\r\n\t1. To draw spotlight on recent studies and research concerned with the regeneration process in animal kingdom and models with emphasis on the cellular origins of regeneration. \r\n\t2. Then, we will be dealing with the reasons for the differences in the regenerative capacity of animals on many levels, including the molecular mechanism, gene expression, epigenetic regulation, common elements affecting regeneration and comparing their contributions to regeneration. \r\n\t3. To provide new insights into how to promote regeneration in mammals.
",isbn:null,printIsbn:"979-953-307-X-X",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"689b9f46c48cd54a2874b8da7386549d",bookSignature:"Dr. Hussein Abdelhay Essayed Kaoud",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/8575.jpg",keywords:"Regeneration, Cellular Basis, Molecular Basis, Differentiation, Epigenetic Regulators, Regeneration Associated Genes, Autotomy, Epimorphosis, Morphallaxis, Polyphyodonty, Vertebrates, Invertebrates",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 17th 2020",dateEndSecondStepPublish:"December 15th 2020",dateEndThirdStepPublish:"February 13th 2021",dateEndFourthStepPublish:"May 4th 2021",dateEndFifthStepPublish:"July 3rd 2021",remainingDaysToSecondStep:"3 months",secondStepPassed:!0,currentStepOfPublishingProcess:4,editedByType:null,kuFlag:!1,biosketch:"A pioneering researcher in molecular biology, epidemiology, aquaculture toxicology, full professor of animal health and environmental pollution senior member, and holder of two registered patents and three scientific records. Veterinary fellowships in animal care and surgeons and wildlife management & conservation.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"265070",title:"Dr.",name:"Hussein Abdelhay",middleName:null,surname:"Essayed Kaoud",slug:"hussein-abdelhay-essayed-kaoud",fullName:"Hussein Abdelhay Essayed Kaoud",profilePictureURL:"https://mts.intechopen.com/storage/users/265070/images/system/265070.png",biography:"Dr. Hussein Kaoud was the Chairman of the Department of Preventive Medicine at Cairo University. He has given lectures in Molecular Epidemiology and Biotechnology at different universities and has been a member of many International Publishing Houses, Reviewer, and Editor for indexed journals. Currently, he works as Full Professor of Preventive Medicine at Cairo University, Egypt. His research interest is focused on Molecular Biology and Advanced Technology of Basic Life Sciences after he had his Ph.D. and D.Sc. He has published more than 300 publications. Dr. Hussein Kaoud has several international books, one international award (USA), 10 Cairo university International Publication awards and the Appreciation Award in Advanced Technological Sciences, from Cairo University. He supervised, examined and discussed many medical dissertations.",institutionString:"Cairo University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"4",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Cairo University",institutionURL:null,country:{name:"Egypt"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"6",title:"Biochemistry, Genetics and Molecular Biology",slug:"biochemistry-genetics-and-molecular-biology"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"297737",firstName:"Mateo",lastName:"Pulko",middleName:null,title:"Mr.",imageUrl:"https://mts.intechopen.com/storage/users/297737/images/8492_n.png",email:"mateo.p@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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by"}}]},chapter:{item:{type:"chapter",id:"9904",title:"Analysis and Experimental Study of a 4-DOF Haptic Device",doi:"10.5772/8687",slug:"analysis-and-experimental-study-of-a-4-dof-haptic-device",body:'\n\t\t
\n\t\t\t
1. Introduction
\n\t\t\t
This chapter presents a new configuration of a haptic device based on a 4-DOF hybrid spherical geometry with a design of a distributed computational platform. The Spherical Parallel Ball Support (SPBS) type device, as it is referred to, consists of a particular design feature with the intersecting joint axes of both active and passive spherical joints. The orientation of the device is determined through the active spherical joint using a special class of spherical 3-DOF parallel geometry. In addition, the passive spherical joint (ball and socket configuration) is introduced in the design to increase the mechanical fidelity of the device. A new forward and inverse kinematics analysis are presented. The study is motivated by deriving a mathematical model and a closed-form solution of the kinematics of the proposed device configuration. A novel desktop computational platform is proposed and studied for creation of haptic feedback. The experimental studies are presented by specifying and demonstrating a virtual wall as a performance-benchmarking tool and aimed to verify a desirable update rate of 1 kHz or more for the haptic effect. A computational algorithm is devised by using a reconfigurable experimental setup that would achieve the desired haptic effect. This framework consists of the 4-DOF prototype, a host computer, and a data acquisition system which uses a microprocessor, a FPGA, integrated circuits and pulse-width-modulation. Such architecture can offer a novel distributed system for tele-operation over the Internet and haptic rendering of deformable objects. Through analysis of the experimental setup, key parameters have been identified for synthesis of a future tele-operation environment.
\n\t\t\t
\n\t\t\t\t
1.1. Objectives
\n\t\t\t\t
The major objective of this research is to design, develop and experiment with a novel haptic hardware environment. The design of this architecture and its building blocks are aimed to be reconfigurable, programmable, portable and scalable such that it supports the integration towards a distributed system framwork of a surgical simulator. In this work, we first specified the haptic effect that we wanted to create as an objective. We then demonstrated a virtual wall as a performance-benchmarking set-up and devised a computational algorithm to verify the desirable update rate for the haptic effect using our custom-designed experimental setup and the force-feedback device (Ma & Payandeh, 2008).
\n\t\t\t\t
The Spherical Parallel Ball Support type device is a prototype based on a 4-DOF hybrid spherical geometry. The orientation of the device is determined by the mobile platform on the active spherical joint using a special class of spherical 3-DOF parallel geometry. In parallel mechanism configuration, the moving end effector is connected to a fixed reference base via multiple kinematic chains. Any two chains thus form a closed kinematic chain which is different in topology in comparison with open loop mechanisms such as the serial robotic arm. Parallel robots (such as the Stewart platform and the Delta robot) usually have wider mechanical bandwidth than traditional articulated robots. This is due to the location of the actuators which can be mounted on the supporting base which as a result can reduce the floating mass of the mechanism. However, it is also known that computational complexities involved in obtaining various kinematic solutions such as forward kinematics can result in more than one unique solution. Our study is motivated by deriving a computational model which can result in a closed-form solution of the kinematics for our proposed haptic device configuration.
\n\t\t\t\t
In addition, we designed and developed a modular and distributed scheme aiming at a parallelization of the main components of haptic interaction tasks (haptic rendering). We present the design and performance study of a data acquisition system (DAS) which is adapted into our framework. The DAS is reconfigurable and capable of controlling the SPBS haptic device at a fast update rate. The local interconnection framework consists of the host control computer, the custom-designed data acquisition system, and the haptic device. The UDP/IP and TCP/IP socket interface are used for communications between the DAS and a host computer in order to collect performance benchmarking results.
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
1.2. Contributions
\n\t\t\t\t
The major contributions of the research are summarized below.
\n\t\t\t\t
\n\t\t\t\t\tAnalysis of a 4-DOF haptic device and derivation of a closed-form solution: a mathematical model and analysis of a new device geometry/configuration is presented. The forward and inverse kinematic solutions and static force mapping are derived.
\n\t\t\t\t
\n\t\t\t\t\tA distributed computational system framework: a novel desktop computational platform for haptic control of the device is developed. Such architecture can offer a novel distributed system for tele-operation over the Internet and haptic rendering of deformable objects using medical imaging data. In addition, software application development is designed to target multiple operating systems support. This provides the flexibility of the targeted operating systems (Windows, Linux, Solaris, etc.) for running the virtual environment (GUI, graphics, and haptics rendering).
\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
2. Analysis of the Haptic Mechanism
\n\t\t\t
In this section, we present the development and experimental results of the Spherical Parallel Ball Support type mechanism (Li & Payandeh, 2002). The distinctive feature of SPBS is that it uses a 4-DOF hybrid spherical geometry (see Figure 1). The objective is to take advantage of the spherical 3-DOF parallel geometry as the supporting platform. Hence, the orientation of a stylus is determined by pure rotation of the platform in its workspace while the translational motion of the haptic handle is supported by a prismatic joint. Unlike model presented in (Gosselin & Hamel, 1994), in this design, the rotational axes of the three actuators are coplanar. The center of the sphere is located below the mobile platform where the haptic gripper handle is connected and also located at this center a passive ball/socket supporting joint. This joint is used for supporting both the resultant user interactive forces and also the static weight of the parallel spherical mechanism. The kinematic architecture and geometric parameters of SPBS are presented first. In order to understand the kinematics of the mechanism, a closed-form solution for the forward and inverse kinematics is developed.
\n\t\t\t
Figure 1.
Design model of the hybrid 4-DOF haptic mechanism.
\n\t\t\t
\n\t\t\t\t
2.1. Kinematic model
\n\t\t\t\t
The architecture of SPBS consists of a particular design using an active/passive spherical joint and an active translational joint. The active spherical joint supports a moving platform connected to a fixed base via a spherical parallel mechanism configuration. There are three symmetrical branches which result in a total of nine revolute joints. Each branch has one active joint. Specifically, the mechanical structure of one of the three branches contains an actuator, an active cam, an active link and a passive link. The off-centre gripper handle is attached to the moving platform via a prismatic joint which constitutes to an additional translational degree of freedom. The rotational axes of all nine revolute joints intersect at a common point “O” known as the center of rotation of the mechanism (this point is also the center of the passive spherical joint in the form of a ball/socket configuration). For purposes of legibility only one of the three branches is shown in Figure 2.
\n\t\t\t\t
Geometrically, the base and the moving platform can be thought of as two pyramidal entities having one vertex in common at the rotational center “O”. The axes of the revolute joints of the base and of the mobile platform are located on the edges of the pyramids. For purposes of symmetry, the triangle at the base of each pyramid is an equilateral triangle.
\n\t\t\t\t
Figure 2.
Geometric parameters of a spherical 3-DOF parallel mechanism.
\n\t\t\t\t
Let angle γ1 be the angle between two edges of the base pyramid, angle γ2 be the angle between two edges of the mobile platform pyramid, and angle βi i = 1, 2 be the angle between one edge and the vertical axis. The angles are related through the following equation (Craver, 1989):
In addition, angles α1 and α2 represent the radial length associated with the intermediate links. The designs presented in (Gosselin & Hamel, 1994) and (Birglen et al., 2002) use a special class of the geometry which lead to a simplification of the forward kinematics problem. The geometry of SPBS also takes into account some implicit design by explicitly defining coplanar active joints. This results in the following geometric parameters being used in the design of SPBS, namely, α1 = 90 , α2 = 90 , γ1 = 120 , and γ2 = 90 , respectively.
\n\t\t\t\t
It has been shown that for the general case the forward kinematic problem can lead to a maximum of eight different solutions. One isotropic configuration has been studied in order to obtain an optimized solution of the kinematic problem. Other approaches have been considered in the past using numerical solutions such as artificial neural networks and polynomial learning networks (Boudreau et al., 1998) to solve the kinematic problem. In the following, a new closed-form algebraic solution of the inverse and forward kinematics problem of the configuration used by SPBS is presented.
Let \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t\ti = 1, 2, 3 be a unit vector (see Fig. 2) defining the revolute axis of the ith actuator. Let ηi\n\t\t\t\ti = 1, 2, 3 be an angle measured from u1 to \n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t,\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t and\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t, respectively. The schematic of SPBS and the reference coordinate frame are shown in Fig. 3. By symmetry, η1 = 0 , η2 = 120 , and η3 = 240 , the following can be defined:\n\t\t\t\t\t
Schematic of SPBS and the reference coordinate system.
\n\t\t\t\t
Let θi\n\t\t\t\t\ti = 1, 2, 3 be the rotation angle of the ith actuator. Then, vector \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tw\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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\n\t\t\t\t\ti = 1, 2, 3 can be defined as a unit vector associated with the revolute joint between the passive link and the active link. Using standard transformation matrices, we can obtain
Similarly, vector \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 i = 1, 2, 3 can be defined as a unit vector along the axis of the ith revolute joint on the mobile platform. Since each of these axes make an angle γ2 = 90 with the others, an orthonormal coordinate frame can be attached to the mobile platform for describing its orientation relative to the reference coordinate frame.
\n\t\t\t\t
We introduce the rotation matrix Q in order to describe the instantaneous orientation of the mobile platform with X-Y-Z fixed angles rotation. Hence, three successive rotations are defined by a rotation of angle 3 about the X-axis, a rotation of angle 2 about the Y-axis, and a rotation of angle 1 about the Z-axis (see Figure 4). Let \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\to\n\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 = X, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\to\n\t\t\t\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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= Y, and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\to\n\t\t\t\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 = Z, respectively. The orientation of the mobile platform can be expressed as
X-Y-Z fixed angles rotation relative to the reference coordinate system.
\n\t\t\t\t
\n\t\t\t\t\t
2.1.1. Derivation of Inverse Kinematics
\n\t\t\t\t\t
Suppose the vector components \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t,\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\t\t\ty\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t,\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t for i = 1, 2, 3 specify a known orientation of the mobile platform relative to the reference frame.
Since the vectors \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tw\n\t\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t and\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t, i = 1, 2, 3 are orthogonal when α2 = 90 , the substitution of (3) and (6) with the geometric parameters of SPBS then lead to simple equations in the sine and cosine of the actuated joint angles,
The solution of the forward kinematic problem for this configuration is discussed below. Using (4) and (5), expressions of vectors \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\ti = 1, 2, 3 as functions of the angles 1, 2, and 3 are obtained. These expressions are then substituted into (7) together with (3). This leads to three equations with the three unknown (1, 2, and 3) as follows,
The solution of these three equations for angles 1, 2, and 3 give the solution of the forward kinematic problem. For the special geometry of our proposed haptic design, a simpler expression for the forward kinematic problem can be obtained. In fact, because of the definition of our fixed reference frame chosen here and the choice of the fixed angles rotation sequence, eq. (11) can be solved for:
Since (23) to (25) are only expressed in terms of the actuated joint angles θ1, θ2, and θ3, these coefficients in (22) can be calculated instantaneously. Four solutions can be obtained algebraically for 2 from (22). Using the two sets of solutions obtained in (14), a total of eight solutions can be obtained for 2.
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Once angle 2 is determined, either (12) or (13) can be rearranged to compute 3 as follows
For the sets of solutions of 1, 2, and 3 that can be obtained, the computation of the rotation matrix Q will result in a maximum of eight different X-Y-Z fixed angles rotation matrices with respect to the reference frame. One of these solutions represents the orientation of the mobile platform corresponding to the input actuated joint angles. By taking into account the physical workspace of SPBS given its joint limits, the corresponding orientation can be selected among the solution set with a sufficient conditional check of \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t> 0, \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t2\n\t\t\t\t\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t> 0, \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t3\n\t\t\t\t\t\t\t\t\t\t\t\tx\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t> 0, and \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t1\n\t\t\t\t\t\t\t\t\t\t\t\tz\n\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t< 0.
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2.2. Jacobians
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In robotics, the Jacobian matrix of a manipulator, denoted as J, is generally defined as the matrix representing the transformation between the joint rates and the Cartesian velocities. For the case of a closed-loop manipulator the notion of this mapping for the direct and inverse kinematic problems are interchanged (Angeles & Gosselin, 1990). The Jacobian matrix is defined as:
where ω is the angular velocity of the platform, \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tθ\n\t\t\t\t\t\t\t\t\t\t•\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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\tis the actuated joint velocity vector.
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An alternative form of (29) with the matrices A and B is rewritten in variant form as,
\n\t\t\t\t\tEquations (30) to (32) are derived using the general case of the spherical 3-DOF parallel geometry (Angeles & Gosselin, 1990). Similarly, the equations are applicable to the geometry of the SPBS device. Equation (30) shows that the angular velocity of the end-effector can be obtained as an expression of the joint velocities. For haptic rendering purposes, the time derivatives of the rotation angles are used, expressing the angular velocity vector, ω, as
where is the vector of the Z-Y-X Euler angles, 1, 2, and 3. The matrix R is derived by using the definition of the angular velocity tensor (a skew-symmetric matrix) and taking partial derivatives of the orthonormal matrix in (4). One can obtain,
\n\t\t\t\t\tEquation (35) gives a practical relationship relating the velocities of the active joint rates as a function of an angle set velocity vector.
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In addition, we would like to obtain a relationship between the input actuator torques and the output torques exerted on the end-effector about the origin O. In particular, we have the relationship, x
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where power is in watts, torque is in Nm, and angular speed is in radians per second.
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Let w be the torque vector exerted by the end-effector and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\tτ\n\t\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 be the active joint torque vector. By using a static equilibrium model and the concept of virtual power, we equate the input and the output virtual powers and obtain the relationship in (39).
\n\t\t\t\t\tEquation (39) provides a mapping of the desired output torque vector in Cartesian space to the joint torque vector. As given by equations (30), (31) and (32), an algebraic solution can be used to compute the matrices J, A, and B, respectively. Note that the vectors \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t,\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tw\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 for i = 1, 2, 3, are all known at any instant during the device simulation. The vectors \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tu\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 correspond to the reference configuration, whereas the vectors \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tw\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 and \n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\tv\n\t\t\t\t\t\t\t\t\t\ti\n\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\n\t\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 have been derived in symbolic forms in the previous inverse and forward kinematics sections. The results from this section form a set of basis equations that can be experimented with the prototype.
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2.3. Static Relationship
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We want to be able to compute the force exerted on the hand of the user holding the tool. A simple point/line model is used for the visualization of the physical tool (handle) of the mechanism. For example, as shown in Figure 5, the vector r represents the position vector of the handle location at which the user would hold the tip of the tool. The triangular (yellow) surface represent the contacting surface and the force vector F represents the reaction contacting force generated by the computational model.
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Figure 5.
Representation of contact force and moment vectors.
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Figure 6.
Haptic device at equilibrium configuration shown in Figure 5.
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\n\t\t\t\t\tFigure 5 and Figure 6 show an example orientation such that the physical tool is leaning against a virtual wall. The triangle in Figure 5 illustrates a virtual plane (wall) defined by three arbitrary points in space. The contact point is where the position vector r intersects the plane. The vector F represents the normal force at the contact point having a direction vector perpendicular to the virtual plane. Therefore, by knowing this force vector with respect to the world coordinate frame, the moment of this force vector can be computed by using the vector cross product between r and F. The moment vector w consists of the x-y-z components which are the moments about each principal axis. This moment vector is the desired output torque vector in Cartesian space. Therefore, we can use it to resolve for the joint torque vector by equation (39). The linear force along the handle of the device is independent of the rest of the degrees of freedom and hence is solved separately. Table 1 shows a summary of the computed values of the key parameters used in this equilibrium example.
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power = torqueangular speed
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3. Computational Hardware Design
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Haptic displays aim to provide operators with a sense of touch, rendering contact forces as if interactions occurring with real objects. Haptic displays are generally used in conjunction with visual displays, where objects are simulated in a virtual world. The applications of both graphical and haptic displays in virtual reality provide the user with the illusion of touching objects and a heightened sense of presence in the virtual world. The computed interactive force between the user representation and a virtual object is rendered to the user via the haptic device. Due to the elaborate sensory perception of the human hand, which registers even very small oscillations, many research studies have shown that update rates of 1 kHz or above are desired for haptic rendering of any physical rigid contact effects. Therefore, many efforts have been devoted to develop various hardware models, control schemes, and haptic rendering controllers in the past years. Our motivation is to develop a hardware setup which supports the real-time force feedback control of the proposed haptic device.
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3.1 Conceptual architecture of the distributed system
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\n\t\t\t\tFigure 7 shows a conceptual architecture of a distributed system framework. The experimental setup presented in this section includes the 4-DOF SPBS haptic device, a data acquisition system (DAS) and a personal computer (PC). Major processing components are experimented on selected hardware contributing to an integrated VR simulation. The host PC is responsible for haptic rendering and providing a Graphical User Interface. The data acquisition system that consists of a microprocessor, a FPGA, integrated circuits, pulse-width-modulation (PWM) is described in the following.
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Figure 7.
System architecture of a conceptual microprocessor-based distributed system.
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Figure 8.
Typical processes associated in haptic rendering with a force display.
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In order to achieve the desired update rates and allow any future expansions, we intend to design and develop the system framework with concepts of concurrency, openness, scalability, and transparency. Potentially we can distribute computational loads, reconfigure, upgrade, and extend for different software and hardware components in order to achieve better system performance. Figure 8 illustrates the main components or processing tasks in a typical simulation hierarchy. The forward kinematics, inverse kinematics, and force mapping (Jacobian) equations were derived in the previous section. The above developments along with collision detection and simulation of materials, such as a virtual wall, are considered as computationally intensive components of any haptic interaction.
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3.2. Hardware subsystems design
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Our proposed local interconnection framework consists of three major components: the host control computer, our custom-designed data acquisition system (DAS) and the SPBS haptic device. The system block diagram of the experimental hardware setup is shown in Figure 9.
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Figure 9.
System block diagram.
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The host control computer is the driver for communicating with the DAS. The user perceives force feedback while manipulating the device. The four axes corresponding to the four DOFs are coupled with four DC brush motors. The user’s movements with SPBS are acquired by DAS and sent to the host. The host PC provides visual displays and haptic rendering based on local models and simulation laws in the environment. The feedback values are sent back to DAS for real-time control of the motors.
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A UDP/IP socket is selected as the primary data communication interface between the host PC and the DAS. The UDP/IP communication is connection-less and is known for having less overhead compared to the TCP/IP communication. The data acquisition system consists of a microprocessor, quadrature decoders, analog-to-digital converter (ADC), digital-to-analog converters (DAC), and servo amplifiers. The DACs provide the feedback voltages through the servo amplifiers to the four motors. We have used the NetBurner MOD5272 development board as the microprocessor unit for controlling data flow. The task of quadrature decoding is distributed and embedded on a Xilinx Spartan-IIE FPGA XC2S200E evaluation kit. The quadrature decoders and ADC serve the purpose of data sampling. A Maxim MAX1203 IC is used for analog-to-digital conversion in this research. The ADC IC is capable of converting an analog voltage input ranged from 0V to 5V into a digital value with 12 bits of resolution. The maximum sampling frequency of the ADC is 2 MHz. By design, the ADC is used with a potentiometer for monitoring the opening and closing of the gripper. In this study, the ADC IC is also configured to collect experimental results (using current monitor output signals).
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A quadrature decoder module is implemented to keep track of the motor positions. We used four Maxon DC brush motors for the four axes. Each Maxon motor uses a HEDL 5540 quadrature encoder capable of generating 500 counts per turn. Each encoder line driver requires a line receiver. Hence, two commercial MC3486 ICs are selected for integration with the motors and encoders used in this study. The Spartan-IIE FPGA on the evaluation kit uses a 50 MHz oscillator to drive the system clock. Power for the board is provided by an external +5 VDC regulated supply. The evaluation board provides jumper-selectable reference, output and termination voltages on a bank of the FPGA to facilitate the evaluation of various I/O standards. The LVTTL I/O standard is selected for integration with the ICs and the NetBurner development board used in this research. In addition, the evaluation kit provides 87 general-purpose I/O via two 50-pin connectors. This is sufficient for the current requirements and future exploration. The channels A and B of each quadrature encoder are used. Therefore, four encoders result in eight input bits. A reset signal for the registers is implemented via a push button on the board for clearing all the motor counts. We use a 16-bit data bus and a 2-bit control bus as the interface between the FPGA and the microprocessor module.
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The DAS uses the NetBurner development board based on Motorola ColdFire5272 microprocessor. The network capability (TCP/IP and UDP/IP) and general purpose I/O ports are particularly useful for system evaluation in this study. The 10/100 Ethernet provides a standard network interface for connection to the host computer or a hub. The data transmission between the Netburner board and the FPGA is achieved through a 2-bit command port and a 16-bit data port as stated. In addition, the Queued Serial Peripheral Interface (QSPI) hardware on board is able to achieve a data rate up to 33Mbps. The DAS uses the QSPI and communicates with the ADC and DAC ICs by enabling different chip select bits. The UART provides a RS-232 serial interface that can be used for monitoring debug output on the host PC for this study.
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The DAC converts the digital data to an analog voltage that feeds into the servo-amplifier. The servo amplifiers are configured to use in current mode, hence desired torque output can be controlled via two reference voltages. The DAC IC used in this project is a Maxim MAX525, which has a serial interface for communicating with the NetBurner board. There are four DAC channels on one IC and each voltage output ranges from 0V to 5V with 12 bits of resolution. The servo-amplifier receives a differential analog input pair. The sign of the differential voltage determines the motor turning direction. The amplitude of the differential voltage determines the motor torque. In our application, we used DC motors with a stall torque rating of 872 mNm. In stall mode, the stall current (and stall torque) is proportional to the applied voltage. Applying twice the voltage results in twice the stall current because when the motor is not rotating (stalled) the armature appears in the circuit as a resistor. Therefore, we can use the rated terminal resistance (0.334 ohms) and the torque constant (19.4 mNm/A) from the motor specification in order to estimate the conversion between our desired torque and the motor current and terminal voltage. For example, if the desired torque is 23.2 mNm, the motor should draw approximately 23.2 / 19.4 = 1.2 A from the power supply. The terminal voltage across the motor leads should be about 1.2 A * 0.334 ohms = 0.4V. In this study, we used a power supply with a 12A nominal output current. Servo amplifiers are the 25A8 models from Advanced Motion Controls. We configured the servo amplifiers to operate in current mode with maximum continuous current rating of 12.5A. Therefore, in our haptic rendering process, we consider a safe operating range for the motors by limiting the torque output to be below 100 mNm.
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3.3. Communication Protocols
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A simple data packet is used for performance benchmarking of the experimental setup. Figure 10 and Figure 11 show a sample data packet and a control data packet.
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Figure 10.
Sample data packet (8 bytes).
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Figure 11.
Control data packet (16 bytes).
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3.4. Host Computer
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\n\t\t\t\t\tFigure 12 illustrates the high-level design hierarchy of the development of a software application on the host computer. The software applications were targeted and tested on the Windows XP and the Linux operating systems. On Windows XP, Microsoft Visual C++ 6.0 was used as the compiler for building the software application. The WinSock API was used to support UDP/IP and TCP/IP communication with the DAS. On Linux, GNU g++ was used as the compiler for building the software application. The POSIX socket was used similarly on Linux in order to support the communication protocol. The GTK+ software library is used to provide the same look and feel of the GUI on Windows and on Linux.
\n\t\t\t\t
Figure 12.
High-level Design Hierarchy.
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\n\t\t\t
4. Experimental Results
\n\t\t\t
\n\t\t\t\tFigure 13 shows the sequence diagram of the virtual environment (VE) and the allocation and distribution of the tasks.
\n\t\t\t
Figure 13.
Sequence diagram of the virtual environment.
\n\t\t\t
As shown, the user and the device represent the human operator manipulating the physical SPBS device while observing the VE and GUI on the PC monitor. The DAS control task represents the control program executing on the NetBurner microprocessor. The multi-threaded software application executing on the host computer consists of two threads. The GUI thread or task is responsible for graphics rendering such as the user interface, the graphical device model and virtual objects to the operator. The control thread on the host computer runs in the background and is responsible for network communication, kinematics, collision detection, mechanics-based simulation, and force mapping of the control process.
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\n\t\t\t\t
4.1. Performance Benchmarking
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Haptic rendering is the process of computing and applying force feedback to the user in response to his/her interaction with the virtual environment. How haptic rendering is implemented should depend on the application requirements, since there is no unique or best solution. Two common approaches are impulsive haptic rendering and continuous haptic rendering (Buttolo & Hannaford, 1997). Impulsive haptic rendering models impulsive collisions such as kicking a ball and hammering a nail. Continuous haptic rendering models extended collisions such as pushing against a wall or lifting an object.
\n\t\t\t\t
A common question is how fast should we sample, and how will delay affect performances. Previous studies suggest a threshold based on human perception, resulting in a requirement for force reflection bandwidth of at least 30-50 Hz for integrated graphics and impulsive forces [11]. To realistically simulate collisions with rigid objects (i..e. high stiffness such as 1000 Nm-1), desired sampling rates are at least 200 Hz. Many state of the art haptic systems use 1000 Hz sampling rates (Mishra & Srikanth, 2000). In the following, we prepare the experimental setup and the operator positions the tool continuously colliding with a virtual wall in the virtual environment. The GUI thread or the graphics rendering loop (see Figure 13) is tuned to execute at about 50 Hz. The average sampling rate of the haptic rendering loop can be measured on the host computer or on the NetBurner. We used the continuous haptic rendering model in order to evaluate the performance of the experimental setup.
\n\t\t\t\t
\n\t\t\t\t\tTable 1 below shows the throughput, sampling rate and tested payload. The sampling rate is defined as how many closed-loop control cycles the host computer can complete in one second. A complete closed loop control cycle requires the host computer to receive a new set of sampled data (motor positions), compute the haptic rendering, and update the control data (voltages). When data is sent over a network, each unit transmitted includes both header information and the actual data being sent. The header identifies the source and destination of the packet, while actual data is referred to as the payload. As indicated in section 3.3, the predefined communication protocol encapsulates the motor positions (the host receives 8 bytes) and control voltages (the host transmits 16 bytes) using a payload of 24 bytes. The performance benchmarking application keeps track of the number of samples/iteration and the actual data size measured in a time interval. The mean sampling rate was the average value over 10 trials. Each trial involved an operator using the device in the virtual environment for a one-minute interval and recorded the sampling rate by using customized firmware on NetBurner. Besides the default size of the data packets, the same experiment was repeated for increasing packet sizes. This allows an observation of the system performance if additional information (such as time stamps) propagated over the networked environment. Table 2 shows the test results with the application executing on Windows XP.
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\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\t\t
Parameter Names
\n\t\t\t\t\t\t\t
Values
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Joint angles (degrees)
\n\t\t\t\t\t\t\t
θ1 = 40.39°, θ2 = 8.42°, and θ3 = 9.43°
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Position vector (metres)
\n\t\t\t\t\t\t\t
r = [ 0.0748, 0.0250, -0.00797 ]
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Force vector (N)
\n\t\t\t\t\t\t\t
F = [ 0, -813.981, 0 ]
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Desired output torque (Nm)
\n\t\t\t\t\t\t\t
w = [ -6.49, 0, -60.88 ]
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Joint torque (Nm)
\n\t\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\t\t
Jacobian
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
Table 1.
Communication Performance Statistics (TCP and UDP) in Windows XP.
\n\t\t\t\t
Comparing the performance of the TCP communication protocol to the UDP, the UDP achieves the desired 1 kHz update rates. The connection-less UDP socket with less overhead outperforms the connection-oriented TCP socket for the intended application of the system. Note that as the size of the data packets increases, the mean sampling rate decreases. Table 3 shows the results by repeating the same experiment on a Linux environment.
\n\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\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\t
\n\t\t\t\t\t\t\t
Payload (bytes)
\n\t\t\t\t\t\t\t
TCP
\n\t\t\t\t\t\t\t
UDP
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Total
\n\t\t\t\t\t\t\t
Rx
\n\t\t\t\t\t\t\t
Tx
\n\t\t\t\t\t\t\t
Mean Sampling Rate (Hz)
\n\t\t\t\t\t\t\t
Mean Throughput (Bytes/sec)
\n\t\t\t\t\t\t\t
Mean Sampling Rate (Hz)
\n\t\t\t\t\t\t\t
Mean Throughput (Bytes/sec)
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
24
\n\t\t\t\t\t\t\t
8
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
768
\n\t\t\t\t\t\t\t
18432
\n\t\t\t\t\t\t\t
1105
\n\t\t\t\t\t\t\t
26520
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
28
\n\t\t\t\t\t\t\t
12
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
765
\n\t\t\t\t\t\t\t
21420
\n\t\t\t\t\t\t\t
1063
\n\t\t\t\t\t\t\t
29764
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
32
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
765
\n\t\t\t\t\t\t\t
24480
\n\t\t\t\t\t\t\t
1020
\n\t\t\t\t\t\t\t
32640
\n\t\t\t\t\t\t
\n\t\t\t\t\t
Table 2.
Communication Performance Statistics (Windows XP and Linux).
\n\t\t\t
\n\t\t\t
\n\t\t\t\t
4.2. Kinematics Verification
\n\t\t\t\t
Other tests have been conducted using the hardware setup, the SPBS device, and a Pentium 4 PC running the software application on Windows XP. As shown in Figure 14, the measured length from the origin (centre of rotation) to the tip of the handle is 0.35m. By moving the tip of the handle to test point 1, the measured coordinate on the device in the physical workspace is (0.346, 0.050, 0.000) ± 0.001m.
\n\t\t\t\t
Figure 14.
Measured test point in physical workspace.
\n\t\t\t\t
Comparing to the model rendered in the virtual environment, as the operator positioned the device to the test point, the calculated coordinate based on measured motor angles, forward kinematics, and a proper scaling of the model is (0.346, 0.050, 0.000).
\n\t\t\t\t
Figure 15.
Test points in physical workspace.
\n\t\t\t\t
By adjusting the position of a camera along the positive x-axis, Figure 15 shows the top view of the device and the previous test point 1 projected onto this view plane at a distance approximately 0.35m parallel to the y-z plane. Table 4 shows the comparison between the measurements on the actual device and the calculated coordinates on the virtual model as the operator manipulated and positioned the tip of the handle to all the test points shown. Note that the experiments were conducted by the operator determining the position of the tip of the handle and estimating a home reference with all motor angles resetting to zero at the starting origin. The imperfect zero-home reference, estimated location of the handle tip, and camera displacements may introduce source of errors during the experiments.
\n\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\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\t
\n\t\t\t\t\t\t\t
Payload (bytes)
\n\t\t\t\t\t\t\t
UDP (Windows XP)
\n\t\t\t\t\t\t\t
UDP (Linux)
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
Total
\n\t\t\t\t\t\t\t
Rx
\n\t\t\t\t\t\t\t
Tx
\n\t\t\t\t\t\t\t
Mean Sampling Rate (Hz)
\n\t\t\t\t\t\t\t
Mean Throughput (Bytes/sec)
\n\t\t\t\t\t\t\t
Mean Sampling Rate (Hz)
\n\t\t\t\t\t\t\t
Mean Throughput (Bytes/sec)
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
24
\n\t\t\t\t\t\t\t
8
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
1105
\n\t\t\t\t\t\t\t
26520
\n\t\t\t\t\t\t\t
1181
\n\t\t\t\t\t\t\t
28344
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
26
\n\t\t\t\t\t\t\t
10
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
1083
\n\t\t\t\t\t\t\t
28158
\n\t\t\t\t\t\t\t
1161
\n\t\t\t\t\t\t\t
30186
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
28
\n\t\t\t\t\t\t\t
12
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
1063
\n\t\t\t\t\t\t\t
29764
\n\t\t\t\t\t\t\t
1134
\n\t\t\t\t\t\t\t
31752
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
30
\n\t\t\t\t\t\t\t
14
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
1042
\n\t\t\t\t\t\t\t
31260
\n\t\t\t\t\t\t\t
1108
\n\t\t\t\t\t\t\t
33240
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
32
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
16
\n\t\t\t\t\t\t\t
1020
\n\t\t\t\t\t\t\t
32640
\n\t\t\t\t\t\t\t
1084
\n\t\t\t\t\t\t\t
34688
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
36
\n\t\t\t\t\t\t\t
18
\n\t\t\t\t\t\t\t
18
\n\t\t\t\t\t\t\t
999
\n\t\t\t\t\t\t\t
35964
\n\t\t\t\t\t\t\t
1063
\n\t\t\t\t\t\t\t
38268
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
40
\n\t\t\t\t\t\t\t
20
\n\t\t\t\t\t\t\t
20
\n\t\t\t\t\t\t\t
980
\n\t\t\t\t\t\t\t
39200
\n\t\t\t\t\t\t\t
1039
\n\t\t\t\t\t\t\t
41560
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
44
\n\t\t\t\t\t\t\t
22
\n\t\t\t\t\t\t\t
22
\n\t\t\t\t\t\t\t
959
\n\t\t\t\t\t\t\t
42196
\n\t\t\t\t\t\t\t
1019
\n\t\t\t\t\t\t\t
44836
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
48
\n\t\t\t\t\t\t\t
24
\n\t\t\t\t\t\t\t
24
\n\t\t\t\t\t\t\t
941
\n\t\t\t\t\t\t\t
45168
\n\t\t\t\t\t\t\t
998
\n\t\t\t\t\t\t\t
47004
\n\t\t\t\t\t\t
\n\t\t\t\t\t
Table 3.
Comparison between measured coordinates and calculated coordinates.
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\n\t\t\t\t
4.3. Haptic Feedback
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In addition to the observation and tracking of a virtual tool, an example haptic scene is prepared for the operator to experience haptic feedback in the environment. A virtual wall is predefined in the scene prior to the experiment. Figure 16 shows the virtual environment (left) and the home position of the device model (right). The sphere rendered in the left region indicates the haptic interface point in the scene.
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Figure 16.
Virtual environment for haptic exploration (virtual wall into page).
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The position of the wall is located at 0.020m into the page (positive z-axis) relative to the origin. The wall (rectangle) is parallel to the x-y plane. The home position of the tool (or straight up) is along the positive x-axis. Figure 16 shows the scene with the camera behind (on negative z-axis) and looking at the origin. The operator performed the experiment by moving the sphere towards the wall along the positive z-axis and colliding the sphere with the virtual wall. Figure 17 shows the position of the sphere as the operator manipulated the tool and moved the sphere accordingly. Figure 18 shows the calculated Cartesian force Fz (Fx = Fy = 0) at the haptic interface point when the sphere collided with the virtual wall.
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Figure 17.
Position of the sphere with respect to the reference coordinate system.
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Figure 18.
Cartesian force at the haptic interface point along the z-axis.
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Figure 19.
Measured torque versus time plot.
\n\t\t\t\t
\n\t\t\t\t\tFigure 19 shows the measured torque versus time plot. The torque was measured by the application of the current monitor output (signals available from the servo amplifiers) and the integration of a low-pass filter circuit and the ADC IC on the DAS. Three axes of the motors were monitored for the torque output during the experiment. The results show the torque experienced by the operator holding the tool and repeatedly colliding with a virtual wall. As seen in the above plots, the period during which the sphere position is at the threshold, i.e. when the spring model is in effect, the force started to increase as the operator attempted to push the sphere further onto the wall. Figure 19 shows the decomposition of the torque into three motor torques felted by the operator. In this example, actuator 1 and actuator 3 were operating in order to generate the reaction force. Using the same virtual scene, the following plots show the experimental results as the operator moved the sphere back and forth from the origin to the wall experiencing a greater reaction force while attempting to penetrate the sphere further into the wall.
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Figure 20.
Position of the sphere with respect to the reference coordinate system.
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Figure 21.
Cartesian force at the haptic interface point along the z-axis.
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Figure 22.
Measured torque versus time plot.
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\n\t\t\t
4. Summary
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This chapter presented the design, modelling and hardware integration of a haptic device. The design of the haptic device is based on the notion of the hybrid spherical mechanism which consists of both a passive and active spherical joints. The passive joint is responsible for supporting the static load and user interaction forces whereas the active joint is responsible for creating the haptic feedback to the user. Closed-form solution for kinematic analysis and force mapping of the device is presented. A novel distributed computational platform is also proposed. The platform exploits the notion of scalability and modularity in the design. Performance of the closed loop system is presented in the context of interacting with a rigid environment and achieving a high sampling rate using either the UDP or the TCP communication protocols.
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\n\t\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/9904.pdf",chapterXML:"https://mts.intechopen.com/source/xml/9904.xml",downloadPdfUrl:"/chapter/pdf-download/9904",previewPdfUrl:"/chapter/pdf-preview/9904",totalDownloads:1873,totalViews:153,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,dateSubmitted:null,dateReviewed:null,datePrePublished:null,datePublished:"April 1st 2010",dateFinished:null,readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/9904",risUrl:"/chapter/ris/9904",book:{slug:"advances-in-haptics"},signatures:"Ma and Payandeh",authors:null,sections:[{id:"sec_1",title:"1. Introduction ",level:"1"},{id:"sec_1_2",title:"1.1. Objectives",level:"2"},{id:"sec_2_2",title:"1.2. Contributions",level:"2"},{id:"sec_4",title:"2. Analysis of the Haptic Mechanism",level:"1"},{id:"sec_4_2",title:"2.1. Kinematic model",level:"2"},{id:"sec_4_3",title:"2.1.1. Derivation of Inverse Kinematics",level:"3"},{id:"sec_5_3",title:"2.1.2. Derivation of Forward Kinematics",level:"3"},{id:"sec_7_2",title:"2.2. Jacobians",level:"2"},{id:"sec_8_2",title:"2.3. Static Relationship",level:"2"},{id:"sec_10",title:"3. Computational Hardware Design",level:"1"},{id:"sec_11",title:"3.1 Conceptual architecture of the distributed system",level:"1"},{id:"sec_11_2",title:"3.2. Hardware subsystems design",level:"2"},{id:"sec_12_2",title:"3.3. Communication Protocols",level:"2"},{id:"sec_13_2",title:"3.4. Host Computer",level:"2"},{id:"sec_15",title:"4. Experimental Results",level:"1"},{id:"sec_15_2",title:"4.1. Performance Benchmarking",level:"2"},{id:"sec_16_2",title:"4.2. Kinematics Verification",level:"2"},{id:"sec_17_2",title:"4.3. Haptic Feedback",level:"2"},{id:"sec_19",title:"4. Summary",level:"1"}],chapterReferences:[{id:"B1",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tAngeles\n\t\t\t\t\t\t\tJ.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tGosselin\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1990\n\t\t\t\t\tSingularity analysis of closed-loop kinematic chains, IEEE Transactions on Robotics and Automation, 6\n\t\t\t\t\t3\n\t\t\t\t\t281\n\t\t\t\t\t290 , 1990\n\t\t\t'},{id:"B2",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBirglen\n\t\t\t\t\t\t\tL.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tGosselin\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tPouliot\n\t\t\t\t\t\t\tN.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tMonsarrat\n\t\t\t\t\t\t\tB.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tLaliberté\n\t\t\t\t\t\t\tT.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t2002\n\t\t\t\t\tSHaDe, a New 3-DOF Haptic Device, IEEE Transactions on Robotics and Automation, 18\n\t\t\t\t\t2\n\t\t\t\t\t166\n\t\t\t\t\t175 , 2002\n\t\t\t'},{id:"B3",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tBoudreau\n\t\t\t\t\t\t\tR.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tDarenfed\n\t\t\t\t\t\t\tS.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tGosselin\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1998\n\t\t\t\t\tOn the Computation of the Direct Kinematics of Parallel Manipulators Using Polynomial Networks, IEEE Transactions on Systems, Man, and Cybernetics- Part A: Systems and Humans, 28\n\t\t\t\t\t2\n\t\t\t\t\t213\n\t\t\t\t\t220 , 1998\n\t\t\t'},{id:"B4",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tButtolo\n\t\t\t\t\t\t\tP.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tOboe\n\t\t\t\t\t\t\tR.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHannaford\n\t\t\t\t\t\t\tB.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1997\n\t\t\t\t\tArchitectures for Shared Haptic Virtual Environments, Computers & Graphics, 21\n\t\t\t\t\t4\n\t\t\t\t\t421\n\t\t\t\t\t429 , 1997\n\t\t\t'},{id:"B5",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tCraver\n\t\t\t\t\t\t\tW.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1989\n\t\t\t\t\tMaster Thesis: Structural Analysis and Design of a Three-Degree-Of-Freedom Robotic Shoulder Module, The University of Texas at Austin, 1989\n\t\t\t'},{id:"B6",body:'\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tGosselin\n\t\t\t\t\t\t\tC.\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\tHamel\n\t\t\t\t\t\t\tJ.\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t1994\n\t\t\t\t\tThe Agile-Eye: a High-Performance Three-Degree-Of-Freedom Camera Orienting Device, Proc. 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1. Introduction
Nanotechnology attracted wide attention over the last decades, leading to a very fast development of materials and processing routes. Different areas such as electronics, cosmetics, medicine/biology, optical systems, energy, and many others, have profited from this rapid growth. Having in mind the environmental issues that we are facing in the modern era, the importance of searching for environmentally friendly, recyclable and low cost nanomaterials and fabrication processes is essential. [1]
This has been a concern in strategic areas as large area electronics (LAE), one of the fastest growing technologies in the world, with projected market growth from $31.7 billion in 2018 to $77.3 billion in 2029. [2] LAE includes many segments (e.g., displays, sensors, logic, memory), which are desired to be seamlessly integrated on virtually any object to create smart surfaces. Due to their good electrical properties, transparency, large area uniformity and good mechanical flexibility, oxide thin films have been crucial materials to advance these concepts. [3] Depending on the metal cations (and on the metal to oxygen ratio), metal oxide thin films can be considered as dielectrics, semiconductors or even conductors. [4, 5, 6] Owing to their remarkable electrical properties, In-based materials, such as ITO (indium tin oxide) and IGZO (indium-gallium-zinc oxide) are currently the multicomponent oxide conductor and semiconductor thin films with larger market relevance in LAE. [4, 7] However, indium is an expensive material, due to its scarcity and high market value, appearing in the current list (2020) of the critical raw materials from the European Commission. [8] The same applies for gallium, another element of IGZO. Therefore, the replacement of these materials is imperative to assure long-term sustainability. [1]
This quest for new oxide materials is naturally also transposed for nanostructures, as their fascinating properties will certainly boost even further the demand for oxide (nano)materials in a plethora of industries. Departing from critical cations, ZnO is perhaps the most widely studied oxide nanostructure. Its properties are nowadays well-known and useful for multiple applications, from photocatalysis, to solar cells or biosensors. [9] It can also be prepared by a multiplicity of methodologies, from vapor- to solution-based processes. [10] Multicomponent oxide nanostructures, particularly those based on sustainable materials, have been significantly less studied, but already show great potential to enhance properties and enlarge the range of applications of oxides. As in thin films, a great advantage of these multicomponent materials is the possibility of tuning their properties by adjusting the cationic ratio. [11, 12] Zinc tin oxide (ZTO) is one of the multicomponent oxides that has been explored and has shown very interesting properties when compared with its binary counterparts (ZnO and SnO2). In fact, ZTO was already demonstrated to exhibit similar properties to IGZO in low-temperature thin film transistors (TFTs), while avoiding the use of critical raw materials. [13]
This chapter provides a literature review on the hydrothermal synthesis of ZTO nanostructures, the main properties of this material, and its applications, highlighting its multifuncionality.
1.1 Hydrothermal synthesis of ZTO nanostructures
Hydrothermal methods have been widely explored and developed in the last years. [14] This method consists in a chemical reaction in an aqueous solution, under high pressure (> 1 atm) and at temperatures usually ranging between 100°C and 300°C. In case of using non-aqueous solvents, the method is called solvothermal. Typically, the solution is kept inside an autoclave and a conventional oven is used as heat source. The pressure inside the autoclave is dependent both on the temperature and the volume used. This allows for a high energy supply for the reactions even at relatively low temperatures. While the typical nucleation and growth mechanism of the oxide nanostructures in these reactions is thought to consist mainly in dissolution–reprecipitation, these mechanisms are often not well understood.
The synthesis of multicomponent oxide materials such as ZTO is usually easier and more efficient by vapor phase methods, such as chemical vapor deposition and thermal evaporation, than by solution processes, due to the higher temperatures of the former. However, vapor phase methods present drawbacks that are important to consider, such as high temperatures (>700°C) and high costs. On the other hand, while inexpensive and simple, the hydrothermal technique still allows for a well-controlled synthesis of the desired nanostructures’ shape and structure with high reproducibility, thus presenting as an excellent alternative to the conventional physical methods. [15, 16] Additionally, while conventional ovens are typically used as the heat source, microwave-assisted synthesis started recently to be widely explored, enabling reduced synthesis duration due to its more efficient and more homogeneous heat transfer process. [17]
1.2 Overview on ZTO nanostructures produced by hydrothermal synthesis
ZTO appears commonly in two main forms, a stable one, Zn2SnO4, and ZnSnO3, a metastable phase. The stable Zn2SnO4 phase is an orthostannate with and inverse spinel structure and is a n-type semiconductor with a band gap of 3.6 eV. [18] ZnSnO3, the metastable phase, can have a rhombohedral structure or a perovskite structure either orthorhombic (−orth) or ordered face centered structure (−fcc). [14, 19] This phase is a well-known piezo/ferroelectric material and presents a band gap of 3.9 eV. [18] Several ZTO nanostructures such as nanoparticles, octahedrons, nanocubes, nanowires, and nanoflowers, have been produced by hydrothermal synthesis, appearing in both ZnSnO3 and Zn2SnO4 phases. Figure 1 shows examples of Zn2SnO4 and ZnSnO3 nanostructures with different morphologies and dimensions (0D, 1D, 2D and 3D) produced by hydrothermal synthesis.
Figure 1.
Multiple ZTO nanostructures obtained by hydrothermal synthesis, analyzed by scanning electron microscopy (SEM): (a) Zn2SnO4 nanoparticles, from reference [28]; (b) fcc-ZnSnO3 nanoparticles produced by our group; (d) rhombohedral-ZnSnO3 nanowires growth on FTO seed-layer, reprinted with permission from [42], copyright (2020) American Chemical Society; (e) orth-ZnSnO3 nanowires synthesized without employing seed-layers (in form of powder), from reference [43]; (f) orth-ZnSnO3 nanoplates, reprinted with permission from [45], copyright (2020) American Chemical Society; (h) orth-ZnSnO3 hollow spheres, reprinted with permission from [47], copyright (2020) American Chemical Society; (i) orth-ZnSnO3 nanocubes produced by our group; and by transmission electron microscopy (TEM): (c) Zn2SnO4 nanorods, reprinted with permission from [37], copyright (2020) American Chemical Society; and (g) Zn2SnO4 nanoplates, reprinted with permission from [34], copyright (2020) American Chemical Society.
Lehnen et al., for example, reported very small Zn2SnO4 quantum dots (with diameters below 30 nm), produced with a microwave-assisted hydrothermal synthesis, followed by high-temperature annealing. [20] Numerous other reports on Zn2SnO4 nanoparticles have been shown (Figure 1a), either using standard hydrothermal synthesis or solvothermal synthesis. [16, 21, 22, 23, 24, 25, 26, 27, 28] Regarding ZnSnO3 nanoparticles (Figure 1b), several hydro and solvothermal routes have been reported for its synthesis. [29, 30, 31, 32] For instance, Beshkar et al. reported the use of the Pechini method at 80°C to synthesize fcc-ZnSnO3 nanoparticles, followed by a calcination at 700°C for 2 h. [33]
Concerning 1D structures, while several reports on Zn2SnO4 nanowires exist, these consist essentially in vapor phase methods, more specifically in thermal evaporation at high temperature (>750°C), [19] showing the difficulty in obtaining the stable phase of ZTO in the nanowire form. [34] This is emphasized by the fact that there are only a few reports for Zn2SnO4 nanowires from hydrothermal synthesis, mostly assisted by seed-layers. For example, Zn2SnO4 nanowires were grown on a stainless steel seed-layer and from Mn3O4 nanowires. [35, 36] Zn2SnO4 nanorods by hydrothermal synthesis were also reported by Chen et al. (Figure 1c), but only organized in 3D flowerlike superstructures. [37] Regarding ZnSnO3, only a few reports for nanowires exist, also consisting typically in physical processes (carbon-thermal reaction, thermal evaporation or CVD processes). [38, 39] For hydrothermal processing of ZnSnO3 nanowires seed-layers are typically used. Lo et al. employed an FTO thin film as seed-layer for this end (Figure 1d). [40, 41, 42] A different approach was reported by Men et al. who transformed ZnO nanowires into ZnSnO3 nanowires by a hydrothermal synthesis. [41] Recently, our group demonstrated for the first time ZnSnO3 nanowires obtained by an one-step hydrothermal synthesis without employing any seed-layer (Figure 1e). [32, 43]
2D structures of ZTO have also been reported. Joseph et al. synthesized fcc-ZnSnO3 flakes by a hydrothermal method at only 100°C. [44] Guo et al. produced orth-ZnSnO3 nanoplates (Figure 1f) by a hydrothermal process at 260°C for 24 h. [45] Chen et al. obtained orth-ZnSnO3 nanosheets through a hydrothermal synthesis at 180°C for 12 h, where a precipitate of ZnSn(OH)6 was achieved followed by a calcination at 600°C for 3 h. [46] Zn2SnO4 nanoplates have also been reported, for example, by Cherian et al. (Figure 1g). [34]
There are also several reports regarding 3D ZTO nanostructures. Gao et al. reported the synthesis of ZnSnO3 hollow spheres (Figure 1h) by hydrothermal synthesis at 120°C for 3 h. [47] A commonly reported shape for ZTO nanostructures is the nanocube shape (Figure 1i). For instance, Chen et al. reported a synthesis which could result in ZnSnO3 nanocubes or ZnSnO3 nanosheets, depending on the processing temperature. [46] The octahedron shape is also common, and octahedrons of Zn2SnO4 have been reported by several groups, being these identified as the most stable phase and shape for ZTO nanocrystals. Zn2SnO4 octahedrons constituted by nanoplates can also be formed. [48]
While Figure 1 shows the wide range of possibilities offered by hydrothermal synthesis within the ZTO system, it is challenging to obtain structures with a targeted phase (ZnSnO3 or Zn2SnO4 in this case) and shape (e.g. nanosheet or nanowire). [40, 49] For this end, a comprehensive tailoring of the synthesis parameters is required.
2. Research methods
Usually the hydrothermal synthesis of ZTO nanostructures is performed inside a teflon-lined stainless-steel autoclave using a conventional oven as heating source. Nevertheless, as previously shown, there are already a few examples of microwave-assisted hydrothermal synthesis of ZTO nanostructures. As an example of a typical method, our synthesis starts with the dissolution of the zinc and tin precursors separately in 7.5 mL of deionized water, followed by their mixture. Then a surfactant (ethylenediamine, EDA) is added, and the solution is magnetically stirred for 30 minutes. The last step is the addition of the mineralizer agent (NaOH). It is observed that milling the precursors before their dissolution in water leads to a more homogeneous result. After the solution preparation, it is transferred into the autoclave and kept in the oven for 24 h at 200°C. After the synthesis, the resultant precipitate (comprising the nanostructures) should be washed several times with deionized water and isopropyl alcohol, alternately, and centrifuged at each time. The nanostructures are usually dried at ≈60°C, in vacuum, for a at least 2 hours. [32, 43]
3. Results and discussion
3.1 Growth mechanism of ZTO nanostructures
3.1.1 Tailoring the chemico-physical parameters of the hydrothermal synthesis
Understanding the influence of each synthesis parameter is a key step in achieving the desired structures. Specifically, considering seed-layer free processes allows evaluation of the intrinsic influence of each synthesis parameter on the nanostructures’ growth. Moreover, the solvent also plays a major role in the process strongly determining the dissolution and diffusion of the species during the synthesis. When the precursors’ solubility is not high enough, precluding an efficient reaction, mineralizer agents can be used (NaOH, KOH, etc.) to increase the solubility of the species. [50, 51]
To understand the growth within Zn:Sn:O system it is essential to revise the main equations related with the chemical reactions behind each ZTO phases. The chemical reaction processes for the formation of ZnSnO3 nanostructures have been represented in the literature by the following equations: [52]
Zn2++Sn4++6OH−→ZnSnOH6E1
ZnSnOH6→ZnSnO3+3H2OE2
Regarding Zn2SnO4, its formation has been described by different reactions depending on the precursors and solvents involved in the synthesis. For example, Li et al. represented the chemical reaction of Zn2SnO4 nanowires through the equations below, which have been the most common in literature. [35]
Zn2++Sn4++6OH−→ZnSnOH6↓E3
Zn2++4OH−→ZnOH42−E4
ZnSnOH6+ZnOH42−→Zn2SnO4↓+4H2O+2OH−E5
On the other hand, Fu et al. employed a different synthesis method to avoid the use of NaOH, using four different amines (surfactants) instead, [53] represented as:
Sn4++3H2O↔H2SnO3+4H+E6
H2SnO3→SnO2↓+H2OE7
Sn4++6OH−→SnOH62−E8
Zn2++4OH−→ZnOH42−E9
SnOH62−+ZnOH42−→Zn2SnO4↓+4H2O+6OH−E10
Several reports show that ZnO and SnO2 crystals can co-exist with ZTO nanostructures when the synthesis parameters differ, even if slightly, from the ideal conditions for ZTO formation. Usually the formation of ZnO (Eq. 11) and SnO2 (Eqs. 12–14) is associated with the two alkaline concentration extremes, higher and lower, respectively. [54]
ZnOH42−→ZnO↓+H2O+2OH−E11
Sn4++3H2O↔H2SnO3+4H+E12
H2SnO3→SnO2↓+H2OE13
H++OH−→H2OE14
In fact, in our previous work on seed-layer free synthesis of ZTO nanowires, using zinc and tin chloride precursors at a fixed concentration ratio it was shown that while for lower NaOH concentrations SnO2 nanoparticles were obtained, for higher NaOH concentrations ZnO nanowires (mixed with fcc-ZnSnO3 nanoparticles) were achieved, whereas intermediate NaOH concentrations yielded ZnSnO3 nanowires. [32] As shown in Figure 2, a similar trend is seen even when increasing only the NaOH concentration (keeping the precursors’ concentration fixed). This suggests that there is an optimal concentration of the mineralizer. These results agree with those reported by Zeng et al., [54] however, while the authors suggest specific values of pH for obtaining the different structures (SnO2, Zn2SnO4 and ZnO), in our case the pH is much higher due to the presence of ethylenediamine (EDA) which yields a pH of at least ≈ 12, showcasing the trend specifically with the variation of the NaOH concentration and not necessarily the overall pH. [32]
Figure 2.
SEM images of resultant nanostructures from synthesis with different precursors’ molar concentrations, i.e., ZnCl2:SnCl4.5H2O:NaOH of (a) 2:1:12 M, (b) 4:2:24 M (from reference [43]) and (c) 8:4:48 M, respectively, while maintaining the same proportion between them. Increasing the precursors’ molar concentrations the materials obtained follow the common trend when increasing only the NaOH concentration: SnO2 nanoparticles, orth-ZnSnO3 nanowires and ZnO nanowires (mixed with fcc-ZnSnO3 nanoparticles).
As mentioned, the precursors’ solubility is a key factor to achieve a well-controlled synthesis. Our previous work showed that for different zinc precursors (zinc chloride or zinc acetate), maintaining the same tin precursor (tin chloride), the reaction differs, being slower and less homogeneous when using zinc acetate, due its lower solubility in the EDA surfactant. The use of surfactants, such as EDA, cetrimonium bromide (CTAB) and sodium dodecyl sulfate (SDS), is very common specially when aiming to induce the growth of 1D nanostructures. Surfactants act as directing growth agents as their molecules aggregate to the surface of the metallic atoms inducing the growth of specific structures/shapes. The solubility of each precursor in the solvents is a key factor for achieving a better synthesis efficiency and homogeneity. This also influences the Zn to Sn precursor ratio required to optimize the achievement of the desired nanostructures.
The duration and temperature of the synthesis are also crucial to determine the achieved nanomaterials. Several reports showed that below 180°C no ZTO phases are obtained, with the intermediate phase ZnSnOH6 being produced instead. [43, 45] Zeng et al. showed that to obtain Zn2SnO4 nanostructures a temperature of at least 200°C and 20 h of synthesis are necessary. [54] Meanwhile, Guo et al. observed that 12 h at 260°C are required to produce orth-ZnSnO3 nanoplates for that specific solution process. [45] In our work on the synthesis of orth-ZnSnO3 nanowires, it was observed that syntheses with 12 h at 200°C were necessary for a predominant growth of nanowires. However, for very long synthesis, or at higher temperatures (220°C), the decomposition of the ZnSnO3 phase into the more stable phases starts to occur. It was also concluded that lower energy levels favor the growth of the more energetically stable phases (Zn2SnO4, ZnO and SnO2), the metastable ZnSnO3 is achievable for intermediate energy levels, and for higher energy levels the decomposition (into Zn2SnO4 and SnO2) of ZnSnO3 starts to occur. Higher solution volumes, corresponding to higher pressure in the synthesis, were found to be necessary for obtaining the ZnSnO3 phase. A general growth mechanism for orth-ZnSnO3 nanowires and Zn2SnO4 nanoparticles was proposed and is shown in Figure 3. [43]
Figure 3.
Schematic of the growth mechanism of ZTO nanostructures (ZnSnO3 nanowires and Zn2SnO4 nanoparticles) on a hydrothermal synthesis as a function of the energy available and the duration of the synthesis. From reference [43].
While tailoring the chemico-physical parameters is always necessary, the use of a seed-layer material, usually a thin film, can be very effective in strongly inducing the growth of a desired structure by means of an epitaxial growth mechanism. This approach is commonly used when 1D structures are aimed, as briefly mentioned in the previous section. The selection of the seed material depends on the desired material and structure (phase and shape) and while several reports for different structures exist, the relation between different seed materials and grown structures was not detailed yet in literature. This depends on a complex interrelation between preferential epitaxial growth and thermodynamical stability of the multiple phases and shapes within the Zn-Sn-O system. While the seed-layer route presents advantages for specific applications such as gate-all-around transistors or photocatalysis, [55, 56] its absence also brings numerous benefits. For instance, one of the main issues related with the use of seed-layers is the common residuals incorporated in the nanostructures, which are usually undesired for the applications. Also, without seed-layers the synthesis is less complex and this approach brings higher degree of freedom concerning the integration of nanostructures into devices. [14, 32, 54]
3.1.2 ZTO phase transformations
Obtaining a single phase and shape of a multicomponent oxide as ZTO is highly desirable due to the different characteristic properties of each phase and shape, still by a hydrothermal synthesis is a challenging process as shown in the last section. In addition, the proper identification of the different possible phases obtained is a difficult task.
As previously presented, ZTO can grow in two different structural phases: Zn2SnO4 and ZnSnO3 (fcc, orth and rhombohedral). Their identification by XRD analysis is challenging since both phases and intermediary compounds show very similar diffraction patterns. While the fcc-ZnSnO3 (ICDD 00–011-0274) has a similar pattern to that of the intermediate phase ZnSn(OH)6 (ICDD 01–073-2384), the orth-ZnSnO3 (ICDD 00–028-1486) pattern can be confused with that of a mixture of Zn2SnO4 and SnO2. In fact, the 00–028-1486 card was deleted from the ICDD database for this reason. Figure 4 shows the XRD peaks of these phases. For clarification, the orth-ZnSnO3 identification was performed by peak indexation, using both treor and dicvol methods, for which the determined crystalline structure was proven to be orthorhombic. [32]
Figure 4.
(a) Representation of XRD peaks of ICDD cards of: ZnSn(OH)6, fcc-ZnSnO3, orth-ZnSnO3, Zn2SnO4 and SnO2. Note that the card 00–028-1486 (orth-ZnSnO3) was deleted from ICDD. (b) In-situ XRD patterns of ZnsnO3 nanowires during annealing until 850°C. (c) SEM images of the ZnsnO3 nanowires before and after the in-situ annealing experiments in XRD.
As previously stated, temperature conditions can induce different phase transformations. For instance, Bora et al. studied the phase transformation of fcc-ZnSnO3 nanocubes into the inverse spinel Zn2SnO4 through Raman analysis during in-situ annealing treatment. [57] In this study the phase transformation occurred at 500°C.
Phase transformation in the ZnSnO3 nanowires, synthesized by our group, was investigated by recording XRD patterns in the course of in-situ annealing treatment up to 850°C. Figure 4b shows the XRD patterns at different temperatures, where no phase transformation is observable bellow 750°C. At 850°C the characteristic peaks of Zn2SnO4 and SnO2 start to be more pronounced, suggesting the phase transformation described in Figure 3. Nevertheless, a nanowire-like morphology is still obtained after this in-situ annealing experiment (Figure 4c), which was somehow unexpected from the experimental results used to propose the growth mechanism shown in Figure 3.
Thermogravimetry (TG) and differential scanning calorimetric (DSC) measurements up to 1350°C were also performed on ZnSnO3 nanowires to shed light into this. A clear transformation occurred at ≈ 570°C with a mass loss of ≈ 4% (Figure 5), which can be attributed to the expected decomposition of ZnSnO3 into Zn2SnO4 and SnO2. Through XRD patterns (Figure 5b) the orth-ZnSnO3 phase is identified before the annealing, while after the annealing a predominance of SnO2 is noticeable (mixed with Zn2SnO4). SEM images presented in Figure 5c show the nanowires before and after the annealing. After annealing, larger and rounder structures are observed for which energy dispersive X-ray spectroscopy (EDS) analysis showed a predominance of Sn (Sn/Zn ratio of 14.5), in agreement with the XRD analysis.
Figure 5.
(a) TG and DSC curves of as-prepared ZnSnO3 nanowires at a heating rate of 10°C/min at N2 atmosphere. (b) XRD patterns and (c) SEM images of ZnSnO3 nanowires before and after annealing (TG-DSC measurements).
The difference of the decomposition temperature observed between the DSC and the XRD annealing treatments can probably be attributed to the annealing process in both techniques. While the XRD annealing is performed through the heating of a platinum foil (where the nanostructures are placed), in DSC the nanostructures are placed in a melting pot, leading to a more efficient heating and faster decomposition of the ZnSnO3 nanowires.
These results show that when annealing processes are demanded to improve the ZnSnO3 crystallinity, it is important to consider phase transformations carefully. Furthermore, it is noticeable that the temperatures to achieve these phase transformations as a post-synthesis treatment are significantly larger than those required during hydrothermal synthesis, owing to the higher energy provided during synthesis due to the combined effect of temperature and pressure.
3.2 Physico-chemical properties of ZTO nanostructures
The wide array of ZTO nanostructures present different physico-chemical properties which are imposed not only by the structures’ shape but also by their phase (Zn2SnO4 or ZnSnO3).
Concerning the optical properties, ZTO is a wide band gap semiconductor, with reported band gap values of 3.46–3.6 eV for Zn2SnO4 and 3.6–3.9 eV for ZnSnO3. [18, 32, 35, 58] Nevertheless, these values are not only dependent on the phase, but also on the shape and size of the nanostructures, with higher band gaps for smaller particles due to the quantum confinement effect. [16]
While optical properties of nanostructures can be determined simply, their electrical properties are much more challenging to access, especially when considering the properties of a single nanostructure. For this reason, there are only a few reports on electrical characterization of single ZTO nanostructures. While most reports are focused on nanowires with lengths >10 μm (mostly produced by physical processes), smaller ZnSnO3 nanowires (lengths <1 μm), produced in our group by hydrothermal synthesis, were probed individually by using nanomanipulators inside SEM, as shown in Figure 6a. For these, an average resistivity (in vacuum) of 7.80 ± 8.63 kΩ·cm was achieved. [32, 59] When compared to the ≈73 Ω·cm reported by Xue et al. for ZnSnO3 nanowires produced by thermal evaporation (990°C), this resistivity is significantly higher, [60] which can be attributed to the higher defect density expected for lower temperature (200°C) and solution-based processes. Concerning Zn2SnO4 nanowires, Karthik et al. reported a resistivity of 6 Ω·cm in vacuum for nanowires synthesized by vapor phase methods at 900°C. [61] Moreover, for Zn2SnO4 nanostructures, which are an n-type semiconductor, mobilities higher than 112 cm2V−1 s−1 have already been reported, highlighting the relevance of using this material for electronic applications. [62]
Figure 6.
(a) SEM image showing the tungsten tips of the nanomanipulators, which are contacting in-situ deposited Pt electrodes for the electrical characterization of a single ZnSnO3 nanowire. Atomic force microscopy characterization of individual ZnO and ZnSnO3 nanowires: (b) topographies in noncontact mode, and (c) contact mode tip oscillation as a function of tip-bias ac-voltage. Reprinted with permission from [63]. Copyright 2020 American Chemical Society.
The ZnSnO3 phase is well-known for its piezoelectric properties. A piezoelectric polarization along the c-axis of ≈59 μC/cm2 was reported by Inaguma et al. for ZnSnO3, being much higher than the ≈5 μC/cm2 reported for ZnO. [64, 65] Moreover, the piezoelectric constants of individual ZnSnO3 and ZnO nanowires produced by hydrothermal synthesis were recently determined by piezoresponse force microscopy (PFM) measurements as 23 pm/V and 9 pm/V, respectively (Figure 6b and c). [63] The enhanced piezoelectric properties reported for ZnSnO3 are related with the higher displacement of the Zn atom in the ZnO6 octahedral cell when compared to the one of the Sn atom in the SnO6 octahedral cell, leading to a higher polarization along the c-axis. [66] Even when compared with other 1D nanostructures produced by hydrothermal synthesis, only the piezoelectric constant of the well-known BaTiO3 (31.1 pm/V) and LiNbO3 (25 pm/V) exceeds the value reported for ZnSnO3. Having sustainability in mind, ZnSnO3 is then a very good alternative to both BaTiO3 and LiNbO3 as these contain critical raw materials. [63]
Table 1 summarizes the optical, electrical, and piezoelectric properties of some of the most typical oxide semiconductor nanostructures. These properties show the potential of ZTO compared with other binary and ternary compounds to achieve the desired multifunctionality to meet the concepts of IoT and smart surfaces while avoiding the use of critical raw materials.
Optical, electrical and piezoelectric properties of some of the most typical oxide semiconductor nanostructures.
The properties marked with * are referent to the bulk materials. Abbreviations: n/a – not applicable.
3.3 Application of ZTO nanostructures
The multicomponent nature, together with the wide range of different ZTO nanostructures provide this material system with truly impressive multifunctionality, which will be briefly covered next, mostly focusing on photocatalysis, energy harvesting and electronic applications.
3.3.1 Photocatalysis and piezo(photo)catalysis
Industrial actions and human activities play a negative environmental impact, raising water pollution. [80] Oxide nanostructured materials present great advantages for breakdown of water pollutants, as their band gaps are close to the visible light range and they have high surface-to-volume ratios. [81] Moreover, multicomponent oxides such as ZTO have a higher stability in aqueous environments when compared with binary compounds, which is significantly advantageous for photocatalytic applications. [82]
The mechanism of photocatalytic activity of ZTO under UV light can be represented by the equations below [14, 54, 83]:
ZTO→e−+h+E15
e−+h+→energyE16
h++H2O→H++OH˙E17
h++OH−→OH˙E18
e−+O2→O˙2−E19
O°2−+H+→HO˙2E20
OH°O°2−HO°2+dye→degradation productsE21
Considering photocatalytic activity under visible light, Jain et al. [84] proposes the following equations:
Zn2SnO4+hv→Zn2SnO4ecb−+Zn2SnO4h+E22
Zn2SnO4ecb−+O2→Zn2SnO4+O2−.E23
Zn2SnO4h++OH−→OH.E24
O2−.+H2O→OH−+HO2.E25
HO2.+H2O→OH.H2O2E26
H2O2→2OH˙E27
Dye+OH.→CO2+H2O+degradation productsE28
Zn2SnO4 nanocrystals were used for the degradation of 50% of reactive red 141 dye in 270 min under sunlight. [85] Different ZnSnO3 structures such as nanowires and nanoplates were already used as photocatalysts for organic pollutants (for example, methylene blue and rhodamine B). [33, 40, 86] Due to its high optical band gap (3.3–3.9 eV) UV light is usually required to photoactivate this material. Nevertheless, fcc-ZnSnO3 nanoparticles were already reported with a very satisfactory photocatalytic behavior on methylene blue degradation under visible light (0.0156 min−1). [81]
Alternatives to the conventional photocatalytic approach have also been explored, making use of the piezoelectric properties of materials such as ZnSnO3 (nanowires and nanoplates) for piezocatalysis (in the dark) [87] or for piezophotocatalysis (under illumination). [42, 87, 88] Indeed, piezoelectricity and ferroelectricity (associated with perovskite structures) have shown to play an important role in photocatalysis, since the photogeneration of electron–hole pairs is enhanced by the dipole moment formed by the polarization electric field across polar materials. [89, 90] A schematic representation of the piezocatalytic mechanism is presented in Figure 7b and shows the influence of the characteristic polarization of the piezoelectric materials, which contributes to the generation of hydroxyl radicals and consequently degradation of rhodamine B. The dye degradation was achieved in 2.5 h, with a degradation rate of 4.5 × 10−2 min−1. [87].
Figure 7.
(a) Piezocatalysis using ZnSnO3 nanoparticles under ultrasound exposure. (b) Schematic of the piezocatalytic mechanism. Reprinted with permission from [87]. Copyright (2020) American Chemical Society.
Other interesting applications of photocatalytic properties have been reported, such as the photocatalytic inactivation of Escherichia coli using ZTO nanocubes under visible light. Only a 10% surviving rate was found for the bacteria, whereas the absorption of the visible light was attributed to the inherent surface defects enhancing the absorption edge in the visible region. [82] With this in mind, lower cost methods for nanostructure production (as hydrothermal methods), which typical result in more defective structures, might be advantageous for these applications as defect levels near the band edges may increase the absorption for lower energy levels.
3.3.2 Piezoelectric energy harvesting with ZTO nanostructures
Nanogenerators are devices that can convert external stimulus into electrical energy, being highly interesting for smart and self-sustainable surfaces, as they can be used for sustainable energy sources, biomedical systems and smart sensors. [91] Due to its excellent ferroelectric and piezoelectric properties, different ZnSnO3 nanostructures (i.e., nanowires, nanoplates, nanocubes) have been widely explored for energy harvesting devices and sensitive human motion sensors, through their piezoelectric (induction of electrical charge by the applied mechanical strain) and piezoresistive (electrical resistivity change by the applied mechanical strain) effects, respectively. [45, 66, 92, 93, 94] The fcc-ZnSnO3 nanocubes have been the most popular ZTO structures for these applications. For instance, Wang et al. reported the nanogenerators of fcc-ZnSnO3 nanocubes mixed with polydimethylsiloxane (PDMS), reaching a maximum output of 400 V, 28 μA at a current density of 7 μA·cm−2. [95] While, Paria et al. mixed fcc-ZnSnO3 nanocubes with polyvinyl chloride (PVC), achieving a maximum output of ≈40 V and ≈1.4 μA, corresponding to a power density of 3.7 μW·cm−3 (Figure 8a). [94]
Figure 8.
Hybrid nanogenerators of: (a) a composite film based on fcc-ZnSnO3 nanocubes and PVC. Reprinted with permission from [94], copyright 2020 American Chemical Society; and (b) a composite film based on orth-ZnSnO3 nanowires and PDMS. (c) Schematic of the charge generation mechanism in the micro-structured devices of (b). Images (b) and (c) were reprinted with permission from [63], copyright 2020 American Chemical Society.
ZnSnO3 nanoplates were also applied for nanogenerators. Guo et al. reported produced nanogenerators fabricated with orth-ZnSnO3 nanoplates embedded in flat films of PDMS, reaching voltage and current outputs of 20 V and 0.6 μA, respectively, under bending stress. [45] More recently in our group, orth-ZnSnO3 nanowires were mixed with PDMS to fabricate nanogenerators of micro-structured composites (Figure 8b). [63] In the same work, a charge generation and displacement mechanism was proposed, as depicted in Figure 8c. Briefly, the micro-structures induced in PDMS are suggested to improve the force delivery to the nanowires, enhancing its piezoelectric signal, while bringing also a triboelectric contribution to the nanogenerator output. This results in an output voltage, current and instantaneous power of approximately 9 V, 1 μA and 3 μW·cm−2, respectively, when applying a force of only 10 N. For higher forces the devices were capable to reach outputs around 120 V and 13 μA, which was shown to be enough energy to light up LEDs and several small electronic devices. [63]
3.3.3 Electronic applications
Electronic applications are always a relevant drive for materials. Multicomponent semiconductor nanostructures as ZTO are particularly interesting for these applications, with wide band gap semiconductors allowing for high-power and high-frequency operations. [50] Field-effect transistors (FETs) are the key elements enabling today’s electronics, being 1D nanostructures particularly interesting in this regard, given the easiness of confining migratory direction of charge carriers through its length, i.e., between source and drain electrodes. Indeed, 1D nanostructures have already proven great usefulness for the upcoming generations of semiconductors in FETs. [96] While several reports already demonstrated ZTO as a candidate for replacement of IGZO in thin film technologies, [13] similarly, ZTO is also one of the most promising multicomponent metal oxides for transistors with nanostructures. [62] Demonstrations of discrete Zn2SnO4 nanotransistors have already been made using nanotransfer molding of ZTO inks followed by annealing at 500°C, or by simple pick-and-place approach of drop-casted ZTO nanowires prepared by CVD above 700°C and by thermal evaporation at 1000°C. [39, 97, 98] While the achievement of on/off ratio ≈106 and field-effect mobility ≈20 cm2/Vs is a good demonstration of the ZTO’s potential, transistors using ZTO nanostructures synthesized by solution processes have not been reported yet. Furthermore, these nanostructures have also been used for the resistive switch layer in the emerging type of memory devices known as memristors. Reports show ZTO as the active material in memristors in the form of both Zn2SnO4 nanowires and ZnSnO3 nanocubes, being the latter especially relevant for this application due to its ferroelectric properties. Properties such as high off/on ratios (>105), long retention times (>5 months) and fast response speeds (<20 ns) are obtained for these devices. [99, 100]
Transforming ZTO or other nanostructures into well-established LAE semiconductor materials, while highly desirable from the performance and functionality point of view, will still require significant advances in reliable techniques for alignment and density control in transparent (and flexible) substrates. [101]
3.3.4 Other applications
Besides the applications briefly presented above, ZTO nanostructures have also been widely used in sensing applications, with gas sensors being the most popular. [102] Their small crystallite size, high surface-to-volume ratios and surface reactivity result in enhanced sensitivities/selectivity, with multicomponent materials typically presenting smaller response times and superior stabilities compared to binary compounds. [103] Moreover, the implementation of these nanostructures in sensors allows miniaturization of the devices, as well as cost reduction. ZnSnO3 has been reported as an excellent humidity sensor, in different nanostructure forms such as nanoparticles or even in composites of ZnSnO3 nanocubes and Ag nanowires. [29, 104] Additionally, ZnSnO3 nanoparticles were used as electrochemical biosensors for label free sub-femtomolar detection of cardiac biomarker troponin T and a composite of Zn2SnO4 nanoparticles and graphene was used for morphine and codeine detection. [105, 106] Recently, Durai et al.. reported ultra-selective sensors, based on ZnSnO3 nanocubes modified glassy carbon electrode (GCE), for simultaneous detection of uric acid and dopamine through differential pulse voltammetry technique. [107] Zn2SnO4 and ZnSnO3 nanostructures of different shapes such as nanoparticles, nanowires and nanocubes, have also been widely explored as photoconductors. [23, 108, 109, 110, 111] While the optical band gap of these materials is typically in the UV energy levels (hence their transparency in visible range), quantum confinement effects or even defect levels near the band edges can be explored to increase the absorption for lower energy levels. Other applications that have been explored using ZTO nanostructures are related with energy storage and conversion. Zn2SnO4 has been widely used as photoanode for dye solar cells in different nanostructure morphologies such as nanoparticles and nanowires. [21, 35] Cherian et al. reported the performance of nanowires and compared with nanoplates of Zn2SnO4 for Li-batteries. [34] Supercapacitors (SC) have also started to be explored using ZTO nanostructures, with Bao et al. having reported the use of Zn2SnO4/MnO2 core shell in carbon fibers showing a capacitance of 621.6 F·g −1. [112]
4. Conclusions
Expanding LAE to IoT and smart surface concepts requires an increasing number of objects to have embedded electronics, sensors and connectivity, driving a demand for compact, smart, multifunctional and self-sustainable technology with low associated costs. While nanomaterials are thought to be able to meet these requirements, playing an important role in the future technological world, low cost and sustainable technologies are demanded. For this, both low cost fabrication methods and sustainable materials must be considered. This chapter shows the versatility of the hydrothermal method to control the growth and morphology of zinc tin oxide (ZTO) nanostructures, and the variety of shapes that can be produced for each of the different ZTO phases. Compared to other preparation methods, especially vapor phase methods, hydrothermal synthesis reveals a large set of advantages from both research and industrial viewpoints. First, while the multitude of parameters to control requires an in-depth understanding of their role in the final products, it also brings enormous flexibility to tune the synthesis process for the desired results. Also, it can be performed at low temperature (< 200°C), which is compatible with a wide range of substrates for direct growth, while assuring lower costs. This links perfectly with the demonstrated upscaling capability of hydrothermal synthesis which is a crucial aspect for industrial implementation.
Furthermore, a summary of exciting results that have been reported regarding application in devices of these ZTO nanostructures over the past few years is presented. The multifunctionality of this material system is highlighted by its successful implementation in energy harvesters, photocatalysis, electronic devices, sensors, and others.
Acknowledgments
The authors would like to thank Ana Pimentel for the TG-DSC measurement.
This work is funded by FEDER funds through the COMPETE 2020 Programme and National Funds through the FCT – Fundação para a Ciência e a Tecnologia, I.P., under the scope of the project UIDB/50025/2020, and the doctoral grant research number SFRH/BD/131836/2017. This work also received funding from the European Community’s H2020 program under grant agreement No. 716510 (ERC-2016-StG TREND), No. 787410 (ERC-2018-AdG DIGISMART) and No. 685758 (1D-Neon). This work is part of the PhD Thesis in Nanotechnologies and Nanosciences defended by Ana Rovisco at FCT-NOVA entitled “Solution-based Zinc Tin oxide nanostructures: from synthesis to applications” in December 2019.
Conflict of interest
The authors declare no conflict of interest.
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Metal oxides have been key materials for this end, finding applications from flexible electronics to photocatalysis and energy harvesting, with multicomponent materials as zinc tin oxide (ZTO) emerging as some of the most promising possibilities. This chapter is dedicated to the hydrothermal synthesis of ZTO nanostructures, expanding the already wide potential of ZnO. A literature review on the latest progress on the synthesis of a multitude of ZTO nanostructures is provided (e.g., nanowires, nanoparticles, nanosheets), emphasizing the relevance of advanced nanoscale techniques for proper characterization of such materials. The multifunctionality of ZTO will also be covered, with special attention being given to their potential for photocatalysis, electronic devices and energy harvesters.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/73846",risUrl:"/chapter/ris/73846",signatures:"Ana Isabel Bento Rovisco, Rita Branquinho, Joana Vaz Pinto, Rodrigo Martins, Elvira Fortunato and Pedro Barquinha",book:{id:"10414",title:"Novel Nanomaterials",subtitle:null,fullTitle:"Novel Nanomaterials",slug:null,publishedDate:null,bookSignature:"Dr. Karthikeyan Krishnamoorthy",coverURL:"https://cdn.intechopen.com/books/images_new/10414.jpg",licenceType:"CC BY 3.0",editedByType:null,editors:[{id:"278690",title:"Dr.",name:"Karthikeyan",middleName:null,surname:"Krishnamoorthy",slug:"karthikeyan-krishnamoorthy",fullName:"Karthikeyan Krishnamoorthy"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1 Hydrothermal synthesis of ZTO nanostructures",level:"2"},{id:"sec_2_2",title:"1.2 Overview on ZTO nanostructures produced by hydrothermal synthesis",level:"2"},{id:"sec_4",title:"2. Research methods",level:"1"},{id:"sec_5",title:"3. Results and discussion",level:"1"},{id:"sec_5_2",title:"3.1 Growth mechanism of ZTO nanostructures",level:"2"},{id:"sec_5_3",title:"3.1.1 Tailoring the chemico-physical parameters of the hydrothermal synthesis",level:"3"},{id:"sec_6_3",title:"3.1.2 ZTO phase transformations",level:"3"},{id:"sec_8_2",title:"3.2 Physico-chemical properties of ZTO nanostructures",level:"2"},{id:"sec_9_2",title:"3.3 Application of ZTO nanostructures",level:"2"},{id:"sec_9_3",title:"3.3.1 Photocatalysis and piezo(photo)catalysis",level:"3"},{id:"sec_10_3",title:"3.3.2 Piezoelectric energy harvesting with ZTO nanostructures",level:"3"},{id:"sec_11_3",title:"3.3.3 Electronic applications",level:"3"},{id:"sec_12_3",title:"3.3.4 Other applications",level:"3"},{id:"sec_15",title:"4. Conclusions",level:"1"},{id:"sec_16",title:"Acknowledgments",level:"1"},{id:"sec_19",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Mancini L, Sala S, Recchioni M, Benini L, Goralczyk M, Pennington D. 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Sci Rep. 2015;4(1):6847.'},{id:"B111",body:'Xue XY, Guo TL, Lin ZX, Wang TH. Individual core-shell structured ZnSnO3 nanowires as photoconductors. Mater Lett. 2008;62(8–9):1356–8.'},{id:"B112",body:'Bao L, Zang J, Li X. Flexible Zn2SnO4/MnO2 Core/Shell Nanocable−Carbon Microfiber Hybrid Composites for High-Performance Supercapacitor Electrodes. Nano Lett. 2011;11(3):1215–20.'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Ana Isabel Bento Rovisco",address:"a.rovisco@fct.unl.pt",affiliation:'
CENIMAT/i3N, Department of Materials Science, NOVA School of Science and Technology (FCT-NOVA) and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
CENIMAT/i3N, Department of Materials Science, NOVA School of Science and Technology (FCT-NOVA) and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
CENIMAT/i3N, Department of Materials Science, NOVA School of Science and Technology (FCT-NOVA) and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
CENIMAT/i3N, Department of Materials Science, NOVA School of Science and Technology (FCT-NOVA) and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
CENIMAT/i3N, Department of Materials Science, NOVA School of Science and Technology (FCT-NOVA) and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
CENIMAT/i3N, Department of Materials Science, NOVA School of Science and Technology (FCT-NOVA) and CEMOP/UNINOVA, NOVA University Lisbon, Campus de Caparica, 2829-516 Caparica, Portugal
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