Properties of lead-free piezoelectric ceramics. (1) BNT: (Bi1/2 Na1/2)TiO3, SBT: SrBi4Ti4O15, NCBT: (Na1/2Bi1/2)0.95Ca0.05Bi4Ti4O15, KNN: (K1/2Na1/2)NbO3, SBN: (Sr,Ba)Nb2O6, BT: BaTiO3; (2) HF: Hot Forging method, TGG: Templated grain growth method.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"6672",leadTitle:null,fullTitle:"Vignettes in Patient Safety - Volume 3",title:"Vignettes in Patient Safety",subtitle:"Volume 3",reviewType:"peer-reviewed",abstract:'Over the past decade it has been increasingly recognized that medical errors constitute an important determinant of patient safety, quality of care, and clinical outcomes. Such errors are both directly and indirectly responsible for unnecessary and potentially preventable morbidity and/or mortality across our healthcare institutions. The spectrum of contributing variables or "root causes" - ranging from minor errors that escalate, poor teamwork and/or communication, and lapses in appropriate protocols and processes (just to name a few) - is both extensive and heterogeneous. Moreover, effective solutions are few, and many have only recently been described. As our healthcare systems mature and their focus on patient safety solidifies, a growing body of research and experiences emerges to help provide an organized framework for continuous process improvement. Such a paradigm - based on best practices and evidence-based medical principles- sets the stage for hardwiring "the right things to do" into our institutional patient care matrix. 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Rajesh Banu",coverURL:"https://cdn.intechopen.com/books/images_new/6839.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"218539",title:"Dr.",name:"Rajesh",middleName:null,surname:"Banu",slug:"rajesh-banu",fullName:"Rajesh Banu"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},ofsBook:{item:{type:"book",id:"10708",leadTitle:null,title:"Topics in Regional Anesthesia",subtitle:null,reviewType:"peer-reviewed",abstract:"\r\n\tThe goal of this book on Topics in Regional Anesthesia is to review selected subjects of importance in daily practice. Since the first years of the introduction of cocaine by Carl Koller in 1884, the evolution of regional anesthesia has been continuous, gradual and safe. Its development has been based on anatomy, the pharmacology of local anesthetics and adjuvant drugs, as well as advances in the various blocking techniques, with ultrasound guidance being the most recent advent. The use of ultrasound in regional anesthesia has shown the reduction of complications, which makes it mandatory to knowledge and acquire skills in all ultrasound-guided techniques.
\r\n\r\n\tUltrasound-guided regional blocks will be reviewed extensively, as well as intravenous regional anesthesia, thoracic spinal anesthesia. The role of regional anesthesia and analgesia in critically ill patients is of paramount importance. In addition, we will review the current role of regional techniques during the Covid-19 pandemic. Complications and malpractice is another topic that should be reviewed. Regional anesthesia procedures in some specialties such as pediatrics, orthopedics, cancer surgery, neurosurgery, acute and chronic pain will be discussed.
",isbn:"978-1-83969-570-4",printIsbn:"978-1-83969-569-8",pdfIsbn:"978-1-83969-571-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"264f7f37033b4867cace7912287fccaa",bookSignature:"Prof. Víctor M. Whizar-Lugo and Dr. José Ramón Saucillo-Osuna",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10708.jpg",keywords:"Regional Anesthesia, Ultrasound-Guided Regional Anesthesia, Local Anesthetics, Preventive Analgesia, Peripheral Blocks, Pediatric Regional Anesthesia, Intravenous Regional Anesthesia, Techniques, Complications, Adjuvants in Regional Anesthesia, Opioids, Alfa2 Agonists",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 23rd 2021",dateEndSecondStepPublish:"March 23rd 2021",dateEndThirdStepPublish:"May 22nd 2021",dateEndFourthStepPublish:"August 10th 2021",dateEndFifthStepPublish:"October 9th 2021",remainingDaysToSecondStep:"18 days",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Whizar-Lugo has published more than 100 publications on Anesthesia, Pain, Critical Care, and Internal Medicine. He works as an anesthesiologist at Lotus Med Group and belongs to the Institutos Nacionales de Salud as an associated researcher.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"169249",title:"Prof.",name:"Víctor M.",middleName:null,surname:"Whizar-Lugo",slug:"victor-m.-whizar-lugo",fullName:"Víctor M. Whizar-Lugo",profilePictureURL:"https://mts.intechopen.com/storage/users/169249/images/system/169249.jpg",biography:"Víctor M. Whizar-Lugo graduated from Universidad Nacional Autónoma de México and completed residencies in Internal Medicine at Hospital General de México and Anaesthesiology and Critical Care Medicine at Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán in México City. He also completed a fellowship at the Anesthesia Department, Pain Clinic at University of California, Los Angeles, USA. Currently, Dr. Whizar-Lugo works as anesthesiologist at Lotus Med Group, and belongs to the Institutos Nacionales de Salud as associated researcher. He has published many works on anesthesia, pain, internal medicine, and critical care, edited four books, and given countless conferences in congresses and meetings around the world. He has been a member of various editorial committees for anesthesiology journals, is past chief editor of the journal Anestesia en México, and is currently editor-in-chief of the Journal of Anesthesia and Critical Care. Dr. Whizar-Lugo is the founding director and current president of Anestesiología y Medicina del Dolor (www.anestesiologia-dolor.org), a free online medical education program.",institutionString:"Institutos Nacionales de Salud",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"3",institution:null}],coeditorOne:{id:"345887",title:"Dr.",name:"José Ramón",middleName:null,surname:"Saucillo-Osuna",slug:"jose-ramon-saucillo-osuna",fullName:"José Ramón Saucillo-Osuna",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000033rFXmQAM/Profile_Picture_1611740683590",biography:"Graduated from the Facultad de Medicina de la Universidad Autónoma de Guadalajara, he specialized in anesthesiology at the Centro Médico Nacional de Occidente in Guadalajara, México. He is one of the most important pioneers in Mexico in ultrasound-guided regional anesthesia. Dr. Saucillo-Osuna has lectured at multiple national and international congresses and is an adjunct professor at the Federación Mexicana de Colegios de Anestesiología, AC, former president of the Asociación Mexicana de Anestesia Regional, and active member of the Asociación Latinoamericana de Anestesia Regional.",institutionString:"Centro Médico Nacional de Occidente",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"347258",firstName:"Marica",lastName:"Novakovic",middleName:null,title:"Dr.",imageUrl:"//cdnintech.com/web/frontend/www/assets/author.svg",email:"marica@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"6550",title:"Cohort Studies in Health Sciences",subtitle:null,isOpenForSubmission:!1,hash:"01df5aba4fff1a84b37a2fdafa809660",slug:"cohort-studies-in-health-sciences",bookSignature:"R. 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Mauricio Barría"}],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:"16758",title:"Magnetoelectric Multiferroic Composites",doi:"10.5772/16415",slug:"magnetoelectric-multiferroic-composites",body:'Magnetoelectric (ME) multiferroics are materials in which ferromagnetism and ferroelectricity occur simultaneously and coupling between the two is enabled. Applied magnetic field H gives rise to an induced polarization P which can be expressed in terms of magnetic field by the expression, P=αH, where α is the ME-susceptibility tensor. Most of the known single-phase ME materials are known to show a weak ME coupling (Fiebig, 2005; Kita et al., 1988; Wang et al., 2003; Prellier et al., 2005; Cheong et al., 2007). A composite of piezomagnetic and piezoelectric phases is expected to have relatively strong ME coupling. ME interaction in a composite manifests itself as inducing the electrical voltage across the sample in an applied ac magnetic field and arises due to combination of magnetostriction in magnetic phase and piezoelectricity in piezoelectric phase through mechanical coupling between the components (Ryu et al., 2001; Nan et al., 2008; Dong et al., 2003; Cai et al., 2004; Srinivasan et al., 2002).
In last few years, strong magneto-elastic and elasto-electric coupling has been achieved through optimization of material properties and proper design of transducer structures. Lead zirconate titanate (PZT)-ferrite and PZT-Terfenol-D are the most studied composites to-date (Dong et al., 2005; Dong et al.,2006b; Zheng et al., 2004a; Zheng et al., 2004b). One of largest ME voltage coefficient of 500 Vcm-1Oe-1 was reported recently for a high permeability magnetostrictive piezofiber laminate (Nan et al., 2005; Liu et al., 2005). These developments have led to magnetoelectric structures that provide high sensitivity over a varying range of frequency and DC bias fields enabling the possibility of practical applications.
In this paper, we focus on four broad objectives. First, we discuss detailed mathematical modeling approaches that are used to describe the dynamic behavior of ME coupling in magnetostrictive-piezoelectric multiferroics at low-frequencies and in electromechanical resonance (EMR) region. Expressions for ME coefficients were obtained using the solution of elastostatic/elastodynamic and electrostatic/magnetostatic equations. The ME voltage coefficients were estimated from the known material parameters. The basic methods developed for decreasing the resonance frequencies were analyzed. The second type of resonance phenomena occurs in the magnetic phase of the magnetoelectric composite at much higher frequencies, called as ferromagnetic resonance (FMR). The estimates for electric field induced shift of magnetic resonance line were derived and analyzed for varying boundary conditions. Our theory predicts an enhancement of ME effect that arises from interaction between elastic modes and the uniform precession spin-wave mode. The peak ME voltage coefficient occurs at the merging point of acoustic resonance and FMR frequencies.
Second, we present the experimental results on lead – free magnetostrictive –piezoelectric composites. These newly developed composites address the important environmental concern of current times, i.e., elimination of the toxic “lead” from the consumer devices. A systematic study is presented towards selection and design of the individual phases for the composite. Third, experimental data from wide range of measurement and literature was used to validate the theoretical models over a wide frequency range.
Lastly, the feasibility for creating new class of functional devices based on ME interactions is addressed. Appropriate choice of individual phases with high magnetostriction and piezoelectricity will allow reaching the desired magnitude of ME coupling as deemed necessary for engineering applications over a wide bandwidth including the electromechanical, magnetoacoustic and ferromagnetic resonance regimes. Possibilities for application of ME composites in fabricating ac magnetic field sensors, current sensors, transformers, and gyrators are discussed. ME multiferroics are shown to be of interest for applications such as electrically-tunable microwave phase-shifters, devices based on FMR, magnetic-controlled electro-optical and piezoelectric devices, and electrically-readable magnetic memories.
We consider only (symmetric) extensional deformation in this model and at first ignore any (asymmetric) flexural deformations of the layers that would lead to a position dependent elastic constants and the need for perturbation procedures. For the polarized piezoelectric phase with the symmetry m, the following equations can be written for the strain and electric displacement:
where pSi and pTj are strain and stress tensor components of the piezoelectric phase, pEk and pDk are the vector components of electric field and electric displacement, psij and pdki are compliance and piezoelectric coefficients, and pεkn is the permittivity matrix. The magnetostrictive phase is assumed to have a cubic symmetry and is described by the equations:
where mSi and mTj are strain and stress tensor components of the magnetostrictive phase, mHk and mBk are the vector components of magnetic field and magnetic induction, msij and mqki are compliance and piezomagnetic coefficients, and mμkn is the permeability matrix. Equation (Eq. 2.) may be considered in particular as a linearized equation describing the effect of magnetostriction. Assuming in-plane mechanical connectivity between the two phases with appropriate boundary conditions, ME voltage coefficients can be obtained by solving Eq. 1. and Eq. 2.
We assume (Eq. 1. and Eq. 2) as the film plane and the direction-3 perpendicular to the sample plane. The bilayer is poled with an electric field E along direction-3. The bias field H0 and the ac field H are along the same direction as E and the resulting induced electric field E is estimated across the sample thickness. Then we find an expression for ME voltage coefficient αE,L=αE,33=E3/H3. The following boundary conditions should be used for finding the ME coefficient:
where v=pv/(pv+\n\t\t\t\t\tmv) and pv and mv denote the volume of piezoelectric and magnetostrictive phase, respectively. Taking into account Eq. 1. and Eq. 2 and the continuity conditions for magnetic and electric fields, Eq. 3. and open circuit condition enables one to obtain the following expressions for longitudinal ME voltage coefficient.
In deriving the above expression, we assumed the electric field to be zero in magnetic phase since magnetostrictive materials that are used in the case under study have a small resistance compared to piezoelectric phase. Thus the voltage induced across the piezoelectric layer is the output voltage. Estimate of ME voltage coefficient for cobalt ferrite (CFO) gives αE,33=325 mV/(cm Oe). However, considering CFO as a dielectric results in αE,33=140 mV/(cm Oe) (Osaretin & Rojas, 2010) while the experimental value is 74 mV/(cm Oe) (Harshe et al., 1993). We believe CFO should be considered as a conducting medium compared to dielectric PZT in the low-frequency region in accordance with our model. The discrepancy between theoretical estimates and data can be accounted for by features of piezomagnetic coupling in CFO and interface coupling of bilayer (Bichurin et al., 2003a). Harshe et al. obtained an expression for longitudinal ME voltage coefficient of the form
The above equation corresponds to a special case of our theory in which one assumes m33/0=1. Thus the model considered here leads to an expression for the longitudinal ME coupling and allows its estimation as a function of volume of the two phases, composite permeability, and interface coupling.
This case corresponds to the poling direction along direction-3 and H0 and H along direction-1 (in the sample plane). Here we estimate the ME coefficient αE,T = αE,31 = E3/H1. Once again, Eq. 1. Eq. 2. and Eq. 3. lead to the following expression for transverse ME voltage coefficient.
Finally, we consider a bilayer poled with an electric field E in the plane of the sample. The in-plane fields H0 and H are parallel and the induced electric field E is measured in the same direction (axis-1). The ME coefficient is defined as αE,IL=αE,11=E1/H1. Expression for αE is given below.
The in-plane ME coefficient is expected to be the strongest amongst the cases discussed so far due to high values of q and d and the absences of demagnetizing fields.
Since the ME coupling in the composites is mediated by the mechanical stress, one would expect orders of magnitude stronger coupling when the frequency of the ac field is tuned to acoustic mode frequencies in the sample than at non-resonance frequencies. Two methods of theoretical modeling can be used for calculating the frequency dependence of ME coefficients by solving the medium motion equation. First approach rests on considering the structure as an effective homogeneous medium and implies the preliminary finding the effective low-frequency material parameters (Bichurin et al., 2003b). The second approach is based on using the initial material parameters of components. A recently reported attempt to estimate ME coefficients using this approach consists in supposing the magnetic layer to move freely, ignoring the bonding to piezoelectric layer while vibration of piezoelectric layer is supposed to be a combination of motions of free magnetic layer and free oscillations of piezoelectric layer (Filippov, 2004, 2005). In case of perfect bonding of layers, the motion of piezoelectric phase is described by magnetic medium motion equation. As a result, the expressions for ME coefficients appear inaccurate. Particularly, the expressions give a wrong piezoelectric volume fraction dependence of ME voltage coefficient.
This section is focused on modeling of the ME effect in ferrite-piezoelectric layered structures in EMR region. We have chosen cobalt ferrite (CFO) - barium titanate as the model system for numerical estimations. The ME voltage coefficients αE have been estimated for transverse field orientations corresponding to minimum demagnetizing fields and maximum αE. (Bichurin et al., 2010) As a model, we consider a ferrite-piezoelectric layered structure in the form of a thin plate with the length L.
We solve the equation of medium motion taking into account the magnetostatic and elastostatic equations, constitutive equations, Hooke\'s law, and boundary conditions. The equation of medium motion has the form:
where u1 is displacement in the traveling direction x. For the transverse fields’ orientation (poling direction of piezoelectric phase, dc and ac magnetic fields are parallel to x-axis), the wave value k is defined by expression:
where ω is the circular frequency, pρ and mρ are the piezoelectric and piezomagnetic densities, v = pv/(pv + mv), and pv and mv denote the volume of piezoelectric and phases, respectively. For the solution of the Eq. 8, the following boundary conditions are used: pS1 = mS1 and pT1 v + mT1 (1-v) =0 at x=0 and x=L, where L is the sample length. The ME voltage coefficient αE 13= E3/H1 is calculated from Eq. 8, Eq. 9. and using the open circuit condition D3=0.
where s2=vmsB11+(1-v)ps11 and eff is effective permeability of piezomagnetic layer. To take into consideration the energy loss, we set ω equal to ω´ - iω´´ with ω´´/ ω´ =10-3. The resonance enhancement of ME voltage coefficient for the bilayer is obtained at antiresonance frequency. ME voltage coefficient, αE, 13 increases with increasing barium titanate volume, attains a peak value for v = 0.5 and then drops with increasing v as in Fig. 1.
Frequency dependence of αE,13 for the bilayer with v=0.5
A key drawback for ME effect at longitudinal modes is that the frequencies are quite high, on the order of hundreds of kHz, for nominal sample dimensions. The eddy current losses for the magnetostrictive phase can be quite high at such frequencies, in particular for transition metals and alloys and earth rare alloys such as Terfenol-D, resulting in an inefficient magnetoelectric energy conversion. In order to reduce the operating frequency, one must therefore increase the laminate size that is inconvenient for any applications. An alternative for getting a strong ME coupling is the resonance enhancement at bending modes of the composite. The frequency of applied ac field is expected to be much lower compared to longitudinal acoustic modes. Recent investigations have showed a giant ME effect at bending modes in several layered structures (Xing et al., 2006; Zhai et al., 2008; Chashin et al., 2008). In this section, we focus our attention on theoretical modeling of ME effects at bending modes. (Petrov et al., 2009)
An in-plane bias field is assumed to be applied to magnetostrictive component to avoid the demagnetizing field. The thickness of the plate is assumed to be small compared to remaining dimensions. Moreover, the plate width is assumed small compared to its length. In that case, we can consider only one component of strain and stress tensors in the EMR region. The equation of bending motion of bilayer has the form:
where 22 is biharmonic operator, w is the deflection (displacement in z-direction), t and ρ are thickness and average density of sample, b= pt+ mt, ρ=(pρ pt + mρmt)/b, pρ, mρ, and pt, mt, are densities and thicknesses of piezoelectric and piezomagnetic, correspondingly, and D is cylindrical stiffness.
The boundary conditions for x=0 and x=L have to be used for finding the solution of above equation. Here L is length of bilayer. As an example, we consider the plate with free ends. At free end, the turning moment M1 and transverse force V1 equal zero: M1 =0 and V1 =0 at x=0 and x=L, where
where E3 and H1 are the average electric field induced across the sample and applied magnetic field. The energy losses are taken into account by substituting for complex frequency +i with /=10-3.
As an example, we apply Eq. 12 to the bilayer of permendur and PZT. Fig. 2 shows the frequency dependence of ME voltage coefficient at bending mode for free-standing bilayer with length 9.15 mm and thickness 3.22 mm for PZT volume fraction 0.67. Graph of αE,31 reveals a giant value αE 31=6.6 V/cm Oe and resonance peak lies in the infralow frequency range. Fig. 3 reveals the theoretical and measured frequency dependencies of transverse ME voltage coefficients for a permendur-PZT bilayer that is free to bend at both ends.
According to our model, there is a strong dependence of resonance frequency on boundary conditions. The lowest resonance frequency is expected for the bilayer clamped at one end. One expects bending motion to occur at decreasing frequencies with increasing bilayer length or decreasing thickness.
Frequency dependence of longitudinal and transverse ME voltage coefficients for a bilayer of permendur and PZT showing the resonance enhancement of ME interactions at the bending mode frequency. The bilayer is free to bend at both ends. The sample dimensions are L = 9.2 mm and total thickness t = 0.7 mm and the PZT volume fraction v=0.6.
Theoretical (line) and measured (circles) frequency dependence of transverse ME voltage coefficients for a permendur-PZT bilayer that is free to bend at both ends and with v=0.67.
In the case of inverse ME effect, external field E produces a deformation of piezoelectric layers due to piezoelectric coupling. The deformation is transmitted to magnetic layers. The inverse piezomagnetic effect results in a change of magnetic parameters of the structure. ME coefficient αH, ij=Hi/Ej can be easily found similarly to ME voltage coefficient using the open magnetic circuit condition, Bi=0. As an example, the expression for αH, 33 takes the form (Huang, 2006)
where k31 is the coupling coefficient for the piezoelectric phase, pv and mv are the volume fractions of piezoelectric and magnetostrictive components.
To obtain the inverse ME effect, a pick up coil wound around the sample is used to measure the ME voltage due to the change in the magnetic induction in magnetostrictive phase. The measured static magnetic field dependence of ME voltage has been attributed to the variation in the piezomagnetic coefficient for magnetic layer. The frequency dependence of the ME voltage shows a resonance character due to longitudinal acoustic modes in piezoelectric layer. Next we derive an expression for the ME susceptibility at EMR. (Fetisov et al., 2007) For the transverse field orientation, the equations for the strain tensor Si in the ferrite and piezoelectric and the magnetic induction B have the form
where ps11 and ms11are the components of the compliance tensor at constant electric field for piezoelectric and at constant magnetic induction for ferrite, respectively; m33 is the component of the permeability tensor, and pd31 and mq11 are the piezoelectric and piezomagnetic coefficients, respectively. Here we take into account only stress components along x axis, because close to EMR we can assume T1>>T2 and T3. Expressing the stress components via the deformation components and substituting these expressions into the equation of the medium motion, we obtain a differential equation for the x projection of the displacement vector of the medium (ux). Taking into account the fact that the trilayer surfaces at x=0 and x=L are free from external stresses, we find the solution to this equation. The magnetic induction arising due to the piezoelectric effect can be found from Eq. 15. The magnetic induction in the trilayer is expressed as:
where W and L are the width and length of the sample. The ME susceptibility is defined by
where
Theoretical (line) and measured (filled circles) ME susceptibility for the PZT-Ni-PZT trilayer structure.
A thorough understanding of high frequency response of a ferrite - piezoelectric composite is critically important for a basic understanding of ME effects and for useful technologies. In a composite, the interaction between electric and magnetic subsystems can be expressed in terms of a ME susceptibility. In general, the susceptibility is defined by the following equations for the microwave region (Kornev et al., 2000; Bichurin, 1994; Bichurin et al., 1990).
Here p is the electrical polarization, m is the magnetization, e and h are the external electrical and magnetic fields, χE and χM are the electrical and magnetic susceptibilities, and χEM and χME are the ME susceptibilities, with
We consider the magnetic susceptibility tensor of a composite which exhibits ME coupling. The sample is subjected to constant electric and magnetic fields and a ac magnetic field. The thermodynamic potential density can be written as:
where W0 is the thermodynamic potential density at Е = 0, and
Here Bikn and bijkn are linear and bilinear ME constants, respectively. The number of independent components is determined by the material structure. The main contribution to WМE arises from the linear ME constants Bikn in polarized composites. If the composite is unpolarized, the bilinear ME constants is dominant. We used the effective demagnetization factor method to solve the linearized equation of motion of magnetization and obtained the following expression for the magnetic susceptibility:
where
Here γ is the magneto-mechanical ratio, ω is the angular frequency,
where β is matrix of direction cosines of axes (
where
Eq. 23. enables us to determine the ME constants of a composite and consequently to interpret the obtained data on the resonant ME effect. As an example, we consider the composite with 3m or 4mm symmetry. The general expression for the magnetic susceptibility tensor of a disk sample magnetized along the symmetry axis has the form
where
Assuming the dissipative term in the equation of motion of magnetization as i(M0m)/M0, where is the dissipation parameter, the magnetic susceptibility tensor components are complex and take the form 1 = + i , where
It follows from Eq. 21. and Eq. 24 that the dependence of the magnetic susceptibility on an external constant electric field is resonant. The nature of this dependence can be explained as follows. By means of ME interactions, the external electric field results in a change in the effective magnetic field Heff in Eq. 24. with 2HME = 2M0(B31 – B33)E0 + 2M0(b31 – b33)E02. The change originates from the piezoelectric phase mechanically coupled to the magnetostrictive phase, and is phenomenological described by ME constants Bikn and bijkn in Eqs. 28 and 29. Thus the variation of the external constant electric field has the same effect as magnetic field variations and reveals a resonant behavior. Expressions for the susceptibility components could be obtained by using the demagnetization factors stipulated by ME interactions according to Eq. 26.
Next we consider specific composites and estimate the magnetic susceptibility and its electric field variation. (Bichurin et al., 2002) Three composites of importance for the estimation are lithium ferrite (LFO) - PZT, nickel ferrite (NFO) - PZT and yttrium iron garnet (YIG) - PZT because of desirable high frequency properties of LFO, NFO and YIG. We consider a simple structure, a bilayer consisting of single ferrite and PZT layers. In order to obtain the susceptibilities, one requires the knowledge of ME constants and the loss parameter. Assuming that the poling axis of the piezoelectric phase coincides with [100] axis of the magnetostrictive phase and │100│ = 1.410-6, 2310-6 and 4610-6 for YIG-PZT, LFO-PZT and NFO-PZT, respectively, we obtained 2M0(B31-B33) = 0.1, 0.6 and 1.4 Oecm/kV for the three bilayer samples. For LFO the following parameters are used: mc11 = 24.471010 N/m2; mc12 = 13.711010 N/m2; mc44 = 9.361010 N/m2; 4Ms =3600 G. Finally, the loss parameters are = 0.025, 0.05 and 0.075 for YIG-PZT, LFO-PZT and NFO-PZT, respectively. Figure 5 shows the static magnetic field dependencies of real and imaginary parts of magnetic susceptibility for layered LFO-PZT, NFO– PZT and YIG – PZT. The results are for a bilayer disk sample with the H and E-fields perpendicular to the sample plane and for a frequency of 9.3 GHz. The static field range is chosen to include ferromagnetic resonance in the ferrite. For E = 0, one observes the expected resonance in the profiles. With the application of E = 300 kV/cm, a down-shift in the resonance field is obvious. The magnitude of the shift is determined by ME constants which in turn is strongly influenced by the magnetostriction constant. The large magnetostriction for NFO leads to a relatively strong E-induced effect in NFO-PZT compared to YIG-PZT. The shift also correlates with resonance linewidth. It is possible to understand the correlation from the fact that the resonance linewidth is dependent on the effective anisotropy field, a parameter that is a function of the magnetostriction.
Figure 6 shows the estimated variation of the real and imaginary parts of the magnetic susceptibility as a function of E for a frequency of 9.3 GHz. The constant magnetic field is set equal to the field for ferromagnetic resonance (FMR). The width of resonance measured in terms of electric field is inversely proportional to the parameter 2M0(B31-B33). It follows from Eq. 29 that a narrow resonance is indicative of strong ME coupling in the composites. Thus NFO-PZT bilayer shows a sharp resonance in comparison to YIG-PZT.
Theoretical magnetic field dependence of the magnetic susceptibility for the multilayer composites of LFO-PZT (curves 1 and 2), NFO– PZT (curves 3 and 4) and YIG– PZT (curves 5 and 6) represents the real (a) and imaginary (b) parts of the susceptibility at 9.3 GHz. Curves 1, 3 are at E=0 and curves 2, 4 at E=300 kV/cm.
Figures 5. and 6. represent the magnetic spectra of the composites obtained by magnetic and electric sweep, respectively. Thus the presented model enables finding ME coefficients from data on the electric field induced shift of magnetic resonance line.
Theoretical electric field dependence of the magnetic susceptibility for the multilayer composites of LFO-PZT (curves 1), NFO– PZT (curve 2) and YIG– PZT (curve 3) represents the real (a) and imaginary (b) parts of the susceptibility at 9.3 GHz.
Here we provide a theory for ME interactions at the coincidence of FMR and EMR, at magnetoacoustic resonance (MAR). (Bichurin et al., 2005; Ryabkov et al., 2006) At FMR, spin-lattice coupling and spin waves that couple energy to phonons through relaxation processes are expected to enhance the piezoelectric and ME interactions. Further strengthening of ME coupling is expected at the overlap of FMR and EMR. We consider bilayers with low-loss ferrites such as nickel ferrite or YIG that would facilitate observation of the effects predicted in this work. For calculation we use equations of motion for the piezoelectric and magnetostrictive phases and equations of motion for the magnetization. Coincidence of FMR and EMR allows energy transfer between phonons, spin waves and electric and magnetic fields. This transformation is found to be very efficient in ferrite-PZT. The ME effect at MAR can be utilized for the realization of miniature/nanosensors and transducers operating at high frequencies since the coincidence is predicted to occur at microwave frequencies in the bilayers.
We consider a ferrite-PZT bilayer that is subjected to a bias field H0. The piezoelectric phase is electrically polarized with a field E0 parallel to H0. It is assumed that H0 is high enough to drive the ferrite to a saturated (single domain) state that has two advantages. When domains are absent, acoustic losses are minimum. The single-domain state under FMR provides the conditions necessary for achieving a large effective susceptibility. The free-energy density of a single crystal ferrite is given by mW = WH + Wan +Wma + Wac, where WH = - M Hi is Zeeman energy, M is magnetization, Hi is internal magnetic field that includes demagnetizing fields. The term Wan given by Wan = K1/M04(M12 M22+ M22 M32+ M32 M12) with K1 the cubic anisotropy constant and M0 the saturation magnetization. The magnetoelastic energy is written as Wma = B1/M02 (M12\n\t\t\t\tmS1 + M22\n\t\t\t\tmS2+ M32\n\t\t\t\tmS3) + B2/M02(M1 M2\n\t\t\t\tmS6 + M2 M3\n\t\t\t\tmS4 + M1 M3\n\t\t\t\tmS5) where B1 and B2 are magnetoelastic coefficients and Si are the elastic coefficients. Finally, the elastic energy is Wac= ½ mc11(mS12 + mS22 + mS32 ) +½ mc44 (mS42 + mS52 + “mc12 (mS1 mS2 + mS2 mS3 + mS1 mS3)” and mcij is modulus of elasticity.
The generalized Hook’s law for the piezoelectric phase can be presented as follows.
where ep15 is piezoelectric coefficient and pE is electric field. Equations of motion for ferrite and piezoelectric composite phases can be written in following form:
The equation of motion of magnetization for ferrite phase has the form
where Heff = - ∂ (mW)/∂ M. Solving Eqs. 31 and 32, taking into account Eq. 30 and open circuit condition, allows one to get the expression for ME voltage coefficient
where
Owing to the prohibition on the use of Pb-based materials in some commercial applications the demand for lead-free ceramics has grown considerably in the last decade. Various systems for nonlead ceramics have been studied and some of these have been projected as the possible candidates for the replacement of PZT. However, the dielectric and piezoelectric properties of all the known nonlead materials is inferior as compared to that PZT and this has been the stimulant for growing research on this subject. For high piezoelectric properties perovskite is the preferred crystallographic family and large piezoelectric and electromechanical constants are obtained from alkali-based ceramics such
The ME voltage coefficient aE vs. frequency profile for a bilayer of PZT of thickness 100 nm and YIG of thickness 195 nm and for dc magnetic field of 3570 (a) and 5360 (b) Oe. The FMR frequency coincides with fundamental ЕMR mode (a) and second EMR mode (b) frequency.
as (Na1/2Bi1/2)TiO3 (NBT), (K1/2Bi1/2)TiO3 (KBT) and (Na0.5K0.5)NbO3. Table VII.1 compares the properties of the PZT and the prominent non-lead based systems. The data shown in this table has been collected from various publications (Nagata & Takenaka, 1991; Sasaki et al., 1999; Kimura et al., 2002; Priya et al., 2003a, 2003b). It can be easily deduced from the data shown in this table that none of the nonlead ceramics qualifies for the direct replacement of PZT. (Na, K)NbO3 ceramics has good longitudinal mode and radial mode coupling factors along with high piezoelectric constants.
Symbol | 33T/0 | Qm | d33 (pC/N) | d31 (pC/N) | k33 (%) | kp (%) | Tc (C) | |
PZT (Mn, Fe doped) | PZT | 1500 | 1000-2000 | 300 | -100 | 60 | 50 | 300 |
(Bi,Na)TiO3 | BNT(1) | 600 | 500 | 120 | -40 | 45 | 25 | 260 |
Bi-layer | SBT(1) | 150 | "/>2000 | 20 | -3 | 20 | 3 | 550 |
NCBT(1) NCBT(1)(HF(2), TGG(2)) | 150 150 | 15 40 | -2 -2 | 15 40 | 2 2 | "/>500 "/>500 | ||
(Na,K)NbO3 | KNN(1) | 400 | 500 | 120 | -40 | 40 | 30 | 350 |
Tungsten Bronze | SBN(1) | 500 | 120 | 30 | 250 | |||
Others | BT(1) | 1100 | 700 | 130 | -40 | 45 | 20 | 100 |
Properties of lead-free piezoelectric ceramics. (1) BNT: (Bi1/2 Na1/2)TiO3, SBT: SrBi4Ti4O15, NCBT: (Na1/2Bi1/2)0.95Ca0.05Bi4Ti4O15, KNN: (K1/2Na1/2)NbO3, SBN: (Sr,Ba)Nb2O6, BT: BaTiO3; (2) HF: Hot Forging method, TGG: Templated grain growth method.
It is well known that the composition corresponding to 0.5/0.5 in the NaNbO3 – KNbO3 (KNN) system has the maximum in the piezoelectric properties. Table VII.2 compares the properties of the annealed and un-annealed KNN samples. KNN has an intermediate phase transition from the ferroelectric orthorhombic phase (FEo) to the ferroelectric tetragonal phase (FEt) at around 200 °C. It is believed that annealing the sample in the tetragonal phase induces (100) oriented domains at room temperature. Since the spontaneous polarization is along <110> in the orthorhombic phase, rapid cooling (100oC/min) from FEt phase (spontaneous polarization along <100>) results in titling of the polarization which provides enhancement of piezoelectric properties.
Sintering Temperature (oC) | Density (gm/cm3) | Log (.cm) | tan (%) | |
1150 | 4.23 | 9.4 | 10 | 720 |
1160 (Annealed) | 4.44 | 9.97 | 4.05 | 616 |
1160 (Unannealed) | 4.45 | 10.14 | 4.75 | 630 |
Properties of unpoled KNN ceramics showing the affect of annealing.
Figure 8 (a) and (b) shows the dielectric constant and loss as a function of temperature for the poled KNN sample. The room temperature dielectric constant is of the order of 350. The dielectric constant curve shows a discontinuity at ~180 °C and 400 °C. These discontinuities are related to the transition from FEo phase to FEt phase and FEt phase to PEc. In the range of 0 – 180 °C, the dielectric loss magnitude remains in the range of 4.2 – 4.5%. No significant difference was observed in the dielectric behavior of the annealed and unannealed samples below 200 °C.
Temperature dependence of dielectric constant and loss for KNN. (a) Dielectric constant and (b) Dielectric loss.
The magnitude of piezoelectric constants at room temperature for annealed samples was found to be: d33 = 148 pC/N and d31 = 69 pC/N. The magnitude of d33 for the unannealed sample was found to be 119 pC/N. Figure 9 (a) and (b) shows the radial mode electromechanical coupling factor (kp) and mechanical quality factor (Qm) as a function of temperature. It can be clearly seen that piezoelectric properties remain almost constant until the FEt phase appears at 180 °C. The magnitude of kp at room temperature is of the order of 0.456 and Qm is around 234. Since in this system the high temperature phase (FEt) is also ferroelectric there is no danger of depoling on exceeding the transition temperature. This provides a considerable advantage over the competing NBT-KBT and NBT-BT systems and for this reason KNN ceramics are the most promising high piezoelectric non-lead system.
Temperature dependence of piezoelectric properties for KNN. (a) Radial mode coupling factor and (b) Mechanical quality factor.
Further improvement in the properties of KNN can be obtained by synthesizing solid solution (1-x)(Na0.5K0.5)NbO3-xBaTiO3. Three phase transition regions exist in (1-x)(Na0.5K0.5)NbO3-xBaTiO3 ceramics corresponding to orthorhombic, tetragonal, and cubic phases. The composition 0.95(Na0.5K0.5)NbO3-0.05BaTiO3, which lies on boundary of orthorhombic and tetragonal phase, was found to exhibit excellent piezoelectric properties. The piezoelectric coefficients of this composition were measured on a disk-shaped sample and were found to be as following: kp=0.36, d33=225 pC/N and ε33T/ε0=1058 (Ahn et al., 2008). The properties of this composition were further improved by addition of various additives making it suitable for multilayer actuator application. The composition 0.06(Na0.5K0.5)NbO3-0.94BaTiO3 was found to lie on the boundary of tetragonal and cubic phase. This composition exhibited the microstructure with small grain size and excellent dielectric properties suitable for multi-layer ceramic capacitor application. Table 3 shows the piezoelectric properties of modified 0.95(Na0.5K0.5)NbO3-0.05BaTiO3 (KNN-BT) ceramics. It can be seen from this table that excellent piezoelectric properties with high transitions temperatures can be obtained in this system making it a suitable candidate for lead – free magnetoelectric composite.
The choice for the magnetostrictive phase in sintered or grown composites is spinel ferrites. In the spinel ferrites, the spontaneous magnetization corresponds to the difference between the sublattice magnetizations associated with the octahedral and tetrahedral sites. Results have shown enhanced magnitude of the ME coefficient for Ni0.8Zn0.2Fe2O4 (NZF) and Co0.6Zn0.4Fe2O4 (CZF). In the nickel zinc ferrite solid solution (Ni1-xZnxFe2O4) as x is increased Zn2+ replaces Fe3+ in the tetrahedral sites and Fe3+ fills the octahedral sites emptied by Ni2+. The net magnetization of nickel zinc ferrite is proportional to 5(1 + x) + 2(1 - x) - 0(x) - 5(1 - x) = 2 + 8x. Thus, the magnetic moment as a function of the Zn content increases until there are so few Fe3+ ions remaining in tetrahedral sites that the superexchange coupling between tetrahedral and octahedral sites breaks down. Figure 10 shows our results on the PZT – NZF and PZT – CZF composites. It can be seen from this figure that CZF is a hard magnetic phase, requires higher DC bias, has lower remanent magnetization and results in larger reduction of the ferroelectric polarization as compared to NZF. On the other hand, a high increase in the resistivity of the Ni-ferrites is obtained by doping with Co. Thus, a combination of NZF and modified KNN-BT phase presents an opportunity to develop magnetoelectric composites with reasonable magnitude of coupling coefficient. Figure 11 (a) and (b) shows the ME response of (1-x) [0.948K0.5Na0.5NbO3 – 0.052LiSbO3] – x Ni0.8Zn0.2Fe2O4 (KNNLS-NZF) composites. A reasonable magnitude of ME coefficient was obtained for the sintered composites (Yang et al., 2011). Compared to PZT based ceramics, this magnitude is about 50% smaller in magnitude.
Additives (in 0.95NKN-0.05BT) | d33 (pC/N) | kp | 3T/0 | Qm | Tc (°C) | Sin. T. (°C) |
None 40,41 | 225 | 0.36 | 1,058 | 74 | 320 | 1,060 |
0.5 mol% MnO2 53 | 237 | 0.42 | 1,252 | 92 | 294 | 1,050 |
1.0 mol% ZnO | 220 | 0.36 | 1,138 | 71 | - | 1,040 |
2.0 mol% CuO 47,54 | 220 | 0.34 | 1,282 | 186 | 286 | 950 |
2.0 mol% CuO + 0.5 mol% MnO2 54 | 248 | 0.41 | 1,258 | 305 | 277 | 950 |
Piezoelectric and dielectric properties of 0.95(Na0.5K0.5)-0.05BaTiO3 + additives.
Comparison of magnetic properties for PZT-NZF and PZT-CZF.
ME coefficient and Hbias for (1-x) KNNLS – x NZF composites.
The working principle of magnetic sensing in the ME composites is simple and direct. (Nan et al., 2008) When probing a magnetic field, the magnetic phase in the ME composites strains, producing a proportional charge in the piezoelectric phase.
Highly sensitive magnetic field sensors can be obtained using the ME composites with high ME coefficients. The ME composites can be used as a magnetic probe for detecting ac or dc fields.
Apart from a bimorph, a multilayer configuration of ME laminates has been reported that enables ultralow frequency detection of magnetic field variations. This configuration can greatly improve the low-frequency capability because of its high ME charge coupling and large capacitance. At an extremely low frequency of f =10 mHz, the multilayer ME laminates can still detect a small magnetic field variation as low as 10−7 T.
ME transformers or gyrators have important applications as voltage gain devices, current sensors, and other power conversion devices. An extremely high voltage gain effect under resonance drive has been reported in long-type ME laminates consisting of Terfenol-D and PZT layers. A solenoid with n turns around the laminate that carries a current of Iin was used to excite a Hac. The input ac voltage applied to the coils was Vin. When the frequency of Hac was equal to the resonance frequency of the laminate, the magnetoelectric voltage coefficient was strongly increased, and correspondingly the output ME voltage (Vout) induced in the piezoelectric layer was much higher than Vin. Thus, under resonant drive, ME laminates exhibit a strong voltage gain, offering potential for high-voltage miniature transformer applications. Figure 12 shows the measured voltage gain Vout /Vin as a function of the drive frequency for a ME transformer consisting of Terfenol-D layers of 40 mm in length and a piezoelectric layer of 80 mm in length. A maximum voltage gain of 260 was found at a resonance frequency of 21.3 kHz. In addition, at the resonance state, the maximum voltage gain of the ME transformer was strongly dependent on an applied Hdc, which was due to the fact that Terfenol-D has a large effective piezomagnetic coefficient only under a suitable Hdc. Other reports have shown that a ME laminate with a coil carrying current Iin has a unique current-to-voltage I-V conversion capability. ME laminates actually act as a I-V gyrator, with a high I-V gyration coefficient (Dong et al., 2006a; Zhai et al., 2006). Fig. 13 shows ME gyration equivalent circuit. At electromechanical resonance, the ME gyrator shows a strong I-V conversion of 2500 V/A, as shown in Fig. 10.
We also observed (i) reverse gyration: an input current to the piezoelectric section induced a voltage output across coils, and (ii) impedance inversion: a resistor Ri connected in parallel to the primary terminals of the gyrator resulted in an impedance G2 /Ri in series with the secondary terminals.
Ferrite–ferroelectric layered structures are of interest for studies on the fundamentals of high-frequency ME interaction and for device technologies. Such composites are promising candidates for a new class of dual electric and magnetic field tunable devices based on ME interactions (Bichurin et al., 2005; Tatarenko et al., 2006). An electric field E applied to the composite produces a mechanical deformation in the piezoelectric phase that in turn is coupled to the ferrite, resulting in a shift in the FMR field. The strength of the interactions is measured from the FMR shifts.
I-V gyration of the ME gyrator.
Ferrite–ferroelectric layered structures enable new paths for making new devices:
(1) Resonance ME effects in ferrite–piezoelectric bilayers, at FMR for the ferrite. The ME coupling was measured from data on FMR shifts in an applied electric field E. Low-loss YIG was used for the ferromagnetic phase. Single crystal PMN–PT and PZT were used for the ferroelectric phase; (2) Design, fabrication, and analysis of composite based devices, including resonators and phase shifters. The unique for such devices is the tunability with E. Our studies on YIG–PZT composites resulted in the design and characterization of a new class of microwave signal processing devices including resonators, filters, and phase shifters for use at 1–10 GHz. The unique and novel feature in ME microwave devices is the tunability with an electric field. The traditional “magnetic” tuning in ferrite devices is relatively slow and is associated with large power consumption. The “electrical” tuning is possible for the composite and is much faster and has practically zero power consumption.
ME gyration equivalent circuit.
The studies on microwave ME effects in YIG–PZT, YIG–PMNPT, and YIG–BST led to the design, fabrication, and characterization of a new family of novel signal processing devices that are tunable by both magnetic and electric fields. The device studied included YIG–PZT and YIG–BST resonators, filters, and phase shifters. As an example, a stripline ferrite–ferroelectric band-pass filters is considered. Design of our low-frequency ME filter is shown in Fig. 14 and representative data on electric field tuning are shown in Fig. 15. The single-cavity ME filter consists of a dielectric ground plane, input and output microstrips, and an YIG–PZT ME-element. Power is coupled from input to output under FMR in the ME element. A frequency shift of 120 MHz for E = 3 kV/cm corresponds to 2% of the central frequency of the filter and is a factor of 40 higher than the line width for pure YIG. Theoretical FMR profiles based on our model are shown in Fig. 6 for bilayers with YIG, NFO, or LFO and PZT. For E = 300 kV/cm, a shift in the resonance field δHE that varies from a minimum of 22 Oe for YIG/PZT to a maximum of 330 Oe for NFO–PZT is predicted. The strength of ME interactions A = δHE/E is determined by piezoelectric coupling and magnetostriction.
ME band-pass filter. The ME resonator consisted of a 110 µm thick (111) YIG on GGG bonded to PZT.
Loss vs. f characteristics for a series of E for the YIG–PZT filter.
It is clear from the discussions here that ME interactions are very strong in the microwave region in bound and unbound ferrite–ferroelectric bilayers and that a family of dual electric and magnetic field tunable ferrite–ferroelectric resonators, filters, and phase shifters can be realized. The electric field tunability, in particular, is 0.1% or more of the operating frequency of filters and resonators. A substantial differential-phase shift can also be achieved for nominal electric fields.
We discussed detailed mathematical modeling approaches that are used to describe the dynamic behavior of ME coupling in magnetostrictive-piezoelectric multiferroics at low-frequencies and in electromechanical resonance (EMR) region. Our theory predicts an enhancement of ME effect that arises from interaction between elastic modes and the uniform precession spin-wave mode. The peak ME voltage coefficient occurs at the merging point of acoustic resonance and FMR frequencies. The experimental results on lead – free magnetostrictive –piezoelectric composites are presented. These newly developed composites address the important environmental concern of current times, i.e., elimination of the toxic “lead” from the consumer devices. A systematic study is presented towards selection and design of the individual phases for the composite.
There is a critical need for frequency tunable devices such as resonators, phase shifters, delay lines, and filters for next generation applications in the microwave and millimeter wave frequency regions. These needs include conventional radar and signal processing devices as well as pulse based devices for digital radar and other systems applications. For secure systems, in particular, one must be able to switch rapidly between frequencies and to do so with a limited power budget. Traditional tuning methods with a magnetic field are slow and power consumptive. Electric field tuning offers new possibilities to solve both problems.
Ferrite–piezoelectric composites represent a promising new approach to build a new class of fast electric field tunable low power devices based on ME interactions. Unlike the situation when magnetic fields are used for such tuning, the process is fast because there are no inductors, and the power budget is small because the biasing voltages involve minimal currents. The critical goal for the future is in the development of a wide class of efficient wide band and low-loss electrically tunable magnetic film devices for battlefield radar, signal processing, and secure and experimental evaluation of characteristics. The anticipated advantages of ME devices are yet to be exploited.
The concept of frailty is frequently mentioned in studies related to the elderly population—health status, self-care dependence, healthcare resources or even the configuration of the wards where care is provided. Looking at the scientific knowledge and clinical practice, frailty in the elderly is considered a relevant dimension of quality of life. Moreover, there is a tendency to accept that individuals with severe frailty have to be considered vulnerable and should be protected.
Frailty has been viewed as a cornerstone of geriatric medicine and a platform of biological vulnerability to a host of other geriatric syndromes and adverse health outcomes [1], such as long-term nursing home stay, injurious falls and death, in community-dwelling older adults independent of medical comorbidities and age. The expression “frailty elderly” was used for the first time in 1970, by researchers from the Federal Council on Aging (FCA) of the United States, with the purpose of describing elderly people who lived in unfavourable socioeconomic conditions and presented physical weakness and cognitive deficit that, with advancing age, began to demand more care; in the 1980s, frailty in the elderly people was understood mainly as synonymous of disability or the presence of a disease, chronic or extreme condition linked with ageing [2]. In 1990, the expression “frailty elderly” was referred for the first time on the Journal of the American Geriatrics Society index [2].
The term “frailty” started to be used frequently in terms of diagnosis, clinical decisions and provision of care. Frailty and cognitive and functional decline are relatively common in older dependent people with health problems. One of the challenges for researchers today has been to study the physical characteristics and psychological symptoms of frailty and to relate them to adverse health outcomes. In this chapter, we intend to analyse the matters that have most attracted the attention of researchers and health professionals who deal with people in situations of frailty.
Understanding frailty has become crucial for caring for the elderly. In older people with dementia, the assessment of frailty is more important than determining the degree of dementia, since it is crucial to develop appropriate care people need; there are old people with moderate dementia but with a severe level of frailty.
In this chapter, we intend to review the concepts of frailty, operationalization strategies and assessment tools and clarify some ideas from the debate on what frailty is.
The concept of frailty has grown in importance because of a need to evaluate the health status of older persons and a need to prevent or at least delay the onset of late-life disability and its adverse consequences [3]. There is to date no clear consensus regarding the definition of frailty; some definitions have been proposed, each with their own strengths and weaknesses [3].
Frailty is a multidimensional concept and can be defined as a dynamic state that affects an individual with declines in one or more domains, such as physical, cognitive, social, attention or senses [4]. There is usually a dependence on self-care and need of support from others. Elderly does not mean frailty, but the ageing process led to frailty, which means that there are changes that reflect ageing-related alterations and involve intrinsic and extrinsic factors which are typical of ageing.
The occurrence of frailty is mainly a state of vulnerability resulting from comorbidities and the overall decline in organ functions. The progression to later stages of dementia often signals a loss of autonomy, dependence and reduction in physical and cognitive function. Frailty of people is positively related with their caregiver burden and associated with higher levels of depression on the caregiver. A lack of understanding about frailty has been identified as a barrier to providing optimal care to elderly people, for example, people with advanced dementia [4].
Frailty is an emerging concept used in the field of geriatrics and gerontology, to make reference to the clinical condition of the elderly. There is a deficit of information regarding the incidence and prevalence of frailty in the elderly, mainly due to the lack of consensus definition that can be used as reference in different populations. There is usually a “clinical sense” about what is frailty and what a frail elderly person is, but there is no agreement, a standard definition regarding this concept, that can assist in the diagnosis of frailty condition. As mentioned above, frailty is often considered an inherent condition of ageing, an attitude that can cause late interventions with minimal potential for prevention or reversing the consequences and adverse effects from the problem.
The concept of frailty, widely used in the recent years, focuses primarily on the physical dimensions. That is why it is understood that the criteria for assessing presence/absence are the physical signs and symptoms, sedentary behaviour, weight loss, exhaustion, slowed gait, decreased muscle strength, with three or more of these five criteria we are facing physical frailty and the presence of one or two criteria indicates pre-physical frailty [5].
The diagnosis of frailty relies currently on the assessment of a small subset of easily measurable clinical markers. Just as conceptual disagreements arise about what frailty means, there are also disagreements about how to evaluate it. While recognizing the multifactorial nature of frailty, it is important to develop an “operational definition” of frailty that is simple enough to be used clinically and to guide prevention and care [3].
Frailty among older persons appears in the investigation as a dynamic process, characterized by frequent changes over time. The evolution of frailty incorporates quantitative and qualitative data, which motivated researchers to invest in modelling. Recent studies have highlighted age, medical factors and higher socioeconomic status to be protective [6]. In the study carried out by the Canadian Study of Health and Aging (CSHA) [6], it was concluded that cognitive status and frailty are associated. Functional decline contributes to increase costs in caring for people with dementia. Despite all the research related to Alzheimer’s disease, very little has been indicated as effective therapies to deal with the disease, although it is known that cognitive decline is one of the first symptoms to appear and that interventions at this level can delay the evolution of the disease [6].
Andrade et al. [2] state that currently, two research groups have distinguished in the pursuit of consensus on the definition of frailty in the elderly: one of them in the United States, at the Johns Hopkins University, and the other one in Canada, the Canadian Initiative on Frailty and Aging (CIF-A). The group of researchers from the Johns Hopkins University produced an operational definition of frailty in the elderly and proposed measurable and objective criteria to the phenomenon. This operational definition starts from the hypothesis that the term is a geriatric syndrome and it can be identified by means of a phenotype that includes five measurable components: (a) unintentional weight loss, greater than 4.5 kg or more than 5% of body weight in the last year; (b) signs of fatigue; (c) reduction of handgrip strength, assessed with a specific instrument and adjusted to the person’s sex and body mass; (d) little physical activity assessed by calorie consumption (measured in kcal), adjusted by sex; and (e) reduction of march activity in seconds, distance of 4.5 m adjusted by gender and height [2].
A second definition was formulated by researchers from the CIF-A, indicated above. This is based on a multidimensional construct—frailty was defined using a more holistic approach, which emphasizes the complex aetiology of the phenomenon, understood as a not optimal condition in elderly, multifactorial and dynamic in nature, relating it to its history or trajectory of life [2]. The indicated trajectory can be shaped by biological, psychological and social, whose interactions result in resources and/or individual deficits in a given context. A tool was developed to measure frailty in the elderly—the Edmonton Frail Scale (EFS)—contemplating nine domains: (I) cognition, (II) general state of (III) functional independence, (IV) support, (V) medication use, (VI) nutrition, (VII) humour, (VIII) continence and (IX) functional performance. These authors consider this scale more comprehensive, especially considering aspects of cognition, humour and social support [2].
Some definitions of frailty promote a multidimensional approach based on an evaluation according to “frailty indexes”, which are calculated considering the accumulation of possible deficits, such as the presence of diseases, abnormal laboratory values, signs and symptoms or disabilities [7, 8].
It is difficult to establish a typology of frailty, given its multidimensional nature. On the one hand, frailty results from an articulation of factors of a physical and psychological nature. On the other hand, it is possible to assess frailty to highlight one or another aspect. Also, the investigation indicates that emotional management strategies can interfere with the signs and symptoms of frailty and with the ability to adjust to different disabilities.
Given the definitive trends in frailty, and although the creation of a typology is sometimes an academic task, we will try to describe four types of frailty in the elderly, on the assumption that they intersect and present common dimensions: physical, cognitive, social and emotional.
Frailty is a clinical situation known for the great vulnerability of the person in terms of the different physiological systems. In addition to the physical dimension, frailty is characterized by problems at the social, emotional and cognitive levels, despite the possibility of delaying its evolution in early stages [3, 9]. Fried et al. [10] proposed a clinical phenotype of frailty, defining it as a situation of increased vulnerability in the person for homeostatic resolution after pronounced distress. This growing vulnerability increases the risk of adverse outcomes, such as falls, fractures, hospitalization and ultimately mortality in elderly people living in organizations in the community or in their own homes.
Four main mechanisms can be identified in the progression of frailty: atherosclerosis, sarcopenia, cognitive deterioration and malnutrition [11]. It has been proven that malnutrition can be the cause of cognitive and functional decline and that the lack of some nutrients can cause cognitive frailty and vascular dementia [11].
There is an evident relationship between functionality and cognition, as evidenced by research evidence and some assessment tools (e.g., Clinical Dementia Rating). Many cross-sectional studies demonstrated the relationship between general cognitive function, emotions and physical frailty [12]. However, it is important to keep in mind that the decline in cognition and capacity of emotional management, given its functions and nature, evokes so many limitations to functionality that it becomes relevant to consider a cognitive frailty as a specific type.
Many studies have focused on the proposed entity of “cognitive frailty” to describe a clinical condition that is characterized by simultaneous occurrence of physical frailty and cognitive impairment in the absence of overt dementia [13]. Alzheimer’s disease is characterized by an association between physical and cognitive decline, but in the opposite direction, people with physical limitations are more predisposed to suffer emotional and cognitive problems. However, it should be noted that in recent years studies are more focused on physical frailty, with a relative paucity of data available for concomitant transitions in cognitive status [6].
An International Consensus Group studied the “cognitive frailty” condition. “Cognitive frailty”, although so defined, implies the presence of physical and cognitive decline. The key symptoms to characterize cognitive frailty are as follows: (1) presence of physical frailty and cognitive impairment and (2) exclusion from the concomitant presence of any type of dementia [14]. At the same time, the group indicated that “cognitive frailty” implies a rigorous diagnosis in terms of memory performance but also of other cognitive functions [14].
“Cognitive frailty” could represent a cognitive entity with specific neuropsychological patterns (executive and selective attention) [14]. The mechanisms in action and how deterioration occurs are not yet fully understood.
The loss of emotional management capacities and of establishing social interactions generates potential situations of frailty. It is also evident that any types of frailty (physical or psychological) also interfere with the emotional and social spheres. Usually, people with frailty (with cognitive impairment) experienced high levels of emotional discomfort and behavioural changes. Even without significant cognitive changes, symptoms usually emerge that emphasize the importance of emotions and social interactions: sadness, loneliness, nervousness, concern for oneself, self-concept, self-care and sense of hope.
The relationship between emotions, behaviour and frailty emerges in studies that explore this association. Emotion, which can be considered positive or negative, interferes with the perception of self-efficacy and the subjective sense of well-being. Furthermore, studies conducted in older adults found that positive emotions were associated with lower disability in the execution of daily living activities, higher levels of mobility, less physical dependence and major likelihood of survival, as well as higher level of adjustment to chronic health problems; on the other hand, negative emotions are correlated with stress sensations and poor coping abilities [15].
Clark and Watson [16] emphasize the relationship between emotions and functionality, which is understood by the well-known association between emotions and behaviour. They concluded, in a study carried out with older adults, that positive emotions may be associated with lower disability in the execution of daily living activities, better mobility, good functional status and major likelihood of survival; on the contrary, negative emotions can be correlated with distress and poor coping abilities. Mulasso et al. [15] provide empirical evidence to the multidimensional theorization and definition of frailty, hypothesizing that a reduced level of positive emotions and high level of negative emotions may contribute to increases in the severity of frailty condition; on the other hand, they highlighted the role of emotion experience in interventions for the prevention of frailty, such as interventions of physical exercise or cognitive training associated with frequent experience of positive emotions.
Simultaneously, studies emphasize also the need to identify risks for frailty [4, 6, 9]. All dimensions that constitute limitations on functionality, carrying out activities of daily living, cognitive impairment and social isolation can and should be considered risks for frailty [4]. There are currently models, mathematical equations and Bayesian networks that allow identifying these risks and even predicting them, conjugating certain variables. Usually, these models take into account demographic, social and clinical variables. These models can have good performance, isolated or conjugated with other evaluation tools. Moreover, they can predict frailty evolution and enable dependent persons to be identified for further specific assessment or interventions.
There are many studies that explore frailty, types of frailty and predictors of frailty every year. The relationship between frailty and functionality and the psychological sphere and relationship between the frailty of the recipient of care and burden on the caregiver are increasingly studied.
Armstrong et al. [17] used of a large database (n = 23,952) with comprehensive health information on home care clients (aged 65+) of eight Community Care Access Centres (CCACs) in Ontario, Canada. In this large cohort of older home care clients, they found that greater evidence of frailty as defined by each of the three measures was associated with greater risk of adverse outcomes. This result additionally confirmed the potential utility of a frailty concept for identifying vulnerable individuals within the home healthcare sector. They concluded that mathematical models can utilize data collected during clinical assessments to provide a quantitative indicator of a client’s level of frailty.
Dudzińska-Griszek, Szuster and Szewieczek [18] developed a study whose aim was to assess conditions that influence grip strength in geriatric inpatients. A comprehensive geriatric assessment was complemented with assessment for the frailty phenotype. Functional assessment included Barthel Index of Activities of Daily Living (Barthel Index), Instrumental Activities of Daily Living Scale and Mini-Mental State Examination. The conclusion was that cognitive function, somatic comorbidity and medical treatment affect grip strength as a measure of physical frailty in geriatric inpatients.
A retrospective cohort study on 18,341 Medicare Advantage enrollees aged 65+ was conducted by Anzaldi et al. [19] in Massachusetts. When analysing the clinical information systems, they identified the presence of 10 syndromes commonly found in the elderly (falls, malnutrition, dementia, severe urinary incontinence, absence of faecal control, visual impairment, walking impairment, pressure ulcers, lack of social support and weight loss), as well as references to the presence of frailty identified in the natural language processing (NLP) algorithm. The main conclusion was that patients identified as “frail” by providers in clinical notes have higher rates of healthcare utilization and more geriatric syndromes than other patients. Certain geriatric syndromes were more highly correlated with descriptions of frailty than others.
Shimada et al. [20] studied the cognitive frailty in 4570 older adults. The aim of the study was to analyse the extent to which a new perspective of cognitive frailty could be considered as a predictor of dementia. There are 2326 women and the average age was 71.9 ± 5.5 years. Physical frailty was defined as the presence of more than one of these symptoms: slow walking speed and muscle weakness. Cognitive frailty was defined as comorbid physical frailty and cognitive impairment. They concluded that cognitive impairment and cognitive frailty could be considered risk factors for dementia. Findings showed clearly that individuals with comorbid physical frailty and cognitive impairment could have a higher risk of dementia than healthy older adults or older adults with either physical frailty or cognitive impairment alone.
The estimation of the prevalence of frailty in patients admitted to intensive care unit (ICU) and its impact on intra-ICU mortality, at 1 month and at 6 months, was developed by Cuenca et al. [21]. A prospective cohort study was conducted. Frailty was present in 35% of patients admitted to the ICU, associated with higher rates of mortality.
Ma et al. [22] carried out a study to determine social frailty status via developing a simple self-reported screening tool, termed the HALFT scale, and to examine the association between social frailty and physical functioning, cognition, depression and mortality among community-dwelling older adults. They state that social frailty is related to adverse health-related outcomes. Moreover, they added that research into the relationship between social frailty and physical functioning remains limited. A prospective cohort study was carried out, with 1697 community-dwelling adults aged ≥60 years from Beijing. The scale developed was based on five items: unhelpful to others, limited social participation, loneliness, financial difficulty and not having anyone to talk to.
The prevalence of social frailty in the participants was 7.7%. Social frailty was positively associated with physical frailty, low levels of physical activity and poor physical functioning. Researchers also found that social frailty was associated with dementia, memory decline, depression and cognitive impairment. Having experienced a negative or traumatic event was also associated with social frailty. Additionally, social frailty was associated with physical functioning, cognition and depression and predicts mortality; they emphasize that interventions aimed at preventing or delaying social frailty are warranted.
In a cross-sectional study carried out by Mulasso et al. [15] the association between frailty and emotional experience was studied in a sample of Italian community-dwelling older adults. Participants consisted of 104 older adults (age 76 ± 8 years; 59.6% women) living in Italy. Frailty and emotion perception were measured with appropriate and valid tools. The Mini-Mental State Examination was used as a screening tool for cognitive functions (people with a score ≤ 20 points were excluded). The researchers stated that frailty increases individual vulnerability to external stressors and involves high risk for adverse geriatric outcomes [15]; findings demonstrate that emotion perception may influence frailty, which is really relevant for the evaluation and prevention of frailty in older adults.
A theoretical study based on research studies that equate the role of nutrition and nutrients in cognitive and functional decline was developed by Gomez-Gomez and Sapico [23]. They state that one of the most important factors to consider in the development of cognitive deterioration is oxidative stress. Consequently, they added that increasing antioxidants in the diet may be one of the therapeutic strategies in the management of these patients.
Some studies were analysed, mainly those that showed the effectiveness of antioxidants in the adjustment of oxidative stress, given their function as free radical scavengers, or factors that potentiate the antioxidant effect. Anyway, the studies emphasized that the inappropriate use of antioxidants could have side effects and become toxic at high doses. Given the multiplicity and some divergence in the results, additional studies are required as well as clinical trials to increase the clinical effectiveness [23].
Several studies were analysed, namely, those that have shown the effectiveness of antioxidants in the adjustment of oxidative stress, either by their function as free radical scavengers or potentiating the antioxidant effect. Studies showed that the inappropriate use of antioxidants could have side effects and toxicity at high doses. However, it was indicated that additional studies are required as well as clinical trials to increase the clinical effectiveness [23].
Abreu et al. [4] examined the healthcare needs of community-dwelling older people, trying to understand the relationship between frailty, functional dependence and healthcare needs among community-dwelling people with moderate to severe dementia. A sample of 83 participants was recruited. The Edmonton Frail Scale was used to evaluate frailty, in addition to tools that were chosen to collect data on other variables. A set of 26 healthcare needs was defined to support the assessment. There was a significant association between “severe frailty” and “severe dementia” and “fully dependent” and “severely or fully dependent in the activities of daily living”. The most prevalent healthcare needs in the sample were food preparation, medication/taking pills, looking after their home, toilet use, sensory problems, communication/interaction, bladder, bowels, eating and drinking, memory, sleeping and fall prevention. In particular, the study shows a set of needs that are present simultaneously in both frailty and dementia stages, according to their severity. They found in the study that 16.7% of people with moderate dementia were also diagnosed with severe frailty. Concerning the needs assessment, the authors state that the concept of “severe dementia” is clearly a limiter in the matter of frailty. As an alternative, they suggest the expression of “advanced dementia”, encompassing people with severe dementia and people with moderate dementia but who also have severe frailty.
Usually, scales assess some domains of frailty in old people (cognition, general health status, functional independence, social support, medication usage, nutrition, mood, continence and functional performance). These tools are important on clinical point of view, for research and decision-making. Several tools that evaluate functionality and cognition also evaluate several dimensions that we are traditionally including in frailty.
Armstrong et al. [17] indicate, in the scope of their study, three conceptually different approaches to the measurement of frailty: (1) Changes in Health, End-Stage Disease and Signs and Symptoms (CHESS) scale, (2) Edmonton Frail Scale (EFS), (3) the frailty index (FI) and the Tilburg Frailty Indicator (TFI).
The CHESS scale is a tool that uses information from the person’s clinical assessment, which is used to calculate the person’s level of decline. The tool was developed using statistical methods, based on the items available in the inter-RAI instruments. It is not a tool for objectively assessing frailty, but it allows assessing the “instability” of health status, which is also a predictor of mortality [17]. The scores ranging from 0 (meaning no instability) to 5 (for the highest level of instability) have been demonstrated to be a strong predictor of mortality (P < 0.0001) in continuing care patients [24].
The EFS is a brief multidimensional clinical measure, widely used and designed to use in both inpatient and outpatient settings [25]. The scale assesses nine domains of frailty in old people (cognition, general health status, functional independence, social support, medication usage, nutrition, mood, continence and functional performance) [25]. Total score can vary from 0 to 17. The participants were classified into categories, and a higher score represents a higher degree of frailty. Severe frail and non-frail participants were defined according of the EFS score from not frail (0–5), vulnerable (6–7), mild frailty (8–9), moderate frailty (10–11) and severe frailty (12–17). The EFS is a measure of frailty compared to the clinical impression of specialists after their more comprehensive assessment. A larger part of the assessment tools is focused primarily on determining the person’s level of functioning in terms of managing activities of daily living and instrumental activities of daily living. In post-operative older adults, high scores on the EFS have been shown to be associated with increased complications and a lower chance of being discharged home after surgery [17].
The FI was developed by Rockwood and Mitnitski based on an idea of “accumulation of deficits” [17]. The FI is based on the view that frailty is a non-specific multifactorial state, best characterized by the quantity, rather than the quality, of the health deficits that the person accumulates during the course of life [26]. The FI is thus calculated as the proportion of potential deficits present in the person and can be calculated from the information present in most previous systems of clinical data (databases) [17].
The TFI is a tool widely used to assess 3 frailty domains and their 15 components. It is a user-friendly questionnaire and has good psychometric properties assessed in the initial validation process, constituting a good strategy for multidimensional assessment of frailty in community settings [27]. The instrument consists of two parts. Part A includes life-course determinants of frailty (sex, age and marital status), and part B assesses 15 components of frailty. The score on total frailty has a range of 0–15; people with a score ≥ 5 are considered frail; for physical, psychological and social frailty, the score ranges are 0–8, 0–4 and 0–3, respectively [28].
Studies carried out in different countries have demonstrated that these tools have in general good psychometric properties and are reliable and valid instruments for assessing frailty in community-dwelling older people [4, 17, 24, 25, 26, 27, 29, 30].
Frailty’s assessment is inseparable from an objective and competent evaluation of healthcare needs. Frailty is a multidimensional concept and can be defined as a dynamic state that affects an individual with declines in one or more domains, such as physical, cognitive, social, attention or senses. The assessment of frailty is of limited interest if healthcare professionals do not invest in assessing the needs of frailty people in healthcare. This assessment must be multidimensional, multifactorial, longitudinal and comprehensive, covering all activities of life.
There are many debates on what are health needs assessment and problem identification. What is important to note is that care needs assessment is a systematic and sequential process, conducted by a care professional, which begins with the assessment of dependency focus, accounts for the presence and efficacy of current help, recognizes perceived need and finally determines the type of intervention needed to meet those needs [31].
It has been recognized that needs in the elderly should be patient-centred; holistic; analysed on by dependent people, caregivers and professionals; communicated to other professionals; and met in order to achieve better coordination between leading disciplines; needs assessment enhances the patient and carers experience and leads to more accurate information, but the level of reassessment by other professionals and the incidence of service duplication should also be reduced [31].
Care needs assessment has to promote an objective, competent evaluation of the self-care deficits. A self-care deficit is an inability to perform certain daily activities dependent on health and well-being. Common activities of daily living are the following: eating, bathing, getting dressed, toileting, transferring and continence. Self-care deficits can arise from physical or mental impairments. In elderly people, some of these problems accumulate and comorbidities appear. Health professionals play an important role when it comes to addressing self-care deficits through assessment and intervention. For assessment, evaluation of needs and identification of focuses of attention are necessary. Intervention can include, but is not limited to, helping patients to manage signs and symptoms, adhere to the therapeutic regime, adjust to deficits and strive to preserve, as far as possible, their self-care capacity.
With the ageing of the population and increased longevity, the need to provide palliative care is emphasized. However, this increased need is not usually accompanied by the availability of beds, which requires the use of indicators to manage the availability of palliative care provision. When to begin palliative care is a troublesome question for patients, families and healthcare providers [32]. Severe frailty is a relevant marker, along with functional dependence, cognitive impairment, symptom distress and family support for beginning palliative care. Frailty, independent of specific diseases, can be associated with a limited life expectancy and therefore is an important indication for palliative care [32]. Frailty is an essential model for palliative care in older adults as optimal medical treatment for the frail patient typically includes preventive, life-prolonging, rehabilitative and palliative measures in varying proportion and intensity based on the individual patient’s needs and preferences [33].
Frailty elderly usually have dependence on self-care and need of support from others. Elderly does not mean frailty, but the ageing process led to frailty, which means that there are changes that reflect ageing-related alterations and involve intrinsic and extrinsic factors which are typical of ageing [4]. Usually, scales assess some domains of frailty in old people (cognition, general health status, functional independence, social support, medication usage, nutrition, mood, continence and functional performance). The occurrence of frailty is mainly a state of vulnerability resulting from comorbidities and the overall decline in organ functions. The progression to later stages of frailty often signals a loss of autonomy, dependence and reduction in physical and cognitive function.
Frailty is commonly positively related with caregiver burden and associated with higher levels of depression on the caregiver. A lack of understanding about frailty has been identified as a barrier to providing optimal care to elderly people. Self-care deficit theories suggest people are better able to recover when they maintain some independence over their own self-care. The evaluation of frailty is closely linked to the identification of dependencies in self-care. The use of frailty and self-care dependence assessment helps to determine the focus of attention, to respect vulnerability, to limit dependence as much as possible and to provide quality, safety and competent care.
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\n\nOut of all of the publishing options available to researchers, why choose to contribute your research to an IntechOpen Edited Volume? The reasons are simple. IntechOpen has worked exceptionally hard over the past years to fine tune the Open Access book publishing process and we continue to work hard to deliver the best for all of our contributors. The quality of published content is of utmost importance to us, followed closely by speed, and of course, availability and accessibility. To view current Open Access book projects that are Open for Submissions visit us here.
\n\nQUALITY CONTENT
\n\nOver the years we have learned what is important. What makes a difference to the researchers that work with us, what they value. Something that is very high not only on their lists, but our own, is the quality of the published content.
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