Hounsfield values of various substances. (Hounsfield, 1980)
\r\n\tLiterature showed the presence of ACE2 receptors on the membrane of erythrocyte or red blood cell (RBC), indicating that erythrocyte (RBC) can be considered as a peripheral biomarker for SARS-C0V2 infection.
\r\n\r\n\tIncreased levels of glycolysis and fragmentation of RBC membrane proteins were observed in the SARS-C0V2 infected patients, demonstrating that not only RBC’s metabolism and proteome but its membrane lipidome could be influenced by SARS-C0V2 infection changing the homeostasis of the infected erythrocyte. This altered RBC may result in the clot and thrombus formation; the major signs of critically ill Covid-19 patients.
\r\n\r\n\tThis book is going to be a succinct source of knowledge not only for the specialists, researchers, academics and the students in this area but for the general public who are concern about the present situation and are interested in knowing about simple non-invasive measures for identifying viral and bacterial infections through their red blood cells.
",isbn:"978-1-83969-121-8",printIsbn:"978-1-83969-120-1",pdfIsbn:"978-1-83969-122-5",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"fa5f4b6ef59e28b6e7c1a739c57c5d2f",bookSignature:"Prof. Kaneez Fatima Shad",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10494.jpg",keywords:"Spike Protein, Hemoglobin, Proteins for Oxygen Transport, Altered Protein Structures, RBC ACE Receptors, RBC ACE-2 Receptors, Carboxypeptidase, Mas Receptor, Metabolomics, Gas Transport, Glucose-6-Phosphate, Phosphoglycerate",numberOfDownloads:4,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 15th 2020",dateEndSecondStepPublish:"November 30th 2020",dateEndThirdStepPublish:"January 29th 2021",dateEndFourthStepPublish:"April 19th 2021",dateEndFifthStepPublish:"June 18th 2021",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"Dr. Shad is a governing body member and mentor of Women in World Neuroscience (WWN), a division of the International Brain Research Organization (IBRO). She is also a member of IBRO-APRC Global Advocacy responsible for brain research funding distribution in this region.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"31988",title:"Prof.",name:"Kaneez",middleName:null,surname:"Fatima Shad",slug:"kaneez-fatima-shad",fullName:"Kaneez Fatima Shad",profilePictureURL:"https://mts.intechopen.com/storage/users/31988/images/system/31988.jpg",biography:"Professor Kaneez Fatima Shad, a neuroscientist with a medical background, received Ph.D. in 1994 from the Faculty of Medicine, UNSW, Australia, followed by a post-doc at the Allegheny University of Health Sciences, Philadelphia, USA. She taught Medical and Biological Sciences in various universities in Australia, the USA, UAE, Bahrain, Pakistan, and Brunei. During this period, she was also engaged in doing research by getting local and international grants (total of over 3.3 million USD) and translating them into products such as a rapid diagnostic test for stroke and other vascular disorders. She published over 60 articles in refereed journals, edited 8 books, and wrote 7 book chapters, presented at 97 international conferences, mentored 34 postgraduate students. Set up a company Shad Diagnostics for the development of cerebrovascular handheld diagnostic tool Stroke meter into a wearable.",institutionString:"University of Technology Sydney",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"6",institution:{name:"University of Technology Sydney",institutionURL:null,country:{name:"Australia"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:[{id:"75447",title:"Detection of Benzo[a]Pyrene Diol Epoxide-DNA Adducts in White Blood Cells of Asphalt Plant Workers in Syria",slug:"detection-of-benzo-a-pyrene-diol-epoxide-dna-adducts-in-white-blood-cells-of-asphalt-plant-workers-i",totalDownloads:4,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"280415",firstName:"Josip",lastName:"Knapic",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/280415/images/8050_n.jpg",email:"josip@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copy-editing and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"1624",title:"Patch Clamp Technique",subtitle:null,isOpenForSubmission:!1,hash:"24164a2299d5f9b1a2ef1c2169689465",slug:"patch-clamp-technique",bookSignature:"Fatima Shad Kaneez",coverURL:"https://cdn.intechopen.com/books/images_new/1624.jpg",editedByType:"Edited by",editors:[{id:"31988",title:"Prof.",name:"Kaneez",surname:"Fatima Shad",slug:"kaneez-fatima-shad",fullName:"Kaneez Fatima Shad"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1359",title:"Underlying Mechanisms of Epilepsy",subtitle:null,isOpenForSubmission:!1,hash:"85f9b8dac56ce4be16a9177c366e6fa1",slug:"underlying-mechanisms-of-epilepsy",bookSignature:"Fatima Shad Kaneez",coverURL:"https://cdn.intechopen.com/books/images_new/1359.jpg",editedByType:"Edited by",editors:[{id:"31988",title:"Prof.",name:"Kaneez",surname:"Fatima Shad",slug:"kaneez-fatima-shad",fullName:"Kaneez Fatima Shad"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5780",title:"Serotonin",subtitle:"A Chemical Messenger Between All Types of Living Cells",isOpenForSubmission:!1,hash:"5fe2c461c95b4ee2d886e30b89d71723",slug:"serotonin-a-chemical-messenger-between-all-types-of-living-cells",bookSignature:"Kaneez Fatima Shad",coverURL:"https://cdn.intechopen.com/books/images_new/5780.jpg",editedByType:"Edited by",editors:[{id:"31988",title:"Prof.",name:"Kaneez",surname:"Fatima Shad",slug:"kaneez-fatima-shad",fullName:"Kaneez Fatima Shad"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6683",title:"Ion Channels in Health and Sickness",subtitle:null,isOpenForSubmission:!1,hash:"8b02f45497488912833ba5b8e7cdaae8",slug:"ion-channels-in-health-and-sickness",bookSignature:"Kaneez Fatima Shad",coverURL:"https://cdn.intechopen.com/books/images_new/6683.jpg",editedByType:"Edited by",editors:[{id:"31988",title:"Prof.",name:"Kaneez",surname:"Fatima Shad",slug:"kaneez-fatima-shad",fullName:"Kaneez Fatima Shad"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"9489",title:"Neurological and Mental Disorders",subtitle:null,isOpenForSubmission:!1,hash:"3c29557d356441eccf59b262c0980d81",slug:"neurological-and-mental-disorders",bookSignature:"Kaneez Fatima Shad and Kamil Hakan Dogan",coverURL:"https://cdn.intechopen.com/books/images_new/9489.jpg",editedByType:"Edited by",editors:[{id:"31988",title:"Prof.",name:"Kaneez",surname:"Fatima Shad",slug:"kaneez-fatima-shad",fullName:"Kaneez Fatima Shad"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"7842",title:"Basic and Clinical Understanding of Microcirculation",subtitle:null,isOpenForSubmission:!1,hash:"a57d5a701b51d9c8e17b1c80bc0d52e5",slug:"basic-and-clinical-understanding-of-microcirculation",bookSignature:"Kaneez Fatima Shad, Seyed Soheil Saeedi Saravi and Nazar Luqman Bilgrami",coverURL:"https://cdn.intechopen.com/books/images_new/7842.jpg",editedByType:"Edited by",editors:[{id:"31988",title:"Prof.",name:"Kaneez",surname:"Fatima Shad",slug:"kaneez-fatima-shad",fullName:"Kaneez Fatima Shad"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{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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As a result, the investigators can directly collect the sample of the decrease such as facial photograph, DNA, fingerprint and dental record in order to compare to possible relatives or with ante-mortem profile (De Valck, 2006). However, the investigators are not always lucky. In severe accidents such aircraft crashes, only little information of the decrease is available, the skin and soft tissue may be completely burnt out and the skeleton can be broken into small pieces due to the impact. The skeleton examination in historical sites by archaeologists presents even more complication. The archaeologists need not only to identify general aspects of the skeleton, for instant age, sex, cause of death, stature and race, but also to estimate the period of death and the possibility to discover the particular person that might be significant in the history.
\n\t\t\tSeveral techniques have been applied to assist the identification of the decrease ranging from the simplest technique which may acquire the evidence from the personal belonging until using the advance scientific techniques. These techniques can be generally categorized into two methods, invasive and non-invasive. The invasive method includes biochemical analysis, microscopy, accelerator mass spectrometry radiocarbon dating (with standard C-14), ancient DNA analysis, histology and endoscope whereas the non-invasive technique involved the aid of engineering technologies such as radiographic analysis and computed tomography (CT) examination.
\n\t\t\tFrom 1975 – 2005, the archaeological researches had been increasingly conducted by means of non-invasive techniques which 112 of 245 researches have applied the non-invasive technique and the trend of investigation gradually moved from invasive to non-invasive examinations (Zweifel, et al., 2009). The first non-invasive technique has been presented to the public in 1896 which the radiographic analysis was used to examine the ibis mummy in Belgium (Van Tiggelen, 2004). Soon after that, archaeologist realized the importance of radiological technique and applied broadly to examine great numbers of mummy (Dedouit, et al., 2010; Friedrich, et al., 2010; Recheis, et al., 1999; Zweifel, et al., 2009). One main advantage of radiography includes the ability to access general aspects of mummy without releasing the bandages which may be destroyed important features or contaminated. In the early 1900s, another non-invasive medical examination device, computed tomography scanner, has been invented by Alessandro Vallebona, but the technology has remained unpopular until the 1970s which modern era of computed tomography scanner began (Hill, 2009). Not too long, computed tomography scanner became an effective tool in examination the autopsy. The computed tomography generally relies on medical imaging processing combined with reverse engineering principles which the object is captured the profile and presented the virtual three-dimensional models in computer. With these advanced features, the perspective of archaeology and forensic medicine has changed into three-dimensional aspect. Consequently, The two-dimensional radiographic image occlusion and the problem such uncertainty from bias of investigator in direct measurements are eliminated.
\n\t\t\tApart from the advantages of computed tomography in forensic medicine, it also becomes an effective clinical diagnosis device in many hospitals. The use of three-dimensional model allows the surgeon to examine the abnormality of organs in any configurations which the two-dimensional technique may be inaccessible. Moreover, the three-dimensional models can be used to simulate the surgical operation prior surgery (Fürnstahl, et al., 2010), subsequently reduce operating time and increase safety of patients. Alternative uses of computed tomography include morphometric study (Chantarapanich, et al., 2008; Mahaisavariya, et al., 2002) and the evaluation the risk of implant usage (Mahaisavariya, et al., 2004; Sitthiseripratip, et al., 2003)
\n\t\t\tThe purpose of this chapter is to present and discuss the medical imaging and reverse engineering techniques by means of demonstrating the application in craniometric study. Obviously, recent craniometric studies have been employed by two-dimensional techniques or direct measurement (Steyn & Işcan, 1997; Deshmukh & Devershi, 2006; Dayal, et al, 2008; Sangvichien, et al., 2008; Matamala, et al, 2009) such as the use of spreading caliper, sliding vernier calliper, mandibulometer and standard flexible steel tape. The diverse mentioned measurement techniques reflect the lack of engineering aids which the current trend in forensic medicine need the advanced technologies to provide the accurate measurements. Therefore, the scope of demonstration includes the brief detail of reverse engineering as to provide for who may not familiar with, data acquisition technique using computed tomography scanner, measurement of skull anatomical parameters and sex determination method based on logistic function. By this way of demonstration, the overview of forensic medicine by aid of advance medical imaging and reverse engineering is obtained.
\n\t\tReverse engineering has been widely applied several years in clinical fields and forensic medicine (Aamodt, et al., 1999; Aghayev, et al., 2008; Fürnstahl, et al., 2010). Initially, reverse engineering was first used in free-form product designs which the conventional “Forward Engineering” has limited drawing functions and time consumption. Product design based on “Forward Engineering”, the process involves turning the conceptual product design to physical product whereas reverse engineering is inversed (Zhou & Xi, 2002).
\n\t\t\tThe process of reverse engineering involves turning the physical product back to the virtual models (normally three-dimension) (Li, et al., 2002; Várady, et al., 1997). From the three-dimensional virtual models, the conceptual design can be obtained. Reverse engineering can be described as two phases which are digitization and reconstruction phase, as summarized in Fig. 1. The digitization phase involves the data acquisition of the physical model using various types of scanner. The initial geometry from the scanner is then obtained in three forms, point clouds, polygon model and series of image depending on the acquisition technique of each scanner. In the reconstruction phase, the obtained data is processed in order to reconstruct the three-dimensional model. with “At this step, the elimination of noise data and filtering of unnecessary data may also be performed. For the production phases, it may be added as a final step in reverse engineering. This phase employs various manufacturing processes to fabricate the three-dimensional virtual model. However, this phase may not be mandatory, because sometime the geometry is only stored in database without any further processing.
\n\t\t\tDiagram of reverse engineering process.
The digitization methods can be categorized into two approaches which are tactile approach (contact method) and non-contact approach (Li, et al., 2002; Várady, et al., 1997). For tactile approach, the device contacts to the physical object directly whereas the non-contact approach uses the medium in digitization instead without contact of device.
\n\t\t\tThe characteristic of tactile approach is relatively simple. Touch probe is used in conjunction with robotic mechanism such as coordinate measurement machine (CMM), articulated arm or computer numerical control (CNC) devices to determine the position of the object (Cartesian coordinate). The accuracy is considered to be a main advantage of tactile approach, nevertheless the digitization process is quite slow and difficult to digitize complex geometry. A wide range of object can be applied with this approach regardless of color, shininess and transparency, this approach is not appropriate for deformable materials.
\n\t\t\tIn non-contact approach, the medium is used to measure the physical object using the principle of reflection or penetration. Laser beam and white light are medium sources commonly found in many three-dimensional scanners and they rely on the principle of reflection. The medium travels from the generator to the object before reflects and transmits to the receiver unit. The determination of geometry can be processed using at least one two-
\n\t\t\tDigitization Methods.
dimensional images combined with some optical parameters such as reflection angle, distance and time of flight. The initial geometry is presented in form of cloud point or of polygon model. Use of laser beam and white light has advantage in fast digitization and continuous data, but too shiny and transparent object present complication.
\n\t\t\tEven the laser beam and white light systems are applied in many forensic studies (Park, et al., 2006; Thali, et al., 2003; Vanezis, et al., 2000), but probably, the most efficient system for forensic studies is the use of non-contact device based on principle of penetration. This system uses the medium that can go though the object to capture both internal and external geometries. The most popular device is computed tomography scanner which involves the use of X-ray.
\n\t\t\tThe digitization process initializes the transmission of the X-ray through the object. A set of data acquisitions is performed with the constant interval throughout entire object which subsequently give a series of slice image (Hounsfield, 1980). Each slice contains the information of object’s position and the value of Hounsfield unit (HU). The density of object is proportional to the Hounsfield value. The higher Hounsfield value indicates high-density object such as enameled and cortical bone whereas the lower Hounsfield value indicates low-density object such as cancellous bone, fat and soft tissue. Various Hounsfield values of various substances are given in Table 1. In order to reconstruct the three-dimensional model, the optimal Hounsfield values must be selected (threshold). After that the threshold regions of each slice are combined to construct the volumetric model.
\n\t\t\tFor the computed tomography device, the speed of digitization and ability to examine the internal topology are considered to be superior, but the artifact (noise data) caused by metallic structure is drawback.
\n\t\t\t\n\t\t\t\t\t\t\tSubstances\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHounsfield values\n\t\t\t\t\t\t | \n\t\t\t\t\t
Air | \n\t\t\t\t\t\t-1000 | \n\t\t\t\t\t
Fat | \n\t\t\t\t\t\t-70 to -90 | \n\t\t\t\t\t
Water | \n\t\t\t\t\t\t0 | \n\t\t\t\t\t
Tissue | \n\t\t\t\t\t\t+20 to +35 | \n\t\t\t\t\t
Blood Volume | \n\t\t\t\t\t\tApprox. +40 | \n\t\t\t\t\t
Bone | \n\t\t\t\t\t\t+900 | \n\t\t\t\t\t
Hounsfield values of various substances. (Hounsfield, 1980)
Specimen of 104 dry cadaveric skulls donated by the Department of Anatomy, Faculty of Medicine, Khon Kaen University, Thailand is used to demonstrate the application of advanced medical imaging and reverse engineering technologies in craniometric study. The cadaver includes 63 males with average age of 55.16 years (standard deviation 18.38 years) and 41 females with average age of 49.00 years (standard deviation 17.94 years). The age rages from 17–81 years at the time of death. The skulls are placed in acrylic box with a set of four. The reverse engineering technique by means of spiral computed tomography scanner (Siemens AG, Germany) is used to capture the profile of each skull as shown in Fig. 3. The data acquisition protocol is axial scan with tube voltage of 120 kV and tube current of 100 mA. The digitization is performed with 1.5-mm slice thickness and the reconstruction is done at 1-mm thickness. Each slice contains the volumetric data that represent the density and position (contour) of the skull. The computed tomography images are then processed with medical image processing software (Mimics, Materialise NV, Belgium). To begin the reconstruction of three-dimensional model, a proper Hounsfield value (normally +900 for bone structure) is selected. After that, the threshold regions are used to calculate the complete topology of three-dimensional skull. The reconstruction process of skull model is illustrated in Fig. 4.
\n\t\t\tA set of skull during data acquisition using computed tomography scanner.
Three-dimensional model reconstruction.
The anatomical landmarks in craniometric study are categorized in to median and bilateral landmarks (Rooppakhun, et al., 2010). The median landmarks are approximately located on sagittal plane. Each of them has only one location. There are 13 median landmarks which the specific definitions can be described as follows:
\n\t\t\t\n\t\t\t\t\t\tGlabella (GL) - the most anterior point of frontal bone between supraorbital in the sagittal plane.
\n\t\t\t\t\t\tBregma (BR) - the crossing of the coronal and sagittal sutures on the top of the skull.
\n\t\t\t\t\t\tOpisthocranium (OPC) - the most posterior point in midline of inion bone which length of the skull is maximum when measure from Galbella point.
\n\t\t\t\t\t\tNasion (NA) - the intersection point of the internasal and frontonasal sutures in the sagittal plane.
\n\t\t\t\t\t\tOpistion (OPS) - the most posterior midsagittal point on the posterior margin of the foramen magnum.
\n\t\t\t\t\t\tBasion (BA) - the most anterior point of the great foramen magnum in the sagittal plane.
\n\t\t\t\t\t\tOrale (OR) - the midpoint on the intersection of posterior alveolar sockets rim of the cavities of two upper central incisors.
\n\t\t\t\t\t\tProsthion (PR) - the lowest, most anterior point on the alveolar portion of the premaxilla, in the median plane, between the upper central incisors.
\n\t\t\t\t\t\tStaphylion (STA) - point in the medial line (interpalatal suture) of the posterior part of the hard palate where it is crossed by a line drawn tangent to the curves of the posterior margins of the palate.
\n\t\t\t\t\t\tNasospinale (NAS) - the lowest point of lower anterior nasal aperture in mid-sagittal plane.
\n\t\t\t\t\t\tGnathion (GN) - The midpoint on the lower border of the mandible in the sagittal plane.
\n\t\t\t\t\t\tPogonion (PG) - The most projecting point of the chin in the standard sagittal plane.
\n\t\t\t\t\t\tInfradentale (ID) - The anterior superior point on the mandible at its labial contact between mandibular central incisors.
For the bilateral landmarks, each of them is located on both sides of skull. There are 17 bilateral landmarks which the specific definitions can be described as follows:
\n\t\t\t\n\t\t\t\t\t\tEuryon (EU) - the lateral point on either side of the greatest transverse diameter of the skull.
\n\t\t\t\t\t\tStaphanion (ST) - the intersection of the superior temporal line and the coronal suture.
\n\t\t\t\t\t\tFrontotemporale (FT) - the most anterior point on either side of temporal crest of the minimum transverse breadth of frontal bone.
\n\t\t\t\t\t\tBolton (BO) - The superior point of the curvature between occipital condyle and posterior margin of foramen magnum.
\n\t\t\t\t\t\tOrbitale (ORB) - the most inferior point of each infraorbital rim.
\n\t\t\t\t\t\tEctoconchion (EC) - the most lateral point on each orbital\'s margin where a line running parallel to upper orbital border cut the lateral orbital margin.
\n\t\t\t\t\t\tMaxillo-frontale (MF) - the intersection point on anterior lacrimal crest and fronto-maxillary sutures.
\n\t\t\t\t\t\tSupraorbitale (SOR) - the most superior point of each superior orbital rim.
\n\t\t\t\t\t\tZygonion (ZG) - The most lateral point on the outline of each zygomatic arch.
\n\t\t\t\t\t\tZygomaxillare (ZM) - The most interior point on each zygomatico-maxillary sutures.
\n\t\t\t\t\t\tNasal (NS) - The most lateral point on each nasal\'s margin where maximum nasal breadth.
\n\t\t\t\t\t\tEndomolare (ENM) - the most medial point of internal curvature surface of alveolar ridge corresponding to second molar tooth.
\n\t\t\t\t\t\tCoronion (CO) - The most superior point on each coroniod process.
\n\t\t\t\t\t\tCondylion superior (CS) - the most superior point on each mandibular condyle.
\n\t\t\t\t\t\tConlylion laterale (CDL) - the most lateral point on each mandibular condyle.
\n\t\t\t\t\t\tGonion (GO) - the point at each mandibular angle that is defined by dropping a perpendicular from the intersection point of the tangent lines to the posterior margin of the mandibular vertical ramus and inferior margin of the mandibular body or horizontal ramus.
\n\t\t\t\t\t\tLaterla infradentale (LID) - the midpoint of a line tangent to the outer margins of the cavities of the lateral incisor of each lower canine teeth.
In order to better understand the previous described definitions, every landmark is also illustrated in Fig. 5.
\n\t\t\tEach of the three-dimensional models of skull is used to determine the anatomical landmark according to previous description. Only one investigator locate the entire landmarks in every skull to avoid uncertainty of intra-observer. The anatomical landmarks are then used to obtain 40 craniometric parameters as shown in Table 2. The measurements are interpreted using statistical analysis and reported in form of average values and standard deviation regarding to gender. In order to distinguish craniometric parameters of each gender, an unpaired t-test is utilized for analysis. A p-value < 0.05 is a significant level that used to determine the difference. In addition, the linear regression and the correlation coefficient are also used for the pair-wise tests.
\n\t\t\tAs also shown in Table 2, the craniometric parameters of male are larger than female. Thirty-one of forty parameters show the statistical significant differences among both genders, especially, Maximum cranial breadth, Facial length, Orbital height-left, Orbital height-right, Palatal breadth, Bicoronion breadth, Bizygometic breadth, Maxillary breadth, Upper facial height, Orbital breadth-left, Orbital breadth-Right, Nasal height, Bicondylar breath, Bi-gonion breadth, Coronion height-left, Coronion height-right, Mandibular body length-left, Mandibular body length-right, Maximum mandibular length-left and Maximum mandibular length-right which present the p-value << 0.001. For Maximum cranial breadth, Facial length, Orbital height-left, Orbital height-right, Palatal breadth, Bicoronion breadth are considered to be relatively different as the p-value < 0.01. The parameters such Ramus height-left, Ramus height-right, Symphysic height shows some degrees of significance. In addition, nine parameters do not present the statistical differences which are Maximum frontal breadth, Anterior inter-orbital breadth, Nasal breadth, Palatal length, Mandibular angle-left, Mandibular angle-right, Notch length-left, Notch length-right, and Symphysic breadth.
\n\t\t\tFrom the pair-wise tests, the correlations of craniometric parameters are different among male and female population. Table 3 and Table 4 show the sample of correlations of craniometric parameters which correlation coefficient (r) are above 0.500. In both populations, the bilateral anatomy presents some degrees of correlation which can be signified the facial symmetry. The linear regression equations are considered to be useful to predict the craniometric parameters in forensic medicine. For example, the defected skull usually miss some landmarks, the use of known craniometric parameters can be used to determine the missing parameters. However, it should be noticed that the obtained missing parameters may not be always precise. The possibility of being can only be determined, but the accuracy strongly depends on the correlation coefficient. The regression scatters plot and 95% interval bands of some pair-wise tests are plotted in Fig. 6 and Fig. 7.
\n\t\t\tThe anatomical landmarks of skull.
\n\t\t\t\t\t\t\tCraniometric Parameter\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLandmark\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAverage (S.D.)\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tp-value\n\t\t\t\t\t\t | \n\t\t\t\t\t|
\n\t\t\t\t\t\t\tMale\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFemale\n\t\t\t\t\t\t | \n\t\t\t\t\t|||
Maximum cranial length | \n\t\t\t\t\t\tGL-OPC | \n\t\t\t\t\t\t173.6 (5.2) | \n\t\t\t\t\t\t165.4 (6.4) | \n\t\t\t\t\t\t<< 0.001 | \n\t\t\t\t\t
Maximum cranial breadth | \n\t\t\t\t\t\tEU\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-EU\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t144.9 (5.6) | \n\t\t\t\t\t\t141.2 (5.5) | \n\t\t\t\t\t\t0.001361 | \n\t\t\t\t\t
Maximum frontal breadth | \n\t\t\t\t\t\tST\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t -ST\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t115.8 (6.7) | \n\t\t\t\t\t\t113.3 (6.7) | \n\t\t\t\t\t\t0.070663 | \n\t\t\t\t\t
Minimum frontal breadth | \n\t\t\t\t\t\tFT\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-FT\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t94.9 (5.1) | \n\t\t\t\t\t\t91.4 (4.9) | \n\t\t\t\t\t\t0.000584 | \n\t\t\t\t\t
Basion-brema height | \n\t\t\t\t\t\tBA-BR | \n\t\t\t\t\t\t138.6 (4.8) | \n\t\t\t\t\t\t132.4 (5.2) | \n\t\t\t\t\t\t<< 0.001 | \n\t\t\t\t\t
Nasion-basion length | \n\t\t\t\t\t\tNA-BA | \n\t\t\t\t\t\t101.8 (4.0) | \n\t\t\t\t\t\t96.0 (3.4) | \n\t\t\t\t\t\t<< 0.001 | \n\t\t\t\t\t
Foramen magnum length | \n\t\t\t\t\t\tBA-OPC | \n\t\t\t\t\t\t36.7 (2.1) | \n\t\t\t\t\t\t34.5 (2.4) | \n\t\t\t\t\t\t0.000006 | \n\t\t\t\t\t
Foramen magnum breadth | \n\t\t\t\t\t\tBO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-BO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t30.5 (2.1) | \n\t\t\t\t\t\t28.9 (1.8) | \n\t\t\t\t\t\t0.000051 | \n\t\t\t\t\t
Nasion-bregma length | \n\t\t\t\t\t\tNA-BR | \n\t\t\t\t\t\t112.9 (4.2) | \n\t\t\t\t\t\t107.3 (6.0) | \n\t\t\t\t\t\t0.000002 | \n\t\t\t\t\t
Facial length | \n\t\t\t\t\t\tBA-PR | \n\t\t\t\t\t\t96.1 (5.4) | \n\t\t\t\t\t\t92.9 (5.5) | \n\t\t\t\t\t\t0.004704 | \n\t\t\t\t\t
Bi-orbital breadth | \n\t\t\t\t\t\tEC\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-EC\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t97.4 (3.8) | \n\t\t\t\t\t\t94.0 (3.8) | \n\t\t\t\t\t\t0.000024 | \n\t\t\t\t\t
Bi-zygometic breadth | \n\t\t\t\t\t\tZG\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-ZG\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t133.7 (5.1) | \n\t\t\t\t\t\t127.7 (5.2) | \n\t\t\t\t\t\t<< 0.001 | \n\t\t\t\t\t
Maxillary breadth | \n\t\t\t\t\t\tZM\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t–ZM\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t104.5 (5.3) | \n\t\t\t\t\t\t99.1 (4.9) | \n\t\t\t\t\t\t0.000001 | \n\t\t\t\t\t
Upper facial height | \n\t\t\t\t\t\tNA-PR | \n\t\t\t\t\t\t70.3 (4.2) | \n\t\t\t\t\t\t66.2 (4.6) | \n\t\t\t\t\t\t0.000019 | \n\t\t\t\t\t
Orbital breadth-left | \n\t\t\t\t\t\tEC\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-MF\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t41.2 (2.2) | \n\t\t\t\t\t\t39.6 (2.4) | \n\t\t\t\t\t\t0.000743 | \n\t\t\t\t\t
Orbital breadth-right | \n\t\t\t\t\t\tEC\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-MF\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t41.5 (2.0) | \n\t\t\t\t\t\t39.8 (2.0) | \n\t\t\t\t\t\t0.000044 | \n\t\t\t\t\t
Orbital height-left | \n\t\t\t\t\t\tORB\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-SOR\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t36.2 (2.3) | \n\t\t\t\t\t\t34.7 (2.5) | \n\t\t\t\t\t\t0.002714 | \n\t\t\t\t\t
Orbital height-right | \n\t\t\t\t\t\tORB\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-SOR\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t36.3 (2.5) | \n\t\t\t\t\t\t34.9 (2.1) | \n\t\t\t\t\t\t0.004341 | \n\t\t\t\t\t
Anterior inter-orbital breadth | \n\t\t\t\t\t\tMF\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-MF\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t21.0 (2.2) | \n\t\t\t\t\t\t20.7 (2.4) | \n\t\t\t\t\t\t0.497642 | \n\t\t\t\t\t
Nasal breadth | \n\t\t\t\t\t\tNS\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-NS\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t27.0 (2.2) | \n\t\t\t\t\t\t26.8 (2.2) | \n\t\t\t\t\t\t0.632101 | \n\t\t\t\t\t
Nasal height | \n\t\t\t\t\t\tNA-NAS | \n\t\t\t\t\t\t52.7 (3.0) | \n\t\t\t\t\t\t49.6 (3.1) | \n\t\t\t\t\t\t0.000003 | \n\t\t\t\t\t
Palatal length | \n\t\t\t\t\t\tOR-STA | \n\t\t\t\t\t\t42.6 (4.2) | \n\t\t\t\t\t\t42.6 (4.4) | \n\t\t\t\t\t\t0.952028 | \n\t\t\t\t\t
Palatal breadth | \n\t\t\t\t\t\tENM\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-ENM\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t39.1 (3.1) | \n\t\t\t\t\t\t37.6 (2.4) | \n\t\t\t\t\t\t0.006430 | \n\t\t\t\t\t
Bi-coronion breadth | \n\t\t\t\t\t\tCO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-CO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t98.6 (5.2) | \n\t\t\t\t\t\t94.3 (5.8) | \n\t\t\t\t\t\t0.002652 | \n\t\t\t\t\t
Bi-condylar breadth | \n\t\t\t\t\t\tCDL\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-CDL\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t123.1 (5.2) | \n\t\t\t\t\t\t118.7 (5.1) | \n\t\t\t\t\t\t0.000870 | \n\t\t\t\t\t
Bi-gonion breadth | \n\t\t\t\t\t\tGO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-GO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t99.1 (6.3) | \n\t\t\t\t\t\t92.8 (6.2) | \n\t\t\t\t\t\t0.000113 | \n\t\t\t\t\t
Coronion height-left | \n\t\t\t\t\t\tCO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-GO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t62.3 (4.9) | \n\t\t\t\t\t\t57.2 (4.8) | \n\t\t\t\t\t\t0.000065 | \n\t\t\t\t\t
Coronion height-right | \n\t\t\t\t\t\tCO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-GO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t62.83 (5.2) | \n\t\t\t\t\t\t57.5 (4.8) | \n\t\t\t\t\t\t0.000043 | \n\t\t\t\t\t
Mandibular angle-left* | \n\t\t\t\t\t\tCS\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-GO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-GN | \n\t\t\t\t\t\t112.4 (5.1) | \n\t\t\t\t\t\t113.9 (6.4) | \n\t\t\t\t\t\t0.298443 | \n\t\t\t\t\t
Mandibular angle-right* | \n\t\t\t\t\t\tCS\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-GO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-GN | \n\t\t\t\t\t\t112.4 (5.5) | \n\t\t\t\t\t\t112.8 (5.6) | \n\t\t\t\t\t\t0.759332 | \n\t\t\t\t\t
Mandibular body length-left | \n\t\t\t\t\t\tGO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-PG | \n\t\t\t\t\t\t92.0 (4.8) | \n\t\t\t\t\t\t87.0 (4.9) | \n\t\t\t\t\t\t0.000083 | \n\t\t\t\t\t
Mandibular body length-right | \n\t\t\t\t\t\tGO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-PG | \n\t\t\t\t\t\t92.5 (4.9) | \n\t\t\t\t\t\t87.6 (5.0) | \n\t\t\t\t\t\t0.000128 | \n\t\t\t\t\t
Maximum mandibular length-left | \n\t\t\t\t\t\tCS\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-PG | \n\t\t\t\t\t\t119.8 (6.1) | \n\t\t\t\t\t\t114.6 (5.1) | \n\t\t\t\t\t\t0.000383 | \n\t\t\t\t\t
Maximum mandibular length-right | \n\t\t\t\t\t\tCS\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-PG | \n\t\t\t\t\t\t120.6 (6.1) | \n\t\t\t\t\t\t115.0 (5.0) | \n\t\t\t\t\t\t0.000079 | \n\t\t\t\t\t
Notch length-left | \n\t\t\t\t\t\tCO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-CS\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t35.3 (2.7) | \n\t\t\t\t\t\t34.1 (4.2) | \n\t\t\t\t\t\t0.202213 | \n\t\t\t\t\t
Notch length-right | \n\t\t\t\t\t\tCO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-CS\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t35.1 (2.7) | \n\t\t\t\t\t\t33.7 (4.0) | \n\t\t\t\t\t\t0.105663 | \n\t\t\t\t\t
Ramus height-left | \n\t\t\t\t\t\tCS\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-GO\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t58.2 (5.0) | \n\t\t\t\t\t\t55.2 (4.5) | \n\t\t\t\t\t\t0.010815 | \n\t\t\t\t\t
Ramus height-right | \n\t\t\t\t\t\tCS\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t-GO\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t58.3 (4.6) | \n\t\t\t\t\t\t55.3 (4.7) | \n\t\t\t\t\t\t0.010342 | \n\t\t\t\t\t
Symphysic breadth | \n\t\t\t\t\t\tLID\n\t\t\t\t\t\t\t\tL\n\t\t\t\t\t\t\t-LID\n\t\t\t\t\t\t\t\tR\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t | \n\t\t\t\t\t\t23.1 (6.0) | \n\t\t\t\t\t\t23.7 (6.0) | \n\t\t\t\t\t\t0.689146 | \n\t\t\t\t\t
Symphysic height | \n\t\t\t\t\t\tGN-ID | \n\t\t\t\t\t\t31.6 (3.5) | \n\t\t\t\t\t\t26.5 (3.1) | \n\t\t\t\t\t\t0.011128 | \n\t\t\t\t\t
Average values of craniometric parameters regarding to gender derived from 104 skulls (63-males and 41-females), (Unit: millimeter, *degree).
\n\t\t\t\t\t\t\tCraniometric Parameter (x vs. y)\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tRegression (Correlation, r)\n\t\t\t\t\t\t | \n\t\t\t\t\t|
Maximum mandibular length-left vs. -right | \n\t\t\t\t\t\ty = 0.916x + 10.470 | \n\t\t\t\t\t\t(0.920) | \n\t\t\t\t\t
Mandibular angle-left vs. -right | \n\t\t\t\t\t\ty = 0.976x + 2.630 | \n\t\t\t\t\t\t(0.904) | \n\t\t\t\t\t
Mandibular body length-left vs. -right | \n\t\t\t\t\t\ty = 0.883x + 11.227 | \n\t\t\t\t\t\t(0.860) | \n\t\t\t\t\t
Coronion height-left vs. -right | \n\t\t\t\t\t\ty = 0.908x + 6.233 | \n\t\t\t\t\t\t(0.858) | \n\t\t\t\t\t
Orbital height-left vs. -right | \n\t\t\t\t\t\ty = 0.875x + 4.561 | \n\t\t\t\t\t\t(0.835) | \n\t\t\t\t\t
Orbital breadth-left vs. -right | \n\t\t\t\t\t\ty = 0.741x + 10.969 | \n\t\t\t\t\t\t(0.835) | \n\t\t\t\t\t
Ramus height-left vs. -right | \n\t\t\t\t\t\ty = 0.724x + 16.146 | \n\t\t\t\t\t\t(0.835) | \n\t\t\t\t\t
Notch length-left vs. -right | \n\t\t\t\t\t\ty = 0.761x + 8.239 | \n\t\t\t\t\t\t(0.770) | \n\t\t\t\t\t
Bi-orbital breadth vs. Orbital breadth-left | \n\t\t\t\t\t\ty = 0.400x + 2.283 | \n\t\t\t\t\t\t(0.685) | \n\t\t\t\t\t
Bi-zygometic breadth vs. Bi-orbital breadth | \n\t\t\t\t\t\ty = 0.473x + 34.210 | \n\t\t\t\t\t\t(0.643) | \n\t\t\t\t\t
Upper facial height vs. Symphysic height | \n\t\t\t\t\t\ty = 0.485x – 2.733 | \n\t\t\t\t\t\t(0.636) | \n\t\t\t\t\t
Maximun cranial breadth vs. Bi-zygometic breadth | \n\t\t\t\t\t\ty = 0.109x + 17.063 | \n\t\t\t\t\t\t(0.626) | \n\t\t\t\t\t
Basion-brema heigth vs. Nasion-bregma length | \n\t\t\t\t\t\ty = 0.516x + 41.339 | \n\t\t\t\t\t\t(0.594) | \n\t\t\t\t\t
Nasal height vs. Upper facial height | \n\t\t\t\t\t\ty = 0.840x + 25.980 | \n\t\t\t\t\t\t(0.592) | \n\t\t\t\t\t
Palatal length vs. Facial length | \n\t\t\t\t\t\ty = 0.734x + 64.806 | \n\t\t\t\t\t\t(0.570) | \n\t\t\t\t\t
Nasion-basion length vs. Bi-coronion breadth | \n\t\t\t\t\t\ty = 0.730x + 24.429 | \n\t\t\t\t\t\t(0.533) | \n\t\t\t\t\t
Bi-condylar breadth vs. Bi-zygometic breadth | \n\t\t\t\t\t\ty = 0.528x + 67.980 | \n\t\t\t\t\t\t(0.570) | \n\t\t\t\t\t
The correlation of craniometric parameters of Thai male population.
The linear regression scatters plot and 95% interval bands of Maximum mandibular length-left (x) vs. Maximum mandibular length –right (y) (Unit: Millimeter).
\n\t\t\t\t\t\t\tCraniometric Parameter (x vs. y)\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tRegression (Correlation, r)\n\t\t\t\t\t\t | \n\t\t\t\t\t|
Mandibular body length-left vs. -right | \n\t\t\t\t\t\ty = 0.930x + 6.626 | \n\t\t\t\t\t\t(0.922) | \n\t\t\t\t\t
Maximun mandibular length-left vs. -right | \n\t\t\t\t\t\ty = 0.883x + 13.821 | \n\t\t\t\t\t\t(0.904) | \n\t\t\t\t\t
Coronion height-left vs. -right | \n\t\t\t\t\t\ty = 0.889x + 6.599 | \n\t\t\t\t\t\t(0.895) | \n\t\t\t\t\t
Notch length-left vs. -right | \n\t\t\t\t\t\ty = 0.831x + 5.335 | \n\t\t\t\t\t\t(0.880) | \n\t\t\t\t\t
Ramus height-left vs. -right | \n\t\t\t\t\t\ty = 0.912x + 4.958 | \n\t\t\t\t\t\t(0.871) | \n\t\t\t\t\t
Orbital breadth-left vs. -right | \n\t\t\t\t\t\ty = 0.693x + 12.370 | \n\t\t\t\t\t\t(0.849) | \n\t\t\t\t\t
Orbital height-left vs. -right | \n\t\t\t\t\t\ty = 0.728x + 9.680 | \n\t\t\t\t\t\t(0.839) | \n\t\t\t\t\t
Mandibular angle-left vs. -right | \n\t\t\t\t\t\ty = 0.737x + 28.837 | \n\t\t\t\t\t\t(0.832) | \n\t\t\t\t\t
Upper facial height vs. Nasal height | \n\t\t\t\t\t\ty = 0.522x + 15.065 | \n\t\t\t\t\t\t(0.765) | \n\t\t\t\t\t
Bi-orbital breadth vs. Orbital breadth-left | \n\t\t\t\t\t\ty = 0.478x - 5.357 | \n\t\t\t\t\t\t(0.759) | \n\t\t\t\t\t
Minimun frontal breadth vs. Maximum frontal breadth | \n\t\t\t\t\t\ty = 0.997x + 22.127 | \n\t\t\t\t\t\t(0.723) | \n\t\t\t\t\t
Maximun cranial breadth vs. Bi-zygometic breadth | \n\t\t\t\t\t\ty = 0.624x + 39.615 | \n\t\t\t\t\t\t(0.662) | \n\t\t\t\t\t
Symphysic height vs. Upper facial height | \n\t\t\t\t\t\ty = 0.784x + 42.987 | \n\t\t\t\t\t\t(0.641) | \n\t\t\t\t\t
Facial length vs. Palatal length | \n\t\t\t\t\t\ty = 0.507x - 4.481 | \n\t\t\t\t\t\t(0.637) | \n\t\t\t\t\t
Maxillary breadth vs. Bi-orbital breadth | \n\t\t\t\t\t\ty = 0.474x + 46.949 | \n\t\t\t\t\t\t(0.609) | \n\t\t\t\t\t
Anterior interorbital breadth vs. Bi-coronion breadth | \n\t\t\t\t\t\ty = 1.638x + 60.166 | \n\t\t\t\t\t\t(0.590) | \n\t\t\t\t\t
Maximum cranial length vs. Nasion-basion length | \n\t\t\t\t\t\ty = 0.314x + 43.994 | \n\t\t\t\t\t\t(0.584) | \n\t\t\t\t\t
The correlation of craniometric parameters of Thai female population.
The linear regression scatters plot and 95% interval bands of Mandibular body length -left (x) vs. Mandibular body length -right (y) (Unit: Millimeter).
The determination of sex from skeleton is one of the critical components in forensic medicine as well as archaeology. The determination can be interpreted based on the average data from craniometric parameters of certain population. The accuracy of sex determination depends on several factors which one of them is osteological elements. Various osteological elements have been used to predict sex of skeleton which includes femur (Yaşar Işcan & Shihai, 1995), tibia (Steyn & Işcan, 1997), pelvis (Durić, et al., 2005), skull (King, et al., 1998), humerus (Işcan, et al., 1998; Robinson & Bidmos, 2009), hyoid (Mukhopadhyay, 2010), talus (Murphy, 2002a) and calcaneus (Murphy, 2002b). However, among aforementioned elements, the best for prediction is pelvis, follow by skull and long bone (Durić, et al., 2005, Işcan, 2005). Rather than osteological element, population variation and method of data processing (data acquisition and statistical analysis) are also among important factors.
\n\t\t\tLogistic regression analysis is a method to analysis multi-variate analysis which aims to predict the probability of occurrence of an event under consideration by fitting the raw data using to a logit function logistic curve. The advantage of logistic regression is less of parameter restrictions than discriminant analysis and regression analysis. The output from the logistic regression analysis can only be “Yes” or “No” which normally designated as “0” and “1”, respectively.
\n\t\t\tBasically, logistic regression function (Z) is written in form of
\n\t\t\twhere β0 is called intercept and β1, β2, β3,β4, …,βn and βn+1 are regression coefficients of x1, x2, x3, x4, …,xn and xn+1 variable, respectively. From the following logistic model of Z, the probability of event (P.E.) under consideration can be calculate through
\n\t\t\tIn equation (2) e is a natural logarithm, its value is approximately 2.71828.
\n\t\t\tThe probability of event varies from “0” to “1”. The near “1” value means the independent variables influences the probability of event whereas the value close to “0” means the independent variables have little effect to probability of event.
\n\t\t\tIn this study, a binary logistic regression using forward stepwise is applied to determine sex based on average data of craniometric parameters in previous section. The fitting process excludes the measurement with high co-linearity. The probability from logistic regression function, “0” indicates male whereas “1” indicates female, respectively. All statistical analysis is preformed using statistic commercial software (SPSS, SPSSTM Inc, United States of America).
\n\t\t\tThere are three logistic regression models used in sex prediction. Model A uses only cranial parameters whereas Model B uses only mandibular parameters. Model C uses combination of cranial and mandibular parameters. From the analysis, the coefficient (β), standard error of means and significant value are reported as shown in Table 5 to Table 7.
\n\t\t\tFor Model A, there are four significant predictors (p < 0.05) in mandible parameters which are Nasion-basion length, Palatal length, Upper facial height and Maxillary breadth. The function is as follows:
\n\t\t\t\n\t\t\t\t\t\t\tCraniometric Parameter\n\t\t\t\t\t\t | \n\t\t\t\t\t\tCoefficient (β) | \n\t\t\t\t\t\tStandard error of mean (S.E.) | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSignificant level\n\t\t\t\t\t\t | \n\t\t\t\t\t
Intercept | \n\t\t\t\t\t\t76.340 | \n\t\t\t\t\t\t15.9577 | \n\t\t\t\t\t\t0.00000 | \n\t\t\t\t\t
Nasion-basion length | \n\t\t\t\t\t\t-0.387 | \n\t\t\t\t\t\t0.0984 | \n\t\t\t\t\t\t0.00008 | \n\t\t\t\t\t
Palatal length | \n\t\t\t\t\t\t0.362 | \n\t\t\t\t\t\t0.1238 | \n\t\t\t\t\t\t0.00349 | \n\t\t\t\t\t
Upper facial height | \n\t\t\t\t\t\t-0.497 | \n\t\t\t\t\t\t0.1608 | \n\t\t\t\t\t\t0.00199 | \n\t\t\t\t\t
Maxillary breadth | \n\t\t\t\t\t\t-0.197 | \n\t\t\t\t\t\t0.0708 | \n\t\t\t\t\t\t0.00530 | \n\t\t\t\t\t
Logistic response model using logistic regression analysis of Model A.
\n\t\t\t\t\t\t\tCraniometric Parameter\n\t\t\t\t\t\t | \n\t\t\t\t\t\tCoefficient (β) | \n\t\t\t\t\t\tStandard error of mean (S.E.) | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSignificant level\n\t\t\t\t\t\t | \n\t\t\t\t\t
Intercept | \n\t\t\t\t\t\t70.589 | \n\t\t\t\t\t\t18.7774 | \n\t\t\t\t\t\t0.00017 | \n\t\t\t\t\t
Bi-gonion breadth | \n\t\t\t\t\t\t-0.184 | \n\t\t\t\t\t\t0.0631 | \n\t\t\t\t\t\t0.00347 | \n\t\t\t\t\t
Coronion height-left | \n\t\t\t\t\t\t-0.310 | \n\t\t\t\t\t\t0.1042 | \n\t\t\t\t\t\t0.00289 | \n\t\t\t\t\t
Mandibular angle-right | \n\t\t\t\t\t\t-0.208 | \n\t\t\t\t\t\t0.0812 | \n\t\t\t\t\t\t0.01033 | \n\t\t\t\t\t
Mandibular body length-right | \n\t\t\t\t\t\t-0.125 | \n\t\t\t\t\t\t0.0888 | \n\t\t\t\t\t\t0.15810 | \n\t\t\t\t\t
Logistic response model using logistic regression analysis of Model B.
\n\t\t\t\t\t\t\tCraniometric Parameter\n\t\t\t\t\t\t | \n\t\t\t\t\t\tCoefficient (β) | \n\t\t\t\t\t\tStandard error of mean (S.E.) | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSignificant level\n\t\t\t\t\t\t | \n\t\t\t\t\t
Intercept | \n\t\t\t\t\t\t88.202 | \n\t\t\t\t\t\t24.4335 | \n\t\t\t\t\t\t0.00031 | \n\t\t\t\t\t
Coronion height-left | \n\t\t\t\t\t\t-0.276 | \n\t\t\t\t\t\t0.1242 | \n\t\t\t\t\t\t0.02614 | \n\t\t\t\t\t
Nasion-basion length | \n\t\t\t\t\t\t-0.596 | \n\t\t\t\t\t\t0.1741 | \n\t\t\t\t\t\t0.00062 | \n\t\t\t\t\t
Palatal length | \n\t\t\t\t\t\t0.581 | \n\t\t\t\t\t\t0.2032 | \n\t\t\t\t\t\t0.00422 | \n\t\t\t\t\t
Upper facial height | \n\t\t\t\t\t\t-0.567 | \n\t\t\t\t\t\t0.2186 | \n\t\t\t\t\t\t0.00956 | \n\t\t\t\t\t
Logistic response model using logistic regression analysis of Model C.Logistic response model using logistic regression analysis of Model C.
where
\n\t\t\tNA-BA = Nasion-basion length (unit: millimeter)
\n\t\t\tOR-STA = Palatal length (unit: millimeter)
\n\t\t\tNA-PR = Upper facial height (unit: millimeter)
\n\t\t\tZM\n\t\t\t\t\tL\n\t\t\t\t–ZM\n\t\t\t\t\tR\n\t\t\t\t = Maxillary breadth (unit: millimeter)
\n\t\t\tFor Model B, there are four significant predictors (p < 0.05) in mandibular parameters which are Bigonion breadth, Coronion height-left, Mandibular angle-right and Mandibular body length-right. The function is as follows:
\n\t\t\twhere
\n\t\t\tGO\n\t\t\t\t\tL\n\t\t\t\t-GO\n\t\t\t\t\tR\n\t\t\t\t = Bi-gonion breadth (unit: millimeter)
\n\t\t\tCO\n\t\t\t\t\tL\n\t\t\t\t-GO\n\t\t\t\t\tL\n\t\t\t\t = Coronion height-left (unit: millimeter)
\n\t\t\tCS\n\t\t\t\t\tR\n\t\t\t\t-GO\n\t\t\t\t\tR\n\t\t\t\t-GN = Mandibular angle-right (unit: degree)
\n\t\t\tGO\n\t\t\t\t\tR\n\t\t\t\t-PG = Mandibular body length-right (unit: millimeter)
\n\t\t\tFor Model C, there are four significant predictors in cranial and mandibular parameters (p < 0.05) which are Coronion height-left, Nasion-basion length, Palatal length, and Upper facial height. The function is as follows:
\n\t\t\twhere
\n\t\t\tCO\n\t\t\t\t\tL\n\t\t\t\t-GO\n\t\t\t\t\tL\n\t\t\t\t = Coronion height-left (unit: millimeter)
\n\t\t\tNA-BA = Nasion-basion length (unit: millimeter)
\n\t\t\tOR-STA = Palatal length (unit: millimeter)
\n\t\t\tNA-PR = Upper facial height (unit: millimeter)
\n\t\t\tThe set of skulls are tested according to logistic regression models (Model A, Model B and Model C) to evaluate the accuracy as reported in Table 8.
\n\t\t\t\n\t\t\t\t\t\t\tModel\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tMale\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tFemale\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tOverall\n\t\t\t\t\t\t | \n\t\t\t\t\t
\n\t\t\t\t\t\t\tModel A\n\t\t\t\t\t\t | \n\t\t\t\t\t\t92.1 | \n\t\t\t\t\t\t90.2 | \n\t\t\t\t\t\t91.3 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\tModel B\n\t\t\t\t\t\t | \n\t\t\t\t\t\t85.0 | \n\t\t\t\t\t\t86.2 | \n\t\t\t\t\t\t85.5 | \n\t\t\t\t\t
\n\t\t\t\t\t\t\tModel C\n\t\t\t\t\t\t | \n\t\t\t\t\t\t95.0 | \n\t\t\t\t\t\t93.1 | \n\t\t\t\t\t\t94.2 | \n\t\t\t\t\t
Accuracy of each logistic model (percentage).
The logistic regression analysis revealed that 4 of 21 cranial parameters and 4 of 11 mandibular parameters are significant predictors (p < 0.05). The Basion-nasion length and Bigonion breadth are the most dimorphic of the cranial and mandibular measurement, respectively. For the best prediction model, Model C which includes both cranial and mandibular parameters is recommended.
\n\t\t\tIn order to predict the gender by the parameters in Model C, the probability of being female can be calculated using equation (2) whereas the probability of being male is then inversed (1-P).
\n\t\t\tThe accuracies from Model C of the present study are compared to previous studies on sexual dimorphism using the skull of some previous studies based on South African white, South African black, Indian and Thai population. Table 9 shows a comparison of measurement techniques and average accuracies obtained from the present study and previous studies which derived from many populations.
\n\t\t\tTo the best of author’s knowledge, there is only one study (Sangvichien, et al., 2007) that determine the sex of skull based on logistic function using on four parameters which as Nasion-basion length, Maximum breadth of the cranium, Facial height, and Bi-zygometic breadth. This presented the accuracy 88.8% for overall sex classification and 82.9% and 92.1% among females and males, respectively.
\n\t\t\tFrom the table, it reveals that the present study yields higher accuracies than the many previous studies. Therefore, the Model C presents in this study can be used to determine the gender of skeleton for intact skull in forensics and archaeology. However, in order to ensure the effectiveness of logistic regression, three skulls with known gender from Thammasat University Hospital, Thammasat University, Thailand are used to test the concept. The skull No.1 and skull No. 3 are adult males whereas the skull No. 2 is adult female.
\n\t\t\tBased on logistic regression Model C which is consider to be the best model for sex prediction in Thais’ skull, Coronion height-left, nasion-basion length, palatal length, upper facial height are measured and predicted the gender. As shown in Table 10, all cases are predicted the gender correctly (3/3). Hence, the determination of sex based on the Model C of logistic regression is considered to be accurate.
\n\t\t\t\n\t\t\t\t\t\t\tPopulation\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tMeasurement Technique\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tStatistical Analysis Method\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAverage Accuracies\n\t\t\t\t\t\t | \n\t\t\t\t\t
South African White (Steyn & Işcan, 1997) 44 males 47 females | \n\t\t\t\t\t\tDirect measurement | \n\t\t\t\t\t\tDiscriminant function | \n\t\t\t\t\t\t80% - 86% | \n\t\t\t\t\t
South African black (Franklin, et al, 2005) 182 males 150 females | \n\t\t\t\t\t\t3D tactile digitizer | \n\t\t\t\t\t\tDiscriminant function | \n\t\t\t\t\t\t75% - 80% | \n\t\t\t\t\t
Indian (Deshmukh & Devershi, 2006) 40 males 34 females | \n\t\t\t\t\t\tDirect measurement | \n\t\t\t\t\t\tDiscriminant function | \n\t\t\t\t\t\t85% - 90% | \n\t\t\t\t\t
Thai (Sangvichien, et al., 2007) 66 males 35 males | \n\t\t\t\t\t\tDirect measurement | \n\t\t\t\t\t\tLogistic function | \n\t\t\t\t\t\t83% - 92% | \n\t\t\t\t\t
South African black (Dayal, et al, 2008) 60 males 60 males | \n\t\t\t\t\t\tDirect measurement | \n\t\t\t\t\t\tDiscriminant function | \n\t\t\t\t\t\t80% - 85% | \n\t\t\t\t\t
Combination (Matamala, et al, 2009) 149 males 77 males | \n\t\t\t\t\t\tDirect measurement \n\t\t\t\t\t\t | \n\t\t\t\t\t\tDiscriminant function | \n\t\t\t\t\t\t82% | \n\t\t\t\t\t
Thai (Present study) 63 males 41 males | \n\t\t\t\t\t\tThree-dimensional CAD Model | \n\t\t\t\t\t\tLogistic function | \n\t\t\t\t\t\t93% - 95% | \n\t\t\t\t\t
Comparison on methods of data assessment and statistical analysis among different studies.
The reconstruction of skull fragment (A) intact (B) intact with reconstruction unit.
\n\t\t\t\t\t\t\tCraniometric Parameter\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSkull No.1\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSkull No.2\n\t\t\t\t\t\t | \n\t\t\t\t\t\t\n\t\t\t\t\t\t\tSkull No.3\n\t\t\t\t\t\t | \n\t\t\t\t\t
Intercept | \n\t\t\t\t\t\t88.202 | \n\t\t\t\t\t\t88.202 | \n\t\t\t\t\t\t88.202 | \n\t\t\t\t\t
Coronion height-left | \n\t\t\t\t\t\t69.63 | \n\t\t\t\t\t\t53.12 | \n\t\t\t\t\t\t72.09 | \n\t\t\t\t\t
Nasion-basion length | \n\t\t\t\t\t\t105.07 | \n\t\t\t\t\t\t95.24 | \n\t\t\t\t\t\t101.06 | \n\t\t\t\t\t
Palatal length | \n\t\t\t\t\t\t58.50 | \n\t\t\t\t\t\t45.82 | \n\t\t\t\t\t\t55.17 | \n\t\t\t\t\t
Upper facial height | \n\t\t\t\t\t\t76.91 | \n\t\t\t\t\t\t72.26 | \n\t\t\t\t\t\t71.81 | \n\t\t\t\t\t
\n\t\t\t\t\t\t | \n\t\t\t\t\t\t | \n\t\t\t\t\t\t | \n\t\t\t\t\t |
Regression Analysis (Z) | \n\t\t\t\t\t\t-3.26 | \n\t\t\t\t\t\t2.43 | \n\t\t\t\t\t\t-0.59 | \n\t\t\t\t\t
Probability of event (P.E.) | \n\t\t\t\t\t\t0.037 | \n\t\t\t\t\t\t0.919 | \n\t\t\t\t\t\t0.357 | \n\t\t\t\t\t
Prediction Gender | \n\t\t\t\t\t\tmale | \n\t\t\t\t\t\tfemale | \n\t\t\t\t\t\tmale | \n\t\t\t\t\t
Exact Gender | \n\t\t\t\t\t\tmale | \n\t\t\t\t\t\tfemale | \n\t\t\t\t\t\tmale | \n\t\t\t\t\t
\n\t\t\t\t\t\t | \n\t\t\t\t\t\t | \n\t\t\t\t\t\t | \n\t\t\t\t\t |
Result | \n\t\t\t\t\t\tcorrect | \n\t\t\t\t\t\tcorrect | \n\t\t\t\t\t\tcorrect | \n\t\t\t\t\t
Craniometric measurement and sex prediction.
Since there is possibility to find skull as fragment bone in forensics and archaeology, then the assessment of necessary craniometric parameters becomes complex. Although the missing craniometric parameters can be predicted using correlation as shown in Table 3 and Table 4, but some correlation coefficients among these craniometric parameters are mostly inferior. With low correlation coefficient, the equation may not be an appropriate solution to determine those missing craniometric parameters.
\n\t\t\tAs a result, a purposed alternative is to reconstruct defected skull surface based on the mirror surface topology of normal side with aids of Computer Aided Design technique as shown in Fig. 8. In fact, this technique is a standard protocol for implant design in cranial reconstruction (Müller, et al., 2003). The purposed alternative relies on the discovery that the symmetric between left and right of bilateral craniometric parameters as presented in Table 2. However, this concept should be further investigated to ensure the usability.
\n\t\tThis study presents advantages of using advance medical imaging and reverse engineering through computed tomography scanner to reconstruct the three-dimensional model of skulls. This is very useful to analyze and measure craniometric parameters based on virtual model. Generally, in forensic medicine and archaeological researches, the study relies on direct measurement and other two-dimensional techniques which may not be accurate. The measurement errors can be influenced by human error, instrumental error, image magnification and image occlusion. The advantage of three-dimensional computed tomography technique includes the analysis of specimen without destruction or damage of specimens as well as the ability to analyze the specimens in configuration which the conventional technique cannot provide. Comparing to the other reverse engineering technologies, computed tomography presents the superior ability in accessing the internal geometry which the other tools find the difficulty in data capturing.
\n\t\t\tIn the craniometric analysis, the medians and bilateral landmarks are accessed. From the analysis, the result reveals that Thai male presents the craniometric parameters greater than Thai female, especially, Maximum cranial breadth, Facial length, Orbital height-left, Orbital height-right, Palatal breadth, Bicoronion breadth, Bizygometic breadth, Maxillary breadth, Upper facial height, Orbital breadth-left, Orbital breadth-Right, Nasal height, Bicondylar breath, Bi-gonion breadth, Coronion height-left, Coronion height-right, Mandibular body length-left, Mandibular body length-right, Maximum mandibular length-left and Maximum mandibular length-right. In both populations, the bilateral anatomy presents some degrees of correlation which may be concluded the facial symmetry.
\n\t\t\tLogistic regression is used to derive functions for sex determination based on average numerical values which obtained from craniometric parameters. Three models are purposed, Model A is based on cranial parameters, Model B is based on mandible parameters and Model C is based on both cranial and mandibular parameters. From the result, Model C provides the best accuracy among other models which is 94.2%. The prediction equation relies on four parameters which are Coronion height-left, Nasion-basion length, Palatal length, and Upper facial height which subsequently produce logistic regression as in equation (5).
\n\t\t\tAs seen in Table 9, our study yields higher accuracies than other previous studies. This is due to two main factors, the accurate landmark identification by the three-dimensional technique and developing logistic regression function from difference sample.
\n\t\t\tIn addition, the authors suggest that the techniques described in this chapter which includes data acquisition, three-dimensional computerized craniometric study and sex determination based on logistic regression function can effectively be applied to the other osteological elements in specific race.
\n\t\tThe research is supported the funding and facilities in part by the National Metal and Material Technology Center (MTEC), National Science and Technology Development Agency (NSTDA) of Thailand and Suranaree University of Technology, Thailand. In addition, the authors are grateful to Department of Anatomy, Faculty of Medicine, Khon Kaen University, Thailand for providing cadaveric skull specimens.
\n\t\tVermiculite is a mineral that belongs to the phyllosilicate subclass of the silicate class. It has an appearance similar to micas at macroscopic level (Figure 1), with varied colors (green, yellow, to brown), leafy habit, hardness about 2, and a density between 2.4 and 2.7 g/cm3.
Vermiculite appearance in hand sample.
Its structure (Figure 2) corresponds to that of the 2:1 group [1], which is composed of two T-O-T layers joined by an interlayer. The T-O-T layer is composed of an octahedral (O) sheet of Mg2+, located between two tetrahedral sheets (T) of Si4+. The interlayer is formed by an octahedral sheet of Mg2+ bound to oxygens or OH− groups. In addition, it contains water.
Vermiculite structure.
In vermiculite, isomorphic substitutions, especially in the tetrahedral sheets of Si4+ to Al3+, are very common. As a consequence of the positive charge difference, compensation occurs with cations in the interlayer space, mainly Mg2+, as mentioned before.
This structure, with spatial group C2/c, is generally disordered [2], that is, it shows stacking defects that alter the regular alternation of the layers parallel to crystallographic axis b (Figure 3).
Disordered layers in the vermiculite structure.
Due to the presence of water and OH− groups, vermiculite can undergo hydration-dehydration processes that depend on various factors such as temperature, pressure, particle size, relative humidity, and chemical composition [1, 3, 4, 5, 6, 7, 8, 9, 10].
The hydration state of vermiculites is defined by the number of layers of water in the interlayer space, with phases having zero, one, and two water layers. These phases were named by [11] as 0-WLHS (state of hydration with 0 water layers), 1-WLHS (state of hydration with 1 water layer), and 2-WLHS (state of hydration with 2 water layers), respectively. As an example, for Mg-vermiculite the basal distances are 9.02 Ǻ for 0-WLHS, 11.50 Ǻ for 1-WLHS, and 14.40 Ǻ for 2-WLHS [9, 10, 11, 12].
The chemical formula of vermiculite is X4(Y2–3)O10(OH)2M,nH2O, where X represents the tetrahedral positions (Si4+ y Al3+), Y the octahedral positions (Mg2+, Fe2+, Fe3+, Cr3+, Ti4+, etc.), and M the cations located in the interlayer space (Mg2+, Ca2+, K+, Na+, etc.) to compensate the charges, as a consequence of the isomorphic substitutions.
In addition to the described mineral that corresponds to vermiculite in the strict sense, there are the so-called commercial vermiculites. These vermiculites consist of various interstratified of mica/vermiculite, vermiculite with different states of hydration, mixtures of mica and vermiculite, etc. The distribution of the different phases would be mosaic-type (Figure 4).
Mosaic distribution of different phases in a commercial vermiculite (modified from Hillier et al. [15], with permission).
The main characteristic of commercial vermiculites is their exfoliation and expansion capacity when the vermiculite is abruptly heated, and that occurs due to the loss of water molecules located between the silicate sheets (Figure 5).
Exfoliation mechanism scheme of a commercial vermiculite when heated at 1000°C for 1 minute; (a) commercial vermiculite; (b) exfoliated commercial vermiculite; (c) scheme of the arrangement in domains of the different intergrowth phases in a particle of a commercial vermiculite; (d) diagram of the exfoliated particle; (e) structure of an ideal vermiculite; (f) structure of the exfoliated ideal vermiculite. Note: Schemes (c) and (d) modified from Hillier et al. [15] with permission.
Authors such as [13] and later [14] found that the greatest exfoliation is achieved in the case of regular mica-vermiculite interstratified. Couderc and Douillet [14] associated this fact with the collision, during the “thermal shock,” of the water molecules of the vermiculite sheets with the mica sheets, producing a greater separation between them; Hillier [15] related exfoliation with the mosaic distribution of the different mineral phases within the vermiculite particles. Lateral phase boundaries between vermiculite and other phases (mica, or vermiculite, and chlorite) would prevent vapor from escaping from a particle, resulting in exfoliation when the pressure exceeds the bonding forces that hold the layers together. This type of thermal exfoliation is the oldest and the one that is still used today mostly in the industry.
Vermiculites can be modified by changes in temperature and pressure, chemical treatments, and irradiation, causing physical and structural changes in the mineral [16, 17, 18, 19, 20, 21, 22, 23, 24].
One of the most notable physical changes is exfoliation and expansion, which are influenced by factors such as water content, type of cations of the interlayer, and interstratifications of vermiculite [10, 17, 25].
Unmodified and modified commercial vermiculites are characterized by their industrial and technological applications [26, 27, 28, 29, 30, 31, 32, 33, 34, 35]. These applications are a function of its physical and chemical properties and the treatment it has undergone, for example, thermal and acoustic insulation, adsorbent of substances, refractories, fire protection, support for hydroponic crops, light concretes, etc. The synthesis of advanced materials such as new glasses of great technological interest constitutes an example of the uses based on chemical applications. Numerous studies on the intercalation of polar organic molecules by clay minerals have been carried out. In addition to water, inorganic or organic substances can be adsorbed in the expandable interlayer space [36, 37].
The objective of this research has been to show the structural changes in commercial vermiculites induced by temperature, pressure, irradiation and chemical treatments, the relationship between these treatments, and crystallinity and the possible causes.
The investigated vermiculite samples come from Catalão (Goiás, Brazil), Paulistana (Piauí, Brazil), China, Libby (Montana, USA), Benahavis (Málaga, Spain), and Sta. Olalla (Huelva, Spain) to compare. Vermiculite from Catalão (hereinafter Goiás) is associated with an ultramafic complex; Paulistana’s vermiculite (hereinafter Piauí) is found in a hybrid basic rock, probably a lamprophyre [38]. The origin of China’s vermiculites is unknown. The origin and mineralogy of the vermiculite of Sta. Olalla have been extensively studied [39, 40, 41, 42]. This vermiculite is formed from phlogopite as a result of the alteration of pyroxenites. Vermiculite from Benahavis occurs in elongated veins, and the host rock is mainly serpentine [43, 44] and can be considered formed by alteration of phlogopite [45].
The weight percent of element oxides of the vermiculites considered in this chapter [10, 46] is in Table 1 and their water content (%) in Table 2.
Sample | Sta. Olalla1 | Benahavis1 | Piauí1 | Goiás1 | China W1 | China G1 | Palabora1 | Libby2 |
---|---|---|---|---|---|---|---|---|
SiO2 | 35.9 | 37.0 | 39.9 | 40.7 | 43.2 | 35.6 | 41.1 | 38.7 |
TiO2 | 0.3 | 2.5 | 1.1 | 0.8 | 1.0 | 1.2 | 1.2 | 1.2 |
Al2O3 | 15.8 | 14.1 | 9.3 | 11.5 | 11.9 | 11.0 | 10.0 | 13.0 |
Cr2O3 | 0.0 | 0.0 | 0.1 | 0.0 | 0.2 | 0.4 | 0.0 | 1.0 |
FeO | 3.3 | 7.6 | 6.7 | 9.6 | 4.3 | 4.6 | 7.9 | 8.6 |
MnO | 0.1 | 0.1 | 0.0 | 0.1 | 0.0 | 0.0 | 0.0 | 0.1 |
MgO | 24.1 | 21.9 | 25.5 | 18.0 | 24.3 | 21.8 | 23.3 | 20.6 |
CaO | 0.3 | 0.1 | 0.2 | 0.0 | 0.4 | 0.9 | 0.2 | 0.0 |
Na2O | 0.1 | 0.1 | 0.0 | 0.1 | 0.7 | 3.5 | 0.1 | 0.3 |
NiO | 0.0 | 0.1 | 0.0 | 0.0 | 0.0 | 0.1 | 0.1 | 0.0 |
K2O | 0.0 | 0.0 | 3.5 | 1.1 | 7.5 | 5.6 | 6.0 | 9.7 |
For the experiments with heat [10, 23], two diffractometers were used: Seifert XRD 3000 diffractometer (Scientific-Technical Services of the University of Oviedo) at 30 mA and 40 kV; Cu-Kα radiation, λ = 1.5418 Å; 2θ range of 3–20°; 2° scans of 0.02° per step; and a count time of 20 s per step and Bruker AXS diffractometer (Plasma Physics Laboratory, National University, Manizales headquarters) at 30 mA and 40 kV (Cu-Kα radiation; λ = 1.5418 Å), 2θ range of 3–40°, 2θ scans of 0.1°, and a count time of 20 s per step.
With an increase of T, the behavior of the vermiculites was different depending on the composition of the vermiculite and the type of heating (ex situ or in situ).
The result with heating ex situ at 1000°C for 1 minute was an expanded and exfoliated light product composed of enstatite in the purest vermiculites (with Mg2+ or Mg2+ and K+ in the interlayer) Sta. Olalla and Benahavis and mica and enstatite in the commercial vermiculites (with K+ and/or Na+ and/or Ca2+ in the interlayer). The exfoliation of the latter was much greater than that of the former.
The diffraction patterns made with temperature increase (40–140°C) in situ using the Seifert XRD 3000 equipment, and a powder sample showed the coexistence of the 2-WLHS phases with two layers and one layer of water, and the 1-WLHS phase was revealed. In the patterns made with the Bruker AXS diffractometer, the last phase did not appear, and it was observed that the structure practically collapsed at 100°C, phase 1-WLHS reappearing as temperature increases.
With gradual increase in T in situ, dehydration of the vermiculites could be observed until practically reaching collapse, although the behavior was different depending on whether the samples contained Mg2+ or Mg2+ and K+ in the interlayer or K+ and/or Na+ and/or Ca2+. In the former dehydration appears to be restricted to 1-WLHS, and dehydroxylation begins at lower temperatures and is faster than in the latter, in which already dehydrated vermiculite coexists with a similar structure to mica.
The experiments at atmospheric pressure P = 1.4⋅10−2 mbar and P = 2.4⋅10−4 mbar were carried out on both powder samples and exfoliation flakes of three vermiculites from Sta. Olalla (Huelva, Spain), Paulistana (Piauí, Brazil), and Western China [9]. A Seifert XRD 3000 diffractometer from the Scientific-Technical Services of the University of Oviedo was used. The conditions of use were 30 mA and 40 kV (Cu-Kα radiation, λ = 1.5418 Å), range 2θ between 2 and 70°2θ, speed 0.02°2θ/20 s. Two commercial Leybold pumps (Trivac D 2.5 E (up to 10–2 mbar) and Turbovac TMP 50 (up to 10–4 mbar)) were used for the vacuum experiments.
The effect of vacuum, like that of temperature, causes dehydration of vermiculite but with a different evolution through the different states of hydration. In fact, under vacuum, the process appears to inhibit itself to a state of hydration with one layer of water (1-WLHS). The role of T is inhibited against that of pressure. The Sta. Olalla vermiculite gave rise to the formation of three different interstratified phases: two phases characterized by an interstratification with interplanar distances, d = 11.5–13.8 Å and d = 9.6–11.5 Å, respectively, and another phase with d = 13.8 Å.
Under vacuum, P = 1.4⋅10−2 mbar, in the Sta. Olalla, vermiculite phase 2-WLHS was observed with two layers of water coexisting with phase 2-WLHS but with a layer of water. In Piauí vermiculite, the evolution of the most characteristic reflection was more remarkable since it disappears, appearing in phase 1-WLHS.
The effect was faster with powder samples, and phase 2-WLHS quickly transforms to phase 1-WLHS.
The transformations undergone by the vermiculites subjected to microwave irradiation (at 800 W and exposure times from 10 to 20 s) were characterized by X-ray diffraction [24]. A PHILIPS X’PERT PRO X-ray diffractometer was used, at 40 mA and 45 kV, Cu-Kα radiation (λ = 1.5418 Å), range of 3–70°2θ, steps of 0.02°, and a count time 1 s per step.
Microwave irradiation of vermiculite samples caused much less water loss than they do when subjected to sudden high-temperature heating; it also caused exfoliation of the material. From a structural point of view, the X-ray diffraction patterns of the vermiculites of Sta. Olalla, China, and Libby showed loss of crystallinity and disorder.
The changes induced by ultraviolet (UV), short wave (254 nm), and long (356 nm) radiation at different times (1 hour, 1 day, and 1 week) in vermiculites from Sta. Olalla, Libby, and China were studied by using X-ray diffraction [46]. A PHILIPS X’PERT PRO X-ray diffractometer was used, at 40 mA and 45 kV, Cu-Kα radiation (λ = 1.5418 Å), range of 3–10°2θ, steps of 0.007°, and a count time 1 s per step. Crystallite size and structural deformation were evaluated using PANalytical software (X’Pert Plus).
In the powder samples of Sta. Olalla, Libby, and China, a decrease in the intensity of the most characteristic reflections was observed as well as a decrease in the size of the crystallite and an increase in deformation. The results were more significant for powder vermiculite from China than for Sta. Olalla and Libby vermiculites, probably due to the coexistence of different hydration states, interstratifications, and superstructures in the initial vermiculite in China. The water loss in these long and short UV irradiated samples for 168 hours was 4 and 4.5% for the Sta. Olalla sample, 0.9 and 1% for the Chinese sample, and 6.4 and 7% for the Libby sample. In the exfoliation flake samples, an increase in the intensity of the most characteristic reflection is observed, in addition to a larger crystallite size and a lower percentage of deformation, so that the crystallinity increased.
By ion exchange of metals (Ni2+, Fe2+, Fe3+) for the Mg2+ of the interlayer in the vermiculite-Mg of Sta. Olalla (Huelva, Spain).
In the case of nickel [35], an aqueous solution of Ni2+ acetate was used, and in the case of iron [47], FeCl2 and FeCl3 solutions were used. The crystal structures of the nickel and iron vermiculites were refined using the DIFFaX+ program [48] (and a later version). The characterization was carried out with X-ray diffraction by transmission using an InEL XRD RG3000 cobalt tube vertical diffractometer (λ = 1.7890 Å) (40 kV, 35 mA) and an InEL CPS 120 detector, in the 2θ range of 4–70° (step 0.03°, total acquisition time of 5400 s). Refinement confirmed the similarity of the Ni2+-, Fe2+-, and Fe3+-vermiculites with the Mg-vermiculite. In the Fe2+-vermiculite reflections corresponding to the akaganeite (β-FeOOH) (JCPDS card 01–075-1594), a phase that was corroborated by Mössbauer spectroscopy (16%) was observed, a technique that also allowed showing the presence of said phase (3%) in the Fe3+-vermiculite. Only vermiculite was detected in the Ni2+-vermiculites obtained from the starting vermiculite, while in the one obtained from the homoionized starting vermiculite (with brucite -Mg (OH)2−), a brucite phase with magnesium and nickel was also detected. In this refinement it was found that Ni2+ and Fe2+ also enter the octahedral layer, although there was no evidence for Fe3+.
Nitric acid treatment at 4 and 8 M was used at room temperature and different treatment times on the purest vermiculite from Sta. Olalla and two commercial vermiculites from Goiás and China, respectively [49]. To quantify potential loss of mass or water, 1 mL of each sample was weighed pre- and post-acidic treatment, and their volume post-treatment was measured. To identify any structural change, X-ray diffraction patterns were taken with a PANalytical X’pertPro diffractometer using 40 mA and 45 kV (Cu-Kα radiation; λ = 1.5418 Å), 2θ scans 5–35o, 2θ step scans of 0.007°, and a counting time of 1 s per step. TEM high-resolution microscope with a resolution of 1.9 Å between points and 1.0 Å between lines was used to obtain TEM and selected area electron diffraction (SAED) micrographs with its accompanied CCD camera (Gatan).
Vermiculites treated with acid suffered (a) slight delamination and color (Figure 6); (b) weight loss (Table 3) due to the mass and water loss; (c) inhomogeneous cation leaching, probably achieved to transfer iron from those octahedral sheets to clusters deposited on vermiculite layers (Figure 7) [50, 51, 52, 53] (and in the samples with high iron content, this element would have prevented further leaching of cations but not water loss); and (d) structural transformation that resulted in the formation of lamellar products with low crystallinity and order, composed by amorphous silica and other phases whose identity and percentage varied depending on the vermiculite type.
Color of treated vermiculite from Sta. Olalla.
Samples | HNO3 molarity | Time | Weight loss (%) |
---|---|---|---|
Sta. Olalla | 4 | 1 | 70 |
7 | 75 | ||
8 | 1 | 72 | |
7 | 70 | ||
Goiás | 4 | 1 | 12 |
7 | 14 | ||
8 | 1 | 47 | |
7 | 47 | ||
China | 4 | 1 | 22 |
7 | 27 | ||
8 | 1 | 53 | |
7 | 52 |
TEM and SAED micrograph of polycrystalline goethite in Goiás vermiculite .
For the experiments with Cr3+ [54] and Cr6+ [55], commercial vermiculite from China thermo-exfoliated at 900°C for 1 minute was used. With Ni2+, commercial from Piauí (Brazil) and China, vermiculites thermo-exfoliated at 1000°C for 1 minute were used [35].
Vermiculite characterization after Cr3+ adsorption was performed with X-ray diffraction using a Bruker AXS D8 Advance diffractometer with an Anton Paar HTK1200 oven at room temperature and 900°C for 1 minute. The equipment conditions were 30 mA and 40 kV, Cu-Kα radiation (λ = 1.5418 Å), range of 3–40°2θ, 0.1° steps, and a count time of 20 s per step.
The X-ray spectra of Chinese vermiculite after having been in contact with a solution of synthetic seawater and dissolved Cr3+ with concentrations of 0.75 and 2.0 ppm suggested that the mica-like phase of the exfoliated vermiculite would have been transformed back into a vermiculite-like structure, similar to that of the original sample. In contrast, in the X-ray spectrum of Chinese vermiculite after having been in contact with distilled water solution and dissolved Cr6+ with concentrations of 1 ppm (Figure 8), no change is observed.
X-ray diffraction of the starting Chinese vermiculite and abruptly heated at 900°C for 1 minute (a) and after having been in contact with 1 ppm Cr6+ in distilled water (b).
Several experiments with vermiculite samples from Sta. Olalla (Huelva, Spain), Libby (Montana, USA), and Goiás (Brazil), in both powder and flakes forms, were carried out [56]: (a) treatment with 30% and 50% hydrogen peroxide solution, at different times for each sample; (b) irradiation with microwaves for 20 s of Libby and Goiás samples; and (c) treatment with 30% and 50% hydrogen peroxide solution in the microwave oven for 20 s of vermiculite samples from Goiás. X-ray diffraction was used to identify structural changes. For the powder samples, a PHILIPS X’PERT PRO diffractometer was used at 40 mA and 45 kV, Cu-Kα radiation (λ = 1.5418 Å), range of 3–70°2θ, steps of 0.02°, and a count time 1 s per step. For the flake samples, a Seifert XDR 3000 T/T diffractometer was used at 30 mA and 40 kV, Cu-Kα radiation (λ = 1.5418 Å), range of 2–10°2θ, steps of 0.02°, and a time of 20 s count per step. The results showed that the vermiculites hardly underwent changes at the structure level, despite the change in appearance and textural (color, exfoliation, corrugation, undulations) (Figure 6). The three vermiculites—Sta. Olalla, Goiás, and Libby—showed a slight increase in the intensity of the main reflection. The change was slower in powder form than in flake samples, at least in Libby vermiculite.
Alcohol (methanol, ethanol, propanol, butanol).
The structural changes of commercial vermiculites treated with alcohol and alcohol for 1 month and subsequent microwave irradiation for 20 seconds were analyzed using X-ray diffraction [57, 58]. The equipment used was a PHILIPS X’PERT PRO diffractometer, at 40 mA and 45 kV, Cu-Kα radiation (λ = 1.5418 Å), range of 3–12°2θ, steps of 0.007°, and a count time of 1 s per step. Changes in the intensity and position of the basal reflections were used to indicate changes in the structural order and in the hydration states. In Sta. Olalla vermiculite, the intensity of the most characteristic reflection decreased with all the alcohols and times investigated. In the Chinese and Libby vermiculites, the intensity of the most characteristic reflections with methanol and ethanol also decreased, while with propanol and butanol, as a function of time, there was an increase in intensity and optimization of the profile of the aforementioned reflections and incipient appearance of phases with different hydration states (in Chinese vermiculite).
The diffraction spectra for the vermiculite particles from China and Libby treated with alcohol for 1 month and subsequent microwave irradiation for 20 seconds, exfoliated and non-exfoliated, are shown in Figure 9 [59]. In these vermiculites treated with butanol or propanol and subsequent microwave irradiation, it should be noted that the crystallinity and the order of phases 2- and 2-1-WLHS of the exfoliated and non-exfoliated particles improved in relation to the untreated ones, except in Chinese exfoliated particles after butanol treatment and subsequent microwave irradiation. The opposite occurred with methanol or ethanol treatment and subsequent microwave irradiation, except in the Chinese exfoliated particles after methanol treatment and subsequent microwave irradiation.
X-ray diffraction of the samples from China (a) and Libby (b) treated with alcohol for 1 month and subsequent microwave irradiation for 20 seconds (Marcos et al. [59]). Note: m = methanol, e = ethanol, b = butanol, p = propanol, ex = exfoliated, no = no exfoliated.
The structural modifications of the investigated vermiculites treated thermally, with vacuum, or irradiation or chemically, consist of the phase transformation and the increase or loss of crystallinity and, therefore, the increase or decrease of the structural order. Depending on the treatment, the increase in crystallinity may be accompanied by the appearance of the majority starting phase, and the loss of crystallinity may be accompanied by the appearance or disappearance of interstratified phases.
Vermiculite responds to an increase of T by transforming its structure, which affects its applications. It is a dynamic process that depends on the composition, size, and shape of the particle, relative humidity, and process conditions (in situ or ex situ heating). With T increase, the transformations occur due to dehydration, greater in the purest vermiculites and less in the most micaceous ones. With abrupt ex situ heating, at 1000°C, with powder samples, the purest vermiculites are transformed into enstatite and the least pure into mica and enstatite; in both cases they appear expanded and exfoliated. With gradual heating in situ, at 1000°C and in flake samples, the structure practically collapses in the purest and the most micaceous vermiculites; although it fails to do so, its crystallinity is very low. Dehydration would occur by the escape of water in the form of steam. This escape would occur when the vapor pressure exceeds the bonding forces that hold the layers together, causing exfoliation and expansion [15]. The process occurs faster in powder samples than in flake samples.
The effect of the vacuum is similar to that of the temperature increase; the transformation also occurs by dehydration, although the process seems to be inhibited to a state of hydration with a layer of water (1-WLHS), without additional dehydration of the samples up to a state of hydration of zero layers of water (0-WLHS). The loss of water was less than with an increase in T. The process is slower than with an increase in temperature in situ since the pressure does not imply an increase in the activation energy as with the first. In addition, it was shown that the dehydration process occurs through different interstratified states in vermiculite. This result has been related to the content of Mg2+ cations in the interlayer, due to its affinity with water molecules. The purest vermiculite of Sta. Olalla showed the most complex dehydration process due to its higher magnesium content in the interlayer. Due to its affinity for water, the higher the content of the cation, the greater the difficulty in eliminating water molecules. When the temperature and the vacuum are acting simultaneously, the sample is dehydrated just after the vacuum is established, and the temperature has no additional effect. The process, as with temperature increase, occurs more quickly in powder samples than in sheet samples.
Microwave irradiation of vermiculite samples caused a loss of water much lower than what they suffer when subjected to sudden heating at high temperature. The said dehydration was slower than with vacuum or with sudden heating at 1000°C. As a consequence, the phase with d = 13.8 Å in Sta. Olalla, for example, could not be observed. The crystallinity loss and structural disorder is attributable to the water loss. There was no collapse of the structure or formation of new phases, probably because this loss was much lower than that produced at a temperature higher than that produced by microwave radiation. The expansion process began in the flake center and advanced toward the edges. The alignment and reorientation of the water dipoles with the applied field generated internal friction that caused the heating of the vermiculite and the vaporization of many of the water molecules. The explanation of steam escape and exfoliation would be the same as when the temperature rises.
The decrease in crystallinity and structural order in vermiculite powder samples irradiated with long and short UV is also attributable to the water loss. On the contrary, in crystalline samples the crystallinity and structural order increased. In this case there was surely rehydration by ambient humidity adsorption.
In the chemical treatment by ion exchange of Ni2+ or Fe2+ or Fe3+ metals by the Mg2+ of the interlayer in the Mg- vermiculite of Sta. Olalla, the decrease in the interplanar distance d002 has been interpreted as due to the interaction of the cation and a possible modification of the interactions between the exchanged cation and the TOT sheets, due to both the nature of the new cation and the variations in the quantity and distribution of the H2O molecules that it induces. The formation of brucite in the homoionized starting vermiculite could be due to the homoionization process itself, consisting of introducing the vermiculite in a solution of MgCl2 in order to eliminate possible impurities such as Na+, Ca2+, etc., coexisting with Mg2+. In the vermiculite intercalated with nickel from this homoionized vermiculite, a brucitic phase with magnesium and nickel was also detected.
According to Ravichandran and Sivasankar [50], the reaction with nitric acid first caused the replacement of the exchangeable cations (Mg2+, Ca2+, K+, Na+) by protons, which will subsequently attacked the layers. Secondly, partial leaching of Al2+, Mg2+, and Fe2+ and Fe3+ from the tetrahedral and octahedral layers occurred. The silicon remained in the form of amorphous silica and quartz; this lasts in a very low percentage, which disappeared with the increase of the acid concentration in any of the samples. The Sta. Olalla sample suffered greater leaching of cations and water loss than the Goiás and China samples, whose high iron content would have prevented further leaching of other cations.
The heat treatment of the vermiculites and subsequent reaction with synthetic seawater solutions with Cr3+ and Ni2+ would have caused the reappearance of the starting vermiculite, by rehydration. Probably, its union with the water trapped in the thermo-exfoliated structure may have made this structure closer to the original, that is, the mica-like structure would have moved back to that of the vermiculite. In aqueous solution Cr3+ would be in the form [Cr(H2O)6] 3+ and Ni2+ as [Ni(H2O)6]2+; in both cases its adsorption in thermally expanded vermiculites would be controlled by different cooperative mechanisms: (1) cation exchange and (2) surface complexation reactions [60, 61, 62, 63]. It is important to note that a very low percentage of Ni2+ could have precipitated in the pores or on the surface of vermiculite such as magnesium and nickel hydroxide, according to the findings in unheated Ni2+-, Fe2+-, and Fe3+- vermiculites [35, 47]. The cation exchange process would be favored by the fact that Cr3+ and Ni2+ have an ionic radius (0.69 and 0.78 Å, respectively), similar to that of Mg2+ (0.72 Å). This ion exchange process would have taken place considering that the product resulting from the heating of vermiculite would constitute a heterogeneous system formed by one or more disordered crystalline phases (mica type) with hydroxyl groups and some cations between layers of the original phase and molecules of water.
This transformation would have occurred due to the rehydration of the sample in the adsorption process, which should be directly related to the characteristics of the cation involved [64]. The transformation in both cases would be consistent with the investigations carried out by Derkowski and McCarty [65] on the rehydration of dehydroxylated smectite in an environment of low water vapor. The equilibrium occurs in the solid/liquid interface, where the available centers located on the surface could be exchanged with the species in the solution. This adsorption process would be the opposite of what happens to vermiculite when it expands to 900°C.
The transformation could have occurred due to two aspects: on the one hand, the ionic exchange of ions of the interlayer with Na+ and other ions of the saline solution and on the other hand the lower force of attraction with the water of the interlayer which has Na+ in relation to Mg2+ or Ca2+ [66]. In the case of no transformation because there was no hydration or dehydration, since there was no change in weight before and after the adsorption of the ion by expanded vermiculite, probably due to the characteristics of the cation involved [64].
In the case of the adsorption of Ni2+ by vermiculite, the behavior would have been similar to that of the adsorption of Cr3+ [54], although it would have to be confirmed experimentally.
The reaction with hydrogen peroxide showed textural rather than structural changes. The water content (Table 4) was practically the same in both the Goiás and Libby samples treated with H2O2 and untreated. The absence of hydration-dehydration is the cause of no phase transformation.
Samples | Treatment | |||||
---|---|---|---|---|---|---|
— | Microwave irradiation | 1000°C | H2O2 | |||
30% | 50% | |||||
Sta. Olalla | 25.6 | 24.9 | 4.9a | H2O wt (%) | ||
Goiás | 12.1 | 12.2 | 5.6 | 12.1 12.7b | 12.1 12.9b | |
Libby | 10.3 | 11.1 | 3.4 | 10.9 | 11.4 |
Water content (%) obtained by thermogravimetry of untreated and treated samples of Sta. Olalla, Goiás, and Libby.
The leached cations, in greater quantity those of the interlayer (Na+, K+, etc.) than those of the tetrahedral and octahedral layers, would be replaced by the H+ ions of the solution [21]. These ions gave rise to two effects: (1) increase of the pH of the solution and (2) corrosion of the vermiculite particles.
The structural changes of commercial vermiculites treated with alcohol, dehydration-hydration, and disorder-order would be related to the replacement of water by alcohol in a very low percentage, with weight loss and, depending on the type of vermiculite, appearance of phases with state of hydration of less layers of water. The structural changes of commercial vermiculites treated with alcohol and subsequent irradiation with microwaves consist of an increase or decrease in crystallinity and order. The results indicated dehydration-hydration and structural order-disorder that would be related to the entry of alcohol into vermiculites by water replacement, that is, by loss of water. The changes occurred in a manner similar to those produced with temperature and vacuum and were less pronounced for the purest vermiculite.
Structural changes of vermiculites induced by the above mentioned treatments provide evaluable information on the relationship between the structure of vermiculite and their industrial applications. In vermiculite applications as intumescent fire barriers [67, 68, 69] where exfoliation at low temperatures is required, the treatment type, in this case microwave irradiation, is more important than the structural change suffered by vermiculite. In the case of vacuum, not only the type of treatment but also the structural changes suffered by the vermiculite influence, since under pressure the vermiculite could act as a deposit mineral and host contaminating elements. Vermiculite irradiated with ultraviolet radiation could be used as material for optoelectronic devices because this radiation is less penetrating and easier and cheaper to obtain than gamma radiation [70]. Fe2+- and Fe3+- vermiculites maintain its paramagnetic character; and Ni2+- vermiculite behaves as a two-dimensional spin-glass system in which planar ferro- and antiferromagnetic interactions compete, responsible for the complex magnetic behavior found. Ni2+- vermiculites are interesting materials to study experimentally or in simulations, with applications to physics, chemistry, materials science, and artificial neural networks in computing [71]. Alcohol treatment and subsequent microwave irradiation may be the procedure for obtaining purest vermiculite from a less pure sample. Nitric acid treatment of vermiculites with high iron content resulted in a lamellar products with high porosity, important in many applications such as low cost and efficient and sustainable adsorbent for dyes and metals [60, 72, 73, 74]. It is important to highlight how exfoliated vermiculites can remain unchanged depending on the valence of the adsorbed ion and the salinity and pH of the medium.
Consequently, the relationship between structural changes of vermiculite and the chemical and physical treatments could contribute to predicting the structural order–disorder of the vermiculite; the obtaining of purest vermiculite; the environmental fate of toxic metals, such as cesium (radioactive metal) in contaminated areas; and developing methods to extract these metals from contaminated soils or waters [75].
Further, the changes suffered by vermiculites due to the treatments applied could give light to ambiguities about their geological origin due to hydrothermal and/or supergene processes. However, most and possibly all macroscopic vermiculite and interstratifications of vermiculite and other phases (mica, chlorite) are believed to be of supergene origin [76, 77]. The changes suffered by vermiculites due to hydrogen peroxide treatment and ionic metal exchange, with water gain, could point to this origin, corroborating both the field and laboratory evidence in early times [76]. Regarding the treatments that involve water loss in vermiculites, it is not discarded that a more detailed study helps to reveal data related to the hydrothermal origin. Some aspects observed in the transformations caused by treatments with water loss could coincide with field observations [78, 79].
Starting vermiculites with high K+ content in the interlayer have more interstratified phases and lower water content and are less crystalline.
The crystallinity loss and therefore the structural disorder increase are caused by the structural water loss. On the contrary, the crystallinity increase is produced by water gain.
The vermiculite transformation by structural water loss occurs with temperature increasing, vacuum, irradiation with microwaves or ultraviolet, and both alcohol and acidic treatment. On the contrary, the transformation by water gain occurs in vermiculites treated with hydrogen peroxide and in those subjected to ionic metal exchange.
Structural changes of vermiculites induced by the abovementioned treatments provide evaluable information on the relationship between the structure of vermiculite and their industrial applications. The said relationship would allow predicting the structural order-disorder of the vermiculite, the obtaining of purest vermiculite, or the environmental fate of toxic metals.
The changes suffered by vermiculites due to the treatments applied could give light to ambiguities about their geological origin and hydrothermal and/or supergene processes. Early field and laboratory evidence and current experiments showing changes in vermiculites caused by treatment with hydrogen peroxide and ion-metal exchange, with water gain, could point to a supergenic origin. Regarding the treatments that involve water loss in vermiculites, it is not discarded that a more detailed study helps to reveal data related to the hydrothermal origin.
The author declares that she has no known competing financial interests or personal relationships that could have appeared to influence the work reported in this chapter.
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