Synthesis of TiO2 NPs by using plant extracts.
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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
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Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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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 incidence of microbial attack in different sectors such as food, textiles, medicine, water disinfection, and food packaging leads to a constant trend in the search for new antimicrobial substances. The increased resistance of some bacteria to some antibiotics and the toxicity to the human body of some organic antimicrobial substances has increased the interest in the development of inorganic antimicrobial substances. Among these compounds, metal and metal oxide compounds have attracted significant attention due to their broad-spectrum antibacterial activities. On the other hand, nanoscale materials are well known thanks to their increased properties due to their high surface area-to-volume ratio. Antimicrobial NPs have shown excellent and different activities from their bulk properties [1, 2].
During last decades, metal oxide nanoparticles, such as zinc oxide (ZnO), manganese oxide (MgO), titanium dioxide (TiO2), and iron oxide (Fe2O3), have been extensively applicable thanks to their unique physiochemical properties in biological applications. Among metal oxide antimicrobial agents, TiO2 is a valuable semiconducting transition metal oxide material and shows special features, such as easy control, reduced cost, non-toxicity, and good resistance to chemical erosion, that allow its application in optics, solar cells, chemical sensors, electronics, antibacterial and antifungal agents [3]. In general, TiO2 nanoparticles (TiO2 NPs) present large surface area, excellent surface morphology, and non-toxicity in nature. Several authors have reported that TiO2 NPs have been one of the most studied NPs thanks to their photocatalytic antimicrobial activity, exerting excellent bio-related activity against bacterial contamination [4, 5, 6, 7].
Antimicrobial activity of nanoparticles is highly influenced by several intrinsic factors such as their morphology, size, chemistry, source, and nanostructure [8, 9, 10, 11]. Specifically, antimicrobial activity of TiO2 NPs is greatly dependent on photocatalytic performance of TiO2, which depends strongly on its morphological, structural, and textural properties [12]. Several TiO2 NPs have been developed through different methods of synthesis. Specifically, in this chapter, eco-friendly synthesis based on biological sources, such as natural plant extracts and metabolites from microorganisms, which have resulted in TiO2 NPs with different size, shape, morphology, and crystalline structures will be presented. Titanium dioxide produces amorphous and crystalline forms and primarily can occur in three crystalline polymorphous: anatase, rutile, and brookite. Studies on synthesis have stated that the crystalline structure and morphology of TiO2 NPs is influenced by process parameters such as hydrothermal temperatures, starting concentration of acids, etc. [13]. The crystal structures and the shape of TiO2 NPs are both the most important properties that affect their physicochemical properties, and therefore their antimicrobial properties [14]. Regarding the crystal structures, anatase presents the highest photocatalytic and antimicrobial activity. Some works have shown that anatase structure can produce OH˙ radicals in a photocatalytic reaction, and as it will be clearly explained below, bacteria wall and membranes can be deadly affected [15, 16].
The potential health impact and toxicity to the environment of NPs is currently an important matter to be addressed. Several works have confirmed that metal oxide NPs conventionally synthesized using chemical methods, such as sol–gel synthesis and chemical vapor deposition, have shown different levels of toxicity to test organisms [17, 18, 19, 20]. In recent years, researchers have emphasized on the development of nanoparticles promoted through environmental sustainability and processes characterized by an ecological view, mild reaction conditions, and non-toxic precursors. Due to this growing sensitivity toward green chemistry and biological processes, ecological processes are currently being investigated for the synthesis of non-toxic nanoparticles.
These biological methods are considered safe, cost-effective, biocompatible, non-toxic, sustainable, and environmentally friendly processes [20]. Furthermore, it has been described that chemically synthesized NPs have exhibited less stability and added agglomeration, resulting in biologically synthesized NPs that are more dispersible, stable in size, and the processes consuming less energy [21].
These biosynthetic methods, also called “green synthesis,” use various biological resources available in nature, including live plant [22], plant products, plant extracts, algae, fungi, yeasts [23], bacteria [24], and virus for the synthesis of NPs. Among these methods, the processes that use plant-based materials are considered the most suitable for large-scale green synthesis of NPs with respect to their ease and safety [25]. On the other hand, the reduction rate of metal ions in the presence of the plant extract is much faster compared to microorganisms, and provides stable particles [26]. Plants contain biomolecules that have been highly studied by researchers like phenols, nitrogen compounds, terpenoids, and other metabolites. It is well known that the hydroxyl and carboxylic groups present in these biocompounds act as stabilizers and reducing agents due to their high antioxidant activity [12]. Thus, plant extracts have been studied as one of the best green alternatives for metal oxide nanoparticles synthesis [27]. In recent years, TiO2 nanoparticles have been obtained by using different plant extracts, but not all of them have been studied for their antimicrobial activity. Table 1 presents a compilation of synthesized TiO2 nanoparticles from green synthesis by using plant extracts that were tested against different microorganisms.
Source | Titanium precursor | Size (nm) | Shape/crystal structure | Target microorganism (method) |
---|---|---|---|---|
Azadirachta indica leaves extract [28] | TiO2 | 25–87 (SEM) | Spherical/anatase-rutile | S. typhi, E. coli, and K. pneumoniae (broth micro dilution method) |
Psidium guajava leaves extract [29] | TiO(OH)2 | 32.58 (FESEM) | Spherical shape and clusters/anatase-rutile | S. aureus and E. coli (agar diffusion) |
Vitex negundo Linn leaves extract [30] | Ti{OCH(CH3)2}4 | 26–15 (TEM) | Spherical and rod shaped/tetragonal phase anatase | S. aureus and E. coli (agar diffusion) |
Morinda citrifolia leaves extract [31] | TiCl4 | 15–19 (SEM) | Quasi-spherical shape/rutile | S. aureus, B. subtilis, E. coli, P. aeruginosa, C. albicans, A. niger (agar diffusion) |
Trigonella foenum-graecum leaf extract [21] | TiOSO4 | 20–90 (HR-SEM) | Spherical/anatase | E. faecalis, S. aureus, S. faecalis, B. subtilis., Y. enterocolitica, P. vulgaris, E. coli, P. aeruginosa, K. pneumoniae, and C. albicans (agar diffusion) |
Orange peel extract [32] | TiCl4 | 20–50 (SEM) | Irregular and angular structure with high porous net/anatase | S. aureus, E. coli, and P. aeruginosa (agar diffusion) |
Glycyrrhiza glabra root extracts [33] | TiO2 | 60–140 (FESEM) | Spherical shape/anatase | S. aureus and K. pneumoniae (agar diffusion) |
Synthesis of TiO2 NPs by using plant extracts.
Different factors need to be evaluated in this research field in order to obtain TiO2 NPs with better properties and to maintain their biocompatibility. It has been shown that nanoparticles obtained from green synthesis can have a better morphology and size translated into better antimicrobial activity. Mobeen and Sundaram have obtained TiO2 NPs from titanium tetrachloride precursor through a chemical and a green synthesis method. Sulfuric acid and ammonium hydroxide were used in the chemical-based method and, in the green synthesis, those chemical reagents were replaced by an orange peel extract [32]. The nanoparticles obtained by using the natural extract presented a well-defined and smaller crystalline nature (approx. 17.30 nm) compared to the nanoparticles synthesized through the chemical method (21.61 nm). Both methods resulted in anatase crystalline structures, and, when evaluating the antimicrobial activity, the more eco-friendly NPs revealed higher bactericidal activity against Gram-positive and Gram-negative bacteria compared to the chemically synthesized nanoparticles.
Bavanilatha et al. have also detailed TiO2 NPs green synthesis with Glycyrrhiza glabra root extract. Antibacterial activity against Staphylococcus aureus and Klebsiella pneumonia were investigated and in vivo toxicity tests using the zebrafish embryonic model (Danio rerio) were also carried out [33]. Results have demonstrated their biocompatibility because healthy embryos of adult fish to different variations of NP and no distinctive malformations were observed at every embryonic stage with respect to embryonic controls.
Subhapriya and Gomathipriya have biosynthesized TiO2 NPs by using a Trigonella foenum-graecum leaf extract, obtaining spherical NPs and their size varied between 20 and 90 nm, and their antimicrobial activity was evaluated through the standard method of disc diffusion [21]. The NPs showed significant antimicrobial activity against Yersinia enterocolitica (10.6 mm), Escherichia coli (10.8 mm), Staphylococcus aureus (11.2 mm), Enterococcus faecalis (11.4 mm), and Streptococcus faecalis (11.6 mm). Results confirmed developed TiO2 NPs as an effective antimicrobial drug that can lead to the progression of new antimicrobial drugs.
Spherical TiO2 NPs were synthesized from plants, in particular by applying a Morinda citrifolia leaf extract, and through advanced hydrothermal method [31]. Developed TiO2 NPs showed a size between 15 and 19 nm in an excellent quasispherical shape. In addition, their antimicrobial activity was tested against human pathogens, such as Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Pseudomonas aeruginosa, Candida albicans, and Aspergillus niger. TiO2 NPs exhibited interesting antimicrobial activity, principally against Gram-positive bacteria.
In addition to plants, other organisms can produce inorganic compounds at an intra or extracellular level. The synthesis of TiO2 NPs through microorganisms, including bacteria, fungi, and yeasts, also meets the requirements and the exponentially growing technological demand toward eco-friendly strategies, by avoiding the use of toxic chemicals in the synthesis and protocols [34]. The metabolites generated by microorganism present bioreducing, capping, and stabilizing properties that improve the NPs synthesis performance. Jayaseelan et al. have stated glycyl-L-proline, one of the most abundant metabolite from Aeromonas hydrophilia bacteria, as the main compound that acted as a capping and stabilizing agent during TiO2 NPs green synthesis [35]. Moreover, the interest in fungi in green synthesis of metal oxide nanoparticles has increased over last years. Fungi enzymes and/or metabolites also present intrinsically the potential to obtain elemental or ionic state metals from their corresponding salts [34, 36]. Different works based on the green synthesis of TiO2 NPs from bacteria and fungus are presented in Table 2. Some of them have been synthesized with antimicrobial and antifungal purposes, and their target microorganisms are also declared.
Microorganism | Titanium precursor | Size (nm) | Shape/crystal structure | Target microorganisms (method) |
---|---|---|---|---|
Aeromonas hydrophilia [46] | TiO(OH)2 | 28–54 (SEM) ~ 40.5 (XRD) | Spherical/uneven | S. aureus, S. pyogenes (agar diffusion) |
Aspergillus flavus [34] | TiO2 | 62–74 (TEM) | Spherical/anatase and rutile | E. coli, P. aeruginosa, K. pneumoniae, B. subtilis (agar diffusion and MIC) |
Bacillus mycoides [37] | Titanyl hydroxide | 40–60 (TEM) | Spherical/anatase | E. coli (toxicity) |
Bacillus subtilis [38] | K2TiF6 | 11–32 (TEM) | Spherical | Aquatic biofilm |
Fusarium oxysporum [36] | K2TiF6 | 6–13 (TEM) | Spherical/brookite | — |
Lactobacillus sp. [51] | TiO(OH)2 | ~ 24.6 (TEM) | Spherical/anatase-rutile | — |
Planomicrobium sp. [39] | TiO2 | 100–500 (SEM) | Irregular/pure crystalline | B. subtilis, K. planticola, Aspergillus niger (agar diffusion) |
Propionibacterium jensenii [52] | TiO(OH)2, 300°C | 15–80 (FESEM) | Spherical | — |
Saccharomyces cerevisiae [51] | TiO(OH)2 | ~ 12.6 (TEM) | Spherical/anatase-rutile | — |
Examples of TiO2 NPs synthesis through microorganisms, both bacteria and fungus strains.
Two important factors that affect NPs synthesis are the type of microorganisms and their source. Some microorganisms widely used in the food industry are Lactobacillus, a bacterium used in dairy products and as a probiotic supplement, and Saccharomyces cerevisiae, a yeast commonly used in bakery. Jha et al. have investigated the effectiveness of both microorganisms to synthesize TiO2 NPs. A comparison between synthesis through Lactobacillus from yogurt and probiotic tablets resulted in different NP sizes: a particle size of 15–70 nm for yogurt, and 10–25 nm for tablets. This difference was due to the purity of the bacteria [40]. In general, TiO2 NP synthesis through microorganisms has not provided stable sizes, being not industrially scalable compared to the synthesis of nanoparticles from plants.
Harmful bacteria, such as Staphylococcus aureus, Burkholderia cepacia, Pseudomonas aeruginosa, Clostridium difficile, Klebsiella pneumoniae, Escherichia coli, Acinetobacter baumannii, Mycobacterium tuberculosis, and Neisseria gonorrhoeae, are responsible for bacterial infections that can cause serious diseases in humans year after year [40]. The principal solution is the use of antibiotics, antimicrobial and antifungal agents. Nevertheless, in recent years there has been an increase in the resistance of several bacterial strains to these substances, and therefore there is currently a great interest in the search for new antimicrobial substances. The antimicrobial nanoparticles have been studied due to their high activity, specifically the metal oxide nanoparticles [41, 42, 43]. In this sense, titanium dioxide nanoparticles are one of the antimicrobial NPs whose study has gained interest during last years.
TiO2 is a thermally stable and biocompatible chemical compound with high photocatalytic activity and has presented good results against bacterial contamination [44]. Table 3 presents some research including the antimicrobial capacity of TiO2 NPs.
Microorganism | NPs | Results |
---|---|---|
Methicillin-resistant Staphylococcus aureus [45] | Fe3O4-TiO2 core/shell magnetic NPs | The survival ratio [%] of bacteria decreased from 82.40 to 7.13%. |
Staphylococcus saprophyticus [45] | Fe3O4-TiO2 core/shell magnetic NPs | The survival ratio [%] of bacteria decreased from 79.15 to 0.51%. |
Streptococcus pyogenes[57] | Fe3O4-TiO2 core/shell magnetic NPs | The survival ratio [%] of bacteria decreased from 82.87 to 4.45%. |
Escherichia coli [46] | TiO2 nanotubes ~ 20 nm | 97.53% of reduction |
Staphylococcus aureus [46] | TiO2 nanotubes ~ 20 nm | 99.94% of reduction |
Bacillus subtilis [47] | TiO2 NPs co-doped with silver (19–39 nm) | 1% Ag-N-TiO2 had the highest antibacterial activity with antibacterial diameter reduction of 22.8 mm |
Mycobacterium smegmatis [48] | Cu-doped TiO2NPs ~20 nm | The percentage of inhibition was around 47% |
Pseudomonas aeruginosa [49] | TiO2 NPs 10–25 nm | Although it was not completely euthanized, their survival was significantly inhibited. |
Shewanella oneidensis MR-1 [48] | Cu-doped TiO2 NPs ~20 nm | The percentage of inhibition was around 11% |
TiO2 nanoparticles against different microorganisms and their antimicrobial activities.
The principal factors differentiating the antimicrobial activity between TiO2 NPs were their morphology, crystal nature, and size. According to López de Dicastillo et al. [11], hollow TiO2 nanotubes presented interesting antimicrobial reduction thanks to the enhancement of specific surface area. This fact can be explained by the nature of titanium dioxide, and one of the main mechanisms of its action is through the generation of reactive oxygen species (ROS) on its surface during the process of photocatalysis when it exposed to light at an appropriate wavelength. It is important to highlight that some research works have evidenced antimicrobial activity of TiO2 NPs increased when they were irradiated with UV-A light due to the photocatalytic nature of this oxide. The time of irradiation varied between 20 min [45] and 3 hours [50].
Titanium dioxide nanoparticles (TiO2 NPs) are one of the most studied materials in the area of antimicrobial applications due to its particular abilities, such as bactericidal photocatalytic activity, safety, and self-cleaning properties. The mechanism referred to the antimicrobial action of TiO2 is commonly associated to reactive oxygen species (ROS) with high oxidative potentials produced under band-gap irradiation photo-induces charge in the presence of O2 [51]. ROS affect bacterial cells by different mechanisms leading to their death. Antimicrobial substances with broad spectrum activity against microorganisms (Gram-negative and Gram-positive bacteria and fungi) are of particular importance to overcome the MDR (multidrug resistance) generated by traditional antibiotic site-specific.
The main photocatalytic characteristic of TiO2 is a wide band gap of 3.2 eV, which can trigger the generation of high-energy electron–hole pair under UV-A light with wavelength of 385 nm or lower [52]. As mentioned above for bulk powder, TiO2 NPs have the same mechanism based on the ROS generation with the advantage of being at nanoscale. This nanoscale nature implies an important increase of surface area-to-volume ratio that provides maximum contact with environment water and oxygen [53] and a minimal size, which can easily penetrate the cell wall and cell membrane, enabling the increase of the intracellular oxidative damage.
Bacteria have enzymatic antioxidant defense systems like catalases and superoxide dismutase, in addition to natural antioxidants like ascorbic acid, carotene, and tocopherol, which inhibit lipid peroxidation or O-singlet and the effects of ROS radicals such as OH2˙− and OH˙. When those systems are exceeded, a set of redox reactions can lead to the death cell by the alteration of different essential structures (cell wall, cell membrane, DNA, etc.) and metabolism routes [54]. In the following sections, several ways that cellular structures were affected in the presence of TiO2 NPs will be described. In order to understand the genome responses of bacteria to TiO2-photocatalysis, some biological approaches related to expression of genes encoding to defense and repair mechanism of microorganism will explained below. Different mechanisms and processes of antimicrobial activity of TiO2 NPs are represented as a global scheme in Figure 1.
Scheme of main antimicrobial activity-based processes.
ROS are responsible for the damage by oxidation of many organic structures of microorganisms. One of them is the cell wall, which is the first defense barrier against any injury from the environment, thus being the first affected by oxidative damage. Depending on the type of microorganism, the cell wall will have different composition; that is, in fungi and yeast, cell walls are mainly composed of chitin and polysaccharides [55], Gram-positive bacteria contain many layers of peptidoglycan and teichoic acid, and Gram-negative bacteria present a thin layer of peptidoglycan surrounded by a secondary lipid membrane reinforced with transmembrane lipopolysaccharides and lipoproteins [56]. Thus, the effect of TiO2 NPs will be slightly different depending type of microorganism.
It has been studied that the composition of the cell wall in Pichia pastoris (yeast) changed in the presence of TiO2, increasing the chitin content in response to the ROS effects [57]. The cell wall of Escherichia coli (Gram-negative) composed of lipo-polysaccharide, phosphatidyl-ethanolamine, and peptidoglycan has been reported to be sensitive to the peroxidation caused by TiO2 [58]. The damage can be quantified by assessing the production of malondialdehyde (MDA), which is a biomarker of lipid peroxidation, or through ATR-FTIR of the supernatant of cell culture, which evidenced the way that porins and proteins on the outer membrane were affected, probably as a result of greater exposure to the surface of TiO2 [59]. In fungi, the release of OH˙ captured hydrogen atoms from sugar subunits of polysaccharides, which composed the cell wall, leading to the cleavage of polysaccharide chain and the exposition of cell membrane [60].
In terms of genetic issues, there is evidence that the bacteria change the level expression of certain genes encoding for proteins involved in lipopolysaccharide and peptidoglycan metabolism, pilus biosynthesis, and protein insertion related to the cell wall which values were lower-expressed after exposition to TiO2 NPs [61].
The second usual cellular target of most of antibiotics is the cell membrane mainly composed by phospholipids, which grant the cell a non-rigid cover, permeability, and protection. Most of the studies with TiO2 NPs have been focused to the loss of membrane integrity caused by oxidation of phospholipids due to ROS such hydroxyl radicals and hydrogen peroxide [62, 63], which led to an increase in the membrane fluidity, leakage of cellular content, and eventually cell lysis.
Gram-positive bacteria present only one membrane protected by many layers of peptidoglycan, whereas Gram-negative bacteria are composed by two membranes, inner and outer, and a thin layer of peptidoglycan between them. The outer membrane is exposed, thus, more liable to mechanical breakage due to the lack of peptidoglycan protective cover, like in Gram-positive bacteria [64]. Some studies have demonstrated a better antimicrobial performance of TiO2 NPs against Gram-positive bacteria [65] while others reported that Gram-negative bacteria were more resistant [66, 67]. It can be concluded that the bacterial inactivation effectiveness depends mainly on the resistant capacity of cell wall structures and the damage level of ROS generation [68].
In contrast with the lower expression of genes related to the cell wall seen before, the level expression of genes encoding for enzymes involved in metabolism of lipid essential for the cell membrane structure, are over-expressed [61]. It would be concluded that cells compensate the initial cell wall damage by reinforcing the second defense barrier, the cell membrane, in a way to provide support against the oxidation produced by ROS.
In fungi, the biocidal effect is not quite different. In the presence of TiO2 NPs and UV light, hydroxyl radicals, hydrogen peroxide, and superoxide anions initially promote oxidation of the membrane, leading to an unbalance in the cell permeability, even decomposition of cell walls [69]. This oxidation can inhibit cell respiration by affecting intracellular membranes in mitochondria. Studies have demonstrated biocidal effects on Penicillium expansum [70], but there is still research on other strains.
Beyond the relatively well-studied initial lipoperoxidation attack of TiO2 NPs on the outer/inner cell membrane of the microorganism, specific mechanisms are still aimed of being solved.
As the oxidative damage generates lipoperoxidation of cell membranes due to their lipid nature, the respiratory chain, which takes place in the double-membrane mitochondria, is also affected. This organelle is a natural source of ROS in aerobic metabolism because superoxide anions are produced in the electron transfer respiratory chain process. Mitochondria can control this fact by converting them into H2O2 by superoxide dismutase (SOD), and finally into water by glutathione peroxidase and catalase [71]. The presence of TiO2 NPs increases the production of ROS at levels that this enzymatic defense mechanism cannot attenuate the damage, even a dysregulation in electron transfer through the mitochondrial respiratory chain implies an increase in ROS generation [72].
The genetic approaches have indicated that changes in level expression in genes related to the energy production in mitochondria prioritize the most efficient pathway to uptake oxygen, which is through ubiquinol coenzyme [61]. This coenzyme presented a higher capacity to exchange electrons, while the coenzyme-independent oxygen uptake pathways were expressed at lower level.
Damage at molecular level in DNA affects all regulatory microorganism metabolism, replication, transcription, and cell division. DNA is particularly sensitive to oxidative damage because oxygen radicals, specially OH˙ produced by Fenton reaction [73], may attack the sugar-phosphate or the nucleobases and cause saccharide fragmentation aimed to the strand break [74].
DNA strand modifications are more lethal than base modifications (punctual mutation). Mitochondrial DNA is more vulnerable to oxidative damage than nuclear DNA because it is closer to a major cellular ROS source [75].
Besides the enzymatic detoxification system (SOD, glutathione and catalase), DNA injuries are covered by a set of structures related to post-translational modification, protein turnover, chaperones (related to folding), DNA replication and repair, which are significantly over-expressed in the presence of TiO2 NPs [61].
Iron is an essential ion for cell growth and survival, but it can turn potentially toxic if some malfunction in homeostatic regulation occurs (i.e., Fenton reaction that produces ROS). Bacteria are able to regulate iron concentration in order to maintain it in a physiological range [76]. This regulation involves directly siderophores to active transport of iron in cell [77], whose coding genes related to siderophore synthesis and iron transport protein are significantly lower-expressed in the presence of TiO2 NPs, decreasing the ability to assimilate and transport it, leading to cell death [61]. The loss of homeostasis regulation was confirmed by ICP-MS analysis, which revealed that the presence of TiO2 NPs significantly reduced the cellular iron level in Pseudomonas brassicacearum, directly proportional to the cell viability [78].
Regarding the functions related to Pi group (PO43−) uptake, major differences were found in the expression of set of genes contained in Pho regulon, which were significantly lower when compared to the control [61]. The Pho regulon is a regulatory network in bacteria, yeast, plants, and animals, related to assimilation of inorganic phosphate, merely available in nature, and essential to nutritional cross-talk, secondary metabolite production, and pathogenesis [79].
This suggested that the microorganisms were highly deficient in phosphorus uptake and metabolism in the presence of TiO2 NPs. It should be also noted that the Pho regulon has been reported to regulate biofilm synthesis capacity and pathogenicity [80].
TiO2 NPs can directly oxidize components of cell signaling pathways and even change the gene expression by interfering with transcription factors [81]. There is evidence to confirm the interference of TiO2 NPs in biosynthesis pathways of signaling molecules that bind lipopolysaccharide, stabilize and protect the cell wall against oxidative damage [82]. Moreover, a significant decrease in the synthesis of quorum-sensing signal molecule related to functions like pathogenesis and biofilm development was observed. This was corroborated through Scanning Electron Microscopy (SEM) images of bacteria (P. aeruginosa) growth in the presence of TiO2 NPs without UV irradiation. Cells appeared mainly non-aggregated and dispersed in the substratum, compared with controls without NPs where cells were mainly aggregated by lateral contact. This suggested that TiO2 NPs not only affected microorganisms by oxidative damage, but also bacteria aggregation and biofilm formation, which directly influenced in pathogenicity [83].
In plants and algae, ROS can act as signaling intermediates in the process of transcription factor controlling stress response by H2O2, which is activated by a GSH peroxidase, and not by peroxides directly. But there is still lack of research in this area [84].
The control of morphology and crystal structure of TiO2 NPs is the most important factor to enhance their antimicrobial activity. The appropriate design based on desirable surface properties given by shaped nanoparticles can improve effectiveness that is also dependent on the type of bacteria. The route of synthesis of TiO2 NPs is also a key factor. Recent works have revealed more eco-friendly synthesis methods, principally based on plant-based compounds and microorganisms, such as bacteria and fungus. Antimicrobial activity of different TiO2 NPs against Gram-positive and Gram-negative bacteria including antibiotic-resistant strains has been confirmed in different works.
Specific studies on antimicrobial mechanisms have evidenced that microorganism exposed to photocatalytic TiO2 NPs exhibited cell inactivation at regulatory network and signaling levels, an important decrease in the activity of respiratory chain, and inhibition in the ability to assimilate and transport iron and phosphorous. These processes with the extensive cell wall and membrane alterations were the main factors that explain the biocidal activity of TiO2 NPs.
The authors acknowledge the financial support of CONICYT through the Project Fondecyt Regular 1170624 and “Programa de Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia” Project FB0807, and CORFO Project 17CONTEC-8367.
The authors declare no conflict of interest.
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",metaTitle:"Retraction and Correction Policy",metaDescription:"Retraction and Correction Policy",metaKeywords:null,canonicalURL:"/page/retraction-and-correction-policy",contentRaw:'[{"type":"htmlEditorComponent","content":"IntechOpen’s Retraction and Correction Policy has been developed in accordance with the Committee on Publication Ethics (COPE) publication guidelines relating to scientific misconduct and research ethics:
\\n\\n1. RETRACTIONS
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\\n\\nIntechOpen believes that the number of occasions on which a Statement of Concern is issued will be very few in number. In all cases when such a decision has been taken by the Academic Editor the decision will be reviewed by another editor to whom the author can make representations.
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\\n\\nA published Erratum will adhere to the Retraction Notice publishing guidelines outlined above.
\\n\\n3.2. CORRIGENDUM
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\\n"}]'},components:[{type:"htmlEditorComponent",content:'IntechOpen’s Retraction and Correction Policy has been developed in accordance with the Committee on Publication Ethics (COPE) publication guidelines relating to scientific misconduct and research ethics:
\n\n1. RETRACTIONS
\n\nA Retraction of a Chapter will be issued by the Academic Editor, either following an Author’s request to do so or when there is a 3rd party report of scientific misconduct. Upon receipt of a report by a 3rd party, the Academic Editor will investigate any allegations of scientific misconduct, working in cooperation with the Author(s) and their institution(s).
\n\nA formal Retraction will be issued when there is clear and conclusive evidence of any of the following:
\n\nPublishing of a Retraction Notice will adhere to the following guidelines:
\n\n1.2. REMOVALS AND CANCELLATIONS
\n\n2. STATEMENTS OF CONCERN
\n\nA Statement of Concern detailing alleged misconduct will be issued by the Academic Editor or publisher following a 3rd party report of scientific misconduct when:
\n\nIntechOpen believes that the number of occasions on which a Statement of Concern is issued will be very few in number. In all cases when such a decision has been taken by the Academic Editor the decision will be reviewed by another editor to whom the author can make representations.
\n\n3. CORRECTIONS
\n\nA Correction will be issued by the Academic Editor when:
\n\n3.1. ERRATUM
\n\nAn Erratum will be issued by the Academic Editor when it is determined that a mistake in a Chapter originates from the production process handled by the publisher.
\n\nA published Erratum will adhere to the Retraction Notice publishing guidelines outlined above.
\n\n3.2. CORRIGENDUM
\n\nA Corrigendum will be issued by the Academic Editor when it is determined that a mistake in a Chapter is a result of an Author’s miscalculation or oversight. A published Corrigendum will adhere to the Retraction Notice publishing guidelines outlined above.
\n\n4. FINAL REMARKS
\n\nIntechOpen wishes to emphasize that the final decision on whether a Retraction, Statement of Concern, or a Correction will be issued rests with the Academic Editor. The publisher is obliged to act upon any reports of scientific misconduct in its publications and to make a reasonable effort to facilitate any subsequent investigation of such claims.
\n\nIn the case of Retraction or removal of the Work, the publisher will be under no obligation to refund the APC.
\n\nThe general principles set out above apply to Retractions and Corrections issued in all IntechOpen publications.
\n\nAny suggestions or comments on this Policy are welcome and may be sent to permissions@intechopen.com.
\n\nPolicy last updated: 2017-09-11
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