Mechanically strong,flexible,and multi-responsive phase change films with a nacre-mimetic structure for wearable thermal management

Phase change materials(PCMs)are a highly promising candidate for thermal energy storage owing to their large latent heat and chemical stability.However,their intrinsic brittle induces poor flexibility and low mechanical strength,which limits them use for wearable thermal management.And,the electrical insulation and weak solar absorption make them lack multi-responsive capability.Herein,we report a facile strategy to synthesize mechanically strong and flexible multi-responsive phase change films by stirring an aqueous dispersion of cellulose nanofibrils(CNFs),MXene(Ti_(2)C_(3))nanosheets,and polyethylene glycol(PEG),followed by air-drying self-assembly and coating with hydrophobic fluorocarbon.The hydrogen bonds and nacre-mimetic synergistic toughening networks formed by ternary CNFs,Ti_(2)C_(3)nanosheets,and PEG endow films with high mechanical strength(16.7 MPa)and strain(10.4%),which are 18.6 and 8.7 times higher than those of pure PEG film,respectively.The films exhibit outstanding flexibility and do not crack or fracture even when bent,twisted,and folded into a complex small boat.Meanwhile,the laminar structure formed by the self-assembly Ti_(3)C_(2)nanosheets enhances electrical conductivity(3.95 S/m)and solar absorption,affording excellent electro-thermal(68.3%–81.0%)and solarthermal(85.6%–90.6%)conversion efficiency,thus achieving multi-response to external stimuli(electron/solar radiation).In addition,the as-prepared films also deliver large latent heat(136.1 J/g),outstanding cyclic and shape stability,leak-free encapsulation even under compressed at above 5000 times its weight,excellent hydrophobicity(131.4°),and self-cleaning function.This work paves the way for developing flexible,mechanically strong,and self-cleaning phase change film with multi-responsive function for wearable thermal management devices under high humidity condition.

Unconventional Fluorescent and Multi-responsive Polysiloxane:Synthesis,Characterization and Biological Applications

Owing to their high significance in fundamental study and diverse applications,stimuli-responsive and fluorescent polymers,particularly those with cluster-triggered emission(CTE)featured by non-conjugated chromophores,have drawn tremendous attention in recent years.In this work,fluorescent and multi-responsive polysiloxane(FRPS)was synthesized by hydrolytic condensation polymerization of 3-aminopropyl methyl diethoxysilane(APMS)with 3-(N-isopropyl propionamide)iminopropyl methyl diethoxysilane(APMS-NIP),which was formed in situ through aza-Michael addition between APMS and N-isopropyl acrylamide.FRPS was not only highly sensitive to temperature,pH and CO_(2) in water,but also showed an enhanced and stimuli-adjustable fluorescence emission.The effects of monomer feeding,pH and CO_(2) on its lower critical solution temperature and fluorescent property were investigated.FRPS fluorescence emission was ascribed to CTE mechanism.In addition,FRPS was shown to be highly potential as physiological indicator for cell imaging,and for controlled release and trace detection of doxorubicin.This study provides therefore a type of stimuli-responsive and fluorescent material for potential applications in biomedical fields,and it is also of great significance for understanding of the fluorescence mechanism of polysiloxane-based stimuli-responsive polymers.

Unconventional Fluorescent and Multi-responsive Polyethyleneimine with LCST and UCST Behavior:Synthesis,Characterization and Biological Applications

Non-aromatic fluorescent and multi-responsive materials,exhibiting inherent fluorescence emission and controlled phase change,have garnered significant attention in recent years.However,the underlying interaction between their fluorescent properties and phase transition remains unclear.In this study,we synthesized a series of catalyst-free aza-Michael addition-based polyethyleneimine(RFPEI)materials by reacting polyethyleneimine(PEI)with N-isopropyl acrylamide(NIPAM).The resulting RFPEI was comprehensively characterized,and demonstrated dual-phase transition behavior(LCST and UCST)in water,which could be finely tuned by adjusting its composition or external factors such as pH.Notably,upon UV irradiation(365 nm),RFPEI exhibited strong fluorescence emission.We further investigated the effects of NIPAM grafting percentage to PEI,polymer concentration,and pH on the LCST/UCST and fluorescent properties of RFPEI aqueous solutions.Moreover,we showcased the great potential of RFPEI as a versatile tool for physiological cell imaging,trace detection,and controlled release of doxorubicin.Our study presents a novel class of stimuli-responsive fluorescent materials with promising applications in the field of biomedicine.

A multi-responsive luminescent sensor towards Fe_(3+) and acetone based on a Cd-containing metal–organic framework

A Cd-containing metal–organic framework（Cd L）, formula as {[Cd_3（L）_2（H_2O）_6] 1.5DMF}, has been synthesized under solvothermal condition by the reaction of 4,40,400-（methylsilanetriyl）tribenzoic acid（H_3L） and Cd^（2＋）ion. Single-crystal X-ray diffraction reveals that Cd L displays a three-dimensional framework with 2-fold interpenetration and DMF molecules locate in the void space of the channels. A topological analysis of the framework indicates Cd Lisa 3,4-connected pto net. The photoluminescence properties of Cd L are systematically studied in detail. Impressively, Cd L shows excellent detection performance towards Fe^（3＋）ion and acetone in the sensing experiments, which undoubtedly demonstrates the great potential of Cd L as a highly selective multi-responsive luminescent sensor for the detection of organic solvents and metal ions.

An amino acid-based gelator for injectable and multi-responsive hydrogel

Hydrogels formed by gelators have attracted growing attention for their promising application in biomaterials and biotechnology, We describe in this paper the generation and characterization of a novel photo-, thermal- and pH-responsive hydrogel based on an amino acid gelator AA-Azo-EG6. Specifically, the gelator bears an amino acid head, an azobenzene （Azo） linker, and a short oligoethylene glycol tail （EG6）. The resulting AA-Azo-EG6 hydrogel is injectable and exhibits interesting helical self-assembled structures, Meanwhile, the hydrogel is able to experience a gel-sol or gel-precipitate phase transition responding to external stimuli. Thus, this AA-Azo-EG6 gelator is a promising building block for intelligent materials and drug delivery.

Simultaneous Optimization of Incomplete Multi-Response Experiments

This article attempts to develop a simultaneous optimization procedure of several response variables from incomplete multi-response experiments. In incomplete multi-response experiments all the responses (p) are not recorded from all the experimental units (n). Two situations of multi-response experiments considered are (i) on units all the responses are recorded while on units a subset of responses is recorded and (ii) on units all the responses (p) are recorded, on units a subset of responses is recorded and on units the remaining subset of responses is recorded. The procedure of estimation of parameters from linear multi-response models for incomplete multi-response experiments has been developed for both the situations. It has been shown that the parameter estimates are consistent and asymptotically unbiased. Using these parameter estimates, simultaneous optimization of incomplete multi-response experiments is attempted following the generalized distance criterion [1]. For the implementation of these procedures, SAS codes have been developed for both complete (k ≤ 5, p = 5) and incomplete (k ≤ 5, p1 = 2, 3 and p2 = 2, 3, where k is the number of factors) multi-response experiments. The procedure developed is illustrated with the help of a real data set.

Multi-response optimization of MIL-101 synthesis for selectively adsorbing N-compounds from fuels

In this work,MIL-101,a metal organic framework,has been synthesized and examined in the adsorptive denitrogenation process.Due to the importance of adsorption capacity and selectivity,the effects of synthesis parameters including metal type,reagent ratio,time and temperature on the MIL-101 performance were investigated by measuring quinoline(QUI)separation from iso-octane.The optimum conditions were determined using a Taguchi experimental design and the multiresponse optimization(multivariate statistical)method.Based on the arithmetic mean of normalized QUI adsorption capacity and QUI/dibenzothiophene(DBT)selectivity,as the objective function,the optimum value of synthesis parameters were found to be manganese as metal type in the structure,180°C for synthesis temperature,15h for synthesis time and 1.00 for reagent molar ratio.Under these conditions,QUI adsorption capacity and QUI/DBT selectivity were 19.3 mg-N/g-Ads.and 24.6,respectively.Accordingly,the arithmetic mean between normalized values of these measured parameters was equal to 1.10,which is in good agreement with the predicted value.The MIL-101 produced under optimum conditions was characterized by determining its specific surface area,X-ray powder diffraction patterns and Fourier transform infrared spectroscopy.Finally,isotherm and kinetic studies indicate that the Langmuir isotherm and pseudo-first-order model can successfully describe the experimental data.

TOPSIS based Taguchi design optimization for CVD growth of graphene using different carbon sources: Graphene thickness, defectiveness and homogeneity

Chemical inhomogeneity of chemical vapor deposition(CVD) grown graphene compromises its usage in highperformance devices. In this study, TOPSIS based Taguchi optimization was performed to improve thickness uniformity and defect density of CVD grown graphene. 1.56% decrease in the mean 2 D/G intensity ratio, 87.96% improvement in the mean D/G intensity ratio, 56.07% improvement in the standard deviation D/G intensity ratio, 25.21%improvement in the standard deviation 2 D/G intensity ratio, and 69.32% improvement in the surface roughness were achieved with TOPSIS based Taguchi optimization. The statistical differences between the copper and silicon substrates have been found significantly in terms of their impacts on the graphene's properties with the0.000 p-value for the mean D/G intensity ratio and with the 0.009 p-value for the mean 2 D/G intensity ratio, respectively. Graphene having 11% lower mean D/G intensity ratio(low defective graphene products) compared to the values given in the literature using single-response optimization was obtained using multi-response optimization.

Effects of Whole-Tree Harvesting on Species Composition of Tree and Understory Communities in a Northern Hardwood Forest

In the northeastern United States, whole-tree harvesting is widely used to supply fuel to biomass energy facilities, but questions remain regarding its long-term sustainability. We have previously reported findings indicating no short-term decrease in forest productivity in whole-tree harvested sites when compared with similar conventionally (stem-only) harvested sites. Here we present additional results of the same study, but focus on the effect harvest treatment has on the species composition of the regenerating forest. Within northern hardwood forests in central New Hampshire and western Maine, regeneration surveys were conducted on four (4) small clearcuts in 2010 and twenty-nine (29) small clearcuts in 2011. The species and diameter of trees > 2 m in height were recorded within 1 m or 2 m-radius plots and used to calculate the biomass fraction of each species. The 2010 study additionally measured the density of trees 2 m in height and the diversity of understory non-tree species. Non-metric multidimensional scaling and multi-response permutation procedures were used to determine the effect of harvest treatment had on community-wide tree species composition. Potential differences were also examined on a species-by-species basis. Both analytic methods indicated no significant differences in species composition of tree species or understory communities. Within the limits of our data, we conclude that no significant effects of residue removal on species composition are observed within our sample of northern hardwood sites at this early stage of stand development.

Efficient multi-response adaptive sampling algorithm for construction of variable-fidelity aerodynamic tables

Adaptive sampling is an iterative process for the construction of a global approximation model. Most of engineering analysis tools computes multiple parameters in a single run. This research proposes a novel multi-response adaptive sampling algorithm for simultaneous construction of multiple surrogate models in a time-efficient and accurate manner. The new algorithm uses the Jackknife cross-validation variance and a minimum distance metric to construct a sampling criterion function. A weighted sum of the function is used to consider the characteristics of multiple surrogate models. The proposed algorithm demonstrates good performance on total 22 numerical problems in comparison with three existing adaptive sampling algorithms. The numerical problems include several two-dimensional and six-dimensional functions which are combined into singleresponse and multi-response systems. Application of the proposed algorithm for construction of aerodynamic tables for 2 D airfoil is demonstrated. Scaling-based variable-fidelity modeling is implemented to enhance the accuracy of surrogate modeling. The algorithm succeeds in constructing a system of three highly nonlinear aerodynamic response surfaces within a reasonable amount of time while preserving high accuracy of approximation.

Multi-response optimization of Ti-6A1-4V turning operations using Taguchi-based grey relational analysis coupled with kernel principal component analysis

Ti-6A1-4V has a wide range of applications, especially in the aerospace field;however, it is a difficultto- cut material. In order to achieve sustainable machining of Ti?6A1-4V, multiple objectives considering not only economic and technical requirements but also the environmental requirement need to be optimized simultaneously. In this work, the optimization design of process parameters such as type of inserts, feed rate, and depth of cut for Ti-6A1-4V turning under dry condition was investigated experimentally. The major performance indexes chosen to evaluate this sustainable process were radial thrust, cutting power, and coefficient of friction at the toolchip interface. Considering the nonlinearity between the various objectives, grey relational analysis (GRA) was first performed to transform these indexes into the corresponding grey relational coefficients, and then kernel principal component analysis (KPCA) was applied to extract the kernel principal components and determine the corresponding weights which showed their relative importance. Eventually, kernel grey relational grade (KGRG) was proposed as the optimization criterion to identify the optimal combination of process parameters. The results of the range analysis show that the depth of cut has the most significant effect, followed by the feed rate and type of inserts. Confirmation tests clearly show that the modified method combining GRA with KPCA outperforms the traditional GRA method with equal weights and the hybrid method based on GRA and PCA.

An amphiphilic molecule with a single fluorophore exhibits multiple stimuli-responsive behavior

Fluorescent materials that respond to multiple stimuli have broad applications ranging from sensing and bioimaging to information encryption.Herein,we report the design and synthesis of a single-fluorophorebased amphiphile DCSO,which shows temperature-,solvent-,humidity-,and radiation-dependent fluorescence.DCSO consists of a dicyanostilbene(DCS)group as a rigid hydrophobic core with oligo(ethylene glycol)(OEG)chains at both ends as a flexible hydrophilic periphery.The DCS group acts as a highly efficient fluorophore,while the OEG chain endows the molecule with thermo-responsiveness.Fluorescent colors can vary from blue to green to yellow in response to external stimuli.On the basis of light radiation,we demonstrate that this system can be applied to time-dependent information encryption,in which the correct information can only be read at a specific time under irradiation.This work further demonstrates the usefulness and application of single-fluorophore-based luminescent materials with multiple stimuli-responsive functions.

Assessment of dead layers thickness of an HPGe detector after an extended operating period using response surface methodology and Box–Behnken design

Purpose This work aims to study the increase in dead layer thickness of an HPGe N-type detector during its operational period from 2012 to 2018.Methods The dead layer was examined along three Ge-crystal surfaces,such as outer frontal,outer lateral,and inner lateral.These parameters were optimized using response surface methodology(RSM)with a Box–Behnken design(BBD).The Monte Carlo calculations using the GAMOS(Geant4-based Architecture for Medicine-Oriented Simulations)code were performed to evaluate the detector’s efficiency at different values of the inactive germanium layer.Results and conclusion The optimal combination of dead layer thickness has been identified using the desirability function approach,which is a useful tool to optimize multi-response problems.To find the variation in dead layer thickness over the operational period,the optimization procedure was reiterated for both experimental efficiencies measured in 2012 and 2018.The obtained results show that dead layers thickness has increased from 0.6141 mm to 0.7447 mm,0.0803 mm to 2.2721 mm,and 1.5012 mm to 1.6091 mm for the outer frontal,outer lateral,and inner lateral surfaces,respectively.

Multiresponsive Polymer Assemblies Achieved by a Subtle Chain Terminal Modification

Inspired by the influence of chemical structure of end groups on the phase transition temperature of thermoresponsive polymers,we demonstrated a strategy to control the multi-responsiveness of polymer assemblies via subtle modification of end groups of thermoresponsive polymer segments and revealed its potential application for drug delivery.By developing polymer assemblies composed of poly(aliphatic ester) as the inner core and thermoresponsive polyphosphoester as the outer shell,we showed that end groups of thermoresponsive polyphosphoester segments controlled the surface property of assemblies and further determined the stimuli-responsive behavior.The phase-transition temperatures of the unmodified polymer assemblies are tightly controlled by their surface properties due to the hydrophilic to hydrophobic transitions of end groups in response to an environmental stimulus (e.g.pH or light irradiation).External control over these surface properties can by asserted by adjusting the chemical structure and composition of the terminal groups of the thermoresponsive polyphosphoesters.

Application of grey relational analysis based on Taguchi method for optimizing machining parameters in hard turning of high chrome cast iron

High chrome white cast iron is particularly preferred in the production of machine parts requiring high wear resistance. Although the amount of chrome in these materials provides high wear and corrosion resistances, it makes their machinability difficult. This study presents an application of the grey relational analysis based on the Taguchi method in order to optimize chrome ratio, cutting speed, feed rate, and cutting depth for the resultant cutting force (Fr) and surface roughness (Ra) when hard turning high chrome cast iron with a cubic boron nitride (CBN) insert. The effect levels of machining parameters on Fr and Ra were examined by an analysis of variance (ANOVA). A grey relational grade (GRG) was calculated to simultaneously minimize Fr and Ra. The ANOVA results based on GRG indicated that the feed rate, followed by the cutting depth, was the main parameter and contributed to respo ses. Optimal levels of parameters were found when the chrome ratio, cutting speed, feed rate, and cutting depth were 12%, 100m/min, 0.05mm/r, and 0.1mm, respectively, based on the multiresponse optimization results obtained by considering the maximum signal to noise (SIN) ratio of GRG. Confirmation results were verified by calculating the confidence level within the interval width.

Hybrid fuzzy-grey-Taguchi based multi weld quality optimization of Al/Cu dissimilar friction stir welded joints

Nowadays aluminum alloys substitute copper in various applications for weight reduction and cost savings. This paper presents fuzzy-grey Taguchi technique for optimization of friction stir welding condition with seven weld quality attributes of dissimilar A1/Cu joints with the minimum number of experiments for effective productivity and product quality. Taguchi＇s L16 orthogonal array was used to conduct the experiments. Fuzzy inference system was adapted to convert the multi quality characteristics into an equivalent single quality parameter which was opti- mized by Taguchi approach. Four parameters namely, rotational speed of the tool, welding speed, plunging depth and tool pin offset were varied in four levels for investi- gating the effects on the process output like tensile strength, compressive strength, percentage of elongation, bending angle, weld bead thickness and average hardness at the nugget zone. The hardness profile is consistent with the variation of the structure within the nugget zone （NZ）. Confirmation experiment was conducted using predicted optimum parameter setting and it showed that the proposed approach could efficiently optimize weld quality parame- ters. The microstructural analyses were also performed for all the zones of the joints at both Al and Cu sides. It revealed the finer grain size at the NZ compared to the base material due to dynamic recrystallization.

Exclusion effects on vegetation characteristics and their correlation to soil factors in the semi-arid rangeland of Mu Us Sandland,China

Exclusion has been applied as a main measure for re-vegetation all over the world.This paper,by comparing the results of year-round exclusion,seasonal exclusion,and non-exclusion,quantified the vegetation variations under three different exclusion measures and their correlation to soil factors.The analysis results for community species component and plant diversity using multi-response permutation procedures(MRPPs)showed that exclusion did change the species com ponent and increase plant diversity remarkably,while the period of exclusion had no significant influence on these two community features.The indicator species analysis and calculation of similarity indices indicated that community for year-round exclusion were becoming xerophytization and unpalatability,and showed highly spatial heterogeneity of plant species distribution,whereas community for seasonal exclusion was under stable non-equilibrium condition.Detrended correspondence analysis(DCA)and detrend canonical correspondence analysis(DCCA)results of relationship between plant species and soil variables demonstrated that soil moisture was a controlling factor for plant species component,microbiotic soil crust cover,soil organic matter,and soil bulk density had significant effects on soil moisture,among which microbiotic soil crust was a leading factor owing to its limitation to rainfall infiltration on the one hand,and its constraints to entrance of herbaceous seeds into soil or to germination of soil seeds on the other hand.As a result of long-term removal of animal grazing,crust kept intact in year-round exclusion community,which was a main reason of community xerophytization.It was also obvious from ordination results that some important environmental factors,such as tempo-spatial change of rainfall and corresponding tempo-spatial change of soil moisture,were neglected during direct gradient analysis.In addition,biodiversity was close related to soil nutrients as well as to soil moisture condition(soil water content and crust cover),and it had positive relation to available N,and negative relation to available P.Higher soil N had advantage to non-leguminous plants growth on nutrition-poor sand land definitely.The impact of P to community component was unclear and should be studied from plant physiology.Further researches on nonequilibrium theory in semi-arid rangeland will provide a sci-entific and flexible animal development paradigm for being implementing livestock fen-raising and grazing-forbidden policies in China.

Optimization of fused deposition modeling process parameters using a fuzzy inference system coupled with Taguchi philosophy

Fused deposition modeling （FDM） is an additive manufacturing technique used to fabricate intricate parts in 3D, within the shortest possible time without using tools, dies, fixtures, or human intervention. This article empiri- cally reports the effects of the process parameters, i.e., the layer thickness, raster angle, raster width, air gap, part orientation, and their interactions on the accuracy of the length, width, and thicknes, of acrylonitrile-butadiene- styrene （ABSP 400） parts fabricated using the FDM tech- nique. It was found that contraction prevailed along the directions of the length and width, whereas the thickness increased from the desired value of the fabricated part. Optimum parameter settings to minimize the responses, such as the change in length, width, and thickness of the test specimen, have been determined using Taguchi＇s parameter design. Because Taguchi＇s philosophy fails to obtain uniform optimal factor settings for each response, in this study, a fuzzy inference system combined with the Taguchi philosophy has been adopted to generate a single response from three responses, to reach the specific target values with the overall optimum factor level settings. Further, Taguchi and artificial neural network predictive models are also presented in this study for an accuracy evaluation within the dimensions of the FDM fabricated parts, subjected to various operating conditions. The pre- dicted values obtained from both models are in good agreement with the values from the experiment data, with mean absolute percentage errors of 3.16 and 0.15, respectively. Finally, the confirmatory test results showed an improvement in the multi-response performance index of 0.454 when using the optimal FDM parameters over the initial values.

Identification and modelling of applicable wear conditions for stir cast Al-composite

A comprehensive study of the tribological performance of the Al-Zn-Mg-Cu/Al2O3 composite and its matrix alloy is presented in this paper, with a specific emphasis to identify and model the applicable wear conditions where the composite provides a minimum of 50% reduction in wear rate and 25% lowering of the friction coefficient. Two-body abrasion experiments following Taguchi L27 orthogonal design have been performed separately on alloy and composite materials, both prepared by the stir casting method. The influence of crucial control factors including silicon carbide (SiC) abrasive size, load, sliding distance, and velocity on the percentage variations of wear rates and friction coefficients between alloy and composite have been studied using the analysis of variance technique and full quadratic regression method. The dominant control factors are identified as abrasive size, load, and the interaction between abrasive size and load. This has been verified by establishing the influence of abrasive size and load on variations of wear mechanisms like microcutting, microploughing, and delamination, identified by means of in-depth characterization of worn surfaces and generated debris for both alloy and composite. The selection of applicable tribological condition for the composite has been accomplished by adopting the multi-response optimization technique based on combined desirability approach to obtain concurrent optimization of the percentage variations of wear rates and friction coefficients. Predictive models correlating the superiority of tribological performance of composite with abrasion conditions have been developed, and these are found to be accurate (errors <10%), as determined by confirmatory experiment.

D-optimal population designs in linear mixed effects models for multiple longitudinal data

The main purpose of this paper is to investigate D-optimal population designs in multi-response linear mixed models for longitudinal data.Observations of each response variable within subjects are assumed to have a first-order autoregressive structure,possibly with observation error.The equivalence theorems are provided to characterise theD-optimal population designs for the estimation of fixed effects in the model.The semi-Bayesian D-optimal design which is robust against the serial correlation coefficient is also considered.Simulation studies show that the correlation between multi-response variables has tiny effects on the optimal design,while the experimental costs are important factors in the optimal designs.