Accurate measurements of thermal properties is a major concern, for both scientists and the industry. The complexity and diversity of current and future demands  require making the thermal characterization methods used in laboratory more accessible and portable, by miniaturizing, automating, and connecting them. Designing new materials with innovative thermal properties or studying the thermal properties of biological tissues often require the use of miniaturized and non-invasive sensors, capable of accurately measuring the thermal properties of small quantities of materials. In this context, miniature electro-thermal resistive sensors are particularly well suited, in both material science and biomedical instrumentation, both in vitro and in vivo. This paper presents a one-dimensional (1D) electro-thermal systemic modeling of miniature thermistor bead-type sensors. A Godunov-SPICE discretization scheme is introduced, which allows for very efficient modeling of the entire system  in a single workspace. The present modeling is applied to the thermal characterization of different biocompatible liquids  using a miniature bead-type thermistor. The numerical results are in very good agreement with the experimental ones, demonstrating the relevance of the present modeling. A new quasi-absolute thermal characterization method is then reported and discussed. The multi-physics modeling described in this paper could in the future greatly contribute to the development of new portable instrumental approaches. The miniaturization of electro-thermal sensors consists of designing and manufacturing ever smaller measuring devices, in order to characterize very limited quantities of material, under a wide variety of operating conditions. This miniaturization has opened up new perspectives in many scientific and technical fields, particularly in medicine, where it has enabled in vivo thermal characterization of biological tissues, that is of crucial importance, for example, in the focal treatment of tumors by magnetic hyperthermia .If some attempts of thermal systems miniaturization at the microscopic scale have been successfully achieved, particularly with the development of labs on a chip, they mainly concern the detection of micro objects , thermalIt is clear that the miniaturization of electro-thermal sensors brings undeniable advantages, such as: a lower thermal inertia; a limited invasiveness of the system to be characterized, which is, therefore, less disturbed by the sensor; and the possibility of using small quantities of material, that is highly desirable in nanotechnologies, for example, where the products to be characterized can be very expensive. However, the miniaturization of electro-thermal sensors can also have drawbacks, the most delicate being certainly the problem of the increasing influence of boundary-effects, mainly due to electrical connections. These connections represent unavoidable heat sinks for the sensor, systematically imposing a precise and delicate calibration before any use ,7. It isthe transient methods, among which we can mention: the pulse-decay method ; the tem methods ,16;the steady-state methods, such as the guarded hot plate and the heated thermocouple methods.There are a large number of thermal characterization methods , which can be classified mainly into two categories ,9,10, wiThese techniques can be implemented using a wide variety of different thermal sensors (temperature or heat flow), such as: thermocouples, negative temperature coefficient (NTC) thermistors, resistance temperature detectors (RTDs), and radiative sensors.In the present paper, we will focus on the transient mode use of miniature resistive electro-thermal sensors, for thermal characterization of solid or liquid materials, in the laboratory or in everyday use conditions. These sensors can be classified into two main categories: the hot metal wires (HMW) or hot metal films (HMF) made of pure metal resistors (RTD), such as platinum or nickel; and the negative temperature coefficient (NTC) thermistors, generally composed of semiconducting metal oxides. All these sensors share the same operating principle: the time evolution of their electrical resistance Among these resistive electro-thermal sensors, bead-type thermistors have the advantages of spherical or quasi-spherical symmetry, being non-traversing and small in size, unlike wire sensors (which are traversing or large in size) and hot film sensors . In conIn contrast, the non-linearity of NTCs has certainly been a major obstacle to the development of various thermal characterization methods using them. If NTCs are indeed used for transient thermal characterization of pulse-decay or temperature step types, however, we do not find in the literature any use in harmonic method of the source/sensor(s) mode ,19,20, wthe self-heating mode , in whicThe implementation modes of miniature resistive sensors used in material characterization can be classified into two main categories:While the 1D systemic modeling proposed in this work allows the simulation of both characterization modes, it is the self-heating mode that will be mainly exposed here.Simulation has become an essential tool in the development of electronic circuits. In electronics, the SPICE (Simulation Program with Integrated Circuit Emphasis) code, developed at Berkeley in the early 1970s , has beeA hybrid approach is used in the present work. The material to be characterized and the composite bead-type NTC (core and sheath) are all discretized in spherical symmetry  using a Godunov-type numerical scheme , while tIn order to avoid natural convection as much as possible during the development of the 1D systemic NTC model, glycerol, a non-ionic liquid with high viscosity, was chosen as test fluid.Because of the high hygroscopicity of glycerol, only fresh liquid  was used, and sealing precautions were taken to avoid dissolution of atmospheric water vapor into the liquid during measurement and storage.Accurate and reproducible determination of the thermal properties of materials using a miniature NTC bead-type thermistor requires a good understanding of the different heat exchanges that take place within the system. It is difficult, if not impossible, to consider absolute measurements of thermal conductivity and diffusivity using NTC thermistors, without a precise knowledge of their internal structure and of the influence of electrical contacts.The sensor used in this work is a miniature high precision epoxy encapsulated bead-type thermistor of type 44004 from Omega, whose resistance at a temperature of 25 °C is equal to 2252 Ohms . One of the most used is certainly the law of Steinhart and Hart [To measure the temperature and Hart :(1)1T=c0Simpler models can also be used , with onWe now review the main energy transfers that take place within the thermistor and its surrounding environment. During a typical liquid thermal characterization experiment, the average electrical power Radiative heat losses L of the connecting wires; use of metal or plastic mounting probe.Thermal losses Under the operating conditions described above, and for varnish insulated copper wires, with a diameter Therefore, heat losses via the electrical connections are considerable and can in no way be neglected in the modeling of the thermistor.Convective losses relation , which gample in .Using the values of In contrast, in the case of NTC immersion in water, considering a temperature difference Poor thermal contacts: There are two main sources of poor thermal contact here: the thermal contacts between the active core of the NTC and its protective sheath and between the sheath and the surrounding medium to be characterized. If the latter is a fluid (which is the case in the present study), we can assume that the corresponding sheath/fluid thermal contact resistance is negligible. In contrast, the contact resistance Considering the 2252@25 Omega thermistor used in this work, having an average external radius Despite its small size, a miniature bead-type NTC is a complicated object from a heat transfer point of view. Indeed, the presence of both metallic electrodes and connecting wires, but also of an active core that can be slab-shaped and surrounded by a prolate spheroid protective shell, does not strictly allow for attribution of particular simplifying symmetries to the However, and given the small size of the miniature bead-type thermistor relative to the volume of fluid to be characterized, the heat transfers outside the active core depend very little on its shape (sphere or slab), as illustrated by the finite element modeling results presented in core see b was adjcore see a. Note tBased on the results presented in a, and constant effective thermal properties: k  and r being the distance to the center of the sphere:An elementary mathematical model, that is frequently used to describe the thermal behavior of a miniature NTC of bead-type, consists of assimilating the whole composite sensor to a single sphere of temperature usivity) . The selsymmetry , with r According to the results and discussions of arts see : the actarts see c of effem et al. , the pret. Therefore, the energy balance of the highly conductive core can be written, using the spherical symmetry of the equivalent 1D model, as:Due to the usual high value of the thermal contrast  is an inert  material at rest, with no heat source term. In this case, its temperature (f) is a biological material, which obeys a differential equation of the Penne type (bioheat transfer equation), for example ,38:(9)1The initial condition to be considered for the partial differential Equation  or 9) i i9) is TWhile both situations  and 9)  9) can bFinally, a perfect thermal contact is assumed between the thermistor sheath and the medium to be characterized  to be characterized is assumed to be homogeneous, at rest, of semi-infinite extent and constant thermal conductivity The simultaneous solving of the (PDEs) partial differential Equations , 6) and and6) anThus, the 1D systemic approach presented in this work consists of solving the PDEs of the equivalent system, while, at the same time, taking into account the operation of the electronic circuits used to provide the power The electronic circuit that was used for both the experimental measurements and the systemic modeling is described in detail in the following paragraph.The electronic circuit shown in Since the temperature variations due to self-heating are generally of small amplitude (a few Kelvins at most), it is necessary to use an analog-to-digital converter (ADC) with a resolution of at least 14 bits. Moreover, as thermal phenomena are generally relatively slow , a sampling period of around 10 ms or more is, therefore, sufficient in most cases. A digital-to-analog converter (DAC) with a resolution of 12 bits or better can be used to provide the excitation signal The inputs ADC0 and ADC1 must have a sufficiently large input impedance The operational amplifiers (OA) used in circuit To make the set-up as versatile as possible, a power OA of type L272 (delivering currents up to 1 A without significant harmonic distortion) was systematically used.The working (or baseline) temperature A Measurement Computing (MC) USB-2537 multi-functions data acquisition board has been used for measurements, providing one 16 bits DAC output and two 16 bits ADC inputs (ADC0 and ADC1). The following precautions must generally be observed when implementing transient thermal characterization methods with the circuit shown in As mentioned before, an approximate 1D systemic modeling of a bead-type NTC is considered in this work, which consists essentially of assuming that heat transfers through the NTC present the spherical symmetry. This 1D systemic modeling of a bead-type NTC relies first on a suitable spatial discretization of the heat Equation  in the sThe discretization process of the present thermal problem, as well as different elementary applications of this discretization, is introduced in the present paragraph.M slices of equal thickness In all cases considered in the present study, we are dealing with  domains having the shapes of spherical shells, for which the discretization schemes are, therefore, perfectly similar. Therefore, we choose to discretize the partial differential Equation , which h1α∂∂tT/M see .Using explicit discretization schemes centered on the node rsion of  can be wsion of , which is composed of five ideal controlled current sources and one capacitor see . Note thTo test the relevance of the Godunov electro-thermal analogy proposed in this work, we first solved Equation  in the cness see a. FigureIt can be seen from The case of a constant heat volumetric source Using current sources at the boundaries rather than voltage sources see a, it is The numerical resolution being more demanding with this kind of boundary condition, it is generally preferable to use a more precise discretization in this case. Finally, solving the bioheat Equation  is also n et al.  for humasolution  for the The previous examples have shown that the approach developed in this work can handle a wide variety of spherically symmetric heat transfer problems, close to the problem of thermal characterization of materials using a bead-type NTC. Thus, we are now ready to propose a 1D systemic modeling of a bead-type NTC, immersed in a fluid at rest.We first consider the ideal case for which the thermal contact between the active core and the sheath is perfect, and the thermal losses along the connecting copper wires are not taken into account. In order to be consistent with the electro-thermal current densities gathered in In the case of an ideal thermal contact between the active core and the sheath, the second term of the right-hand side of  is alreaWe have found that simulating thermal characterization of materials by self-heating mode, using the ideal NTC core equivalent model shown in The ideal model shown in rest see . The NTCFinally, the complete 1D systemic model proposed in this work is represented in In order to adequately model the experimental conditions, Dirichlet boundary condition (BC) Note that it would also be possible to propose a more elementary 1D model than the one developed here. In this more basic model, the active core would be assumed to be punctual, and the heat transfer through the sheath would be modeled using a simple thermal resistance In this last part, experimental results obtained with different 44004 type NTCs are compared to the numerical results provided by the 1D systemic modeling developed in the previous paragraphs.Glycerol has been chosen here as a reference liquid in order to determine the values of the different effective parameters needed by the 1D NTC spherical equivalent model.As mentioned in  at 20∘C ) and the at 20∘C ,39) madeSince NTC manufacturers give very little information about the physical properties of the materials used to produce their thermistors, typical starting values were assigned to a number of unknown parameters used in the model. These values were further refined by minimizing the following quantity, over a large number of tests The model parameters values leading to the minimization of the model does not require the knowledge of the active core thermal conductivity the values of the value of the shell external radius Note that:A number of tests have been carried out with glycerol, which have led to the values shown in In order to test the relevance of the loss resistance .0mm see . The immThree thermistors from the same lot were tested, namely: NTC1, NTC2, and NTC3. Thus, it can be seen from the curves of Note that very similar experimental and numerical results were also found at other operating temperatures  see .When When Note that, in this work, the characteristic time Analyzing the curves shown in The 1D systemic modeling proposed in this work allowed to highlight the existence of two characteristic times of the thermal transfers, when bead-type NTCs are used for thermal characterization of materials by self-heating methods. The knowledge of these characteristic times can help to a better understanding of the operation of bead-type NTCs used for thermal characterization of materials, as it will be illustrated in the following paragraph.Various kinds of possible electrical excitations can be consider to heat the NTCs used in transient thermal characterization methods: current step through the NTC (using a precise current source) and resistance step (used in constant temperature heating techniques (CTHT)), and voltage step (using a divider bridge). From the point of view of the control circuit, thermal characterization using a constant voltage excitation is relatively easier to implement than CTHT; thus, it is very common to use a voltage step to heat NTCs in transient thermal characterization. Several signal processing methods can be considered in order to extract the thermal conductivity from the temporal variations of For example, Kharalkar et al. proposed to write the quantity ing form :(22)Pe approach was applied to the determination of the thermal conductivity Determination of the model parameters values 0 mm see .The model parameters values obtained from the glycerol thermal characterization see  were useVoltage step excitation of the NTC , a small amount of agar-agar powder has been added to 100W0G samples in order to limit the influence of free convection.The red dashed curves shown in ngly see . Thus, tFinally, the curves presented in The same measurements as in The values of the glycerol–water mixtures densities CoolProp .Finally, as in the case of pure water thermal characterization, the curves presented in As in the case of pure water and 40W60G mixture thermal characterizations, the curves presented in The series of measurements exposed in the previous paragraphs  were repThe results gathered in However, it is also observed from A new method for measuring the thermal conductivity of liquids, with the advantage of requiring only one reference liquid, has been introduced and described in this work. This new quasi-absolute approach has proved to be easy to implement, fast , and quite accurate, regardless of the thermal conductivity range covered during the measurements.The development of this new thermal characterization method was made possible through the use of a realistic 1D electro-thermal systemic modeling of the whole system , based on a Godunov-SPICE type discretization scheme. This systemic modeling has allowed to highlight two characteristic times of heat transfers within a self-heated thermistor, allowing for better understanding of the operating of bead-type NTCs when they are used for thermal characterization of liquids at rest.The discretization scheme and the 1D systemic modeling  used in the present study were fully described and documented in the paper. Note that the different computer codes (written in Python 3.8) used for the control of the electrical circuit and the processing of the experimental measurements, as well as the SPICE scripts used for computing the systemic modeling numerical results, are available upon request from the author.The perspectives of this work are numerous. First, from the point of view of thermal characterization, other viscous reference materials (such as pastes and gels) will be tested, and the method will be applied to the measurement of a wide range of thermal conductivities, as a function of temperature. We believe that the precise positioning of the NTC sensor at the specific immersion length By changing the boundary condition considered in the present 1D systemic modeling (at the interface between the insulating shell and the fluid), it will also be possible to consider the application of the present approach to the measurement of fluids thermal characteristics when they are flowing.Systemic 1D modeling of positive temperature coefficient (PTC) silicon thermistors (silistor) is also considered as a possible extension of the present work.


The controllabilitystudy is an integral part of chemical processdesign. In this work, the controllability of two special distillationtechniques, extractive distillation and pressure swing distillation,designed for the separation of azeotropic mixtures is investigatedwith dynamic tools. The control design interface of Aspen Plus andMatlab are applied for the modeling and evaluation of the two systems.Dynamic controllability indices are determined and aggregated in adesirability function. The results are compared to obtain efficienthelp for process design activity. The pressure swing distillationshows significantly better controllability features than the extractivedistillation. The reason can be the fact that in the case of the extractivedistillation, a third compound, the extractive agent, is added tothe system to carry out the separation, therefore making the systemmore complex. As far as the selection of manipulated variables isconcerned, in the case of the extractive distillation, the refluxflows should be preferred to the reflux ratios but in the case ofthe pressure swing distillation, the reboiler heat loads are preferredto the reflux ratios since those are closer to the controlled compositions.Both separation systems show worse controllability features if theproduct purity requirement is approaching to the pure products, thatis, close to 100%. Although the energy consumption of the pressureswing distillation is higher than that of the extractive distillation,it has the inherent feature that it can be automatically heat integrateddue to a column operated at high pressure and, as a consequence, highertemperatures. It affects the central nervous system andliver and has the potential to induce cancer.2 For this reason, THF should be controlled during production fromgetting into process effluents.Tetrahydrofuran (THF) is an excellent solvent and it is commonlyutilized within the chemical industry. It is also often used as astarting material or chemical intermediate in the synthesis of variousproducts such as adhesives, coating products, and cleaning products.The water miscibility of THF and its high vapor pressure promotesits transfer to the atmosphere and to both surface and ground waters.3 and pressure swing distillation (PSD)4 are two techniques that have been extensivelyused in the commercialized separation of the mixture of THF–water.The extractive distillation (ED) process requires an additional agentin the form of an entrainer or a solvent. From the literature, variousdesign criteria guiding the selection of a suitable entrainer suchas capacity, stability, noncorrosivity, cost, volatility, and selectivityare highlighted.7 The pressure swing distillation (PSD) process, onthe other hand, does not involve any additional entrainer or solvent.As a result, it is considered to be an eco-friendly process.THF is produced in most commercialprocesses as a mixture withwater. Ordinary distillation cannot separate the THF–watermixture because of the formation of a minimum boiling homogeneousazeotrope. Several alternative distillation techniques can be consideredfor azeotropic mixture separation. Among them, extractive distillation(ED)3 studied the separation by extractivedistillation and demonstrated the design option for the choice ofentrainer. An experimental work has also been used to compare variousentrainers for THF–water separation.7 For the separation of an equimolar THF–water mixture, Ghugeet al.8 simulated both extractive distillationand pressure swing distillation. Their works have been on selectionof the suitable process on the basis of the total annual cost (TAC).They have obtained the conclusion that ED has a lower TAC comparedto the PSD. These studies are based on steady-state process design.Extractive distillation is the most widely used method for THF–waterseparation, and several steady state designs are available. Xu andWang11 Such studies can be carried out through control structure design,which is a well-known field.13 Douglas14 has described the conceptual design of chemicalprocesses. Ziegler and Nichols15 have developedthe principle of process controllability, which is a process of achievingand maintaining desirable equilibrium values. Other authors, for example,Emtir and Fonyo,16 have documented thatthe mutual influence of process design and control may complicatethe process design activity. It is necessary that the synthesis ofcontrol structures should be considered over the early stage of theprocess design in order to make a complete assessment of the designalternatives.17However, dynamic controllability studies have to be carried outto validate the applicability of the technology in the industry.18 A good technologyought to have the capability to cope with the disturbance to a certainextent. Based on their steady-state findings, various researchershave investigated the dynamic control of EDs and PSDs.21 Luyben’s work detailed the dynamic control of the PSD withheat integration for separating a THF–water azeotrope.22 These researchers have presented control structuresand tuning procedures for use in Aspen Plus Dynamics for the processes.Iqbal et al.21 presented the control structureof ED using a Hi-Selector control logic to maintain the total entrainerflow rate.The control structuredesign studies should be performed duringthe process operation analysis in the presence of disturbance. Therate of feed flow and its composition always meet disturbance in thedistillation processes.23 The relative gain arraynumber  is used to find the bestmanipulated and controlled variable pairing. The lower the relativegain array number, the lower the system interaction at that frequency,with zero being ideal.12In this work, for the ED and PSD processes, we investigatethedynamics and stability by designing control strategies to effectivelyhandle the feed rate and composition disturbances with a focus onmaintaining product purity. We study the interactions among the controlloops as well as how the pairings of controlled and manipulated variablesaffect the behavior of the separation systems at different puritylevels. The control design interface (CDI) feature of Aspen Plus Dynamicsis used to accomplish linearization and controllability indices inthe frequency domain. Controllability indices are calculated usingMatlab and then aggregated in one parameter with the use of the desirabilityfunction. These controllability indices are the Morari resiliencyindex (MRI), conditioning number (CN), and the relative gain arraynumber (RGAno). MRI for the open-loop transfer function is describedas the minimal singular value for a specific input and output direction.The highest is the MRI, and the best is the system. The conditioningnumber is the maximum over the minimum singular value of the processopen loop frequency function. By using MRI and its associated CN,an open loop system can be evaluated to withstand model uncertaintiesand disturbances.22.124 and Ghugeet al.8 have explored the suitability ofDMSO and reported that it is efficient for the separation. The mostsuitable thermodynamic property model for this process is NRTL.25 The binary interaction parameters for the components were regressedby Aspen Plus and are shown in This simulationis on the basis of a case study of an equimolar feed of THF–watermixture. The feed flow rate is 100 kmol/h. DMSO is selected as theentrainer. Deorukhkar et al.8 The molar reflux ratio,total number of theoretical stages for the extractive and the solventrecovery columns (EDC and SRC), the mixtures of the feed stage andthe solvent feed stage for the extractive column, and the feed stagelocation for the solvent recovery column are considered. The workis completed for both 95.0 and 99.9 mol % THF product purities. The various design variables for the two columns are optimizedwith the use of the Aspen Plus built-in sensitivity analysis functionality.The sensitivity analysis is done according to the method describedby Ghuge et al.2.2The pressureswing distillation flowsheet is shown in Other design parametersare shown in 2.3.Based on thesteady-state simulations, the energy requirements of the two separationalternatives for both product purities are determined and presentedin Table 19 In spite the fact that the pressure swing distillationsystem needs more energy than the extractive distillation system,it has the advantage that it can be automatically energy integrateddue to the high-pressure column. This column, as a consequence ofthe higher pressure, operates on higher temperatures.The energy requirement results are in agreement with those of Luyben.8The amountof energy required increases with the purity of theproduct. This is also consistent with other literature.310 Theratio of height to diameter is set as 2. To allow for dynamic operation,pumps and valve pressures are set. As suggested from the literature,PI controllers are used.21 Variables are chosento manipulate the product compositions based on the control structuredesign heuristic criterion that the nearest potential manipulatedvariable is chosen. The first manipulated variable in each pairingdetermines the product A composition, whereas the second determinesthe product B composition. For the extractive distillation, one extracontrol loop, that is, pairing is needed for the control of the purityof the entrainer. The pairings are shown in The reflux drum sizes and the column sump sizes are calculatedbefore the simulation is exported into Aspen Dynamics. A 5 min holdup if 50% filled heuristic is used.26 The methodology for controllability analysisis established on the basis of the study by Gabor and Mizsey,17 which is the fastest methodology for calculatingthe controllability indices within the frequency domain.The built-in Ziegler–Nicholstuning method of ASPEN is used.Time constants are determined on the basis of load rejection investigationswith disturbances in the feed composition and feed flow rate.Inthis method, the state space representation for the dynamicsystem is obtained through the CDI module of Aspen Plus Dynamics.A script that matches the input and output variables is created, andthe desired matrices are calculated. In order to run the script, theinput variables selected must be fixed, whereas the output variablesmust be free. If the simulation is run until a steady state is reached,then the state space matrices are generated by CDI. On the basis ofthe matrices, the controllability indices can be calculated in thefunction of the frequency. A Matlab code is written that presentsgraphs of the controllability indices as functions of frequency.Morari resiliency index (MRI),condition number (CN), andrelative gain array number (RGAno).These controllability indices include the following:12 A largeMRI value indicates better controllability.MRI is defined as the least singular value of the open loopfrequencyfunction matrix for the process.The CN is definedas the ratio of the highest and lowest singularvalues of the process open loop frequency function matrix. The matrixis considered to be ill-conditioned if it exceeds 100, and thereforethe process is less controllable. The generally acceptable range ofCN value is 1–10.G. The definition of RGAis as follows:T indicates the transponationof the corresponding matrix. The RGA value denotes the interactionsamong the control loops in the process. RGAno is described as follows:I isthe unit matrix.In the case of RGAno, there existsa square matrix (RGA) for anonsingular square matrix Pairings with weaker interactions are preferred.These are depictedby low RGAno.28 is selected for such an aim. Individual desirability functions arecalculated for each controllability index, and their geometric averageis calculated to form the desirability function for a system usingthe formulas below:a and b are 0.0004 and 0.007, respectively, and D is theaggregated desirability function for a system.It is preferred that the three controllabilityindices are aggregatedin one number. The so-called desirability functionThis aggregatedvalue represents a way to perform direct comparisonsbetween different alternatives, that is, controllability alternatives.Desirability values closer to 1 are preferable as they indicate goodprocess controllability.4The controllability indices for the different processes are shownin Controllability indices and desirability values for the systemsinvestigated are presented in The pressureswing distillation has significantly highervalues than the extractive distillation system, indicating bettercontrollability features;Both separationsystems can be definitely better controlledat lower purity products, 95 mol %, than in the case of high purities,99.9 mol %. This is indicated by the desirability indices that arehigher with two orders of magnitude than those of the 99.9 mol % productpurity case;Comparing the two controlstructures for the extractivedistillation, R1-R2-Q2 and/or L1-L2-Q2, that one shows better controllabilityfeature, that is, higher desirability values, where the reflux flowsare used as manipulated variables both in the case of extractive distillationand pressure swing distillation;In thecase of the pressure swing distillation, thereare only two control loops and therefore two manipulated variablesfor the two product compositions. If the heat loads, that is, Q1-Q2are applied as manipulated variables, then the control shows bettercontrollability features and higher desirability values. This is inagreement with the heuristic, that is, the manipulated variable shouldbe close to the controlled variable.The comparison of the desirabilityindices is clear:5Two frequently studied and applied specialdistillation structuresdesigned for the separation of azeotropic mixtures, the extractivedistillation and the pressure swing distillation, are studied fromcontrollability point of view.According to the results, thepressure swing distillation has significantlybetter controllability features than the extractive distillation.It can be due to the fact that in the case of the extractive distillation,a third compound, the extractive agent, is added to the separation,making the system more complicated. Also, the time constants of thesystem determined from step responses are higher in the case of extractivedistillation.Although the pressure swing distillation has higherenergy consumptionthan the extractive distillation, but due to the high-pressure column,there is an inherent possibility for heat integration between thetwo columns, reducing the energy consumption significantly. It isimportant to note that heat integration is also possible in extractivedistillation but with lower percentage saving.When the productpurity is higher, the systems have higher timeconstants, and the controllability features become poor. This conclusionis in agreement with the experiences.if the reflux flowrate is low, thenthe control of theproduct composition is usually better with use of reflux flow as themanipulated variable andthe reboilerheat loads are closer to the controlledvariables, therefore these are the better manipulated variables forbottom product composition control.As far as the set of themanipulated variables is concerned, theselection of the reflux flow rates as manipulated variables provesto be better over the reflux ratio in the cases of extractive distillation.In the case of the pressure swing distillation, the reboiler heatloads are a better set of manipulated variables. The results are inagreement with the heuristic recommendations, that is,Theresults can support the process design step, and the controllabilityfeatures show preferences to the pressure swing distillation overthe extractive distillation.


The analysis of the normalized variations of the aforementioned parameters allowed the distinguishing of two behaviors: downfall in the first two weeks, and recovery in the last two weeks. Instrumental results suggest a physiological and ballistic  recovery after four weeks. As concerns the explosive skills, the observational data are insufficient to show complete recovery.This study proposes the instrumental analysis of the physiological and biomechanical adaptation of football players to a fatigue protocol during the month immediately after the COVID-19 lockdown, to get insights into fitness recovery. Eight male semi-professional football players took part in the study and filled a questionnaire about their activity during the lockdown. At the resumption of activities, the mean heart rate and covered distances during fatiguing exercises, the normalized variations of mean and maximum exerted power in the Wingate test and the Bosco test outcomes  were measured for one month. Questionnaires confirmed a light-intensity self-administered physical activity. A significant effect of fatigue (Wilcoxon signed-rank test  The COVID-19 pandemic lockdown has definitely changed the world of sports and football in particular. All agonistic  and amateur tournaments were canceled or postponed by several nations. Because of strict safety measures adopted by football clubs, athletes in Italy underwent a two-month forced rest period without any form of agonistic training, which is an extremely peculiar situation from a both physical and psychological point of view. Although individual training programs were assigned to football players, the absence of an athletic trainer and the prolonged self-isolation could have played a decisive negative role in the athletes’ physical preparation, especially at the semi-professional level. In general, elite players’ off-season rest period lasts from two weeks to a maximum of four weeks, in which training sessions are still present but reduced in terms of intensity . Indeed,social” components. Indeed, psychological and motivational factors assume an essential role in keeping a healthy fitness and achieving optimal performances [According to a survey carried out by Pillay et al. on several athletes, 65% of male participants trained every day during COVID lockdown while 23% every alternate day. Nevertheless, the training load and intensity were less intense for the great majority of the athletes . Negativormances . Social ormances . In addiormances ,8. The aormances , the preOur opinion is that controlled monitoring of athletes’ response to a constant fatigue protocol could give useful information on their recovery process and, so, the correct timing for a return to sport. In order to achieve this objective, the Wingate test , the BosAmong all the aforementioned parameters, the mean heart rate could give useful information about the physiological adaptation of the participants’ bodies during the duration of the study while the Wingate and Bosco tests allow us to study the evolution of the explosive and ballistic abilities of the athletes and, so, their level of performance. In particular, the Wingate test is an anaerobic test that could be commonly used to quantify anaerobic power for the evaluation of anaerobic fitness levels and to assess anaerobic training effects . It consThis study takes place as a unicum for the instrumental assessment of athletes while regaining physical fitness after a forced stop, given the extraordinary nature of the situation. Indeed, the forced rest period we experienced last year was a mere consequence of the pandemic and it cannot be considered as an extension of the traditional off-season period. In particular, the lockdown happened from March to May, when the competitive activities were still ongoing (while the off-season period is at the end of the activities by definition) and it introduced several additional factors that are not involved in a normal off-season period . Several studies have already focused on the effects of the pandemic lockdown on athletes, giving useful information on the preventive procedures to carry out for their correct re-introduction in training ,19. HoweEight semi-professional football players  were involved in tests. Athletes, in accordance with the Helsinki protocol, signed an informed consent form and filled out a questionnaire to take part in the tests. No participant had a record of cardiovascular/respiratory disease nor evidence of neuromuscular diseases. The present study was approved by the joint ethical committee of the Scuola Normale Superiore and Scuola Superiore Sant’Anna . Participants filled a questionnaire on their training activities during the forced rest period, to report the type and amount of their physical activities during the 2-month-long lockdown. The short questionnaire also included information about the change in habits in the self-administered training session before and after the lockdown.The acquisition protocol was carried out in an uncontrolled environment . Athletes performed an initial 15 min warm-up phase of dynamic stretching, joint mobility exercises, and core potentiation. The training program in the month of recovery consisted of a fatigue protocol based on high-intensity lactic-acid exercises (shuttles with direction changes) in an uncontrolled environment  to better simulate standard football training. In particular, the protocol was structured as follows: 5 main phases spaced out by 2 min rest period. In the first and last phases (5 min) athletes had to continuously perform two-way 25 m shuttles in 10 s separated by 10 s recovery time each. The remaining phases are composed of three-way 25 m shuttles to be completed in 10 s, separated by a 10 s recovery time each .fT) and contact time (cT) during jumps in the Bosco test were directly estimated from the accelerometers of the corresponding Magneto-Inertial Measurement Units (MIMU), as introduced in our previous work [fT and cT represent the starting point from which all the other parameters were estimated.During the training sessions, participants wore a smartwatch  for real-time heart rate monitoring and GNSS tracking. In particular, the Apple Watch measures the heart rate by photoplethysmography, which returns an estimation every 5 s . Unfortuous work . Tf and From MIMU signals four groups of parameters were computed:(i)fT) and contact time (cT). As mentioned before, these two variables represent the starting point from which all the other parameters were calculated;Time parameters: flight time ((ii)m is the body mass and Power parameters: mean exerted power;leration .(iii)maxh [RSI) [Displacement parameters: maximum height (hmax ) and reaax [RSI) ;(2)hmax(iv)sfn), which is the average stiffness of the musculoskeletal system, modeled as a spring, during the ground contact phase [Kinematic parameters: leg stiffness sAs for the Wingate test, the aforementioned parameters were estimated before and after the fatiguing protocol to assess their variations due to fatigue. In particular, all the parameters  were measured in training sessions for one month. A preliminary training session (25 May 2020) was carried out to better re-introduce the athletes’ to intense physical activity. This session consisted of a simplified version of the fatigue protocol and was not included in the analysis. The subsequent training sessions were weekly grouped, as follows: two acquisitions during the first (26–28 May 2020) and second weeks (1–3 June 2020) and one acquisition during the third (9 June 2020) and fourth weeks (17 June 2020). In order to define a single set of parameters for each week, the mean values of heart rate, mean and maximum power, and Bosco test outputs were considered in the weeks with more than one acquisition.An in-depth analysis of the training habits’ effects on performance and physiological adaptation was carried out analyzing the questionnaire information, by reporting descriptive statistics.The Kolmogorov–Smirnov test was used to test the normality of the distribution of the instrumental parameters. Once it was confirmed that all the parameters belonged to non-gaussian populations, their comparison was carried out using non-parametric tests. In particular, the Wilcoxon signed rank-sum test was used to verify if there was a difference between pre and post-effort parameters each week. Furthermore, the effects of fatigue on the Wingate performance were estimated using the Cliff’s Delta effect size.In addition, the temporal evolution of the parameters was evaluated through Friedman’s test, which corresponds to repeated measures non-parametric one-way ANOVA, and the Bonferroni test for the post hoc analysis. This statistical test allowed the assessment of whether the athletes underwent a recovery in physical strength by choosing the variable “time” as the test comparison way. The same comparison was carried out on GNNS data about the total distance covered each day, in order to evaluate the reproducibility of the fatigue protocol. To assess the inter-subject variability, the Coefficients of Quartile Variations (CQV) of the mean heart rate and total covered distance were computed. As concerns power parameters and Bosco test outputs, their normalized variations were considered in this study to reduce the effect of inter-subject variability.The aforementioned tests were carried out with the software “Matlab”  assuming a significance threshold α = 0.05.The results of the survey among the eight athletes who participated in the study are reported in Friedman’s and Bonferroni tests did not show significant differences between the four weeks in terms of covered distances. . Low valConcerning heart rate data, Friedman’s and Bonferroni tests showed significant differences between the first two and the last two weeks, thus suggesting a conceptual split in the data set in two main phases : in the Athletes who reported less than 45 min of daily training during the lockdown were characterized by higher mean heart rates  and morep < 0.05—Results from the Wingate tests objectively confirm that fatigue reduces significantly the athletes’ ability to exert power. Indeed, a significant decrease in the exerted power was observed between the acquisitions taken before and after the fatigue protocol in all the four experiment weeks  for the mean and maximum power  were significantly influenced by fatigue (p < 0.05—p < 0.05) for all the parameters. The Wilcoxon signed-rank test showed that three out of six parameters extracted from this test  biomechanical performance by means of the Wingate and Bosco tests, which gave information on the athlete exerted power and ballistic ability respectively and (ii) physiological adaptation by means of the mean heart rate analysis during the training session. The reason for selecting the Wingate test, already adopted in several fields  is thatp < 0.05 for the mean heart rate) were found in accordance with studies on the fitness recovery in normal pre-season sessions [p > 0.05 for the Wingate parameters  across the weeks. This phenomenon could be explained by the fact that the pool of participants is limited to only eight athletes, limiting the power of a statistical analysis across the weeks. The aforementioned trend is also confirmed by the Bosco test outputs , which were measured using single wearable inertial sensors, placed on the right foot. In addition, the Wingate test showed significant effects for all four weeks, comparing measures before/after effort, while for the Bosco test parameters differed only for the first three weeks. In other words, the performances before and after the fatigue protocol in the Bosco test suggested the recovery of the athletes’ ballistic ability was achieved at week four. These results could lead to two possible interpretations: (i) the Wingate test, results in more sensitivity to the fatiguing protocol than the Bosco test; and/or (ii) athletes recovered their ballistic ability faster  than their explosive ability .Relevant differences between the first and last week  followed by a recovery, which has a triple aspect: (i) a physiological one ; (ii) an explosive one , which is characterized by a slow recovery (pre–post fatigue parameters keeps their significant difference after four weeks); and (iii) a ballistic one , characterized by a recovery that is no longer detectable at week four. It could be speculated that in the downfall phase athletes were not able to metabolize the working load of the training sessions because of the muscle weakness due to prolonged rest periods. Elements to confirm this hypothesis comes from the analysis of two subgroups of athletes building on the amount of time spent training during the lockdown. Athletes’ who trained more than 45 min were characterized by lower and less variable mean heart rate values and smaller variations in the exerted power, showing better adaptability. On the other hand, participants’ who trained less than 45 min were characterized by higher heart rate values , slower physical adaptation , and bigger susceptibility to fatigue . Similar results were found for the Bosco test parameters analysis.To the authors’ knowledge, no previous studies have monitored the recovery of the physiological behavior and ballistic/explosive performance after a prolonged and abnormal forced rest period like the one we have experienced last year. In particular, most of the research has focused on the comparison between the off-season and the end of the pre-season periods, or between the end of the off-season and the in-season, showing the negative effects of a long rest period and the positive outcomes of a training program after it. Only Grazioli et al.  analyzedCaldwell at al.  found siIn the Silva et al.  review pFessi et al.  measuredThis study is not without limitations. The first open issue of this work is the lack of a pre-lockdown assessment and the lack of an accurate reporting of physical activities conducted during the lockdown. In particular, the proposed questionnaire was intended as a qualitative report and did not allow us to accurately estimate the amount of training.Another limitation of the proposed study is the debated reliability of the Apple watch in estimating the heart rate at high intensities workouts. The scientific literature is not clear about the topic. Some studies ,31 showeIn conclusion, even if the pool of tested athletes was limited (n = 8), thanks to the instrumental approach we achieved some preliminary responses to better understand how such an unpredictable stop from team training would affect the response to fatigue of soccer players. Athletes’ biomechanical response was characterized by an initial rapid decrease in the performance  in the first two weeks with a negative peak in the second week, followed by an improvement phase due to recovery. In addition, physiological behavior  followed a similar pattern characterized by a fatigue phase  and a recovery one . Instrumental data between the last two weeks did not differ significantly in the Bosco test, suggesting that a ballistic recovery would need at least 3–4 weeks of training. Elements indicative of a full recovery of explosive skills were not confirmed in the four weeks observation window.


Health support has been sought by the public from online social media after the outbreak of novel coronavirus disease 2019 (COVID-19). In addition to the physical symptoms caused by the virus, there are adverse impacts on psychological responses. Therefore, precisely capturing the public emotions becomes crucial to providing adequate support. By constructing a domain-specific COVID-19 public health emergency discrete emotion lexicon, we utilized one million COVID-19 theme texts from the Chinese online social platform Weibo to analyze social-emotional volatility. Based on computed emotional valence, we proposed a public emotional perception model that achieves: (1) targeting of public emotion abrupt time points using an LSTM-based attention encoder-decoder (LAED) mechanism for emotional time-series, and (2) backtracking of specific triggered causes of abnormal volatility in a cognitive emotional arousal path. Experimental results prove that our model provides a solid research basis for enhancing social-emotional security outcomes. The pandemic of the novel coronavirus disease 2019 (COVID-19) highlights the vital role of online social media in the development of sudden public health. When the public is in home isolation (to avoid outdoor gathering activities and to reduce chances of infection), people are more likely to share on social networks benign symptoms and conditions , as well as inconveniences associated with those conditions [Several scholars have been concerned about the psychological impact and have identified that the media played a vital role during the COVID-19 pandemic because the public sought security through excessive use of Internet information related to the events ,3,4. To We integrated both abnormal emotional volatility detection and triggered causes into a perception model to dynamically monitor the public’s emotional reactions. The volatility is reflected in emotional valence, which is generally considered to be an expression of emotional intensity and strength. We first constructed a discrete emotion lexicon that for measured and monitored the public’s emotional state with regard to COVID-19 public health emergencies. In addition, we proposed a public emotional perception model that integrated deep learning to detect abrupt timing by the stimulus. Experimental results show that our domain-specific emotional lexicon can capture the public emotional situation, and the perception model not only provides a solution to real-time dynamic monitoring of the public’s emotional state but also serves as an aid for detecting actual emotional causes. Public health emergencies concern the safety of people’s livelihood, and our research provides a solution using the online social media context to identify in advance potential emotional risks. The remainder of this paper is organized as follows: In contrast to the existing studies on event evolution and emotion classification, we managed to solve how specific discrete emotions depict the psychological level of the public during an emergency. We refined the relevant research in the two subsequent sections: Lexicon-based sentiment analysis has shown promise for analyzing the impact of user emotions on social networks ,10,11. TTo this end, it was necessary to construct an emotional lexicon based on human cognitive psychology, which is suitable for accurately describing the changes of public emotional and stress states in online social media during the COVID-19 pandemic.There is a lack of research on the specific factors influencing public mentality during the COVID-19 pandemic , and theHowever, our definition of the cause of emotion is different from the prior ones. We maintain that emotion at the semantic level is the description of the emotional body and emotional target object, which can be achieved by syntactic and lexical analysis. The emotional cause was proposed based on the OCC model of emotion , a rule Therefore, we detected the most obvious type of emotions among the public due to their different psychological acceptance of media information and government measures, analyzed the effect of different causes of abnormal emotion, and emphasized the most extensive public risk factors.https://www.datafountain.cn/competitions/423, accessed on 3 March 2020) for the period between 1 January 2020 and 20 February 2020, during which time a total of 1 million Chinese Weibo data were collected. We calculated the emotional categories and emotional valences of different individual public posts within the unit time interval to integrate the public collective emotions and detect hot events. To cover all of the candidate events, we referred to an emerging social media site, zhiweidata.com, as well as the traditional media Nanfang Metropolis Daily “Special COVID-19”. We performed the LDA topic model in the test corpus to make the detection of epidemic events more representative. For the evaluation of perplexity and coherence score, the optimal number of topics equaled 7. Other relevant reports had different divisions on the number and type of topics according to the contents and objects. Our research team individually labeled the major COVID-19 events into topics by personal cognition of real events, in addition to topic classifications made by news reports. Finally, we summarized 7 topics (listed in Table 2) based on the content from the open data we used and used the LDA topic model to label the corpus by the dominant percentage score. Meanwhile, the time points were labeled in the form of text similarity to major events and served as the basis for our response to the public. The experiment selected the 230 COVID-19 themes dataset :latility ,25. http://www.sogou.com/labs/resource/ca.php, accessed on 20 June 2017) and satisfied the maximum conditional probability. In addition, we extracted high-frequency word sequences of the test corpus and expanded the domain emotion lexicon by word vector similarity. On the basis of calculating the cosine distance, we used the k-NN algorithm to locate the most relevant candidate words that matched the target words. By adjusting the threshold range of k, we determined the emotional category of the new candidate words and assigned value to them. After repeated experiments and manual verification, we chose k = 5 given the premise of similarity greater than 0.6, and finally expanded to 2455 domain-specific extra words on the topic of the COVID-19 public health pandemic.Secondly, we combined context representation by using the Google open source tool Word2vec and the CBOW language model. We trained the semantic word vectors from 3.5G SogouCA  from the lexicon. Following the experience of previous work, volatility was considered with different levels of valence. With the increase in valence, the number of words in the lexicon and domain words decreased continuously, but the effect of emotional volatility was more noticeable under the same situation. Because a value of 0 in a dimension means there is no emotional expression in the corresponding dimension, we removed the non-zero valence lower than a certain threshold for all eight dimensions. Then, we statistically compared the original with the expansion, as well as with the words retrieved in the emotion lexicon, the coverage of the test corpus, and the count and coverage of COVID-19 domain words under different valence thresholds in The experiment showed that the expanded domain lexicon significantly improved the matching of the COVID-19 corpus compared with the original. The coverage of both the domain words and the test corpus increased 5-fold, reaching 74.84%. After testing and observing the change in emotional volatility under each threshold, the coverage rate of the corpus and field decreased significantly after 0.4. Therefore, we chose 0.3 as our optimized threshold, where the coverage rate of the corpus was still close to 50% under the condition of 42.52% coverage rate of field words, and the emotional volatility of eight dimensions was still relatively obvious.We observed whether the improved lexicon was consistent with the emotional fluctuations of the public. For each microblog content, there is also the phenomenon of emotional co-occurrence. This causes the valence in each dimension to weaken, and it is the reason why we optimized emotional valence to 0.3 to intensify the emotional volatility. The calculation method of emotional valence within a unit time interval We outline the data timeline in The results show that the adapted emotional lexicon is scientific and effective in psychological quantification. Therefore, as far as discrete emotion research is concerned, it is necessary to analyze the volatility of each emotion carefully to find the types of emotions that are specifically relevant to the events.In the midst of a public health security emergency, the public’s emotional state is more sensitive and fluctuates at the time point where the reaction occurs after being stimulated. It is difficult to locate the abrupt time points of public emotions because the data are sparse. This poses a great challenge when trying to create an effective model. Thus, we propose an LSTM-based attention encoder-decoder (LAED) mechanism for emotional time-series to solve this problem, as illustrated in The model is trained to reconstruct “normal” emotional time-series by taking the most recent emotional time-series instance as the encoder input and jointly predicting several future emotional time-series instances as the decoder output. Then, the reconstruction error between the real target and the decoder output is obtained and used to compute the likelihood of an anomaly at this time point. In the training process, the model only considers a normal instance and predicts a normal instance. The intuition is that when the model encounters new data, including normal and abnormal instances, the reconstruction error of the abnormal emotional valences would be higher than that of the normal ones.q = 1) if the prediction accuracy was low. In this process, We built a continuous time-series on The context vector Similar to Malhotra , we diviThen, we estimated the parameters To separate the abrupt emotional time points from emotional time-series, we utilized a simple and effective threshold adjustment method to find the optimal The purpose of our study was to identify major events that caused an emotion outburst. Because of the limited information available while quarantined at home, the public paid significant attention to the pandemic news. However, depending on the release time of media reports and the transfer behaviors of online users, emotional volatility inevitably delayed or persisted. For this reason, we pinpointed the cause of the sudden change in the preceding period of the time window. Based on what we found, the most obvious emotion types inspired the public in From the perspective of semantic features, each event has a unique corresponding eight-dimensional emotional valence; thus, we compared the difference in emotional distribution of the event and of the day. The distribution distance was measured by the Kullback–Leibler divergence . Then, wvalenced reactions in the OCC model provided an important theoretical basis for tracing abnormalities. Emotion theory provides a psychological foundation for human cognition so that the exact discrete emotion is ruled in its elicitation condition. In particular, the OCC theory contains detailed discrete emotions in a context concerning the different consequences of events, actions of agents, and aspects of objects, and OCC theory is widely used as a computational model to depict the human cognition process. It identifies the underlying cognitive structure and emotional dimensions . This apfocus in the OCC model in Each discrete emotion is elicited by a unique pattern of cognitive appraisals, and situations with the same appraisal pattern will induce the same emotion . At the We computed the emotional distribution of public opinion events and topics according to the abnormal emotions found by the LAED model. We tracked the emotion arousal path to ensure each topic was related to the emotional elicitation conditions. Thus, we obtained the emotional distribution of the candidate scenario in The method of emotion arousal path highlights the properties of emotion, which identify the issue of finding the most influential event according to the content. Because events are diverse, the emotion arousal path has a fixed induced path from the cognition process, so it more accurately positions the induced causes. The larger the KL value, the greater the difference between the two distributions. In brief, while the situational distribution was the most similar to the overall distribution of the day, we obtained the smallest KL value, which meant that this situation was more likely to influence the public emotion. Thus, we clearly identified emotional spikes when events occurred using the emotional arousal path and target-triggered causes.For the triggered reasons, we chose the order of emotion-induced ranking metrics in precision in Equation (10) and mean average accuracy (MAP) in Equation (11):In this section, we provide the results of this study. Our emotional perception model was able to position an abrupt time point during COVID-19 that reflected the superiority of our model. Additionally, we include a visual display of pertinent research and reach important conclusions. The evaluation criteria for the model were geared toward the emotional change detection task. We used the LAED model to detect abnormal emotional valence. Depending on the training of regular “normal” emotions on The set Before we present the LAED model performance, we demonstrate eight emotional volatilities in terms of the day. As shown in in On the top of the figure, all four volatilities are positive emotions, and the bottom are negative emotions. Overall, most emotional valences showed a downward trend in the early two months, as shown by the red dotted line, except for anxiety and hate. There were two main findings:(1) There was an upward trend of the negative emotions: hate and anxiety. Hate maintained a higher valence from 20 January, when academician Nanshan Zhong announced the phenomenon of “human-to-human” transmission, where we pinpoint a red dot in the figure. This news also triggered anxiety to an obvious increase, with the greatest anxiety identified on 29 January, when all 31 provinces in mainland China launched a first-level response to public health emergencies; thus, we marked them as well. pandemic news and data reports and scientific breakthroughs and knowledge dissemination, which correspond to the emotion arousal path of Aspects of Objects and Consequence of Events. Thus, we believe that hate and anxiety, which differ from other emotions in volatility trends, are more sensitive and accurate in emotional cause tracing.Notably, these two events belong to the topic of emotion arousal path, surprise was identified as a compound appraisal both of Actions of Agents and Consequence of Events; thus, tied to the reaction of agents and events, where Wuhan was the agent for the public in focus. Furthermore, we also found that the trends of sorrow and anger were similar to those of the positives, possibly because the national pandemic prevention measures eased the emotion of the public.(2) Almost all positive emotions showed a significant downward trend, where the red dotted lines appear in a similar direction in January. It was on 20 January that all positive emotions dropped sharply in the black volatility line, and almost all of them reached the lowest valence as a result. The difference is that the spike of surprise was quite early on 4 January, when Wuhan reported a total of 44 unexplained cases of viral pneumonia. In the We need to determine the reasons for these abrupt emotional changes based on the LAED model and cognitive emotion arousal path. Although we observed valence according to the results of daily statistics, the abnormal time point cannot be specifically identified owing to the lack of data on a daily basis. We present the model effect of emotional abrupt time point detection based on hourly intervals in months, and use the January data, a total of 744 h, as an example. The reason we selected January data was because COVID-19 was unknown during the initial stage. It provided a comparison of emotional volatility before and after policy control and social governance.Based on the results of our previous analysis, hate, anxiety, and surprise were found to be attractive because they are different from other emotions. In our model detection results shown in , the lowx axis around 380, the first higher position of hate, the National Health Commission did not rule out the possibility of human-to-human transmission and thus triggered a significant hate valence increase among the public. Then, around the 490 position, the emotion surge was reignited owing to the human-to-human transmission. The follow-up was identified around position 580, when the global high-risk events were defined by the WHO, and the Red Cross Society reported more events. The positions of the emotional time points were seen to correspond completely with the pandemic public opinions.Hate has an obvious valence rise process, and the overall trend of volatility shows several key event detections in As pointed out in Although the intuitive sense in COVID-19 is the dominance of negative emotions, our government is always issuing policies, opening information, and vigorously promoting positive emotions. Surprise, the volatility varying greatly in Many spikes and abnormalities appear after each data update and the diagnosis treatment, which indicates that the public paid attention to the world around them as well as the pandemic prevention plan when quarantined at home. In addition, we found that the valence at night (in a day) is much greater than during daytime trading. Although the government announced relevant news and policies in the daytime, the media generally reported it to the public on the evening news. Considering the spread of information transmission, the fluctuations of public emotions were especially apparent between 10:00 p.m. and 12:00 p.m. This situation was identified in all eight emotions.We show that the emotional distribution of events is an important factor that can be traced back to the overall emotional response on each particular day. We can also visualize the distribution of eight-dimensional emotions . We compared the Pearson correlation coefficient between infected persons and discrete emotions and found some interesting phenomena.p < 0.01), and surprise was negatively correlated with the number of infected persons (p < 0.05). When time shifts to late January, on 31 January, the total number of confirmed cases was over 10,000, while the number of suspected cases exceeded 20,000. We first construct the correlation heat map for January in Next, we show the correlation for February in Our research summarized the evolution the law of public emotions in public health emergencies. However, the labeled anomaly of the emotion abrupt time point is rare, which is always a major challenge to the anomaly detection task. Moving forward, we will stick to our social-emotional perception model to discover other potentials in public health, and conduct extensive experiments on other domains and tasks, such as public safety, to further validate the model’s feasibility and stability.Our study focused on monitoring and measuring public emotions embedded in the social media context during public health emergencies, and provided three contributions: (1) the construction of a discrete emotion lexicon representing the public under the state of the COVID-19 pandemic, (2) the accurate detection of emotion abrupt time points for different discrete emotions affecting the public, and (3) the location of specific emotional causes that induced abnormal emotion following the emotional arousal path, using the OCC emotion model. The public emotional perception model has a more prepared traceability scheme for the induced causes and has confirmed that information disclosure including prevention and control measures have driven positive emotions, such as love and expect.


The nonrenewable nature of fossil energy has led to a gradual decrease in reserves. Meanwhile, as society becomes increasingly aware of the severe pollution caused by fossil energy, the demand for clean energy, such as solar energy, is rising. Moreover, in recent years, electronic devices with screens, such as mobile phones and computers, have had increasingly higher requirements for light transmittance. Whether in solar cells or in the display elements of electronic devices, transparent conductive films directly affect the performance of these devices as a cover layer. In this context, the development of transparent electrodes with low sheet resistance and high light transmittance has become one of the most urgent issues in related fields. At the same time, conventional electrodes can no longer meet the needs of some of the current flexible devices. Because of the high sheet resistance, poor light transmittance, and poor bending stability of the conventional tin-doped indium tin oxide conductive film and fluorine-doped tin oxide transparent conductive glass, there is a need to find alternatives with better performance. In this article, the progress of research on transparent electrode materials with sandwich structures and their advantages is reviewed according to the classification of conductive materials to provide reference for research in related fields. As the nonrenewable and highly polluting nature of fossil energy sources and the relatively high carbon emissions gain more attention from society, the importance of finding efficient and easily accessible clean energy sources is self-evident . Solar eThe development of TCO has been ongoing for more than a century. TCO was first discovered in 1907 by Bakdeker, who prepared transparent CdO conductive films by sputtering and thermal oxidation ,9. More Because the demand for transparent conductive films has been high owing to the mass production of electronic devices, many researchers have started to seek alternatives to ITO to obtain new transparent electrodes with easily available raw materials and excellent performance. At the same time, to meet the flexible requirements of many new products, such as portable flexible solar panels, emerging folding screen mobile phones, curved display devices  and wearAlthough the conventional single-layer transparent electrode has the advantage of a simple structure, the simple structure makes it difficult to have multiple performance advantages simultaneously. The conventional single-layer transparent electrode is often limited by a certain aspect of its performance, resulting in obvious shortcomings that make it difficult to meet the needs of different applications. In recent years, sandwich structure transparent electrodes have attracted much attention because of their relatively low preparation cost and preparation difficulty , their ability to synthesize the advantages of different materials through the synergistic effect of each layer of materials, their superior mechanical properties and flexibility, and their higher light transmittance and electrical conductivity compared with single-layer transparent electrodes . At presAs conductors, metals tend to have low resistance and good flexibility. Using metals as the materials for composite electrodes can strengthen the mechanical properties of composite electrodes and enhance their electrical conductivity. In general, the light transmittance of a metal is negatively related to its thickness, while the electrical conductivity of a metal is positively related to its thickness. Therefore, to use metal as a component of transparent electrodes, it is necessary to make the metal have a certain thickness that achieves both high light transmittance and low electrical resistance. To meet the requirement of light transmittance, the metal thickness should be controlled at least within 10 nm . At the Many recent studies have been carried out based on metal layers as the conducting body. For example, Bingel  used theChoi et al.  used a s0) for the IZO film exceeds 12 after less than 400 bending cycles with a bending radius of 5 mm, as shown in In terms of transmittance, the transmittance of Ag fiber in the visible light band (400–800 nm) is almost constant at approximately 90%. The light transmittance of the Ag fiber/IZO composite electrode increases from about 50% to greater than 80% in the 400–500 nm interval and fluctuates around 80% in the 500–800 nm interval. It can thus be assumed that the main influence comes from the IZO. However, even though the IZO reduces the transmittance, the transmittance is still better than that of the single-layer IZO film from the control group set up in the study. In addition, the structure has excellent mechanical properties in bending and electrical conductivity. The relative change rate /quartz substrate structure. The undoped Ga2O3-NP solution was first spin-coated on the quartz substrate, which was dried, immersed in SWNT, and dried in nitrogen . The transmittance was basically higher than 80% with a wavelength of 300–400 nm and was between 90% and 100% with a wavelength of more than 400 nm. However, the resistance of the resultant composite structure was still much higher than that of commercial ITO films; however, the problem may be solved by doping the Ga2O3-NP.In a study by Kim et al.  a two-lanitrogen . The I–Vnitrogen  and lighnitrogen  of the S2O3 nanostructures could achieve excellent light transmission. Future work in this direction should focus on simultaneously enhancing the electrical properties and optical properties of these kind of transparent conductive films in order to expand their applications [The above-mentioned works related to the new structures or novel compositions. Although the low sheet resistance and the high light transmission can still not be well balanced in these works, there are still some points can be ported to the future work. For example, the ZnO-NR structure electrode in the first study of this section can be used as an electron transport layer in solar cells and can increase the efficiency of photovoltaic conversion . In the ications .Metal compounds include the typical metal oxides. Some metal compounds have electrical conductivity and light transmission to a certain extent simultaneously, making it possible to prepare thicker composite electrodes. However, in recent years, there have not been many composite electrodes based on metal compounds with new compositions or structures. There are two possible reasons for this. On the one hand, conventional electrodes of the same type based on such materials as ITO and AZO are very mature; on the other hand, metal compounds do not have an advantage in terms of conductivity, which is the most important property of electrodes. In addition, it is difficult to achieve a greater advantage in light transmittance at the same time, because the mature electrodes themselves already have high light transmittance. Nevertheless, some new worthy structure ideas are being adopted and developed, possibly leading to the emergence of more excellent electrodes.At present, the most representative and promising carbon-based material is graphene. Since its invention in 2004, graphene has been favored in many fields because of its excellent thermal conductivity, electrical conductivity, mechanical properties, and light transmittance. Because of its excellent electrical properties and light transmittance ,43 graph2–103 Ω/sq when the light transmittance at a wavelength of 550 nm of the multilayer graphene–graphene scrolls is in a range of approximately 87–97%. The mechanical properties of the three-layer graphene–graphene scrolls structure are also excellent, with only an eight-fold increase in resistance at 1000 strain cycles compared with an approximately 100-fold increase in the control. When a graphene layer breaks under bending state, the graphene scrolls can also act as a conductive structure between the cracks. Due to its long length, the graphene scrolls can usually bridge cracks of micron width, thus avoiding the deterioration in sheet resistance. This is also the common strategy used by most flexible electrodes to solve the problem of flexible conductivity. Sometimes in multi-layer structures there is a situation where a membrane layer is not flexible or is not flexible at all. In this case, the adjacent flexible layer will bridge the cracks in the less flexible layer, and the non-adjacent flexible layer will continue to perform its electrical conductivity so that the overall electrical conductivity of the films does not change significantly.Liu et al.  develope3/graphene/MoO3 structure n/MoO3, i.e., the (MG)nM structure with n = 5, the light transmittance was still more than 85%, and the sheet resistance was approximately 200 Ω/sq. The team also studied (graphene)n/MoO3, i.e., the GnM structure. It was revealed that the GnM structure had a small increase in light transmittance (~1.5–3%) and an increase in sheet resistance of 150–300 Ω/sq. The overall performance was inferior to that of the (MG)nM structure. In a subsequent mechanical test using (MG)3M electrodes on polyethylene terephthalate (PET) substrates, the relative rate of change in the sheet resistance of the sample remained almost constant at approximately 0% for 1000 repetitions of bending with a 10 mm radius of curvature and 1% strain. In contrast, even bending tests performed with a 5 mm radius of curvature and 2% strain resulted in a relative rate of change in the range of only 3–7%. The thermal evaporation and transfer printing processes used in this study may inhibit the creation and expansion of cracks within the layer.Cho et al. , howevertructure . Becausefunction , p-dopinction [3 ,49. The The above two studies show that, although the light transmittance of the composite electrodes is quite good, the sheet resistance is on the order of 102 Ω/sq for the smallest value and 103 Ω/sq for the largest value. This resistance is still high for an electrode, which inevitably leads to unsatisfactory product performance in practical applications or the heating of the electrode material over a long period of time. Combining graphene with the metal layer introduced in the first part of this review may lead to better sheet resistance. The structure developed by Chen et al.  used a cThe films prepared in these three works in this section all perform well, with both low sheet resistance and high light transmission. The pure graphene electrode used in the first study has excellent light transmission and mechanical properties. The second group has a thin thickness comparable to that of electrodes using layered metals. The third group combines the advantages of graphene and metal nanowires; although slightly lower in light transmittance, the sheet resistance in this study is to the most closed to that of the metal layer electrodes. Graphene-containing transparent conductive films are full of potential.As a focus of research in recent years, graphene is indispensable in the field of transparent electrodes. While the sheet resistance of graphene is not ideal when it is used alone, its comprehensive performance can be enhanced when combined with metals. For example, the mechanical properties of graphene enable it to provide good protection for the nanostructures within the coating, and further enhancing the mechanical properties of the electrode can meet the needs of gradually developing flexible electronic devices. There is still considerable room for the development of graphene in this field with huge application prospects. Combining graphene with other structures discussed in this review might lead to the development of new electrodes with amazing performance, which is a topic worthy of further research and development.Organic materials are often neglected in the research field of transparent electrode conductivity, with most studies focusing on inorganic metal or nonmetal materials. Nevertheless, many organic materials have driven technological progress to some extent  and someKim et al.  used orgIn a study by Singh et al. , organicThe number of studies using polymers as one of the raw materials to make transparent electrodes is relatively small compared with studies of the other structures mentioned in the references above. Moreover, the performances of some of the few structures prepared are not very good. Nevertheless, there are still some structures that are worth studying, and several of the above studies show that certain polymers with outstanding physical properties lead to a relatively large improvement in the overall performance of the corresponding composite electrodes. Future research could be devoted to compensating for the shortcomings in the physical properties of these polymers through other structures, such as the enhancement of mechanical properties by the NF-r-CA layer in the first study and the maintenance of electrical conductivity after bending by the PEDOT:PSS layer in the second study ,56.1–102 nm, which suggests that the thickness of transparent conductive films with good overall performance should be at least within this order of magnitude. Given the limitations of the current preparation technology, too thin film generally possesses higher sheet resistance, and too thick film usually has a significant reduction in light transmission.Here we have summarized the thickness, sheet resistance, and transmittance of some above introduced film electrodes . In termThe performance of each material in terms of sheet resistance varies. The lowest sheet resistance is the AZO/Ag/AZO structure with only 6.2 ohm/sq, and the highest sheet resistance is the triple AGZO structure with 2.5 Mohm/sq. The conductivity of transparent conductive films is of paramount importance, and high sheet resistance will undoubtedly affect performance in applications where low sheet resistance means the ability to conduct higher currents with less current thermal effects. In the section on sheet resistance, it can be noted that studies using metal or metal nanowires tend to have low sheet resistance, mostly in the order of 1–10 ohm/sq. The only exception is the study of AgNWs/ZnO-TF/ZnO-NR structures with their sample sheet resistance reference values above 100 ohm/sq. It should also be noted that when using the current mainstream four-probe method to measure sheet resistance, if the silver nanowires are on the surface, their actual conductivity should be higher than the measured value. It is not difficult to understand this theory, i.e., assuming that there are two sets of studies with silver nanowires and silver layers on the surface and that they have the same measured sheet resistance, it is clear that the contact area of the silver nanowires in contact with the probe will be smaller than that of a normal layer structure and that the former will tend to outperform the latter in terms of actual conductivity. Sheet resistance was on average higher in those studies that did not use metals or metal nanowires, a result that is not surprising considering that metals are still the first choice for conductivity, but some of the studies related to non-metallic materials also exhibited a low sheet resistance. As in the two studies with graphene and no AgNWs, the sheet resistance is in the range of 100–200 ohm/sq, while the ITO/PEDOT:PSS/PET structure achieves an even better 40–60 ohm/sq. In general, the current research prefers to combine metals with metal oxides or non-metallic materials in order to achieve low sheet resistance, but at the same time, some completely non-metallic electrode structures also have good sheet resistance, which shows us the potential and value of research in this direction. Perhaps in the future, non-metallic transparent conductive films can also achieve low sheet resistance comparable to that of metal-containing electrodes.In the third section, most of the studies have light transmittance in the 80–90% range. The light transmittance levels of carbon-based transparent conductive films are slightly higher than the other types of studies, and the light transmittance of organic-based related studies fluctuates up and down. However, in general, the light transmittance of these studies is good enough for relevant devices such as solar cells or display devices.In terms of material flexibility, both metal-based, carbon-based and organic-dominated materials show good performance. The carbon-based and some organic matter-based electrodes perform very well. Most metal oxides are difficult to ensure flexibility due to their brittle nature and often require the use of nanostructures or distributed structures to increase their flexibility.The more commonly used transparent electrode preparation processes are magnetron sputtering, spin coating , wet etching, solution electrostatic spinning, MVD, and other methods. Metal-based and metal-compound-based transparent electrodes are predominantly used by magnetron sputtering, wet etching, and spin-coating. Spin-coating is mainly applied to the deposition of nanostructures such as silver nanowires and gallium oxide nanoparticles. The preparation of carbon-based and organic-dominated materials is more variable and often depends on the specific material and the specific structure. Examples include the CVD and PECVD methods used for depositing graphene, the preparation of graphene scrolls at the expense of metals, the preparation of organic matter electrodes by the MVD method and spin coating, etc. Some commonly used methods of preparation are not covered in this study, such as molecular beam epitaxy and vacuum vapor deposition. The magnetron sputtering method is highly efficient and produces good quality films, but the preparation temperature is often high and is suitable for metals and metal compound materials with good heat resistance. Spin coating is simple and inexpensive, but the nanostructures deposited by it are often randomly distributed, making it difficult to guarantee good contact between the nanostructures and requiring additional methods to be devised to regulate the distribution of the nanostructures. Among the mainstream methods of graphene preparation, CVD is more suitable for the preparation of thin film electrode materials. Depending on the structure and purpose of each study, there will be significant variability in the subsequent preparation methods. As organic materials are usually not resistant to high temperatures, low temperature preparation methods are often preferred in order to avoid damaging the structures and compositions of the organic materials.In the preparation process, as the preparation of flat film layers often used in magnetron sputtering or spin coating and other methods for the cleanliness of the substrate required high standard, so first before the preparation can choose the appropriate substrate cleaning methods, such as the use of piranha solution, air plasma, the use of ultrasonic cleaning, the use of pure water for rinsing, etc., which will better ensure the cleanliness of the substrate surface. A smooth and flat film layer has a significant improvement in light transmittance. During the preparation process, nanostructures are usually prepared by spin-coating, in which multiple spin-coating and annealing can be carried out. The multiple spin-coating is done to reduce or avoid cracking of the film layers, while the annealing enhances the adhesion between the layers. The nanostructures should not be placed on the surface layer, as more wear will result in poorer contact between the nanostructures, but in the middle layer, where they can be protected by the film on both sides. The nanostructures should not be placed on the surface layer, as more wear will result in poorer contact between the nanostructures, but in the middle layer, they are protected by the film on both sides, thus improving the durability of the electrodes. Secondly, after the nanostructures have been prepared, as they are not spatially continuous, a small amount of filling in the gaps between the nanostructures may be considered to enhance the surface flatness and filling with a conductive medium may also enhance their electrical conductivity. In the preparation of spatially structured film layers, such as the aforementioned ZnO-NR and graphene spools, the choice or innovation of preparation method needs to take into account the actual situation of the target structure. For example, graphene scrolls are prepared using a sacrificial metal layer, which allows the graphene layer to be rolled up into a scroll by surface tension. Finally, the layers can also be arranged to achieve the tightest possible bond, taking into account the difference in adhesion between the different materials.In recent years, sandwich-structure-based multilayer films have been selected to make transparent conductive films. In this review, four main research directions different from the conventional transparent conductive films based on the different selection of materials were introduced. First, as the most common conductive medium, metal is used the most frequently in the field of sandwich structure transparent conductive films, whose applications are also the most mature. The main design ideas used are to control the thickness of the metal so that it obtains a certain light transmittance while retaining good conductivity or to use nanofiber structures to maintain the light transmittance of the film. However, the metal film thickness is limited by its light transmittance. The fabrication of ultrathin metal films with smooth surfaces and no faults requires advanced processing technology, which also limits the reproducibility of the electrode. Moreover, the fabrication of nanostructure metal layers is limited by the high production cost . TherefoThe key point in the field of sandwich structure transparent conductive films is the composite structure with the multiple layers of films. As mentioned earlier in this review, the principle that the multilayer film structure needs to follow is such that each layer should have its own independent characteristics  At the same time, as a whole, they must influence the overall structure with their respective advantages through the synergistic effect between the materials. The number of research studies in this field is still small, including in some more mature research directions, and some research is still less worthy of further development. The future research should focus on the diversification of the structure with the existing materials, such as the use of a silver nanofiber structure. Meanwhile, it is worth trying to combine different types of material in multiple ways, such as composite electrodes made of graphene, metal, and organic materials, to combine the strengths of the materials better and enhance the comprehensive performance of the composite electrode.