Selective applications of silver nanoparticles synthesised using plant extracts.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"10061",leadTitle:null,fullTitle:"21st Century Surface Science - a Handbook",title:"21st Century Surface Science",subtitle:"a Handbook",reviewType:"peer-reviewed",abstract:"Surface sciences elucidate the physical and chemical aspects of the surfaces and interfaces of materials. Of great interest in this field are nanomaterials, which have recently experienced breakthroughs in synthesis and application. As such, this book presents some recent representative achievements in the field of surface science, including synthesis techniques, surface modifications, nanoparticle-based smart coatings, wettability of different surfaces, physics/chemistry characterizations, and growth kinetics of thin films. In addition, the book illustrates some of the important applications related to silicon, CVD graphene, graphene oxide, transition metal dichalcogenides, carbon nanotubes, carbon nanoparticles, transparent conducting oxide, and metal oxides.",isbn:"978-1-78985-200-4",printIsbn:"978-1-78985-199-1",pdfIsbn:"978-1-83962-640-1",doi:"10.5772/intechopen.87891",price:119,priceEur:129,priceUsd:155,slug:"21st-century-surface-science-a-handbook",numberOfPages:294,isOpenForSubmission:!1,isInWos:null,hash:"69253b3c7ba801a5fcd9c47827345f93",bookSignature:"Phuong Pham, Pratibha Goel, Samir Kumar and Kavita Yadav",publishedDate:"November 26th 2020",coverURL:"https://cdn.intechopen.com/books/images_new/10061.jpg",numberOfDownloads:2308,numberOfWosCitations:0,numberOfCrossrefCitations:1,numberOfDimensionsCitations:2,hasAltmetrics:0,numberOfTotalCitations:3,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 11th 2019",dateEndSecondStepPublish:"March 17th 2020",dateEndThirdStepPublish:"May 16th 2020",dateEndFourthStepPublish:"August 4th 2020",dateEndFifthStepPublish:"October 3rd 2020",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,editors:[{id:"236073",title:"Dr.",name:"Phuong",middleName:"Viet",surname:"Pham",slug:"phuong-pham",fullName:"Phuong Pham",profilePictureURL:"https://mts.intechopen.com/storage/users/236073/images/system/236073.jpg",biography:"Phuong Pham is a Distinguished Research Fellow at the College of Information Science and Electronic Engineering and Zhejiang University-University of Illinois at Urbana-Champaign Joint Institute (ZJU-UIUC), Zhejiang University, China. He earned a Ph.D. degree from SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University (SKKU), South Korea (2016). Then, he has spent a few years as a Postdoctoral Researcher and a Research Fellow at the School of Advanced Materials Science and Engineering, SKKU, and at the Center for Multidimensional Carbon Materials (CMCM), Institute for Basic Science (IBS), UNIST, South Korea, respectively. He has published >30 peer-reviewed articles/patents/books in prestigious journals/publishers such as Chem. Rev., Chem. Soc. Rev., Adv. Mater., 2D Materials, Carbon, Nanoscale, RSC Advances, ACS Omega, Royal Soc. Open Sci., JJAP, InechOpen, etc. He has published 5 books/book chapters and is serving as an Editorial Member of some scientific journals and as a member at ACS, AAAS, APS, ERMS, etc. In addition, he is a recipient of the National Postdoctoral Award for Excellent Scientists by China Government and the NSF award for outstanding young scholars (China). Dr. Pham's research interests are focusing on materials science, electronics devices, plasma engineering, chemical synthesis, transfer strategies of thin films, doping mechanism (acceptors, donors), new doping technique development, nanocomposite, block copolymer, plasma engineering for OLED, transistors, sensor, photodetector, flexible display, and wearable electronics.",institutionString:"Zhejiang University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Zhejiang University",institutionURL:null,country:{name:"China"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"315718",title:"Dr.",name:"Pratibha",middleName:null,surname:"Goel",slug:"pratibha-goel",fullName:"Pratibha Goel",profilePictureURL:"https://mts.intechopen.com/storage/users/315718/images/system/315718.jpg",biography:"Dr. Pratibha Goel received her PhD from the Indian Institute of Technology Delhi (IITD) in 2016. 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Ali",surname:"Shahid",slug:"ahmad-ali-shahid",fullName:"Ahmad Ali Shahid"},{id:"179289",title:"Dr.",name:"Idrees Ahmad",surname:"Nasir",slug:"idrees-ahmad-nasir",fullName:"Idrees Ahmad Nasir"}]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"84261",firstName:"Iva",lastName:"Simcic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/84261/images/4758_n.jpg",email:"iva.s@intechopen.com",biography:"As a Commissioning Editor at IntechOpen, I work closely with our collaborators in the selection of book topics for the yearly publishing plan and in preparing new book catalogues for each season. 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Abdurakhmonov",coverURL:"https://cdn.intechopen.com/books/images_new/6914.jpg",editedByType:"Edited by",editors:[{id:"213344",title:"Dr.",name:"Ibrokhim Y.",surname:"Abdurakhmonov",slug:"ibrokhim-y.-abdurakhmonov",fullName:"Ibrokhim Y. Abdurakhmonov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5481",title:"Phylogenetics",subtitle:null,isOpenForSubmission:!1,hash:"d8bc33a0fbb63445b9a8d9831519e753",slug:"phylogenetics",bookSignature:"Ibrokhim Y. Abdurakhmonov",coverURL:"https://cdn.intechopen.com/books/images_new/5481.jpg",editedByType:"Edited by",editors:[{id:"213344",title:"Dr.",name:"Ibrokhim Y.",surname:"Abdurakhmonov",slug:"ibrokhim-y.-abdurakhmonov",fullName:"Ibrokhim Y. Abdurakhmonov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"763",title:"Wire Robots Part I: Kinematics, Analysis & Design",doi:"10.5772/5365",slug:"wire_robots_part_i__kinematics__analysis___design",body:'One drawback of classical parallel robots is their limited workspace, mainly due to the limitation of the stroke of linear actuators. Parallel wire robots (also known as Tendon-based Steward platforms or cable robots) face this problem through substitution of the actuators by wires (or tendons, cables,... ). Tendon-based Steward platforms have been proposed in (Landsberger and Sheridan, 1985). Although these robots share the basic concepts of classical parallel robots, there are some major differences:
(a) Conventional parallel manipulator (b) Parallel Wire Robot.
The flexibility of wires allows large changes in the length of the kinematic chain, for example by coiling the tendons onto a drum. This allows to overcome the purely geometric workspace limitation factor of classical robots.
Wires can be coiled by very fast drums while the moving mass of the robot is extremely low, which allows the robot to reach very high end effector speeds and accelerations.
Wires are modeled as unilateral constraints, i.e. wires can only transmit pulling forces.
The number of wires m can be increased to modify the workspace, to carry higher loads or to increase safety due to redundancy. Thus, having an end effector (in the following called platform) with n degrees-of-freedom (d.o.f.) more than n parallel links are used to connect the platform to the base frame.
This contribution is organized as follows: The section 2 the classification of wire robots, based on several approaches is presented. Furthermore, the kinematic calculations for wire robots are described which is followed by the description of the force equilibrium in section 3. Based on the force equilibrium, methods for workspace analysis and robot design are proposed in section 4 and 5, respectively. This contribution is extended in Part 2 (Bruckmann et al., 2008a) by the description of dynamics, control methods and application examples. Within this and the next chapter, the following abbreviations are used:
Br vector r denoted in coordinate system nA matrix A
BRPtransformation matrix from coordinate systemA−T shorthand for (A−1)T
For wire robots, different classifications based on the difference between the number
of wires m and the number d.o.f. n have been proposed. Further on, this difference is called the redundancy r = m − n. According to (Ming and Higuchi, 1994) wire robots can be categorized based on the redundancy as follows:
CRPM (Completely Restrained Parallel Manipulator): The pose of the robot is completely determined by the unilateral kinematic constraints defined by the tensed wires. For a CRPM at least m = n + 1 wires are needed.
IRPM (Incompletely Restrained Parallel Manipulator): In addition to the unilateral constraints induced by the tensed wires at least one dynamical equation is required to describe the pose of the end effector.
In (Verhoeven, 2004) the category of CRPMs is further divided into two categories. The class of the CRPMs is restricted to robots with m = n+1 wires. Wire robots with m > n + 1 are called RRPMs (Redundantly Restrained Parallel Manipulator). Note that within this definition CRPM and RRPM robots can convert into IRPM robots if they are used at poses where external wrenches (inertia and generalized forces and torques applied onto the platform) are necessary to find completely positive wire forces. Therefore in (Verhoeven, 2004) another classification is proposed based on the number of controlled d.o.f. and is listed below.
1T: linear motion of a point
2T: planar motion of a point
1R2T: planar motion of a body
3T: spatial motion of a point
2R3T: spatial motion of a beam
3R3T: spatial motion of a body
Here T stands for translational and R for rotational d.o.f.. It is notable that this definition is complete and covers all wire robots. The classification of (Fang, 2005) is similar to Verhoeven’s approach. Here, three classes are defined as:
IKRM (Incompletely Kinematic Restrained Manipulators), where m < n
CKRM (Completely Kinematic Restrained Manipulators), where m = n
RAMP (Redundantly Actuated Manipulators), where m ≥n + 1
This chapter as well as the next one focuses on CRPM and RRPM robots. For IRPM see e.g. Maier (2004).
Inverse kinematics refers to the problem of calculating the joint variables for a given end-effector pose. For the class of robots under consideration those are the lengths of the wires, comparable to the strokes of linear actuators. Therefore, the kinematical description of a wire robot resembles the kinematic structure of a Stewart-Gough platform, presuming the wires are always tensed and can thus be treated as line segments representing bilateral constraints. Modeling a wire robot as a platform, which is connected to m points on the base by m bilateral constraints, it is reasonable to denote the platform pose x =[ B r T\n\t\t\t\t\t
immediately. Hence, the length of the ith wire can be calculated by
Kinematics of a wire robot.
Based on the relatively simple inverse kinematics, a position control in joint space can be designed for a wire robot which already may deliver satisfying results. Note, this simple calculation only holds for the described simple guidance. While it may be sufficient for simple prototypes, it suffers from a very high wear and abrasion. Thus it is not feasible for practical applications. An alternative concept is the roller-based guidance which is e.g. widely used in theatre and stage technology, see fig. 4. As a drawback, the kinematical description becomes more difficult due to to the posedependent exit points points Bs i of the wires. The roller with radius
Roller-based guidance.
Here Bbi denotes the vector to the point, at which the wire enters the roller. With this knowledge the vector Bmi to the midpoint of the i−th roller can be constructed
where RzB,
where
In a projection onto the plane D,
Therefore the wire length can be calculated by
Analog to the Stewart-Gough platform, the forward kinematics is much more complicated, in particular for the case of roller guidances.
In opposite to the inverse kinematics, where the equations are decoupled and therefore straight forward to solve, the forward kinematics problem is more involved. In general the forward kinematics are not analytically solveable. However, in some cases a geometrical approach allows a closed solution. To be more precise, a setup with three base points connected to one platform connection points leads to the task of finding the intersection points of three spheres where the radii of the spheres represent the measured lengths of the wires and the centers of the spheres are the base points bi. Hence, the spheres represent possible positions of the endpoints of the wires. Note, that a point-shaped wire guidance is presumed. More details can be found in (Williams et al., 2004). Nevertheless, in general no analytical solution is at hand. Thus, numerical approaches have to be employed to find the solution, which is disadvantageous in terms of computation time, especially when the computation has to be done in real-time. The forward kinematics problem is generally described by m nonlinear equations in n unknown variables.
If point-shaped wire guidances are used,
Since in kinematics positive wire tensions are assumed, the wires are modeled as bilateral constraints, already six constraints fix the platform, i.e. r rows of the inverse Jacobian
holds. The position at the time t1 can be calculated by forward integration in time
Taylor expansion of the second term around t0 delivers
Neglecting terms of second order and higher leads to
Approximating the differential quotient by the difference quotient gives
where
Using these simplified expressions, the platform pose x can be approximated by xapp:
For xapp (t), the inverse kinematics and the pose estimation error
Once again using the approximations
it follows
where lapp(t) is calculated by the inverse kinematics for xapp(t). Noteworthy, this approach works only for small pose displacements. When displacements become larger, an iteration can improve the precision of the calculated pose by using x(t) as the estimate xapp(t) for the next step (Merlet, 2000). In (Williams et al., 2004), the authors show an iterative algorithm for a roller-based wire guidance neglecting the pivoting angle.
The end effector of wire robots is guided along desired trajectories by tensed wires. This design is superior to classical parallel kinematic designs in terms of workspace size - due to the practically unlimited actuator stroke creating potentially large workspaces - and mechanical simplicity. On the other hand and caused by the unilateral constraints of the wires, the workspace of wire robots is primarily limited by the forces which may be exerted by the wires. The unilateral constraints necessitate positive forces. Practically, long wires will sag at low tensions which makes kinematical computations more complicated and may lead to vibration problems. Hence, the minimum allowed forces in the wires should never fall below a predefined positive value. Against, high forces lead to increased wear and elastic deformations. Therefore the working load of wires is bounded between predefined values fmin\n\t\t\t\t
Forces for a wire robot.
The force vectors fi can be written as
since the forces act along the wires. Hence, the force and torque equilibrium can be written in matrix form
with
or in a more compact form as
In the following the matrix AT is called structure matrix. It is noteworthy that the structure matrix can also be derived as the transpose of the Jacobian of the inverse kinematics, but generally, it is easier to construct it based on the force approach (Verhoeven, 2004).
In practical applications knowledge of the workspace of the robot under consideration is essential. In contrast to conventional parallel manipulators using rigid links, the workspace of a wire robot is not mainly limited by the actuator strokes, since the length of the wires is not the main limiting factor, just restricted by the drum capacity. In fact, the workspace of a wire robot is limited anyway by the wire force limits fmin and fmax. A pose r is said to be part of the workspace if a wire force distribution f exists, such that fmin\n\t\t\t\t
In order to perform a discrete workspace analysis at first an assumed superset of the workspace is discretized. Mostly an equidistant discretization is desired. This leads to a set of points, which is then tested with respect to the chosen workspace requirements. This is a widely used approach, but nevertheless, some considerations should be taken into account:
The calculation of the workspace conditions for the grid points generally requires the verification of a valid wire force distribution. Since it is sufficient to identify any valid distribution, fast calculation methods as presented in section (Bruckmann et al., 2008a) can be employed.
For some parallel kinematic mechanisms, typically symmetrical configurations are singular, leading to uncontrollable d.o.f. of the end effector. Thus, it is recommended to explicitly test at symmetrical poses of the end effector.
Generally, it is desired to rule out gaps in the workspace. Using a discrete approach, this is intrinsically impossible, but for practical usage, one may try to increase the grid resolution. Clearly this leads to a dramatical increase of the number of points to be checked and thus to extremely long computation times. To come up against this, parallelisation of the calculation by partitioning the workspace and allocation to different processing units is helpful and especially for this problem very efficient due to the independency of the workspace parts. Nevertheless, up from a specific resolution, continuous methods as presented in the next section should be considered.
In this section a method to compute the workspace of a wire robot, formulating this task as a constraint satisfaction problem (CSP), is shown. The CSP can be solved using interval analysis. However, other solving algorithms are also conceivable. The presented formulation can also be used for design just by interchanging the roles of the variables (Bruckmann et al., 2007), (Bruckmann et al., 2008b). This fact simplifies the generally complicated and complex task of robot design. For details see section 5. In (Gouttefarde et al., 2007) also interval analysis is used to determine the workspace of a wire robot. A criteria for the solvability of the interval formulation of eqn. 24 is given. In particular, the interval formulation is reduced to 2n n × m systems of linear inequalities in the form of eqn. 24. The solvability of those 2n systems of linear inequalities guarantees the existance of at least one valid wire force distribution. Based on this criteria a bisection algorithm is presented. This approach is beneficial in terms of the number of variables on which bisections are performed since no verification or existance variables are required. Here, however the CSP approach is presented due to its straight forward transferability to robot design.
A constraint satisfaction problem (CSP) is the problem of determining all
where
Within this definition
c is the vector of the calculation variables,
v is the vector of the verification and,
e is the vector of the existance variables.
The solution set for calculaton variables of a CSP is called XS i.e.
where X c is the so-called search domain, i.e. the range of the calculation variables wherein for solutions is searched.
Examining eqn. 25, the structure matrix AT needs to be inverted to calculate the wire forces f from a given platform pose and given external forces w. Since AT has a non-squared shape, this is usually done using the Moore-Penrose pseudo inverse. Thus, the calculated forces will be a least squares solution. In fact, not a least squares result but a force distribution within predefined tensions is demanded. To overcome this problem, the structure matrix is divided into a squared n × n matrix
In this equation, fsec is unknown. Every point and wrench satisfying
Force equilibrium workspace of plain manipulator, 2 translational d.o.f., wT = (0, 0)N, fmin = 10N, fmax = 90N.
and leading to primary wire forces
belongs to the workspace. Hence eqns. 31 and 32 represent a CSP of the form of eqn. 28 with f sec as existence an variable. To calculate a workspace for a specific robot, the following variable set for the CSP is used:
The platform coordinates are the calculation variables.
The wire forces fsec are the existence variables.
Optionally, the exerted external wrench w and desired platform orientations can be set as verification variables. The workspace for a fix orientation of the platform is called constant orientation workspace according to (Merlet, 2000). On the other hand, sometimes free orientation of the platform within given ranges must be possible within the whole workspace. The resulting workspace is called the total orientation workspace.
In fig. 6, the workspace of a simple plain manipulator is shown, based on the force equilibrium condition. In fig. 7, the workspace under a possible external load range is shown. Fig. 8(b) shows an example of the workspace of a spatial CRPM robot prototype while fig. 9(b) is the same protoype in a RRPM configuration with 8 wires. Additionally, the RRPM workspace was calculated with a verification range of ±3
Force equilibrium workspace of plain manipulator, 2 translational d.o.f., wT = ([−20, 20]N, [−20, 20]N), fmin = 10N, fmax = 90N.
Interval Analysis is a powerful tool to solve CSPs. Therefore a short introduction is given in the following section. For two real numbers a, b an interval I = [a, b] is defined as follows
where
Then b is called the supremum and a the infimum of I. A n-tupel of intervals is called box or interval vector. It is possible to define every operation
Let I0, I1\n\t\t\t\t\t\t
where
Hence
where < occurs if one variable appears more than once. This phenomenon is called overestimation and causes additional numerical effort to get sharp boundaries. For sure the same holds for min and Inf. Thus for input intervals I0,..., In interval analysis delivers evaluations for the domain I0 × I1 ×... × In. This evaluation is guaranteed to include all possible solutions, e.g.
(a) SEGESTA prototype with 7 wires (b)Workspace of the SEGESTA prototype with 7 wires.
while
As shown in detail in (Pott, 2007), a CSP can be solved using interval analysis which guarantees reliable solutions (Hansen, 1992),(Merlet, 2004b),(Merlet, 2001). Solving the CSP with interval analysis delivers a list of boxes LS representing an inner approximation of XS. According to eqn. 29, the solutions in LS hold for total Xv and a subset of Xe. Additionally, available implementations for interval analysis computations are robust against rounding effects. The following CSP solving algorithms have been proposed in (Pott, 2007) and (Bruckmann et al., 2008b). To use it for the special problem of analyzing wire robots, they have been extended. Details are described in the next sections.
(a) SEGESTA prototype with 8 wires (b)Workspace of the SEGESTA prototype with 8 wires.
Algorithm Verify
Verify is called with a box
is valid for the given box
Define a search domain in the list
Take the next box
If the diameter of the box
If existence variables are present, call Existence with
Evaluate
If Inf
If Sup
If Inf
Divide the box on a verification variable and add the parts to
Algorithm Existence
Existence is a modification of Verify. It is called with the boxes
is valid. Here the domain Xe is represented by the list of boxes
Define a search domain in the list
If
Take the next box
If the diameter of the box
Evaluate
If Inf
If Sup
If Inf
Algorithm Calculate
Calculate is called with a search domain for
Define a search domain in the list
Create the lists
Take the next box
If the diameter of the box
If verification variables are present, call Verify with
If the result of Verify is valid, move the box to the solution list
If the result of Verify is invalid, move the box to the invalid list
If the result of Verify is finite, move the box to the finite list
Calling Sequence
Let Xc,Xv,Xe\n\t\t\t\t\t\t
Preliminary Checks
Since solving the force equilibrium is a computationally expensive task, favorable prechecks are demanded to reduce computation time. An effective check is to examine the interval evaluation of
one can conclude that the poses under consideration do not belong to the workspace under the given load w due to the non-existance of valid wire force distributions. The resulting preliminary workspace is an outer estimate and excludes poses which are not treated furthermore. Another possibility to reduce the computation time is to take symmetries into account. If symmetry axes as well as a symmectrical load range are present it is sufficient to compute only one part of the workspace and to complete the workspace by proper mirroring.
Besides the force equilibrium, additional workspace conditions can be applied. Due to the high elasticity of the wires (using plastic material, e.g. polyethylene), the stiffness may be low in parts of the workspace. Thus, for practical applications, especially if a predefined precision is required, it may be necessary to guarantee a given stiffness for the whole workspace. Otherwise, the compensation of elasticity effects by control may be required. Generally, this should be avoided as far as possible by an appropriate design. As shown in (Verhoeven, 2004), the so-called passive stiffness can be described as the reaction of a mechanical system onto a small pertubation, described by a linear equation:
where
Here, L is the diagonal matrix of the wire lengths and k \' is the proportionality factor (force per relative elongation), treating the wires as linear springs. For the calculation, the inverse problem
is solved and evaluated where only domains having a position pertubation within the predefined limits
(a) Stiffness workspace of plain, (b) Combined force equilibrium and manipulator stiffness workspace of plain manipulator.
A pose of a wire robot is said to be singular if and only if
Therefore all wire robots with pure translational d.o.f. are singularity free except those, which are always singular (Verhoeven, 2004). For a wire robot with rotational and translational d.o.f. the workspace certainly has be to checked for singularities. Since within the workspace analysis (discrete or continuous) typically a system of linear equations is solved, the singularity criteria eqn.46 can be checked implicitly. Mechanically, at singular poses certain d.o.f. become uncontrollable (overmobility). Often this happens in symmetrical configurations.
In analogy to the problem of link collisions for conventional parallel manipulators, wire collisions have to be avoided. Due to their normally small diameter one possibility is to consider the wires as lines. In (Merlet, 2004a) an algorithm is proposed to determine the regions in which collisions between wires as well as the collisions between wires and the end-effector occur. Practically, wires have certain diameter and thus, a predefined minimum distance (at least the wire diameter) should be always ensured. Therefore, the well-known problem of determining the smallest distance between two lines arises. Since the lines are known after solving the inverse kinematics this is a very basic task but may be computational expensive. Clearly, the distance condition has to be formulated as a inequality. Hence, this criteria can be easily included in the CSP formulation.
While workspace analysis examines the properties of already parametrized manipulators which allows to determine the applicable use cases, robot design describes the opposite task of finding the optimal robot for a given task. Generally, the task is abstracted e.g. as a desired workspace or a desired path or trajectory. To identify the optimal robot, usually different designs have to be compared with respect to the desired properties which makes the design process generally a computationally expensive task. Finally, one or more designs turn out as most favourable. In parallel to the analysis methods, again both discrete as well as continuous methods are available and show differences in the analysis quality and the calculation effort. For the continuous approach the CSP formulation can be used again which is amongst others advantageous in terms of implementation effort. The interchanging of the roles of the variables turns the workspace analysis just into a design task. According to (Merlet, 2005), the design (or synthesis) task can be divided into two separated subtasks:
structure synthesis: This step includes the determination of the topology of the mechanical structure. In particular, the number and type of d.o.f. of the joints and their interconnection is identified.
dimensional synthesis: Here position and orientation of the joints as well as the length of the links is specified.
For the special case of a wire robot, the structure synthesis covers different aspects: While the link topology itself is fixed, one has to choose the number of wires wisely.
Additionally, the concurrence of at least two (in the planar case) or three (in the spatial case) platform connection points may be prudential:
Forward kinematic calculations become much easier (see section 2.3).
The number of design parameters is reduced, which is beneficial in terms of computation time.
The occurence of wire collisions is reduced since wires can intersect in at most one point.
The workspace is comparably large (Fang, 2005).
After completion of the structure synthesis a dimensional synthesis can be performed. For a wire robot this is nothing but the identification of feasible base points. This section is addressed to dimensional synthesis mainly.
Discrete methods are widely used for wire robot design. In (Fattah and Agrawal, 2005) and (Pusey et al., 2004) both the parameter set and an assumed superset of the workspace are discretized. Then for every point on the resulting parameter grid the discretized workspace is computed and its volume is determined by counting the points on the grid fulfilling all workspace conditions. The approaches share the same concept:
Build up an equidistant Grid of the design variables and loop through all parameter sets.
For every parameter set, specify a superset of the workspace and discretize it by an equidistant grid.
Loop through all grid points of step 2. For every point, determine if a valid wire force distribution according to eqn. 25 and 26 exists.
Count all points belonging to the workspace and store the number for every parameter set.
Obtain the maximum volume workspace, i.e., the maximum of all workspace volumes that are counted in step 4, and the associated optimized design variables.
Instead of the volume of the workspace a different optimization criterion can be employed. To increase the practical usability and the robustness of the design, a dexterity criterion is proposed, which uses the condition number of the structure matrix AT. These approaches have two drawbacks. Since the design variables are discretized, every combination of parameters is checked. Hence, this method is computationally intensive. Furthermore, no desired workspace can be guaranteed by the obtained design. Hay and Snyman use a special optimizer instead of a grid of the design variables (Hay and Snyman, 2004), (Hay and Snyman, 2005). Again, in this approach a desired workspace is not guaranteed by the obtained optimal design.
Examining eqn.28, eqn.31 and eqn.32, the roles of the variables can arbitrary be assigned. An imaginable choice is
The winch poses and platform fixation points are the calculation variables. Thus, the calculation delivers robot designs solving the CSP.
The platform coordinates are verification variables. Hence, the workspaces of all resulting robot designs will cover the set given in Xv for the platform coordinates for sure.
Optionally, the exerted external wrench w and desired platform orientations can be set as verification variables to extend the applicability of the emerged designs for certain process wrenches and tasks.
The wire forces fsec are the existence variables.
The suggested choice of variables leads to a CSP, whose solutions are robot designs. Furthermore, each obtained robot can reach every point given in Xv for the platform coordinates with every orientation and wrench given in Xv. Generally, the design task is deemed to be more complicated than the analysis. Here, the methods and formulations are inherited and just adapted to the design problem. Nevertheless, robot design is a computationally intensive task. The use of parallel computations is strongly advised. Solving the CSP is advantageous due to the following reasons:
The workspaces of the resulting designs are guaranteed to have no holes or singularities.
The design process can be extended by a global optimization step.
The interval CSP solver can be effectively parallelized.
Optimization is always performed with respect to a cost function. In industrial application usually the term optimal is used with respect to economic aspects, i.e. costs. In the case of wire robots, the most cost-driving factor are the wire winch units. However, optimizing the number of winches is part of the structure synthesis. Thus, here another cost function has to be chosen. This choice is generally arbitrary. Nevertheless, a reasonable choice is the volume expansion. On one hand, reducing the expansion of the robot saves space within a production facility which reduces costs, on the other hand, the required wire lengths are minimized. In literature, usually the optimization is performed with respect to the size (or volume) of the workspace or the integral of workspace indices over the workspace. This gives finally the robot with optimal (e.g. largest) workspace with respect to some criterion, but it says nothing about its shape and its usability for applications. Thus, here another approach is used (Pott, 2007): Not a maximum size of the workspace is demanded, but the guaranteed enclosure of a predefined domain is desired. The optimization is performed using interval analysis. Let a list L of n boxes of robot designs,e.g. a solution of the according CSP be given. The following algorithm performs the required steps for a minimization (maximization is performed analogously):
Set i = 0 and Fopt = [0,0].
Set i = i + 1. If i > n the algorithm finishes.
Take the i-th element li of L and compute its cost function F(li).
If Sup(F(li)) < Sup(Fopt), set Fopt = F(li).
If Sup(F(li)) < Inf(Fopt) delete all elements of the solution list and initialize it with li. Goto 2.
Store li in the solution list. Goto 2.
If Inf(F(li)) < Sup(Fopt) store li in the solution list.
Discard li and goto 2
For performance reasons the optimization can be included in the CSP Solver. This will reduce computation time drastically since non-optimal designs are discarded at an early stage. An example for the optimization of an 1R2T robot is shown in fig. 11(b). For the upper winches, y-positions are free, for the lower ones, the x-positions are the free optimization parameters.
(a) 1R2T example (b) 1R2T robot optimized for shown desired quadratic workspace.
The Design-to-Workspace method results in manipulators, guaranteed to have a desired workspace. Thus, the manipulator is able to perform every task within this workspace. Nevertheless, from the economic point of view, there is a need for manipulators which perform a specific task in minimum time, with minimum energy consumption or with lowest possible power. A typical industrial application is e.g. the pick-and-place task, moving a load from one point to another. Usually, this task is performed within series production, i.e. it is repeated many times. In such an application the optimal manipulator for sure finishes the job in minimal time with respect to the technical constraints (here, the term optimal is used with respect to minimal time without loss of generality). Thus, the set-up of a specialized (i.e. taskoptimized) manipulator can be profitable. When using classical industrial robots, the freedom to modify the mechanical setup of the robot is very limited. Thus, only the trajectories can be modified and optimized with respect to the task. Due to the modular design of a wire robot, the task-specific optimization can be seperated into two tasks:
Optimization of the robot: within all suitable designs, the robot which performs the task in shortest time is chosen.
Optimization of the trajectory: within all possible trajectories, the trajectory which connects the points in shortest time is chosen. The concepts needed for this step are partly explained in (Bianco and Piazzi, 2001b),(Bianco and Piazzi, 2001a) and (Merlet, 1994).
By treating this task as a CSP, both claims can be optimized at the same time. In particular, the final result contains the robot which is able to perform the task quickest and the corresponding trajectory description. To perform an optimization of the wire robot and the trajectory simultaneously, the latter is planned first. Afterwards it is checked whether the complete trajectory belongs to the workspace. The robot designer may provide a predefined trajectory or leave this up to the optimizer. The parameters of the trajectory are therefore either fixed or calculation variables. Hence, the CSP looks the same as in eqn.31 and eqn.32 except the previous trajectory generation. For integrated optimization, the variables are assigned as follows. Note, that also a separate optimization of robot and trajectory is possible:
Robot optimization
The robot base is described by the positions of the winches. To optimize the robot, the winches can be moved. Therefore, bi are calculation variables
The end effector is described by the positions of the platform anchor points pi. To optimize the robot, these points can be moved on the platform. Therefore, pi are calculation variables
Trajectory optimization
The path is described by a polynomial of fourth order without loss of generality. Besides the start and end poses, also the velocities are predefined. This leaves one free parameter, e.g. the start acceleration for translational d.o.f. or the orientation at half travel time for rotational d.o.f.. These can be set as calculation variables.
To describe the trajectory, additionally the travel time T has to be defined. To calculate the minimum time, T is a calculation variable.
For the whole trajectory, a path parameter t is assigned. Usually, it is normalized between zero and one. Since the whole trajectory shall betraced for validity, t is a verification variable
Optionally, the exerted external wrenches w can be set as verification variables. Note, that within the trajectory verification the dynamics of the robot are taken into account by adding the inertia loads resulting from the calculated accelerations to the platform loads w. The example in fig. 12(b) shows the result of an optimization for a point-to-point (PTP) movement. A n = 3 d.o.f. wire robot with m = 4 wires is considered (see fig. 12(a)). It consists of a bar-shaped platform of 0.1m length, connected by four winches to the base frame. Free optimization parameters were the y-position of the upper right winch, the travel time and the intermediate acceleration of the rotation angle at T = 0.5.
(a) 1R2T example (b) 1R2T robot optimized for shown desired PTP trajectory
In this chapter, the analysis and design of wire robots was discussed. The required basics like kinematics and the force equilibrium - which is the one of the main workspace criteria - were introduced as well as serveral classification approaches. The analysis of wire robots was described as a CSP task which can be solved by interval analysis. Besides reliable results, the same CSP can be used for robot design by a variable exchange, which is generally a challenging problem. In addition to this continuous approach, also the more straightforward discrete methods are shortly introduced. The next chapter is dedicated to the application and control of wire robots. Therefore, the dynamical description as well as different methods to calculate a force distribution for a given pose and platform wrench are presented. Based on this, some control concepts are described. The use of wire robots for several fields of application is demonstrated by a number of examples.
This work is supported by the German Research Council (Deutsche Forschungsgemeinschaft) under HI370/24-1, HI370/19-3 and SCHR1176/1-2. The authors would like to thank Martin Langhammer for contributing the figure design.
The antimicrobial potential of silver (Ag) and Ag-based solutions has long been established, however, their application was considered obsolete upon the discovery of antibiotics [1, 2]. In recent years, the developing crisis of multi-drug resistant pathogenic infections has led to the resurgence in this metal, however, with the use of nanotechnology to generate its nanoparticle form. For this reason, tremendous efforts have been extended in nanotechnology, particularly in the development of green synthetic strategies for silver nanoparticle (AgNPs) production to facilitate their use in antimicrobial therapeutic applications [3].
The interest in silver nanoparticles (AgNPs) as an alternative to current antibiotics has increased profoundly over the last few years. This is owed to the cumulative incidence of microbial drug-resistant infections and the lack of appropriate treatment thereof [4]. The World Health Organisation report of 2014 highlighted the probability of a post-antibiotic era in which common infections and minor injuries could potentially result in fatalities [5]. Accordingly, concerted efforts have been extended by global pharmaceuticals to formulate new or improved antibiotics. However, despite high research cost-intensive investment in the last decade or so only two new classes of antibiotics have been introduced into the market [6, 7]. The imperative need for the uncovering of novel antimicrobial scaffolds has led to the resurgence of silver, however, in its nano-particulate form [8].
The antimicrobial activities of AgNPs are well established and currently researchers are striving to develop greener synthetic strategies for their production [1, 9]. The use of nanotechnology for the synthesis of AgNPs from environmentally compatible biomaterials is evolving into an important branch of science and technology [10]. To this end, a variety of biological extracts have been explored for the bottom-up synthesis of AgNPs [11]. However, there is an ongoing search to identify novel capping structures to produce AgNPs with increased bio-efficacies. In this context, this chapter points to highlight the use of plants as an alternative green technology for nanoparticle synthesis and their biomedical applications as potential biofactories for antibacterial, antifungal and anti-cancer agents.
Established technologies for AgNP synthesis and other metal preparations can be categorised distinctly into two approaches, namely: “top to bottom”, which is normally employed by physicists and “bottom to up”, a construction favourite of chemists [12, 13]. Both approaches converge at the nanodimension but vary drastically in the synthetic technology. “Top to bottom” approaches apply various physical methods such as grinding, milling, sputtering, evaporation-condensation and thermal/laser ablation to break down bulk solid materials to their nanoparticulate form. “Bottom to up” approaches entail various chemical and biological methods to synthesise nanoparticles by the self-assembly of atoms such as Ag+ into nuclei that further develop into nano-sized particles [9].
Important physical “top to bottom” methods for nanoparticle preparation include evaporation-condensation and laser ablation techniques [14]. Evaporation-condensation applies a tube furnace at atmospheric temperature wherein primary material (metal Ag) contained in a boat; is centred in the furnace and vaporised into a carrier gas [9]. Several inadequacies have been identified with this technique, for example, the furnace occupies a large space, requires high energy input whilst raising the environmental temperature around the source material and requires long durations to achieve thermal stability. Additionally, a major drawback to this type of synthesis is the resulting imperfections in the surface structure of the derived nanoparticles which can ultimately alter their physical properties [9, 15]. In laser ablation, irradiation is used to remove material from a bulk metal in solution. The efficacy of this technique and characteristics of nascent particles is largely dependent on a number of parameters including the wavelength of the laser, duration of laser pulses, laser fluence, ablation duration and the effective liquid medium with or without surfactants [16, 17]. An important advantage of laser ablation for AgNP preparation is the absence of chemicals in solution which could potentially contaminate the nanoparticle preparation [18].
Regarding “bottom to up” approaches, wet chemical reduction is the most frequently practiced method for nanoparticle preparation [15] although, several other methods have been reported [19, 20, 21, 22]. As the name suggests, wet chemical reduction involves the reduction of a metal salt precursor in aqueous or organic solution. Various organic and inorganic compounds successfully utilised as reducing agents in the synthesis of AgNPs include: ascorbate; borohydride; citrate; elemental hydrogen; formaldehyde; N-N-dimethyl formamide (DMF); Tollen’s reagent; and polyethylene glycol blocks [15, 23, 24]. In addition to reducing agents, protective stabilising agents are also included in the reaction solution to prevent agglomeration of nascent nanoparticles [25, 26]. With stability achieved, this method can be useful to produce high nanoparticle yields with low preparation costs [27]. However, the efficacy of this method is challenged by the potential contamination of nascent nanoparticles by precursor chemicals, the use of toxic solvents and the generation of hazardous by-products [13, 28].
Evidently, the aforementioned physical and chemical methods have certain limitations that restrict their use in the preparation of nanoparticles for biological applications [29]. In this regard, concerted efforts have been extended to develop nanoparticle synthetic strategies that are environmentally sound. Essentially, this would entail the use of benign, biotechnological tools and has given rise to the concept of green technology. This technology can best be described as the use of biological routes such as plants and microorganisms or their byproducts in the synthesis of nanoparticles [29, 30, 31]. These bio-inspired methods (Figure 1) are not only environmentally welcoming but are cost effective and can be easily up-scaled for large productions [32].
Different approaches for AgNP synthesis. Adapted from [9, 33].
As previously eluded, biological approaches for AgNP synthesis employ the use of living organisms or their extracts as capping/reducing agents in a synthetic reaction. To date, a variety of biological entities have been explored for their Ag+ reducing abilities and include viruses, bacteria, plants, algae, fungi, yeast and mammalian cells [11, 13, 34, 35, 36]. Biological synthesis can be divided into two strategies, specifically: bioreduction and biosorption. Bioreduction occurs when metal ions undergo chemical reduction into biologically stable complexes. Many organisms have displayed dissimilatory metal reduction involving the coupling of reduction with oxidation of an enzyme. The resulting stable, inert nanoparticles can then be safely extracted from the reaction mixture. Alternatively, biosorption involves the attachment of metal ions onto an organism itself, such as on the cell wall. Various bacteria, fungi and plant species express peptides or possess modified cell wall structures that are capable of binding metal ions, thereby forming stable complexes in the form of nanoparticles [36].
In this review, the use of plant and bacterial biological material for AgNP synthesis will be discussed. For a review on the use of alternative biological entities as AgNP factories, studies by the following authors are recommended [11, 36, 37].
Plants have shown the capacity to hyper-accumulate metals as a means to protect themselves from insects and herbivores. This observation has paved way for the technology known as phytoextraction, wherein plants are employed to extract minerals from various groundwater and soil sediments. Major applications of phytoextraction include the mining of precious metals from unfeasible ground sites (phytomining), stabilisation or recovery of non-naturally occurring contaminants (phytoremediation) and the addition of essential metals to growing crops. Interestingly, studies have unveiled that metals accumulated by the plant are usually deposited in the form of nanoparticles. This has stimulated interest for the use of plants as factories for nanoparticle synthesis [35]. Whole plants have been explored for the synthesis of nanoparticles when grown on the appropriate metal enriched substrates. Species such as Brassica juncae (mustard greens) and Medicago sativa (alfalfa) have demonstrated the ability to accumulate AgNPs. For example, 50 nm sized AgNPs, at a high yield (13.6% of total plant weight) were reported for M. sativa when grown on silver nitrate (AgNO3) [38]. Additionally, icosahedral gold nanoparticles of 4 nm size were observed in M. sativa and semi-spherical copper nanoparticles of 2 nm size were observed in Iris pseudacorus when the plants were grown on gold and copper salt enriched substrates, respectively [39, 40].
Although whole plants can potentially serve as factories for nanoparticle synthesis, several disadvantages have been identified with this technology especially when up-scaling for industrial applications. For example, physical attributes of nanoparticles such as size and shape vary upon the localisation of the particles in the plant due to the differences in metal ion content in different plant tissues and the possibility of nanoparticle movement and penetration [39]. This heterogeneity of important bioactivity-determinants such as size and shape [41, 42] limit the use of these nanoparticles and especially in applications where mono-dispersed nanoparticle preparations are required. Furthermore, recovery of nanoparticles from living plants entails laborious extraction, isolation and purification procedures and may potentially result in low yields [35].
The use of plant broths/extracts in nanoparticle synthesis was introduced by Shankar et al., (2003). In their study, compounds responsible for the reduction of metal ions were extracted and used as reducing agents in a synthetic reaction mixture, resulting in the extracellular production of nanoparticles [43]. This strategy tentatively offers several advantages compared to the use of whole plants. For example, nanoparticle formation occurs considerably faster as opposed to whole plants which require diffusion of metal ions throughout the plant body. Additionally, the use of extracts would be more economical due to the ease of purification [35].
This in vitro approach has been actively developed and applied to a variety of plant flora for the synthesis of AgNPs [28]. Various organ extracts: stem, root, leaf, bark, fruit and fruit peel have demonstrated the ability to reduce Ag+. Particularly, biomolecules (Figure 2) such as proteins, amino acids, enzymes, polysaccharides, alkaloids, tannins, phenolics, saponins, terpenoids and vitamins present in the extracts act as both reducing and stabilising agents [9].
Major plant metabolites involved in the synthesis of metal nanoparticles: (A)-terpenoids (eugenol); (B & C)-flavonoids (luteolin, quercetin); (D)-a reducing hexose with the open chain form; (E & F)-amino acids (tryptophan, tyrosine). Adapted from [35].
Terpenoids are a class of diverse organic polymers manufactured in plants from five-carbon isoprene units and display strong antioxidant activities. In a previous study by Shankar et al., involving gold nanoparticle synthesis from geranium leaf extracts, it was suggested that these polymers were actively involved in the reduction of gold ions into stable nanoparticles [44]. Later Singh et al. reported that eugenol, the main terpenoid found in Szyygium aromaticum (clove), played an important role in reducing AgNO3 and HAuCL4. The Fourier transform infrared (FTIR) spectroscopy analysis of their study suggests that the dissociation of the proton from the OH group in eugenol leads to the formation of intermediate resonance structures which can undergo further oxidation. This latter reaction may be coupled to the reduction of Ag+ and subsequent formation of stable AgNPs [45].
Flavonoids are made up of a large group of polyphenolic compounds containing various classes such as anthocyanins, isoflavonoids, flavonols, chalcones, flavones and flavanones. There are several functional groups present on flavonoid compounds that can participate in nanoparticle formation. It has been hypothesised that the tautomerization of flavonoids from the enol to keto form releases a reactive hydrogen atom that can participate in the reduction of metal ions. For example, studies involving AgNP synthesis from Ocimum sanctum extracts indicate that synthesis is likely to be the result of tautomerization of the flavonoids luteolin and rosmarinic acid [46]. Additionally, some flavonoids can chelate metal ions with their carbonyl groups or π-electron. Quercetin is an example of a flavonoid with strong chelating activity [35]. These mechanisms may explain the prevalence of flavonoid groups adsorbed on to the surface of AgNPs derived in previous studies [47, 48]. Further indication of flavonoid involvement in nanoparticle synthesis is provided by a study using Lawsonia inermis, in which the flavonoid apiin was extracted and successfully employed in the synthesis of gold and Ag nanoparticles [49].
Sugars contained in plant extracts are also capable of inducing nanoparticle formation. It is known that monosaccharides in the linear form containing an aldehyde (e.g. glucose), are capable reducing agents [35]. Monosaccharides harbouring a keto-group may act as antioxidants upon tautomeric transformation from a ketone to an aldehyde (e.g. fructose). In this regard, glucose is reportedly more efficient at metal ion reduction than fructose due to the kinetics of tautomerism from a ketone to an aldehyde which limits the reducing potential of fructose. Disaccharides and polysaccharides may also participate in the reduction of metal ions however, this is largely dependent on the ability of their monosaccharide components to take on an open chain configuration within an oligomer. Examples include lactose and maltose. In contrast, sucrose is unable to participate in metal ion reduction because the linkage of its glucose and fructose monomers restrict the formation of open chains. However, when sucrose was placed in tetrachloroauric and tetrachloroplatinic acids, nanoparticle formation proceeded [50]. This may be due to the acidic hydrolysis of sucrose yielding glucose and fructose. In general, it is suggested that nanoparticle formation by sugars occurs by the oxidation of an aldehyde group into a carbonyl group which subsequently leads to the reduction of metal ions and nanoparticle formation [44].
FTIR analysis of plant derived metal nanoparticles have revealed the presence of proteins on their surface, suggesting that proteins may also possess metal ion reducing ability. However, amino acids have displayed differences in their potential for metal ion reducing and binding efficiencies. For example, lysine, cysteine, arginine and methionine have been shown to bind Ag+. In a separate study, aspartate was used to reduce tetrachloroauric acid forming nanoparticles, whilst valine and lysine did not possess this ability. Amino acids capable of binding metal ions are thought to do so through their amino or carboxyl groups or through side chain groups: carboxyl groups of aspartic and glutamic acid, imidazole ring of histidine, thiol of cysteine, thioether of methionine, hydroxyl group of serine; threonine and tyrosine, carbonyl groups of asparagine and glutamine [35].
Linkage of amino acids in a peptide chain may also affect the ability of individual amino acids to bind and reduce metal ions. For example, the R-carbon of amines and carboxylic acids in a peptide bond are inaccessible for association with metal ions. However, the free side chains of individual amino acids can still participate in binding and reduction of metal ions although, this is largely dependent on the amino acid sequence. Tan et al. demonstrated that synthesised peptides derived from amino acids with strong binding abilities and high reducing activities displayed lower reduction than expected [51]. A previous study suggested that protein molecules capable of nanoparticle formation display a strong attraction of metal ions to the regions on the molecule responsible for reduction however, their chelating activity is limited [52]. It was also suggested that the amino acid sequence of a protein can influence the size, shape and yield of derived nanoparticles. For example, the synthetic peptide GASLWWSEKL was found to rapidly reduce metal ions forming a large number of small nanoparticles (˂10 nm), however, replacement of the N- and C- terminal residues forming the peptide SEKLWWGASL led to slower reduction and formation of larger nanospheres and nanotriangles (40 nm). These findings seemingly suggest that peptides and proteins present in plant extracts probably play a vital role in determining nanoparticle size and shape and potentially affect the overall yield of the nanoparticles [51].
There exists a vast array of literature pertaining to the use of bacteria as factories for nanoparticle synthesis [53, 54]. Bacteria have a marked advantage over other microbial systems such as fungi due to their abundance, rapid growth rate, cheap cultivation and the relative ease of their manipulation [55]. Their ubiquitous nature has led to their exposure and proliferation in many environmental extremes and ultimately depends on the natural defence mechanisms of these microorganisms to resist the effects posed by environmental stresses [56]. Bacteria have demonstrated these defence mechanisms in a few non-optimal growth conditions including environments contaminated with metal ions.
AgNP synthesis by bacteria can occur intracellularly or by the use of their extracts [53]. Several studies have reported intracellular synthesis by a variety of bacterial species and as similarly reported for the use of whole plants, this technology is associated with long duration periods for nanoparticle synthesis. For example, Pugazhenthiran et al. reported an incubation time of 7 days for AgNP synthesis from Bacillus sp. [57]. Kalimuthu et al. reported a reaction time of 24 hours for AgNP synthesis by Bacillus licheniformis [58]. Although this reaction time was more industrially significant, the authors reported an additional extraction to acquire the derived nanoparticles. Synthesis of AgNPs by the use of bacterial cell free supernatant (CFS) extracts was reported by Shahverdi et al., (2007). Interestingly, nanoparticle synthesis occurred within five minutes of Ag+ coming into contact with the CFS [59]. Thus, this method presents the greatest potential for industrial production of AgNPs from bacteria. Several other studies have reported on the production of AgNPs from bacterial CFS extracts but not at the previously stated formation rate [60, 61]. This seemingly suggests that bacterial extracts differ in their metal ion reducing abilities and may require an external energy source to accelerate nanoparticle formation.
As previously stated, metal nanoparticle synthesis in bacteria may potentially occur through resistance mechanisms attained by these organisms to overcome the toxic effects of metals. These strategies include redox state changes, efflux systems, intracellular precipitation, metal accumulation and extracellular formation of complexes (Figure 3) [56]. In an early study, Slawson et al. observed that the Ag resistant strain Pseudomonas stutzeri AG259, was capable of accumulating AgNPs (35–46 nm) within its periplasmic space. The formation of these nanoparticles was thought to have occurred by a mechanism involving the NADH-dependent reductase enzyme which undergoes oxidation to form NAD+. The lost free electron may potentially reduce Ag+ to AgNPs [62]. Later, He et al. reported that the NADH-dependent reductase enzyme may similarly participate in the extracellular formation of gold nanoparticles by the bacterium Rhodopseudomonas capsulata [63]. Other studies have reported nanoparticle formation without the use of biological enzymes. Non-enzymatic nanoparticle synthesis by a Corynebacterium sp. was reported by Sneha et al. [64]. Organic functional groups present at the cell wall were thought to induce metal ion reduction [64]. Sintubin et al. proposed a two-step mechanism for AgNP formation by several lactic acid bacteria, involving biosorption of Ag+ on the cell wall which is coupled to the subsequent reduction of these ions to form the nanoparticles [65]. Parikh et al. identified a gene homologue in a Ag-resistant Morganella strain with a 99% nucleotide sequence similarity to a periplasmic Ag-binding protein-encoding gene [66]. Johnston et al. further reported the production of a small non-ribosomal peptide, delftibactin by Delftia acidovorans which they believed to be associated with a resistance mechanism. By producing inert gold nanoparticles bound to delftibactin, gold ions no longer caused toxicity to the cells [67].
Metabolites and mechanisms involved in AgNP synthesis in bacteria: (a)-uptake of Ag+ and activation of reduction machinery; (b)-electron shuttle system involving various cofactors and enzymes; (c & d)- intra or extracellular localisation of AgNPs; (e)-electrostatic interaction between Ag+ and cell wall peptides/proteins & (f)-extracellular reduction by enzymes or other metabolites released in solution. Adapted from [53].
There are three main phases in the synthesis of metal nanoparticles from plants and plant extracts. Initially, an activation phase takes place during which metal ions are reduced from mono or divalent oxidation states to zero-valent states, followed by nucleation of the reduced atoms. This step is immediately followed by a growth phase where small neighbouring nanoparticles coalesce into larger particles with greater thermodynamic stability while further biological reduction occurs. As growth proceeds nanoparticles aggregate to form various shapes such as: cubes, spheres, triangles, hexagons, pentagons, rods and wires [68]. Lastly, a termination phase follows in which nanoparticles acquire the most energetically favourable conformation, which ultimately determines the final shape of the particles (Figure 4) [69]. This step is largely influenced by the ability of the plant extract to stabilise the resulting nanoparticles. For example, the high surface energy of nanotriangles results in their decreased stability. Such nanoparticles would then acquire a more stable morphology such as a truncated triangle to minimise Gibbs free energy unless the stability is supported by the given extracts. It can be tentatively suggested that a similar mechanism occurs by the use of bacterial extracts since proteins and metabolites may also participate in Ag+ reduction as previously stated.
Schematic representation of nanoparticle synthesis using a plant extract. Adapted from [35].
Several controlling factors affect the synthesis and morphology of derived nanoparticles. Several researchers have associated these variations with the choice of adsorbate and catalyst used in the synthetic process [29, 70]. However, reaction parameters have also been shown to strongly affect the synthesis of nanoparticles from biological extracts.
Studies have revealed that the pH of a reaction solution strongly influences the formation of the produced nanoparticles. Variances in reaction pH tend to induce variability in the shape and size of the produced nanoparticles. Lower acidic pH values tend to produce larger particles when compared to higher pH values. In a study employing Avena sativa (oat) biomass for the production of gold nanoparticles, larger particles (25–85 nm) where formed at pH 2 whilst smaller particles (5–20 nm) were formed at pH 3 and 4 [71]. The researchers suggested that at pH 2, fewer functional groups were available for particle nucleation resulting in aggregation of the particles. A similar finding was observed in the synthesis of gold nanoparticles from the bacterium Rhodopseudomonas capsulate. At an increased pH of 7, spherical particles in the range of 10–20 nm in size were observed. In contrast, lowering the reaction pH to 4 resulted in the formation of nanoplates [63].
Temperature is an important factor in any synthesis. With respect to nanoparticle formulation with the use of biological entities, temperature elevation has demonstrated catalytic behaviour by increasing the reaction rate and efficiency of nanoparticle formation. For example, a study on the influence of reaction temperature in the synthesis of AgNPs from neem leaf extracts suggested that temperature elevation (10–50°C) was correlated with enhanced reduction of Ag+ [72]. It was also noted that smaller sized AgNPs were produced at 50°C, similar to the finding of Kaviya et al. in the production of AgNPs from Citrus sinensis peel extracts using varying temperatures [73]. Similarly, this trend was observed in the production of AgNPs from the spent culture supernatants of Escherichia coli [61]. The authors tentatively suggested that the increased reaction rate might be because of temperature on a key enzyme participating in nanoparticle synthesis. However, the study importantly revealed that temperature elevation above 60°C contrastingly favoured the production of larger sized particles. The reason for this observation was reported as follows: at high temperatures, kinetic energy of the molecules increase resulting in rapid reduction of Ag+ (facilitating reduction and nucleation), to the detriment of secondary reduction on the surface of nascent particles in the growth phase. However, higher temperatures beyond the optimum are thought to increase the growth of the crystal around the nucleus, resulting in the production of larger particles [48, 61].
Temperature has also been demonstrated to affect the structural form of nanoparticles. For example, AgNP synthesis using Cassia fistula extracts resulted in the formation of Ag nanoribbons at room temperature whilst spherical AgNPs were formed at temperatures above 60°C [74]. High temperatures in the study were thought to alter the interaction of plant biomolecules with the faces of Ag, inhibiting the coalescence of adjacent nanoparticles.
Sunlight irradiation, a recently reported primary energy source for nanoparticle formation, has been observed to derive AgNPs with desired physical attributes. Recent studies on sunlight driven AgNP synthesis using Allium sativum (garlic extract) and Andrachnea chordifolia ethanol leaf extract revealed that sunlight rapidly enhanced nanoparticle formation to produce spherical AgNPs with average diameters of 7.3 nm and 3.4 nm, respectively [75, 76]. In addition, this use of sunlight has also been used in AgNP synthesis from Bacillus amyloliquefaciens CFS to produce circular and triangular crystalline AgNPs with an average diameter of 14.6 nm [77].
A variety of literature reports on the synthesis of AgNPs with differing morphologies. Understanding the effects of these morphological characteristics on bioactivity is therefore an important consideration when deriving nanoparticles for therapeutic purposes. Characteristically, AgNPs are small (1–100 nm) and therefore possess a large surface area that facilitates their interaction with bacterial cell membranes [41, 78]. However, it has been suggested that within this confined size range, AgNPs present a size-dependent inhibition spectrum. Martinez-Castanon et al. reported that AgNPs of 7 nm in size had minimum inhibitory concentration (MIC) values of 6.25 μg ml−1 and 7.5 μg ml−1 for E. coli and Staphylococcus aureus, respectively. In contrast, larger nanoparticles (29 nm) capped with the same reducing agent displayed higher MIC values for the respective strains [79]. These results are in accordance with other studies that report nanoparticles of ˂ 10 nm in size display improved bactericidal activities [42, 80].
The interaction of AgNPs of varying shapes with E. coli cells has unveiled that shape plays an important factor in bioactivity. Pal et al. reported that at a low Ag content of 1 μg, truncated triangular nanoparticles showed nearly complete inhibition of E. coli cells, whilst spherical nanoparticles with a total silver content above 12.5 μg displayed a reduction in colony forming units. Rod-shaped particles and AgNO3 presented inferior activities when compared to truncated triangular and spherically shaped AgNPs [41].
Considering these factors and the aforementioned factors affecting synthesis of nanoparticles, it can tentatively be suggested that the fine tuning of reaction parameters such as pH or temperature may be applied in producing AgNPs with these desired physical attributes. However, the use of sunlight irradiation provides a promising alternative in this regard.
There exists an abundance of literature reporting on antimicrobial activities of biologically derived AgNPs [81, 82, 83, 84]. Most of these studies utilise the disc diffusion assay [85] or agar well diffusion assay [86] to establish inhibitory effects. Positive indication of inhibitory activities are visualised by zones of inhibition on a microbial lawn. Veersamy et al. reported zones of inhibition of S. aureus and E. coli to be 15 mm and 20 mm respectively for AgNPs (20 μg ml−1) derived from mangosteen leaf extracts [48]. Similarly, Logeswari et al. reported zones of inhibition of AgNPs synthesised from various plant extracts against several bacterial strains [81]. Although diffusion techniques are preferred amongst researchers, they seem to be labour-intensive. In addition, many researchers do not establish the initial concentration of AgNP solution prior to antimicrobial evaluation [82, 87]. Such disparities make comparison between published data inapplicable [88].
Determination of minimum inhibitory concentration (MIC) by the broth microdilution or macrodilution method [89, 90] is easy to access and provides accurate information with respect to microbial susceptibility. Moreover, MIC values are reported in various concentration units such as μg ml−1, μg l−1 or ppm thereby facilitating comparison between publications [53]. These methods are therefore attractive for AgNP bioactivity analysis. Furthermore, determination of MICs is an important consideration for any therapeutic agent in development to assess their toxicity at the specified concentration range. As previously mentioned, the antimicrobial effects of AgNPs are well established. However, a relatively confined amount of studies has been conducted to elucidate their mechanisms of antimicrobial action. These mechanisms are poorly understood and have failed to achieve consensus amongst researchers. Despite this, three common mechanisms of bactericidal activity have been proposed by various studies. These include the uptake of Ag+ (1), generation of reactive oxygen species (ROS) (2) and cell membrane disruption (3) (Figure 5) [91].
Interactions of AgNPs with bacterial cells: (1) release of Ag+ and generation of ROS; (2) interaction with cell membrane proteins; (3) accumulation in cell membrane and disruption of permeability; (4) entry into the cell and release of Ag+, leading to generation of ROS and damage of cellular DNA. In turn, generated ROS may affect DNA, cell membrane and membrane proteins whilst released Ag+ may affect cell membrane proteins and DNA. Adapted from [91].
Since Ag+ are known to possess antibacterial activities, their release from AgNPs may potentially aid to the bioactivity of the nanoparticles. It is therefore fitting to consider the mechanistic action of Ag+ on bacterial cells.
The NADH–ubiquinone reductase has been established as one of the major targets for Ag+. Specifically, the binding of Ag+ to this enzyme may be responsible for their bactericidal effect even at minute concentrations [92]. Later, Dibrov et al. reported the binding of Ag+ to transport proteins leads to the leakage of protons and ultimately induces the collapse of the proton motive force [93]. Such interactions with transport proteins may be attributed to the strong affinity of Ag+ to thiol groups found on cysteine residues of these molecules [94]. Ag+ has also been reported to inhibit phosphate uptake and additionally causes an efflux of intracellular phosphate [95]. It has also been hypothesised that the antimicrobial effect of Ag+ is correlated with the disruption of DNA replication. DNA molecules in a relaxed conformation can be replicated effectively. However, when Ag+ are present in bacterial cells, DNA molecules enter a condensed form and replicating ability diminishes which ultimately leads to cell death [8].
The exposure of bacterial cells to AgNPs leads to the generation of ROS [96]. Naturally, ROS are metabolic by-products of respiring beings. Whist low levels of these species are skilfully controlled by various antioxidant defence mechanisms, high levels of ROS results in oxidative stress which is detrimental to any living organism. Metals can serve as catalysts and produce ROS in an oxygen containing environment [97]. AgNPs are therefore likely to catalyse reactions with oxygen leading to the production of excess free radicals. Kim et al. demonstrated the generation of free radicals from AgNPs by means of spin resonance measurements. Toxicity of AgNPs and AgNO3 diminished upon addition of an antioxidant suggesting that the mechanism of action against bacterial strains was associated with the formation of free radicals from AgNPs. The generation of excess free radicals attack membrane lipids resulting in the breakdown of the membrane and cause damage to DNA [1].
The release of Ag+ from nanoparticles attached to the membrane and nanoparticles inside the cell also play a role in the generation of ROS. Ag+ released on the membrane are capable of ROS generation by acting as electron acceptors whilst those present inside the cell more likely to interact with thiol groups of respiratory chain enzymes as previously stated, or scavenging superoxide dismutase enzymes [98]. The effect of ROS scavengers on E. coli cells was reported by Inoue et al.. Specifically, ROS such as superoxide anions, hydroxyl radicals, hydrogen peroxide and singlet oxygen contributed to the bactericidal activity against E. coli [99]. According to literature, the bactericidal effect of AgNPs may also be the result of damage to the outer membrane of bacterial cells. Previous studies by Sondi and Salopek-Sondi suggested that treatment of E. coli cells with AgNPs induced changes in the membrane morphology (Figure 6a). This resulted in increased membrane permeability and shifts in normal transport through the plasma membrane [100]. Morones et al. hypothesised that these mechanisms could explain the number of nanoparticles found inside E. coli cells (Figure 6b). AgNPs with oxidised surfaces were also reported to induce the formation of holes on the surface of E. coli cells and portions of the cellular surface were observed to be eaten away [101]. The attachment and penetration of AgNPs has also been observed in P. aeruginosa (Figure 6c), V. cholera and S. typhus [80].
Transmission electron micrographs of (a) E. coli cell after 1 h treatment with 50 μg cm−3 AgNPs; (b) E. coli cell after 30 min treatment with 100 μg ml−1 AgNPs (c) P. aeruginosa cells after 30 min treatment with 100 μg ml−1 AgNPs [80, 100].
The mechanism of AgNP adhesion and penetration of bacterial cell membranes remains to be elucidated. Literature reports indicate that electrostatic interactions between positively charged particles and negatively charged cell membranes is essential for the bioactivity of these particles [102, 103]. However, this strategy does not validate the adhesion and penetration abilities of negatively charged nanoparticles [104]. The researchers argued that although the particles were negatively charged, interactions between the particles and building elements of the membrane are likely to have occurred causing structural changes and degradation of the membrane. Morones et al. proposed that the interaction of AgNPs and bacterial membranes could be attributed to the strong affinity of the particles to sulphur containing proteins present on the membrane [80]. These interactions are thought to be conserved in the interaction of Ag+ and thiol groups on respiratory enzymes and transport proteins [80, 91].
Sondi and Salopek-Sondi [104] further reported that damage to E. coli cell membranes might also occur due to the incorporation of AgNPs into their membrane structure. Scanning electron microscopy revealed the formation of “pits” on the surface of the membrane [100]. Similar findings were observed by [102]. Amro et al. [109] additionally reported the formation of irregularly shaped “pits” on the outer membrane of E. coli cells through the progressive release of lipopolysaccharide molecules. This release of LPS molecules was induced by metal depletion in the cells [105]. A membrane with such morphological changes would display a high increase in permeability, rendering the cell incapable of regulating proper transport through the membrane as previously described.
Although these studies have been conducted on Gram-negative bacteria, AgNPs have also been reported to exert inhibitory activities against Gram-positive bacteria which differ from their counterparts based on differences in cell wall structure [106]. It can be tentatively suggested that AgNPs may form interactions with Gram-positive bacteria through surface proteins present on the cell wall. Once penetrated, the mechanisms of bacterial activity are conserved with that of Gram-negative bacteria.
A relatively confined amount of literature focuses on the mechanisms of antifungal activity exerted by AgNPs. However, based on the studies that have been reported, it seems that inhibition of fungal growth by AgNPs may be the result of damage to fungal cellular membranes. Kim et al. demonstrated the effect of AgNPs on Candida albicans. Transmission electron microscopy (TEM) analysis revealed that the treatment of cells with AgNPs lead to the formation of “pits” on the cell membrane which ultimately disrupts membrane potential [107]. A similar finding was made by Nasrollahi et al. who reported that AgNP incubation with C. albicans led to damage of the cell membrane [108]. Endo et al. reported that disruption of membrane integrity inhibits the normal budding process of daughter cells. Therefore, the authors suggested that AgNPs exert their inhibitory activity by inhibiting the budding of daughter cells due to the destruction of the cell membrane [109].
AgNPs may also disrupt antioxidant defences in fungal cells. Eukaryotic cell studies suggest that AgNPs directly interact with gluthathione, gluthathione reductase or enzymes responsible for maintaining proper levels of gluthathione [110]. With respect to fungal cells, it has been hypothesised that Ag+ largely affect the function of membrane bound enzymes such as those in the respiratory chain. It has also been reported that exposure of fungal cells to Ag+ led to the loss of DNA replication ability. This results in the deactivation of ribosomal subunit protein expression and synthesis of non-functional enzymes and cellular proteins [111].
From these findings it can be tentatively suggested that bactericidal mechanisms of AgNPs are conserved in their inhibition of fungal cells. In summary, AgNPs exert their antimicrobial effects by releasing Ag+, disrupting the cell membrane/wall, generating ROS and inhibiting proper DNA replication.
The unique physico-chemical and biological properties of AgNPs have extremely promising industrial and medical applications, as previously mentioned. However, there exists a dearth of knowledge regarding the effects of prolonged exposures to nanoparticles on human health and the environment [112]. It is therefore imperative to establish the in vitro and in vivo cytotoxic effect of AgNPs in mind for therapeutic purposes.
Human contact with nanoparticles occurs in the form of intravenous injection, oral administration, inhalation and dermal contact [113]. Injection of AgNPs in vivo results in short circulation times and broad tissue distribution. Target sites often include the liver (main target), spleen, lungs and kidneys [114]. Inhalation studies suggest that AgNPs become deposited in the olfactory mucosa and olfactory nerves which can potentially induce impairment and dysfunction of brain cells [115] in addition to immunotoxicity [116]. With regard to oral administration, migration of AgNPs to the gastrointestinal tract promotes dissolution of the particles which subsequently releases Ag+ [117]. A recent study on oral exposure to Ag+ indicated that these ions interact with sulphur leading to the formation of sulphur containing Ag granules in the intestinal epithelium [118]. The authors suggested that during intestinal digestion, Ag+ give rise to particle formation, possibly in the form of Ag2S or AgCl salt. They further added that this formation might influence their uptake and reduce the toxic effects of Ag+, however the effects of Ag salts on the intestine are yet to be elucidated [118, 119]. Reports on the exposure of workers to low doses of Ag dust indicated no significant changes in health status.
Many researchers have demonstrated the cytotoxic effects of AgNPs in vitro, however there is still a lack of consistent and reliable data amongst publications. For example, in a recent review, Kim and Ryu (2013) attributed oxidative stress, apoptosis and genotoxicity to be the main in vitro outcome of AgNP exposure [120]. Later, Gliga et al. identified a major drawback of this review, highlighting that the AgNPs were different in each study, i.e. synthesised by different techniques, of varying size distributions and coatings, tested on different cell lines under different cell culture conditions and often without the use of appropriate controls [121]. Additionally, Hackenberg et al. reported cytotoxicity of human mesenchymal stem cells at a concentration of 10 μg ml−1 AgNPs (˂50 nm), whereas Samberg et al.reported no toxicity of progenitor human adipose-derived stem cells at concentrations up to 100 μg ml−1 AgNPs (10–20 nm) [122, 123]. To determine the effect of size on cytotoxicity, Liu et al. compared the cytotoxicity of AgNPs ranging in size from 5 to 50 nm on four different cell lines (A549, HepG2, MCF-7 and CGC-7901) and reported that 5 nm AgNPs were most toxic [124]. On the contrary, Kim et al. reported the enhanced release of lactate dehydrogenase (LDH) and reduced cell viability in the presence of 100 nm sized AgNPs when compared to smaller AgNPs (10–50 nm) [125]. It can be noted that the variation in parameters in these studies makes it difficult to observe trends and come to accurate assumptions. To achieve some consensus in this regard, Gliga et al. studied the cytotoxic effect of varying sized AgNPs capped by various agents on the normal bronchial epithelial cell line (BEAS-2B). They reported that 10 nm sized AgNPs induced cytotoxicity irrespective of the capping agents, at high concentrations (20–50 μg ml−1), whilst larger AgNPs did not display significant cytotoxic effects at all tested concentrations. The group additionally reported that at non-cytotoxic concentrations (10 μg ml−1), significant DNA damage was observed for all AgNPs independent of size and coating. In contrast, panda et al. reported no genotoxicity of AgNPs capped with protein at 20–80 μg ml−1 for 24–55 nm sized particles [126].
Overall, it is difficult to establish the cytotoxic effect of AgNPs due to the differences in nanoparticle synthetic methods, their various sizes and capping agents and lastly the diverse evaluation tests used to determine toxicity. In fact, by using different organisms and/or culture cells there is no conclusive evaluation of AgNP toxicity [127]. However, bearing in mind the results presented in this review, it can be tentatively suggested that smaller sized AgNPs are more cytotoxic than larger sized particles at higher concentrations.
The physiochemical characteristics of metal nanoparticles render them applicable across a genre of multi-disciplinary fields for a variety of uses including catalysis [128]; micro-electronics [129]; solar energy conversion [130] amongst many others [131]. They have also been recognised for their potential in a number of medical applications [132]. However, the use of nanoparticles derived from physical and chemical synthetic routes raises health and toxicity concerns due to the nature of the reaction conditions which may ultimately affect the properties of the derived particles [133].
Biologically derived nanoparticles provide a greener alternative to nanoparticles derived from the aforementioned routes since, the synthesis methods used to derive these particles are clean and non-toxic [9]. As a result, they are suitable for a number of biomedical applications (Table 1) including: cancer therapy; drug delivery; tumour detection; genetic disorder diagnosis; tissue repair; cell labelling; antimicrobial development; targeting and immunoassays and yet to be discovered applications [37, 114, 132, 134, 135, 136].
Plant | Applications | Reference |
---|---|---|
Moringa oleifera | Anti-microbial | [137] |
Eclipta prostrata | Anti-protozoal | [138] |
Gelidiella acerosa | Anti-fungal | [139] |
Melia azedarach | Anti-cancer | [140] |
Lampranthus coccineus | Anti-viral | [141] |
Malephora lutea | Anti-Alzheimer | [142] |
Melia azedarach | Wound healing | [143] |
Ocimum sanctum | Anti-diabetic | [144] |
Allium sativum | Antioxidant | [145] |
Selective applications of silver nanoparticles synthesised using plant extracts.
With respect to biologically derived AgNPs, their major exploitation exists in the development of antimicrobial agents due to their renowned microbial inhibitory activities and with the current status on antimicrobial drug resistance, these particles are being extensively sought after as possible alternatives to antibiotics [1, 8].
In conclusion, it can be established that green synthetic strategies using plant and bacterial based extracts are promising alternatives to produce AgNPs. However, to produce AgNPs with enhanced bioactivities, morphological characteristics such as size and shape need to be finely tuned. Furthermore, the use of extracts with known medical value provides with attractive capping substrates that may potentially enhance the bioactivities of the produced particles.
This study was made possible through financial support from the National Research Foundation. The research facilities were provided by the University of KwaZulu-Natal.
Authors declare no conflict of interest.
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. I have served as the editor for many books, been a member of the editorial board in science journals, have published many papers and hold many patents.",institutionString:null,institution:{name:"Sheffield Hallam University",country:{name:"United Kingdom"}}},{id:"54525",title:"Prof.",name:"Abdul Latif",middleName:null,surname:"Ahmad",slug:"abdul-latif-ahmad",fullName:"Abdul Latif Ahmad",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"20567",title:"Prof.",name:"Ado",middleName:null,surname:"Jorio",slug:"ado-jorio",fullName:"Ado Jorio",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidade Federal de Minas Gerais",country:{name:"Brazil"}}},{id:"47940",title:"Dr.",name:"Alberto",middleName:null,surname:"Mantovani",slug:"alberto-mantovani",fullName:"Alberto Mantovani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"12392",title:"Mr.",name:"Alex",middleName:null,surname:"Lazinica",slug:"alex-lazinica",fullName:"Alex Lazinica",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/12392/images/7282_n.png",biography:"Alex Lazinica is the founder and CEO of IntechOpen. After obtaining a Master's degree in Mechanical Engineering, he continued his PhD studies in Robotics at the Vienna University of Technology. Here he worked as a robotic researcher with the university's Intelligent Manufacturing Systems Group as well as a guest researcher at various European universities, including the Swiss Federal Institute of Technology Lausanne (EPFL). During this time he published more than 20 scientific papers, gave presentations, served as a reviewer for major robotic journals and conferences and most importantly he co-founded and built the International Journal of Advanced Robotic Systems- world's first Open Access journal in the field of robotics. Starting this journal was a pivotal point in his career, since it was a pathway to founding IntechOpen - Open Access publisher focused on addressing academic researchers needs. Alex is a personification of IntechOpen key values being trusted, open and entrepreneurial. Today his focus is on defining the growth and development strategy for the company.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"19816",title:"Prof.",name:"Alexander",middleName:null,surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/19816/images/1607_n.jpg",biography:"Alexander I. Kokorin: born: 1947, Moscow; DSc., PhD; Principal Research Fellow (Research Professor) of Department of Kinetics and Catalysis, N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow.\r\nArea of research interests: physical chemistry of complex-organized molecular and nanosized systems, including polymer-metal complexes; the surface of doped oxide semiconductors. He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). 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Focus of his research activity is drug delivery, physico-chemical characterization and biological evaluation of biopolymers micro and nanoparticles as modified drug delivery system, and colloidal drug carriers (liposomes, nanoparticles etc.).",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"61051",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"100762",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"St David's Medical Center",country:{name:"United States of America"}}},{id:"107416",title:"Dr.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Texas Cardiac Arrhythmia",country:{name:"United States of America"}}},{id:"64434",title:"Dr.",name:"Angkoon",middleName:null,surname:"Phinyomark",slug:"angkoon-phinyomark",fullName:"Angkoon Phinyomark",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/64434/images/2619_n.jpg",biography:"My name is Angkoon Phinyomark. I received a B.Eng. degree in Computer Engineering with First Class Honors in 2008 from Prince of Songkla University, Songkhla, Thailand, where I received a Ph.D. degree in Electrical Engineering. My research interests are primarily in the area of biomedical signal processing and classification notably EMG (electromyography signal), EOG (electrooculography signal), and EEG (electroencephalography signal), image analysis notably breast cancer analysis and optical coherence tomography, and rehabilitation engineering. I became a student member of IEEE in 2008. During October 2011-March 2012, I had worked at School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex, United Kingdom. In addition, during a B.Eng. I had been a visiting research student at Faculty of Computer Science, University of Murcia, Murcia, Spain for three months.\n\nI have published over 40 papers during 5 years in refereed journals, books, and conference proceedings in the areas of electro-physiological signals processing and classification, notably EMG and EOG signals, fractal analysis, wavelet analysis, texture analysis, feature extraction and machine learning algorithms, and assistive and rehabilitative devices. I have several computer programming language certificates, i.e. Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS). 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