 50 Ω load. For a matrix of Nmicrocells microcells, the dynamic range is limited by the condition that (Nph×PDE/Nmicrocells)<1, where Nph is the number of photons, and PDE the Photon Detection Efficiency of the SiPM.
Photon and electron avalanche induced in the two silicon configurations (p+nn+ and n+pp+).
In other words,the average number of photons per cell should be less than 1. If the number of detected photons is much smaller than the number of cells, the signal is fairly linear and saturates when the number of photons is about equal to the number of cells. Saturation is well described by:
The active layers of silicon are very thin (2–4 mm), theavalanche breakdown process is fast and the signalamplitude is big. Therefore, very good timing propertieseven for single photons can be expected. Fluctuations inthe avalanche development are mainly due to a lateralspreading by diffusion and by the photons emitted in theavalanche [48, 49]. Asshown in Figure 34for the case of 1x1 mm2 MPPC, operation at high overvoltage (high gain) improves the time resolution.
The dependence of the FWHM as a function of the number of photoelectrons as shown in Figure 35is in fair agreement with Poisson statistics. The resolution with 15 photo-electrons, typical of applications where SiPM are coupled to small volume, high light yield scintillators, is better than 25 ps.
The range of electrons in Silicon as obtained from a GEANT4-based simulation.
Dynamic range
Time resolution for 1 and 4 photons for the 1x1 mm2 MPPC as a function of Vbias.
Time resolution as a function of the number of fired pixels
The present commercial production of avalanche Geiger-mode photodiodes gives the starting point for a new photomultiplier age, based on p–n semiconductors. As an example, in the Hamamatsu production at least three types of n+pp+ Multi-Pixel Photon Counter (MPPC) exist: 1600 (25μmx25μm), 400(50μmx50μm) and 100 (100μmx100μm) pixels segmentedonto a 1x1-mm2 total active area. The achieved gain, 105–106 at 70–72 V reverse bias voltage, makes possiblethe one photon level detection. The dark count rate is suppressed to a few hundreds kHz level,by setting a threshold at 0.5 p.e.. It decreases to 1 kHz for 1.5 p.e. and it is not significant for 2-3 p.e. Thermally generated free carriers can be further reduced by cooling the device. The temperature coefficient of noise rate at 0.5 p.e. threshold is -5%/ºC. With the present structures the most sensitive wavelength region is around 400 nm where the PDE is 25% for the 1600 pixels type, 50% for the 400 pixels type and 65% for the 100 pixels type [34], reflecting thehigher geometric factor value.
At present, the silicon wafer cost and the thermal dark current limit the dimensions of the SiPM photodetector at a few mm2.
Now the question is how to detect photons from large surfaces and/or volumes.
Their transport and/or focusing from surface and volume can be achieved in three different ways:
collecting photons and conveying them towards a single SiPM device;
enlarging the sensitive detector area by ordering several SiPMs in a pixelated matrix shape or by focusing the light to the sensitive area by Winston cones, pyramidal waveguides or lenses
making a photon conversion by a vacuum hemispherical photocathode which focuses photoelectrons on a SiPM (VSiPMT).
The reduction of geometrical area can be obtained by using wavelength shifter fibres embedded in the plastic scintillator body and connected at the other end to the SiPM.
Light collection from large scintillators or complex geometries can sometimes be aided through the use of optical elements that employ wavelength shifting technique.Many liquid or plastic scintillators incorporate an organic additive whose function is to absorb the primary scintillation light and reradiate the energy at a longer wavelength. It is emitted isotropically uncorrelated respect to the direction of absorbed light.
The same light collection principle can be applied using plastic fibers whose contains a wavelength medium. For best light propagation along the fiber one want a large shift between the optical absorption and the emission band so that minimal self-absorption takes place.
One of the first experience in this technique has been achieved in T2K experiment with the usage of wavelength shifter fibers.In this application [50],the counters are readout via WLS fibers embedded into S-shaped grooves in the scintillator from both ends by multi-pixel avalanche photodiodes operating in a limited Geiger mode. A customized 667-pixel MPPC was developed for T2K by Hamamatsu Photonics [51] with a sensitive area of 1.3×1.3 mm2 and a pixel size of 50×50 μm2; the sensitive area is larger than those available previously and relaxes the mechanical tolerances required for coupling to the WLS fibers used extensively in the experiment.
Image compression from large-surface detectors can be realized using matrices of single SiPM pixels. Such a device is particularly suitable in experiments detecting the Cherenkov or fluorescence light in the atmosphere. A lightconcentrator can be usedtoenhancethenumberof incident photonsonthesensitivesurfaceof the detector.
Some experiment for VHE gamma-ray astronomy (as example VERITAS [52], MAGIC [53] and HESS [54]) already use non-imaging light collectors to concentrate lighton photomultiplier tubes, while light concentrators are also widely used in diverse fields, as solar energy production.
Compound Parabolic Concentrators (CPC), also known as Winston cones [55], are light-collection devices intended to concentrate light on a smaller area by maximizing photon density per unit surface.Characteristic parameters for CPCs are: dimensional geometry, compression, acceptance angle and collection efficiency. CPCs are usually produced with amorphous (vitreous) materials like commercially available B270 and BK7.
A three-dimensional compound parabolic concentrator is designed by rotating a parabola aroundthe optical axis. The analytical description of theCPC profile is given by the following equation [55]:
in which θmax is the acceptance angle and a’ the exit aperture radius. randz are, instead, the reference axes as shown in Figure 36.
CPC Profile
As shown in Figure 37 a Winston cone is a double paraboloid built from two off axis parabolas, such that the focal point of onefalls to the edge of another. The reflecting surface is obtained by rotating the parabola around the concentrator axis.
CPC profile and acceptance angle (θmax).
The overall length of the parabolic concentrator is conditioned by the symmetry that must ensure to pass both edging rays and isthus limited by the maximum entrance diameter. The overall length is given by:
Since the diameter of entrance surface is:
resulting:
A useful ratio for describing the characteristics ofa concentrator is the geometrical concentration ratio or compression [55] defined as:
The theoretical maximum concentration ratio for a three-dimensional design is thus given by:
where θmax is the acceptance angle. The acceptance angle (or the cut-off angle) is the angle beyondwhich most of the light entering the concentrator is reflected out of it: the rays inside the collector undergo multiple reflections, and some of therays that enter at angles smaller than the limit value can be turned back; some rays incident at angles larger than the limit angle are instead transmitted.
The optical concentrationratio, considering losses (the optical efficiency), isthe amount of emerging light at the exit aperturecompared to the amount of the incident light on theentrance aperture. The attenuation in the concentrator results from reflection losses, scattering and absorption.Light collection efficiency depends on the radiation incident angle (relative to the Winston cone symmetry axis) and on the acceptance angle. In particular, the efficiency drops as large as the acceptance angle.
Thus, defining the transmission efficiency
where nd is the number of photons reaching the exit aperture and Nphot is the total number of photons penetrating the entrance aperture, the collection efficiency (
The collection efficiency is strictly related to the number of multiple reflections before reaching the exit aperture.
Even if the CPC have been designed for solar energy applications, their utilization in low photon detection is attractive to extend the detection surface. In this case, also the impact point on entrance surface has to be taken into account since this leads to a non homogeneous efficiency. As we will show, better results are obtained with acceptance angles lower than 5°.
As shown in Figure 38/left (related to a cone with an acceptance angle of 10° and 8° incident photons), it’s possible to identify areas on the entrance surface for which the number of multiple reflections is almost the same.
Left: Transmission zones of rays on the entrance surface of a CPC having θmax = 10º for impinging photons at 8º; Right: Rejections zones of rays on the entrance surface of a CPC having a θmax of 10º, for impinging photons at 11.5º: remark in (1) two little zones where the transmission is preserved.
Likewise, it’s possible to identify the areas where the photons exit from the entrance surface after reflections inside the CPC, without reaching the exit surface. These areas are shown in the Figure 38/right, for an 11,5º incident photons.
In order to estimate the collection efficiency of the light concentrator and to study its dependence on the length of the funnels and on the angle of incidence, we carried out several Monte Carlo simulations. Photons with given direction were produced at the entrance aperture and their path was followed until they were either absorbed by the funnel walls or left the funnel through one of the apertures. Various types of paraboloids and pyramidal light concentrators were examined in the simulations.
Figure 39shows a Winston cone simulated with a 0º acceptance angle with an entrance and exit apertures of a radius of 28 mm and 5.5 mm, respectively, corresponding to a concentration ratio of 25.91.
The transmission and collection efficiency for this device as a function of photon incident angle (with an uniform distribution of photon impact point) is shown in Figure 40.
As shown inFigure 40, the transmission efficiency, evaluated as nd/Nphot, is strongly suppressed for non-perpendicular photon incident angles, in the case of devices designed with a 0º acceptance angle. However, the efficiency is about 50% for 10º incident angles.
The collection efficiency takes into account also the compression ratio (
D model of the CPC with an acceptance angle of 0º used for the simulation.
Simulated transmission (left) and collection efficiency as a function of incident photon angle.
It makes sense the use of a CPC to increase the detection surface of a silicon device only if the deviceshave a large acceptance angles. To explore this option, a detailed simulation of a CPC with 25º acceptance angle (CPC25° ) has been performed.CPC25° is an optical glass B270 cone having 9.01 mm entrance diameter, 2.50 mm exit diameter, and is 19.25 mm long,commercially available by Edmund Optics [56]. Figure 41/leftshows the tridimensional model used in the simulations while Figure 41/rightshows the CPC25° used for the measurements.
Left: 3-D model of the CPC25° having an acceptance angle of 25º. Right: A photography of the CPC cone used for measurements mounted on its support.
Simulations show that the concentrator is able to transmit photons with incident angle up to about 25º with a good collection efficiency, ranging between 0.5 and 0.8 depending on the incident angle. A small lack in the transmission efficiency is evidenced for 0º incident photons, with respect to the case of a 0º acceptance angle designed one.
In order to experimentally check for the simulation accuracy, we used two different settings. The first set up is shown inFigure 42.
The experimental setup.
The efficiency of a CPC25° has been measured as a function of the impact position on the concentrator entrance surface by employing a computer controlled x-y movement with a position precision of tens of microns. A λ=407 nm highly collimated pulsed laser beam (spot diameter = 0.9 mm) has been sent on the CPC25° and both beams at the entrance and exit surfaces have been measured by a double channel Power Meter Newport mod. 2936-C.
The intrinsic efficiency measured is strongly dependent on the impact point of the photon on the entrance surface, as shown in Figure 43.
The measurements of the transmission efficiency along the CPC25° diameter, superimposed to the simulation results, are shown inFigure 44for impinging photons at 0° and at 20°: the simulation correctly reproduces the measurements and confirms the efficiency dependence on the photon impact point on the entrance surface.
Discrepancy in the maximum collection efficiency between data and simulation is mainly due to the optical coupling between the CPC25° and the Power Meter probe, but also to the photon absorption in the B270 glass, to the intrinsic Power Meter probe efficiency and its dependence on the photon incident angle.
The same measurement has been repeated for several angles of incidence of photons.
This study shows as, to increase the detection surface of a SiPM by using parabolic concentrators, devices designed for small acceptance angles are preferred, with the better choice corresponding to 0°, but limiting in this way the field of view. In any case, the detection of radiation produced at fixed angles, as in experiments in which Cherenkov radiation has to be detected, can profit of this solution.
Transmission efficiency on the entrance surface of the CPC25°.
Comparison between simulation and actual data on the CPC25° (CPC having an acceptance angle of 25º) for impinging photons at 0° (Left) and at 20º (Right).
Differently, a pyramidal device can be considered. Simulation studies have been carried on this geometric structure (Figure 45).
D model of the pyramidal concentrator used in the simulation and a photography of the pyramidal concentrator used for measurements
The pyramidal concentrator simulated in this work is an optical glass N-BK7 device, with 7.5 x 7.5 mm2 entrance surface, 2.5 x 2.5 mm2exit surfaceand 50 mm long, commercially available by Edmund Optics [56]. Figure 45/right shows the pyramidal light concentrator used for the measurements.
From simulation, a good transmission efficiency, almost uniform up to 20° is obtained for this geometry, as shown inFigure 46.
Efficiency curve of the pyramidal concentrator as a function of the impinging angle of the photons.
Also for this concentrator, the efficiency has been measured as a function of the impact position on the entrance surface, by using the experimental set-up described inFigure 42. The transmission efficiency measured is shown in Figure 47, Figure 48 and Figure 49 for different incident angles.
Measurement of the transmission efficiency on the entrance surface of the pyramidal concentrator for 0º impinging photons.
Measurement of the transmission efficiency on the entrance surface of the pyramidal concentrator for 5º impinging photons.
Measurement of the transmission efficiency on the entrance surface of the pyramidal concentrator for 10º impinging photons.
Measurement results show that transmission efficiency of such a pyramidal light concentrator has a slight dependence on the impact point except for the case of incident angles of 10°. In fact, as shown inFigure 49, in this case large part of the entrance surface (about an half) results in a very low efficiency (about 10%). Actually, this partial inefficiency may be due to the very large angles of exiting photons (>60°), out of the angular acceptance of the Power Meter probe.
A second methods adopted to evaluate the effect of light concentrators is based on the measurement of photons detected with a 3x3 mm2 MPPC S10931-025Pby Hamamatsuarranged at the exit surface of the concentrator (Figure 50).
The experimental set-up: light concentrator on the MPPC
The average number of incident photons on the concentrator, can be determinedby measuring the laser power on one of the two outputs of the splitter. The MPPC signal, amplified by the National Semiconductor LMH6624 chip as already described, has been measured on the oscilloscope andan estimation of the overall efficiency of the system (light concentrator + MPPC) has been doneby evaluating the number of photons detected by the MPPC. Laser power has been set to 40 photons per pulse on the surface of the CPC25°, with an incidence angle of 0º. The maximum total efficiency for several distances of impact point from the center along one diameter (Figure 51)has been measured. Results show that a maximum obtainable efficiency is 0.1, while observing dynamic range it is possible to note that this shape of concentrator is not useful to increase the field of view of a MPPC.
Number of photoelectrons as a function of the distance of impact point from the centre
The same experimental set-up has been used to measure the efficiency of pyramidal concentrator (seeFigure 52).
Experimental set-up for pyramidal concentrator using an MPPC as a sensitive device.
Figure 53 shows the efficiency measurement for several distance of impact point from the center (along one dimension) and for several incident photon angles. Again it can be observed that the maximum total efficiency is 0.1, but in this case the total surface is enhanced. Furthermore, the efficiency results to be very uniform for incident angles in the range 0°-10°.
The efficiency of the concentrator will be surely enhanced by developing SiPMs in which a front-side structure with quenching resistors is integrated into the silicon bulk. In this mode obstacles for light like metal lines or contacts, can be omitted and therefore the fill factor would only be limited by the gaps indispensable for the optical cross-talk suppression and it can reach in principle 100% [57]. Being the fill factor of present SiPM of the order of 30% (see Figure 13 and Figure 16) and taking into account it represent the main contribution to the concentrator efficiency, it will be possible to achieve very interesting overall efficiencies of the order of 35-40%. In this way, the features of a SiPM and concentrator can largely overcome the properties of the classical PMT.
One option to further improve the angular coverture of a silicon device could be to combine it with vacuum technology. One can replace the dynodes structure of a photomultiplier with a silicon photodiode(HPD – Hybrid Photo Detector or with an avalanche photodiode (HAPD- Hybrid Avalanche Photo Detector). The detection of photon starts as in anordinary photomultiplier at the photocathode,where a photoelectron is produced.
Efficiency measurement for several distance of impact point from the center (along one dimension) and for several angles of the incident photon.
A pioneering configuration using a gain G = 1 p–i–n diode has been proposed 10 years ago by Hamamatsu and DEP. Using p–i–n diodes the signal amplification is given by the number of electron–hole pairs produced by electrons emitted from the photocathode, accelerated by a high-intensity electric field and injected into the target diode. The gain depends on the energy of incident photoelectrons: at 4 kV operational voltage, about 1100 electron–hole pairs are generated. However, in many applications where an higher sensitivity is required, such a small gain (further reduced by the photocathode QE) limits the lowlevel light detection capability.
More recently, a gain improvement was obtained using diodes in avalanche regime (APD), with a resulting additional gain of ~20–50. The overall photomultiplier gain increases, yet not enough for low light level detection. In addition, the fluctuations in the avalanche multiplication, limit the useful gain range.
The idea, which starts from these experience and from the consolidation of the Geiger-APDs, is to combine them into a sort of classical vacuum tube: electrons emitted by a photocathode can be collected and focused on an array of G-APDs, which acts as the amplifier. The junction works as an electron multiplier with a gain of 105–106, equivalent to the dynode chain of a classical VPMT. Thus the Vacuum Silicon Photomultiplier Tube (VSiPMT) would consist of the following:
a photocathode for photon–electron conversion,
an electric field to accelerate and focus the photoelectrons on asmall area covered bythe G-APD array,
With 10 kV between photocathode and SiPM, the range of 10 keV photoelectrons impinging on the silicon is 1.5 μm(as shown in Figure 32). In a conventional front illuminated n+pp+ structure, the n+ layer has to be enough shallow(≤ 0.5 μm) in order to have an efficient ionization in the p region. With standard equipment for detector fabrication, layers with a junction depth of 100 nm can be obtained [32]. In addition the high-field region should be as thin as possible in order to have more ionization beyond it, maximizing the electron trigger probability. Otherwise, at lower voltages, a junction structure p+nn+ is needed. The ionization should happen in the p+ side allowing electrons to pass the whole high-field zone with high avalanche efficiency. In both cases photoelectrons spend most of the ionization within the p layer thickness. In contrast with the photon detection, the precise range of the photoelectrons permits the optimization of the thickness of the junction n+pp+ or p+nn+ layers, minimizing the depletion region with great advantage for lowering the dark current, increasing at same time the efficiency and the time resolution.
Recently C. Joram and al. at CERN [58] performed a very interesting study concerning the response of SiPM devices to the electrons impinging. Results they found have been so encouraging and interesting to influence also the title they give to the article: “Proof of principle of G-APD based hybrid photo detectors”. In practice they demonstrate the feasibility of such a solution, already preannounced by our group in [2]. The CERN group, thanks to their usual activities, had the possibility of making a detailed test just dedicated to this aspect. We consider their result as a precious confirmation of our previous theories concerning this arrangement.
Exploiting the full fill factor of a front illuminated SiPM described in a previous paragraph, an ultimate design for a new semiconductor hybrid photomultiplier is possible. It consists of a hemispherical vacuum tube with a deposited photocathode and a special SiPM in which quenching resistor and electric contacts are integrated in the bulk. The admittance of such a component on the sensitive surface allows the full geometrical efficiency of a SiPM used as amplifying element, making it very attractive also in this application. So in this way this hybrid PMT results equivalent to those, already existing, manufactured with APD (gain 102), but with a gain comparable to the standard PMT (106-107).
In conclusion, photoelectrons emitted by the photocathode are accelerated, focused and then amplified by Geiger junctions (Vacuum Silicon PhotoMulTiplier,VSiPMT,). Such an amplifier, which would substitute the classical dynode chain, presents several attractive features such as small size, low cost, high gain, high efficiency, absence of an external voltage divider, no power consumption, weakened dependence on magnetic fields.
These developments will offer an attractive response to the necessity of increasing active surfaces with high sensitivity.
As a last point we wish to underline the possible applications of SiPMs in cryogenic environments. Both SiPM matrices and VSiPMTs can be considered as a promising alternative to classical photomultipliers for VUV scintillation detection in liquid noble gas experiments requiring a high sensitivity to very low energies to detect neutralino Dark Matter signals (see for instance [59, 60]). The drop of thermal noise at low temperatures, three orders of magnitude at -95° for liquid Xenon, enhances the linearity and the single photon detection capability. The above considerations regarding the front and back illuminated SiPM induce to envisage a quantum efficiency of 25% in VUV region [61]. These figures encourage the use of these new devices in cryogenic environment [62].
The so-called silicon photomultipliers (SiPMs, MPPCs by Hamamatsu, etc.) are already replacing photomultiplier tubes in many applications. Recently this new photon detector is operative on different R&D lines in various applications. High performances characterize such a device: reduced dimensions, high gain, low power supply, single photon sensitivity, magnetic field operation, very good time resolution, low cost. In particular low power supply and negligible power consumption together with a single photon counting, make it very interesting also in hostile environments (space, astronomy) and suitable for a wide variety of applications (including medicine and biology).The drawback of this detector are the reduced dimensions limited by the dark count and silicon cost. To collect photons both from great surfaces or/and volumes and to increase the field of view of such a photo detector, three solutions have been presentedin this paper. Apart the classical and proven technique of detecting scintillation light from large volume using WLS fibers, which diameter dimensions are compatible with the active part of the present commercial SiPM, two innovative solutions are presented to improve the field of view and/or focus the light: cones and pyramidal light concentrators assembled in single SiPM or organized in a matrix shape. Such a device are applied both to read Cherenkov detector on beam experiments (RICH) and astronomical telescopes. A second solution simplifies and improves the classical PMT performances by replacing the dynode amplification chain with a SiPM in a Hybrid configuration. A similar photo detector using a lower APD gain has been implemented and it is already operative. There is space to implement both solutions. To do this at the best, advanced SiPM have to be realized. Two are the critical features that have to be solved in the next years: the dark noise reduction and the elimination of the dead region around the microcell (fill factor) where the quenching resistor is positioned. Already today it has been proposed a front-side illuminated detector structure with quenching resistors integrated into the silicon bulk. In this concept, the fill factor is only limited by the gaps necessary for optical cross-talk suppression. Compared to existing devices the proposed detector has the potential of a very high photon detection efficiency.
Olive oil is one of the basic components of Mediterranean diet with health protective characteristics [1]. It has been used for centuries due to its preventive and therapeutic characteristics [2, 3]. Olive oil have positive effects on preventing or improving atherosclerosis, cardiovascular diseases, serum lipoprotein levels, oxidative stress, obesity, type 2 diabetes, inflammation and cancer [4, 5, 6, 7, 8].
Health protective effect of olive oil is based on its chemical composition [4, 5, 9, 10]. Olive oil’s chemical composition may be divided into major and minor components. Major components of olive oil are related with its fatty acid content. Primary monounsaturated fatty acid (MUFA) of olive oil is oleic acid [3]. Minor components of olive oil constitute nearly 2% of the weight of olive oil and include more than 230 minor chemical compounds [3, 10]. These chemical compounds include aliphatic alcohols, triterpene alcohols, sterols, hydrocarbons, pigments, volatile compounds, and phenolic compounds [2, 3]. Olive oil has at least 30 phenolic compounds. These are phenolic acids and derivatives, phenolic alcohols, secoiridoids, lignans and flavones [10, 11, 12].
Oleic acid, which is the basic fatty acid of olive oil [8, 13], and the minor compounds of olive oil, including tocopherols, β-carotene, lutein, squalene, lipophilic and hydrophilic phenols, are considered to be responsible for its positive impacts on human health [3, 14]. Olive oil protects human health by changes in epigenetic, metabolic and physiologic mechanisms [2]. This chapter reviews the fatty acid composition and minor components of olive oil and their effects on human health.
Triglycerides constitute 98–99% of total weight of olive oil. Basic fatty acid of olive oil is oleic acid (55–83%), which is one of the MUFA. Besides, olive oil contains fatty acids such as palmitic acid, stearic acid, linoleic acid and α-linolenic acid (Table 1) [3, 10].
Fatty acids | Common name |
---|---|
Saturated | Myrictic acid |
Palmitic acid | |
Margaric acid | |
Stearic acid | |
Arachidic acid | |
Behenic acid | |
Lignosceric acid | |
Monounsaturated | Palmitoleic acid |
Heptadecenoic acid | |
Oleic acid | |
Eicosenoic acid | |
Polyunsaturated | Linoleic acid |
α-linolenic acid |
Fatty acids composition of olive oil.
Positive impact of olive oil over human health is related with its oleic acid content [9]. MUFA in olive oil is considered to reduce hypercholesterolemia, hypertension, atherosclerosis and cardiovascular mortality [8, 13]. Besides, olive oil consumption increases MUFA intake rather than saturated fatty acids (SFA), which, in turn, protects from cardiovascular diseases [15, 16, 17].
In 1985, it was noticed that the replacement of SFA with MUFA intake in diets reduce low-density lipoprotein (LDL) cholesterol level [18]. It was found that the replacement of carbohydrates in diet with MUFA reduced triglycerides (TG), very low-density lipoprotein (VLDL) cholesterol, blood pressure, C-reactive protein (CRP) and increased high-density lipoprotein (HDL) cholesterol and apolipoprotein A1 (Apo-A1) levels [19, 20, 21]. In an another study with the replacement of SFA with olive oil, which has the same amount of energy in diet, LDL cholesterol levels decreased whereas HDL cholesterol levels did not change [22]. Replacement of partially hydrogenated vegetable oil with MUFA had positive impact on cardiovascular risk parameters, such as LDL cholesterol, TG, Apo-A1 and Apo-B levels [23]. It was indicated that following a MUFA rich diet increased HDL cholesterol levels and decreased TG levels [24]. In a meta-analysis it was found that replacement of SFA with MUFA or polyunsaturated fatty acids (PUFA) significantly reduced total and LDL cholesterol levels [25]. In an another meta-analysis it was determined that consuming diets high in MUFA can improve metabolic risk factors among patients with type 2 diabetes [26]. In a meta-analysis of 12 randomized controlled studies high MUFA diets (>12%) were compared to those with low MUFA diets (≤12%). Significant differences between high- and low-MUFA diets were determined with respect to fat mass, systolic blood pressure and diastolic blood pressure. Therefore, high MUFA diets are important dietary regimens for obesity and cardiovascular disease [27].
Such positive impacts of olive oil on human health are related with high oleic acid, proper amount of linoleic and α-linolenic acid, and limited amount of SFA that it contains. High amount of oleic acid and proper amount of linoleic acid helps cells to protect their integrity and slows down the process of aging. Besides, low levels of α-linolenic acid demonstrate anti-inflammatory and vasodilatory effects [2].
Olive oil is rich in terms of minor compounds with antioxidant characteristics, such as polyphenols, carotenoids, squalene and tocopherols. Tyrosol, hydroxytyrosol, flavonoids (apigenin, luteolin), oleuropein and oleocanthal are among the phenolic compounds of olive oil with antioxidant characteristics (Table 2) [2, 6].
Minor components |
---|
|
Minor components of olive oil.
The amount of squalene, which is the basic hydrocarbon in olive oil ranges between 0.8 and 13 g/kg. Squalene has antioxidant activity and helps to lower serum cholesterol levels. Regular squalene intake by using olive oil in diets protects human health from cancer and cardiovascular diseases [28]. The most important carotenoids in olive oil are luteolin and β-carotene. These compounds have antioxidant characteristics that maintain the neutralization of reactive oxygen species (ROS) [2].
Triterpenes have also antioxidant and anti-inflammatory effects [11]. Regular consumption of olive oil maintains antioxidant intake. These compounds reduce free radicals and prevent damages to the cellular membrane, mitochondria, and DNA, with beneficial effects on aging and cancer risk. Especially, phenolic compounds in olive oil have strong antioxidant effect [2, 6].
Polyphenols are compounds with diverse characteristics, which protects human health from chronic diseases [6]. They are described as phenolic compounds, which consists of one or more hydroxyl groups and aromatic rings [10]. Phenolic compounds in olive oil are classified as phenolic acids, flavonoids, secoiridoids, lignans, and phenolic alcohols (Table 3).
Phenolic compounds | Common compound name |
---|---|
Flavonoids | |
|
|
|
|
Lignans |
|
Phenolic acids and derivatives | |
|
|
|
|
|
|
Phenolic alcohols |
|
Secoiridoids |
|
Phenolic compounds in olive oil.
Phenolic compounds in olive oil may have lipophilic and hydrophilic characteristics. Tocopherols are among the lipophilic phenols. Alpha-tocopherols are the most common type of tocopherols in olive oil. Tocopherols especially prevent lipid oxidation in cellular membrane. Due to this reason, they are considered as the most important antioxidant agents in structures that contain lipid [14]. Tocopherols may be found in other oil types. However, hydrophilic phenols (phenolic acids and alcohols, secoiridoids, flavonoids and lignans) do not exist in oil types other than olive oil [3, 10]. Oleuropein, hydroxytyrosol and tyrosol are among the important phenolic compounds of olive oil [2, 6].
On average, olive oil consists of 500 mg/kg phenol [29] and the amount of phenol in different types of olive oil may range between 40 and 1000 mg/kg [10]. A study conducted in Spain found that daily polyphenol intake from olive and olive oil was 90.4 mg, which constitutes 11% of total daily polyphenol intake [30].
Phenolic compounds display a board spectrum of health promoting characteristics, including lipid-improving, anti-oxidant, anti-inflammatory, anti-atherogenic, anti-thrombotic, anti-mutagenic, anti-microbial effects [6, 7, 8]. Beneficial effects of olive oil’s phenolic compounds on human health include improvements in oxidative stress, lipid metabolism, platelet and endothelial functions, and inflammation [6, 8, 14]. Oleuropein and hydroxytyrosol are principal minor phenolic components of olive oil and these antioxidant components prevents diabetes, cardiovascular diseases, neurodegenerative diseases, cancer, inflammation and oxidative stress through its nutrigenomic and immunomodulatory effects [4, 5]. Also oleacein has antioxidant, anti-inflammatory, anti-proliferative and antimicrobial properties and it may play a special role in decreasing the progression of atherosclerosis [31].
A study conducted on 200 healthy male participants, administered 25 ml/day of three olive oils that had low (2.7 mg/kg), medium (164 mg/kg) and high (366 mg/kg) phenolic content. The study found that higher phenolic content was associated with decrease in oxidative stress markers and improvements in lipid profile [32].
Phenolic compounds in olive oil have strong antioxidant characteristics and radical scavenging activities [29]. Regular olive oil consumption maintains phenolic compound intake and protects human health [14]. Taking these into consideration, we may suggest that biological characteristics of olive oil decrease the prevalence of chronic diseases [6, 8, 14].
Olive oil rich diet protects human health from cardiovascular diseases, hypertension, inflammation, oxidative stress, obesity, type-2 diabetes, and cancer [4, 5, 6, 7, 8].
Cardiovascular diseases arise from malfunctioning of heart and blood vessels and include problems, such as coronary heart disease, atherosclerosis, cerebrovascular diseases, peripheral artery disease, congenital heart disease, deep venous thrombosis, pulmonary embolism, myocardial infarction and stroke. Eating habits, and especially total fat and fatty acid intake are among the reasons of cardiovascular diseases [33]. ‘Prevención con Dieta Mediterránea’ (PREDIMED) study that conducted in Spain and randomly assigned participants, who were at high cardiovascular risk, to one of three diets: a Mediterranean diet supplemented with extra-virgin olive oil (EVOO), a Mediterranean diet supplemented with mixed nuts, and a control diet that was advised to reduce dietary fat. Compared to the control group, the Mediterranean diet supplemented with EVOO or mixed nuts was associated with 30% lower risk of major cardiovascular events for a period of 5 years [34]. In an another study, it was found that olive oil consumption, specifically EVOO, is associated with reduced risks of cardiovascular disease and mortality in individuals at high cardiovascular risk. For each 10 g/day increase in extra-virgin olive oil consumption, cardiovascular disease and mortality risk decreased by 10 and 7%, respectively [35].
A study that followed stroke incidence in three French cities for an average of 5.25 years found that the participants with high olive oil consumption had a 41% lower risk of stroke compared to those who never used olive oil. The same study found that higher plasma oleic acid was associated with lower stroke incidence and that the participants with higher plasma oleic acid levels had a 73% reduction of stroke risk compared to the participants with lower plasma oleic acid levels [36]. Another study, which followed Italian women for an average of 7.85 years, found that cardiovascular disease risk was lower for women in the highest quartile of olive oil intake (35.0 ± 0.1 g/day) compared to those in the lowest quartile of olive oil intake (16.8 ± 0.1 g/day) [37].
Another study conducted in five Spanish regions compared non-consumers of olive oil with participants that consumed ≥29.4 g/2000 kcal/day and found that the highest quartile of olive oil consumption was associated with a 26% reduction in risk of overall mortality and a 44% reduction in cardiovascular disease mortality. The study also found that for each increase in olive oil intake of 10 g/2000 kcal/day, there was a 7% decreased risk of overall mortality and a 13% decreased risk of cardiovascular disease mortality [38].
EVOO that is frequently consumed in Mediterranean countries, tends to produce a less prothrombotic environment, promoting antioxidant and anti-inflammatory effects with a greater endothelial protective capacity, which in turn, prevents cardiovascular diseases [22]. Besides, another study in which, healthy participants were administered virgin olive oil (VOO) for 3 weeks found that VOO supplementation altered the expression of 10 genes related to atherosclerosis development and progression [39].
Phenolic compounds of olive oil protects blood lipids from oxidative damage [8]. LDL oxidation is among the main risk factors that contribute to the development of atherosclerosis and cardiovascular diseases. Oxidation of LDL results in the formation of plaque within the arterial wall. Oxidized LDL levels should be taken into consideration as an indicator of oxidative damage and subclinical atherosclerosis. Oxidation of lipids and LDL apolipoproteins is taken by scavenger receptors on monocytes, smooth muscle cells and macrophages in an uncontrolled process, which, in turn, leads to formation of foam cells as an early feature of atherosclerosis [40]. Phenolic compounds delay atherosclerosis by reducing the expression of oxidized LDL and cellular adhesion molecules [2, 14]. Consumption of VOO, which is rich in terms of phenolic compounds significantly decreased LDL cholesterol levels in 1 week [41].
Due to vessel damage, endothelial adhesion molecule expression, platelet activity and aggregation is stimulated. Circulating macrophages and other molecules are adhered to the endothelium, which scavenge LDL and TG, becoming foam cells [42]. Phenolic compounds in olive oil prevent endothelial adhesion molecule expression and platelet aggregation. Hydroxytyrosol, oleuropein, aglycon and luteolin are crucial to prevent platelet aggregation [8]. Oleocanthal-rich extra virgin olive oil may influence platelet aggregation responses in healthy male adults [43]. Oleacein by inhibiting neutral endopeptidase activity, adhesion molecules expression and elastase release might play a role in the protective effects of olive oil against endothelial injuries [44]. Oleacein enhances anti-inflammatory activity of human macrophages by increasing CD163 expression. It could play a potential role in the prevention of inflammatory disease related to atherosclerosis [45]. Additionally, oleacein possess ability to diminish the destabilization of carotid plaque and it could be useful in the reduction of ischemic stroke risk [46]. For that reasons it is possible to emphasize that olive oil rich diet protects human health from cardiovascular diseases.
Positive effects of EVOO consumption on blood pressure have been noticed. EVOO intake contributes to the decrease in diastolic and systolic blood pressure in hypertensive individuals. When compared with vegetable oil that is rich in terms of PUFA, EVOO consumption has a positive effect on blood pressure [47]. A study conducted in five European countries found that consumption of 25 ml/day olive oil significantly decreased systolic blood pressure [48].
In a meta-analysis conducted in the recent years compared dietary regimes with a high amount of MUFA (>12%) with those ≤12% for a period of more than 6 months and found that diets with high amount of MUFA decreased systolic blood pressure, and diastolic blood pressure [27].
Antioxidant effect of EVOO is related with the fact that EVOO consumption reduces the generation of ROS. This effect prevents endothelial dysfunction, which is responsible for hypertension [49]. Related with this, the comparison of EVOO with olive oil or corn oil reveals that inflammatory markers (TXB2 and LTB4) decreased and serum antioxidant capacity increased only in the group of participants, who were administered EVOO [50].
Increase in oxidative stress causes an increase in ROS. Superoxide anion (O2−), hydroxyl radical (OH), and hydrogen peroxide (H2O2), which are also known as ROS, are the oxidizing agents that highly aggressive against the principal biological components of the organism, including lipids, proteins, mitochondria, and DNA. When lipids in the cell membrane are subjected to this action, oxidation that alters membrane permeability takes place. This, in turn, results with early aging of cells. When enzymes, mitochondria and proteins are subjected to this phenomenon, they can lead to metabolic disorders and inflammation in blood vessels, heart, kidney or joints. On the other hand, if DNA undergoes oxidation, the risk of cancer increases. Minor components of olive oil protects mitochondria and DNA from oxidation and decreases the generation of free radicals [2, 11]. Both oleuropein and oleacein are important antioxidant compounds of olive oil and they are stronger scavengers of O−2 and H2O2 [51].
Increase in ROS is associated with atherosclerosis, cancer and neurodegenerative diseases. Oxidative stress increases the levels of lipid peroxide and oxidized glutathione (GSSG), and decreases the levels of glutathione (GSH) and glutathione peroxidase (GSH-Px). Consumption of olive oil that is rich in terms of phenols improves the balance of GSH and GSSG, increases GSH-Px levels and decreases lipid peroxide levels. Consequently, cellular oxidative damage may be decreased by consumption of olive oil with high phenol content [32, 52]. In a controlled before and after supplementation trial with 45 healthy adults found that regular consumption of 50 ml/day EVOO rich in phenolic compounds during 30 days increases plasma antioxidant capacity and antioxidant enzyme activity (catalase and superoxide dismutase). Also it was observed increase in superoxide dismutase and decrease in catalase gene expression [53].
Cell aging, atherosclerosis, diabetes, rheumatoid arthritis, pulmonary emphysema, cataract, Alzheimer and Parkinson diseases, dementia, and development of breast, prostate, colon and skin cancers are related with continuous oxidative damage of cells. Oxidative damage may be partially prevented when the activation of free radicals is inhibited by nutrients, such as minor compounds of EVOO [2, 11]. In order to protect aging that is caused by the damage of free radicals, EVOO intake should start during the early childhood period [54].
EVOO may prevent inflammation when chronic inflammation is associated with pathological cases, such as obesity. Anti-inflammatory effects of EVOO is depends on its fatty acid content and antioxidant compounds [54]. In a randomized controlled trial in healthy adults found that VOO consumption decreased plasma oxidative and inflammatory status and the gene expression related with both inflammation and oxidative stress [55].
Increase in the concentration of inflammatory markers is associated with a higher risk of cardiovascular disease. Plasma thromboxane B2 (TXB2) and leukotriene B4 (LTB4) are known as the pro-inflammatory agents. TXB2 increases platelet aggregation in blood whereas LTB4 leads to cellular damage [56]. Bogani et al. [50] determined that consumption of EVOO that is rich in phenolic components decreases the concentration of inflammatory markers such as TXB2 and LTB4 and increases the serum antioxidant capacity whereas no such decrease was found for other oil types such as olive oil and corn oil.
Interleukin-6 (IL-6) and CRP, which are among the inflammatory markers increase in case of cardiovascular diseases. Olive oil with high phenolic compounds has anti-inflammatory effect and decreases CRP and IL-6 levels in circulation [57]. Oleocanthal, which is among the phenolic compounds of olive oil, prevents cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2) activities, which have roles in the inflammation process. Inhibition of cyclooxygenase (COX) enzymes results in the reduction of arachidonate to the eicosanoids, prostaglandins and thromboxane [58]. It have been proven to possess that oleacein have antioxidant and anti-inflammatory activities. Oleacein enhances anti-inflammatory activity of human macrophages by increasing CD163 expression [45]. For that reasons, anti-inflammatory effects of olive oil enables protection from diseases that are related with inflammation [8].
Additionally, EVOO reduces the expression of genes involved in the inflammatory response, including intercellular adhesion molecule-1 (ICAM-1), vascular cells adhesion molecule-1 (VCAM-1) and monocyte chemotactic protein-1 (MCP-1), and interferes with the activation of major transcription factor that controls the inflammatory endothelial activation, namely nuclear factor kB (NF-kB). It was known that minor compounds of EVOO, such as phenols, carotenoids and tocopherols, prevent the activation of NF-kB at cellular level [2].
The anti-inflammatory effects that arise from the consumption of olive oil phenolic compounds have been shown to provide protection against inflammatory diseases. Thus, due to the reduction of the risk of inflammation, it can be said that the Mediterranean populations have low rate of cardiovascular mortality and certain types of cancer [8].
Positive effects of olive oil consumption over weight control are widely known. Olive oil increases postprandial thermogenesis. Besides, it may contribute to an increase in fat oxidation. Furthermore, oleic acid may increase satiety, thus reducing food intake. The effect of fatty acids over weight gain may be related with neurotransmitters, intestinal peptides or thermogenesis [59]. The presence of fatty acids in the small intestine lumen induces a number of changes in the gastrointestinal function and inhibits appetite and energy intake. Gastrointestinal hormones, including cholecystokinin, glucagon-like peptide-1 and peptide YY are crucial to regulate appetite and control nutrition intake [60]. One of the studies found that oleic acid caused a slower gastric emptying, promoted the release of cholecystokinin and peptide YY, and a lower subsequent energy intake for both normal weight and obese participants [61].
Comparison of EVOO with cream, which has the same amount of energy but higher SFA levels indicated that olive oil significantly promoted postprandial fat oxidation and stimulated diet-induced thermogenesis [62]. Due to this reason, SFA may be replaced by MUFA for overweight and obese persons in order to lower body weight and fat weight [63].
Oleoylethanolamide (OEA), which is a by-product of oleic acid, acts as a hormone and may lead to satiety and decrease meal frequency. Nutritional intake of oleic acid stimulates the activation of OEA mobilization in the proximal small intestine, which, in turn, leads to satiety. Oleic acid in diets is precursor of OEA synthesis in erythrocytes. OEA decreases during fasting and increases after meals [64]. OEA production in small intestine serves as a molecular sensor linking fat intake to satiety [65]. In addition, OEA resembles to endocannabinoid anandamide in structural terms. Anandamide has an appetizing effect and activates cannabinoid receptors (CB1). Nevertheless, independent of the cannabinoid receptors, OEA has anorectic effect and increases satiety between meals [65].
OEA regulates satiety and appetite, thus contributes to a decrease in body weight. This effect is related with the engagement of peroxisome proliferator-activated receptors-α (PPAR-α). Following food intake, activation of PPAR-α receptor in intestine plays a role in the stimulation of vagus nerves, creating satiety in paraventricular nucleus (PVH) of hypothalamus [64]. OEA decreases meal frequency, increases lipolysis, and modulates the inflammatory response together with PPAR-α by reducing the activity of nuclear factor NF-kB activity, and increasing the catabolism of LTB4 in macrophages [2]. For that reasons, it has been suggested that the increase in OEA production may prevent overnutrition [2].
Additionally, proinflammatory cytokines, such as leptin, tumor necrosis factor alpha (TNF-α), MCP-1, and IL-6 are released from adipose tissue and this phenomenon triggers chronic inflammation [66]. EVOO prevents inflammation in cases such as obesity, which are associated with chronic inflammation [54]. EVOO consumption by obese individuals may reduce inflammatory responses [22]. Anti-inflammatory effect of EVOO may be related with its fatty acid content and antioxidant compounds [54].
In addition to all these characteristics, the consumption of olive oil together with legumes, vegetable dishes and salads is believed to have positive effects on digestive system, glycemic responses and weight control [59]. A 3 years follow-up of a Mediterranean diet supplemented by VOO and nuts found that Mediterranean diet, especially rich in VOO is associated with higher levels of plasma antioxidant capacity and the reduction in body weight after 3 years of intervention in a high cardiovascular risk population [67]. All these reflect the fact that olive oil consumption together with a Mediterranean diet may prevent weight gain [8, 13].
Olive oil with its MUFA content improves glucose metabolism [8, 13]. When high-MUFA diets were compared with high-PUFA diets, there was a significant reduction in fasting plasma glucose level [26]. In addition, it was determined that decreases of SFA levels and increases of oleic acid levels in cellular membranes do not change insulin secretion but improves insulin sensitivity [2].
Prevention of diabetes might be attributable to the antioxidant property of EVOO, thus, oxidative stress seems to be implicated in β-cells dysfunction and eventually diabetes [68]. After 6 hours of consumption of 50 ml VOO, significant changes occurred in gene expression related with insulin sensitivity [69]. On the other hand, four cohort studies, including 15,784 T2D cases and 29 trials, were included in a recent meta-analysis, which indicated that the highest olive oil intake showed a 16% reduced risk of type 2 diabetes compared with the lowest intake. Additionally, in case of patients with type 2 diabetes, olive oil supplementation resulted in a significant reduction of HbA1c and fasting plasma glucose compared to the control group [70]. Additionally, change from polyunsaturated to monounsaturated diet in type 2 diabetes reduced insulin resistance [71]. For these reasons, olive oil could be beneficial for the prevention and management of type 2 diabetes [70].
Obesity causes an increase in inflammation [54]. Additionally, free fatty acids and glycerol release from adipocytes. Increase in the levels of proinflammatory cytokines, ROS and free fatty acids, result with risk of insulin resistance, which, in turn, may lead to type-2 diabetes [66]. Olive oil consumption contributes to weight loss, which is one of the strongest risk factors for type 2 diabetes [72]. All these reveal that olive oil, which is the fundamental ingredient of Mediterranean diet, may have a preventive role for type 2 diabetes [4, 5, 6, 7, 8].
Epidemiologic studies found that cancer incidence was lower in countries such as Greece, Italy and Spain, which are characterized by high EVOO consumption [54]. Meta-analysis of 19 case-controlled studies reveals that cancer risk for the highest olive oil consuming group was 60% lower than the lowest olive oil consuming group. Besides, the study demonstrated that the increase in olive oil consumption was associated with protection from breast and gastrointestinal cancer [73].
High corn oil diet allows the development of malignant adenocarcinomas in rats whereas high EVOO consumption does not have such an effect. Excessive intake of oleuropein, which is one of the phenols in olive oil, has no toxic effects. Additionally, it has antimicrobial, antioxidant, hypotensive, hypoglycemic and antiangiogenic properties. Due to this reason, it is believed that oleuropein has anti-tumor activities. In case of rats with one or more large tumors (>2 cm diameter), addition of 1% oleuropein to drinking water showed strong antineoplastic effects and lead to the disappearance of tumor within 9-to-12 weeks due to antiangiogenic mechanisms that have direct inhibitor effects over cells. The study found that oleuropein in olive oil is an important compound with antineoplastic activity [74].
EVOO has antineoplastic effect on breast cancer in females. EVOO consumption reduces breast cancer risk in postmenopausal women [72]. In the presence of high levels of fatty acid synthase enzyme, oleic acid inhibits the oncogenic effect of epidermal growth factor receptor (HER2) gene by reducing the transcription activity of this gene. Furthermore, EVOO had a strong tumoricidal action on HER2 as a result of phenols, mainly oleuropein aglycon, which is related to inhibition of HER2 gene [75].
Oxidative damage of DNA starts carcinogenesis. Consumption of olive oil that is rich of phenols may inhibit oxidative DNA damage [76]. Cell proliferation and prevention of cell death are among the other factors that lead to tumor formation and development. Hydroxytyrosol in olive oil may prevent cell proliferation. Besides, oleuropein and hydroxytyrosol induce the death of breast cancer cells [77]. Due to these reasons, phenolic compounds in olive oil maintains the integrity of cells and prevents the development of tumors [8, 77].
Compounds of EVOO may show antitumoral effects as a result of metabolic and pathophysiological mechanisms, and may prevent the transformation of human cells into malignant cells and form metastases [2].
Olive oil has protective effects against inflammation and oxidative stress. Besides, it protects human body from various diseases, including, cardiovascular diseases, hypertension, obesity, type 2 diabetes and cancer. The basic fatty acid of olive oil, namely oleic acid, and minor compounds of olive oil, primarily phenolic compounds with their antioxidant activities, are responsible for the positive effects of olive oil over human health. Olive oil polyphenols have antioxidant, anti-inflammatory, antimicrobial, antiviral, anti-atherogenic, anti-thrombotic, anti-mutagenic and hypoglycemic characteristics. Hydroxytyrosol, tyrosol, and oleuropein are the phenolic compounds that are mainly responsible for antioxidant activity of olive oil. Through antioxidant and anti-inflammatory mechanisms, olive oil leads to epigenetic, metabolic and physiologic changes, which protects human health. Due to this reason, regular consumption of olive oil may be effective to decrease the risk of chronic diseases.
MUFA | monounsaturated fatty acids |
SFA | saturated fatty acids |
LDL | low-density lipoprotein |
TG | triglycerides |
VLDL | very low-density lipoprotein |
CRP | C-reactive protein |
HDL | high-density lipoprotein |
Apo-A1 | apolipoprotein A1 |
PUFA | polyunsaturated fatty acids |
VOO | virgin olive oil |
EVOO | extra-virgin olive oil |
PREDIMED | Prevención con Dieta Mediterránea |
ROS | reactive oxygen species |
O2− | superoxide anion |
OH | hydroxyl radical |
H2O2 | hydrogen peroxide |
GSSG | oxidized glutathione |
GSH | glutathione |
GSH-Px | glutathione peroxidase |
TXB2 | thromboxane B2 |
LTB4 | leukotriene B4 |
IL-6 | interleukin-6 |
COX-1 | cyclooxygenase-1 |
COX-2 | cyclooxygenase-2 |
COX | cyclooxygenase |
ICAM-1 | intercellular adhesion molecule-1 |
VCAM-1 | vascular cells adhesion molecule-1 |
MCP-1 | monocyte chemotactic protein-1 |
NF-kB | nuclear factor kB |
OEA | oleoylethanolamide |
CB1 | cannabinoid receptors |
PPAR-α | proliferator-activated receptors-α |
TNF-α | tumor necrosis factor alpha |
HER2 | epidermal growth factor receptor |
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