We report a simple hole-blocking material （biphenyl-3,3＇-diyl）bis（diphenylphosphine oxide） （BiPh-m-BiDPO） based on our recent advance. The bis（phosphine oxide） compound shows HOMO/LUMO levels of ∽-6.71/- 2.5...We report a simple hole-blocking material （biphenyl-3,3＇-diyl）bis（diphenylphosphine oxide） （BiPh-m-BiDPO） based on our recent advance. The bis（phosphine oxide） compound shows HOMO/LUMO levels of ∽-6.71/- 2.51 eV. Its phosphorescent spectrum in a solid film features two major emission bands peaking at 2.69 and 2.4eV, corresponding to 0-0 and 01 vibronic transitions, respectively. The measurement of the electron-only devices reveals that BiPh-m-BiDPO possesses electron mobility of 2.28 × 10^-9-3.22× 10^-8cm2 V-1s-1 at E = 2- 5 × 10^5 V/cm. The characterization of the sky blue fluorescent and red phosphorescent pin organic light-emitting diodes （OLEDs） utilizing BiPh-m-BiDPO as the hole blocker shows that its shallow LUMO level as well as the low electron mobility affects significantly the power efficiency and hence operational stability, relative to the luminous efficiency, especially at high luminance. In combination with our recent results, the present study provides an indepth insight on the molecular structure-property correlation in the organic phosphinyl-containing hole-blocking materials.展开更多
Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery...Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.展开更多
Enhancement of the nonlinear optical(NLO)output power of lasers requires urgent development of an NLO crystal with a significant second-harmonic generation(SHG)response and sufficient birefringence for phase-matching ...Enhancement of the nonlinear optical(NLO)output power of lasers requires urgent development of an NLO crystal with a significant second-harmonic generation(SHG)response and sufficient birefringence for phase-matching capability;however,simultaneously optimizing these two key parameters remains a great challenge.In contrast to traditional single-anion units,the stereochemically-active lone pair Sb^(3+)ion is coordinated by S^(2-)and I^(-) ions to yield the mixed-anionic Sb SI chalcohalide that can enhance hyperpolarizability and anisotropic polarizability concurrently.As anticipated,Sb SI exhibited the largest SHG response(5.7×Ag Ga S_(2)@1.91μm)among phase-matching Sb-based sulfides,the favorable laser-induced damage threshold(LIDT,2.3×Ag Ga S_(2)@2.09μm),and the giant calculated birefringence(0.62@1.91μm).Structural analysis and computational simulations indicate that the highly polarizable mixed anion determine the enormous SHG response and birefringence.展开更多
Correlation between tunable optical properties and push-pull structural characters has attracted extensive attention in material science and nonlinear optics.Here,several indacenodithiophene(IDT)derivatives denoted as...Correlation between tunable optical properties and push-pull structural characters has attracted extensive attention in material science and nonlinear optics.Here,several indacenodithiophene(IDT)derivatives denoted as IDT-2NA,NA-IDT-CN,and IDT-2CN with different terminal substituents are investigated comparatively to demonstrate their intrinsic structure-property relationships.Interestingly,the IDT core acts diverse roles as acceptor(A)and donor(D)in the obtained three derivatives.Symmetric IDT-2NA with a D-A-D architecture shows an absorption maximum around 459 nm in THF.Contrary to the symmetric analog IDT-2CN with a reverse A-D-A feature,NA-IDT-CN with a different D-D'-A motif characterizes an obvious solvent polarity effect.Theo-retical calculation and electrostatic potential results confirm the terminal substituents with different electronic conjugation play vital roles in affecting the resultant photophysical properties.Utilizing the femtosecond open-aperture Z-scan technique,significant two-photon absorption(2PA)capabilities are obtained ranging from 540 to 900 nm.The 2PA cross section(δ_(2pA) )maximum about 5390 GM of centrosymmetric IDT-2CN exhibits at 600 nm.Distinct excited-state dynamics with the help of femtosecond transition absorption supports the effective intramolecular charge transfer which accounts for enhancing theδ_(2pA) values.Their potential optical power limiting applications based on the 2PA mechanism were further evaluated.The limiting thresholds were found to be 2.793.35 mJ/cm^(2) for the three IDT derivatives with a sequence of IDT-2CN<IDT-2NA<NA-IDT-CN.The distinct structural motifs and effective 2PA capabilities in the current work may provide reliable insights into the push-pull IDT chromophores for advanced nonlinear optical applications.展开更多
Polymer informatics faces challenges owing to data scarcity arising from complex chemistries,experimental limitations,and process-ing-dependent properties.This review presents the recent advances in data-efficient mac...Polymer informatics faces challenges owing to data scarcity arising from complex chemistries,experimental limitations,and process-ing-dependent properties.This review presents the recent advances in data-efficient machine learning for polymers.First,data preparation tech-niques such as data augmentation and rational representation help expand the dataset size and develop useful features for learning.Second,modeling approaches,including classical algorithms and physics-informed methods,enhance the model robustness and reliability under limited data conditions.Third,learning strategies,such as transferlearning and active learning,aim to improve generalization and guide efficient data ac-quisition.This review concludes by outlining future opportunities in machine learning for small-data scenarios in polymers.This review is expect-ed to serve as a useful tool for newcomers and offer deeper insights for experienced researchers in the field.展开更多
Noteworthy challenges such as severe side reactions,interfacial instability,and dendrite growth have plagued rechargeable alkali metal batteries for a long time.Alleviating the plight necessitates innovative membranes...Noteworthy challenges such as severe side reactions,interfacial instability,and dendrite growth have plagued rechargeable alkali metal batteries for a long time.Alleviating the plight necessitates innovative membranes capable of modulating ion transport and establishing stable interfaces.The exploration of implemented membranes with thermal/mechanical and electrochemical stability is crucial for achieving high-performance and safe alkali metal batteries.Crystalline covalent organic framework(COF)membranes have emerged as promising materials for next-generation energy storage systems due to their tunable porosity and exceptional physicochemical properties.This review specifically examines the critical role of COF membranes in enabling sustainable alkali metal(Li/Na/K)batteries,with a particular focus on design principles,performance advantages,and key challenges of COF membranes.The discussion emphasizes structure-property relationships specifically relevant to rechargeable battery applications,supported by recent decades of research.Impressively,this mini review further identifies three critical research frontiers:reticular chemistry-guided materials design,multifunctional composite architectures,and in-situ characterization techniques.This targeted analysis provides actionable insights for developing COF membranes that address the fundamental limitations of current alkali metal battery technologies.展开更多
Polyelectrolytes(PEs)are polymers carrying ionizable groups along the chain backbone and play an important role in life and environmental sciences,industrial applications and other fields.Due to the complicated topolo...Polyelectrolytes(PEs)are polymers carrying ionizable groups along the chain backbone and play an important role in life and environmental sciences,industrial applications and other fields.Due to the complicated topological structure and electrostatic correlations of PEs,PEs exhibit very rich phase behavior and morphologies in both bulk and confined solutions.So far,many theories,simulations and machine learning approaches have been proposed to study the behavior of polyelectrolyte solutions,especially the intrinsic structure-property relationships.In this perspective,from a personal point of view,we present several recent trends in polyelectrolyte solutions.The main themes considered here are accelerated development of sequence-defined polyelectrolyte(SDPE)via artificial intelligence technology,liquid-liquid phase separation in bulk SDPE solutions,adsorption behaviors of SDPE in the vicinity of a single dielectric surface,and surface forces between two charged surfaces mediated by SDPE solutions.展开更多
Direct coal liquefaction products offer a considerable quantity of cycloalkanes, which are the valuable candidates for making the high energy density fuels. The creation of such fuels depends on designing molecular st...Direct coal liquefaction products offer a considerable quantity of cycloalkanes, which are the valuable candidates for making the high energy density fuels. The creation of such fuels depends on designing molecular structures and calculating their properties, which can be expedited with computer-aided techniques. In this study, a dataset containing 367 fuel molecules was constructed based on the analysis of direct coal liquefied oil. Three convolutional neural network property prediction models have been created based on molecular structure-physical and chemical property data from the library. All the models have good fitting ability with R2 values above 0.97. Then, a variational autoencoder generation model has been established using the molecular structures from the library, focusing on the structure of saturated cycloalkanes. The structure-property prediction model was then applied to the newly generated molecules, assessing their density, volumetric calorific value, and melting point. As a result, 70000 novel molecular structures were generated, and 25 molecular structures meeting the criteria for high energy density fuels were identified. The established variational autoencoder model in this study effectively assimilates the structural information from the sample set and autonomously generates novel high energy density fuels, which is difficult to achieve in traditional experimental methods.展开更多
Copper-ceria sheets catalysts with different loadings of copper（2 wt.%, 5 wt.% and 10 wt.%） supported on ceria nanosheets were synthesized via a depositioneprecipitation（DP） method. The prepared catalysts were sys...Copper-ceria sheets catalysts with different loadings of copper（2 wt.%, 5 wt.% and 10 wt.%） supported on ceria nanosheets were synthesized via a depositioneprecipitation（DP） method. The prepared catalysts were systematically characterized with various structural and textural detections including X-ray diffraction（XRD）, Raman spectra, transmission electron microscopy（TEM）, X-ray absorption fine structure（XAFS）, and temperature-programmed reduction by hydrogen（H2-TPR）, and tested for the CO oxidation reaction. Notably, the sample containing 5 wt.% of Cu exhibited the best catalytic performance as a result of the highest number of active CuO species on the catalyst surface. Further increase of copper content strongly affects the dispersion of copper and thus leads to the formation of less active bulk CuO phase, which was verified by XRD and H2-TPR analysis. Moreover, on the basis of in-situ diffuse reflectance infrared Fourier transform spectroscopy（in-situ DRIFTS） results, the surface Cu~＋ species, which are derived from the reduction of Cu^（2＋）, are likely to play a crucial role in the catalyzing CO oxidation.Consequently, the superior catalytic performance of the copper-ceria sheets is mainly attributed to the highly dispersed CuOx cluster rather than Cu-[Ox]-Ce structure, while the bulk CuO phase is adverse to the catalytic activity of CO oxidation.展开更多
In order to solve the problem of poor interpretability of support vector re- gression （SVR） applied in quantitative structure-property relationship （QSPR）, a com- plete set of explanatory system for SVR was establ...In order to solve the problem of poor interpretability of support vector re- gression （SVR） applied in quantitative structure-property relationship （QSPR）, a com- plete set of explanatory system for SVR was established based on F-test, The nov- el explanatory system includes significance tests of model and single-descriptor im- portance, single-descriptor effect and sensitivity analysis, and significance tests of interaction between two descriptors, etc. The results of example indicated that the explanatory results of the new system were consistent well with those of stepwise linear regression model and quadratic polynomial stepwise regression model. The explanatory SVR model will play an important role in regression analysis such as QSPR.展开更多
Extractive distillation is an effective method for separating azeotropic or close boiling point mixtures by adding a third component.Various technologies for performing the extractive distillation process have been ex...Extractive distillation is an effective method for separating azeotropic or close boiling point mixtures by adding a third component.Various technologies for performing the extractive distillation process have been explored to protect the environment and save resources.This paper focuses on the improvement of these advanced technologies in recent years.Extractive distillation is retrieved and analyzed from the view of phase equilibrium,selection of solvent in extractive distillation,process design,energy conservation,and dynamic control.The quantitative structure–property relationship used in extractive distillation is discussed,and the future development of extractive distillation is proposed to determine how the solvent affects the relative volatility of the separated mixture.In the steady state design,the relationship between the curvature of the residue curve and parameters of the optimal steady state is also highlighted as another field worthy of further study to simplify the distillation process.展开更多
Recent technical progress in the industry has led to an urgent requirement on new materials with enhanced multi-properties.To meet this multi-property requirement,the materials consisting of three and more elements ha...Recent technical progress in the industry has led to an urgent requirement on new materials with enhanced multi-properties.To meet this multi-property requirement,the materials consisting of three and more elements have attracted increasing attention.However,facing to the nearly unknown huge multi-component materials system,the traditional trial and error method cannot provide sufficient data efficiently.Therefore,an efficient material innovation strategy is significant.The first-principles calculation based on the density functional theory is a powerful tool for both the accurate prediction of material properties and the identification of its underlying thermodynamics and dynamics.At the same time,the advances of computational methods and computer calculation abilities that are orders of magnitude faster than before make the high throughput first-principles calculations popular.At present,the simulation-assisted material design has become a main branch in the material research field and a great many successes have been made.In this article,the advances of the high throughput first-principles calculations are reviewed to show the achievements of the first-principles calculations and guide the future directions of its applications in ceramics.展开更多
An oil-in-water (O/W) solvent evaporation method was used to prepare biodegradable microspheresbased on poly(D,L-lactic acid) (PLA). Nifedipine, a hydrophobic drug, was chosen as a model molecule in the studyof drug e...An oil-in-water (O/W) solvent evaporation method was used to prepare biodegradable microspheresbased on poly(D,L-lactic acid) (PLA). Nifedipine, a hydrophobic drug, was chosen as a model molecule in the studyof drug entrapment and release. Effect of preparation conditions on the size, morphology, drug loading, and releaseprofiles of micropheres was investigated. Based on in vitro release experimental findings, a diffusion/dissolutionmodel was presented for quantitative description of the resulting release behaviors and drug release kinetics fromPLA microspheres analyzed. The mathematical models were used to predict the effect of microstructure on theresulting drug release. It provided an approach to determine the suitable structure parameters for microspheres toachieve desired drug release behaviors.展开更多
Recently,molecule-based luminescent materials have been drawing extensive attention due to their desirable properties and promising applications in the fields of sensors,lighting display and cell imaging.Crystalline p...Recently,molecule-based luminescent materials have been drawing extensive attention due to their desirable properties and promising applications in the fields of sensors,lighting display and cell imaging.Crystalline polymorph is an intriguing phenomenon that the presence of multiple packing and aggregate architectures of the same molecular system.The studies on polymorphs for molecule-based fluorophores provide the opportunities to adjust the mode of molecular packing and photophysical properties,which will help to illustrate the structure-property relationship.In this review,we focus on the recent progress in various feasible methods of molecule-based crystalline polymorphism growth and their adjustable photofunctional properties,which will open up possibilities of variant optical applications.Firstly,several effective ways to prepare and screen polymorphs are sorted out.And then,we discuss the discrepant properties and multifunctional applications(such as sensors,laser and OFET).Finally,the development trends and future prospects of these polymorphs are also briefly introduced.展开更多
In nature,the properties of matter are ultimately governed by the electronic structures.Quantum chemistry(QC)at electronic level matches well with a few simple physical assumptions in solving simple problems.To date,m...In nature,the properties of matter are ultimately governed by the electronic structures.Quantum chemistry(QC)at electronic level matches well with a few simple physical assumptions in solving simple problems.To date,machine learning(ML)algorithm has been migrated to this field to simplify calculations and improve fidelity.This review introduces the basic information on universal electron structures of emerging energy materials and ML algorithms involved in the prediction of material properties.Then,the structure-property relationships based on ML algorithm and QC theory are reviewed.Especially,the summary of recently reported applications on classifying crystal structure,modeling electronic structure,optimizing experimental method,and predicting performance is provided.Last,an outlook on ML assisted QC calculation towards identifying emerging energy materials is also presented.展开更多
Twenty eight alkyl(1-phenylsulfonyl) cycloalkane carboxylates were computed at the B3LYP/6-31G* level. Based on linear solvation energy theory, two quantitative correlation equations of the molecular structures of alk...Twenty eight alkyl(1-phenylsulfonyl) cycloalkane carboxylates were computed at the B3LYP/6-31G* level. Based on linear solvation energy theory, two quantitative correlation equations of the molecular structures of alkyl(1-phenylsulfonyl) cycloalkane carboxylate com- pounds to their chromatographic retention (capacity factor lgKW) and the toxicity for photo- bacterium phosphoreum (–lgEC50) were developed by using the molecular structural parameters as theoretical descriptors (r2 = 0.9501, 0.9488). The two quantitative correlation equations were consequently cross validated by leave-one-out (LOO) validation method with q2 of 0.9113 and 0.9281, respectively. The result showed that the two equations achieved in this work by B3LYP/6-31G* are both more advantageous than those from AM1, and can be used to predict the lgKW and –lgEC50 of congeneric organics.展开更多
The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is st...The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is still not completely known owing to their complex interactions with human sweet receptor, which may be different from that of other sweeteners to some extent. In this contribution, predictive quantitative structure-property relationship(QSPR) models have been developed for diverse aspartame analogues using Materials Studio 5.0 software. The optimal QSPR model(r2 = 0.913, r2 CV = 0.881 and r2 pred = 0.730) constructed by the genetic function approximation method has been validated by the tests of cross validation, randomization, external prediction and other statistical criteria, which shows that their sweetness power is mainly governed by their electrotopological-state indices(SssCH and SsNH), spatial descriptors(Shadow length: LX, ellipsoidal volume and Connolly surface occupied volume) and topological descriptors(Chi(3): cluster and Chi(0)(valence modified)), which partially supports both multipoint attachment theory proposed by Nofre and Tinti et al. and B-X theory proposed by Kier et al.. Present exploited results provide the key structural features for the sweetness power of aspartame analogues, supplement the mechanistic understanding of the sweet perception, and would be also helpful for the design of potent sweetener analogs prior to their synthesis.展开更多
The n-octanol/water partition coefficients （lgKow） of 18 substituted anilines were determined at 25 ℃ by shake-flask method. The geometrical optimization of substituted anilines has been performed at B3LYP/6-311G^...The n-octanol/water partition coefficients （lgKow） of 18 substituted anilines were determined at 25 ℃ by shake-flask method. The geometrical optimization of substituted anilines has been performed at B3LYP/6-311G^＊＊ level with Gaussian98 program, and the molecular surface areas of substituted anilines were calculated using ChemOffice 2004 program. The calculated structural parameters of substituted anilines were used as theoretical descriptors and the two-parameter （molecular surface area （MA） and the energy of the highest occupied molecular orbital （EaoMo）） quantitative structure-property relationship （QSPR） model of lgKow for substituted aniline with molecular structural parameters was developed by multi-linear regression method. The regression coefficient square （r^2） is 0.990 and the standard deviation SE 0.109. The model was validated by variance inflation factors （VIF） and t-test, and the results show that there exists small self-correlation between variables of the model with perfect stability. The model gives results in good qualitative agreement with experimental data. At last, the model was applied to predict lgKow values of five substituted anilines whose lgKow values have not been determined experimentally.展开更多
Optimized calculations of 75 PCDDs and their parent DD were carded out at the B3LYP/6-31G＊ level by density functional theory （DFT） method. The structural parameters were obtained and significant correlation betwee...Optimized calculations of 75 PCDDs and their parent DD were carded out at the B3LYP/6-31G＊ level by density functional theory （DFT） method. The structural parameters were obtained and significant correlation between the C1 substitution position and some structural parameters was found. Consequently, the number of C1 substitution positions was taken as theoretical descriptors to establish two novel QSPR models for predicting lgKow and -lgSw of all PCDD congeners. The two models achieved in this work contain two variables （Na and Nβ）, of which r = 0.9312, 0.9965 and SD = 0.27, 0.12 respectively, and t values are all large. The variation inflation factors （VIF） of variables in the two models herein are both less than 5.0, suggesting high accuracy of the lgKow and -lgSw predicting models, and the results of cross-validation test also show that the two models exhibit optimum stability and good predictive power. By comparison, the correlation and predictive ability of the present work are more advantageous than those obtained using semi-empirical AM1 and GC-RI methods.展开更多
There is an ever-growing demand for lightweighting of steel for structural applications,particularly for automobile and transportation applications.It is mainly to improve the fuel efficiency,reduce the CO_(2) emissio...There is an ever-growing demand for lightweighting of steel for structural applications,particularly for automobile and transportation applications.It is mainly to improve the fuel efficiency,reduce the CO_(2) emissions and cater the increased passenger safety.Hence,the main focus is to reduce the density of the steel structure without affecting other properties.This can be achieved by down-gauging of the conventional steel by replacing the steel with higher strength,however,it is limited by dent resistance and stiffness.So,the novel idea is to reduce the density of the steel itself.It is well-known that addition of Al to steel reduces the density of the steel.About 1wt% of Al addition to steel can reduce the density by 1.3%,decreases the elastic modulus by 2% and it improves the strength by about 40 MPa.There is a new class of low-density/lightweight steel with addition of about 6-9 wt% Al to steel.Addition of higher than 9 wt%of Al in steel leads to embrittlement issues due to ordering and environmental effect.These disordered Fe-Al lightweight steels have raised considerable interest due to their low-density,high ductility,costeffectiveness and feasibility for bulk production.The low-density steels are envisaged in the development of an advanced lightweight ground transportation system,huge structures and also for certain defence applications and in thermal power plants.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No U1301243the National Key Research and Development Program of China under Grant No 2016YFB0400701
文摘We report a simple hole-blocking material （biphenyl-3,3＇-diyl）bis（diphenylphosphine oxide） （BiPh-m-BiDPO） based on our recent advance. The bis（phosphine oxide） compound shows HOMO/LUMO levels of ∽-6.71/- 2.51 eV. Its phosphorescent spectrum in a solid film features two major emission bands peaking at 2.69 and 2.4eV, corresponding to 0-0 and 01 vibronic transitions, respectively. The measurement of the electron-only devices reveals that BiPh-m-BiDPO possesses electron mobility of 2.28 × 10^-9-3.22× 10^-8cm2 V-1s-1 at E = 2- 5 × 10^5 V/cm. The characterization of the sky blue fluorescent and red phosphorescent pin organic light-emitting diodes （OLEDs） utilizing BiPh-m-BiDPO as the hole blocker shows that its shallow LUMO level as well as the low electron mobility affects significantly the power efficiency and hence operational stability, relative to the luminous efficiency, especially at high luminance. In combination with our recent results, the present study provides an indepth insight on the molecular structure-property correlation in the organic phosphinyl-containing hole-blocking materials.
基金the Science and Engineering Re-search Board(SERB),India for providing the financial assistance to support this work(Project No.SRG/2020/002449).
文摘Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.
基金supported by the National Natural Science Foundation of China(Nos.21921001,22075283,92161125,22175172,21827813,U21A20508)the Youth Innovation Promotion Association of Chinese Academy of Sciences(Nos.2020303,2021300)the Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(No.2020ZZ108)。
文摘Enhancement of the nonlinear optical(NLO)output power of lasers requires urgent development of an NLO crystal with a significant second-harmonic generation(SHG)response and sufficient birefringence for phase-matching capability;however,simultaneously optimizing these two key parameters remains a great challenge.In contrast to traditional single-anion units,the stereochemically-active lone pair Sb^(3+)ion is coordinated by S^(2-)and I^(-) ions to yield the mixed-anionic Sb SI chalcohalide that can enhance hyperpolarizability and anisotropic polarizability concurrently.As anticipated,Sb SI exhibited the largest SHG response(5.7×Ag Ga S_(2)@1.91μm)among phase-matching Sb-based sulfides,the favorable laser-induced damage threshold(LIDT,2.3×Ag Ga S_(2)@2.09μm),and the giant calculated birefringence(0.62@1.91μm).Structural analysis and computational simulations indicate that the highly polarizable mixed anion determine the enormous SHG response and birefringence.
基金the National Natural Science Foundation of China(22172097)the Shaanxi Provincial Sci-ence Fund for Distinguished Young Scholars(2025JC-JCQN-044)+1 种基金the National Key Research and Development Program of China(2022YFA1205502)the 111 Project(B14041).
文摘Correlation between tunable optical properties and push-pull structural characters has attracted extensive attention in material science and nonlinear optics.Here,several indacenodithiophene(IDT)derivatives denoted as IDT-2NA,NA-IDT-CN,and IDT-2CN with different terminal substituents are investigated comparatively to demonstrate their intrinsic structure-property relationships.Interestingly,the IDT core acts diverse roles as acceptor(A)and donor(D)in the obtained three derivatives.Symmetric IDT-2NA with a D-A-D architecture shows an absorption maximum around 459 nm in THF.Contrary to the symmetric analog IDT-2CN with a reverse A-D-A feature,NA-IDT-CN with a different D-D'-A motif characterizes an obvious solvent polarity effect.Theo-retical calculation and electrostatic potential results confirm the terminal substituents with different electronic conjugation play vital roles in affecting the resultant photophysical properties.Utilizing the femtosecond open-aperture Z-scan technique,significant two-photon absorption(2PA)capabilities are obtained ranging from 540 to 900 nm.The 2PA cross section(δ_(2pA) )maximum about 5390 GM of centrosymmetric IDT-2CN exhibits at 600 nm.Distinct excited-state dynamics with the help of femtosecond transition absorption supports the effective intramolecular charge transfer which accounts for enhancing theδ_(2pA) values.Their potential optical power limiting applications based on the 2PA mechanism were further evaluated.The limiting thresholds were found to be 2.793.35 mJ/cm^(2) for the three IDT derivatives with a sequence of IDT-2CN<IDT-2NA<NA-IDT-CN.The distinct structural motifs and effective 2PA capabilities in the current work may provide reliable insights into the push-pull IDT chromophores for advanced nonlinear optical applications.
基金supported by the National Natural Science Foundation of China(No.22473006)the Central Government Guiding Local Science and Technology Development Fund(No.2025ZY01029).
文摘Polymer informatics faces challenges owing to data scarcity arising from complex chemistries,experimental limitations,and process-ing-dependent properties.This review presents the recent advances in data-efficient machine learning for polymers.First,data preparation tech-niques such as data augmentation and rational representation help expand the dataset size and develop useful features for learning.Second,modeling approaches,including classical algorithms and physics-informed methods,enhance the model robustness and reliability under limited data conditions.Third,learning strategies,such as transferlearning and active learning,aim to improve generalization and guide efficient data ac-quisition.This review concludes by outlining future opportunities in machine learning for small-data scenarios in polymers.This review is expect-ed to serve as a useful tool for newcomers and offer deeper insights for experienced researchers in the field.
基金supported by the National Natural Science Foundation of China(22171136,52202138)the Natural Science Foundation of Jiangsu Province(BK20200472,BK20220079)+3 种基金the Medical Innovation and Development Project of Lanzhou University(lzuyxcx-2022-156)CAMS Innovation Fund for Medical Sciences(CIFMS,2019-I2M-5-074,2021-I2M-1-026,2021-I2M-3-001)the Frontier Technologies R&D Program of Jiangsu(Grant no.BF2024033)G.Z.acknowledges the support of the Thousand Young Talent Plan.
文摘Noteworthy challenges such as severe side reactions,interfacial instability,and dendrite growth have plagued rechargeable alkali metal batteries for a long time.Alleviating the plight necessitates innovative membranes capable of modulating ion transport and establishing stable interfaces.The exploration of implemented membranes with thermal/mechanical and electrochemical stability is crucial for achieving high-performance and safe alkali metal batteries.Crystalline covalent organic framework(COF)membranes have emerged as promising materials for next-generation energy storage systems due to their tunable porosity and exceptional physicochemical properties.This review specifically examines the critical role of COF membranes in enabling sustainable alkali metal(Li/Na/K)batteries,with a particular focus on design principles,performance advantages,and key challenges of COF membranes.The discussion emphasizes structure-property relationships specifically relevant to rechargeable battery applications,supported by recent decades of research.Impressively,this mini review further identifies three critical research frontiers:reticular chemistry-guided materials design,multifunctional composite architectures,and in-situ characterization techniques.This targeted analysis provides actionable insights for developing COF membranes that address the fundamental limitations of current alkali metal battery technologies.
基金supported by the National Natural Science Foundation of China(Nos.22273112 and 22203100).
文摘Polyelectrolytes(PEs)are polymers carrying ionizable groups along the chain backbone and play an important role in life and environmental sciences,industrial applications and other fields.Due to the complicated topological structure and electrostatic correlations of PEs,PEs exhibit very rich phase behavior and morphologies in both bulk and confined solutions.So far,many theories,simulations and machine learning approaches have been proposed to study the behavior of polyelectrolyte solutions,especially the intrinsic structure-property relationships.In this perspective,from a personal point of view,we present several recent trends in polyelectrolyte solutions.The main themes considered here are accelerated development of sequence-defined polyelectrolyte(SDPE)via artificial intelligence technology,liquid-liquid phase separation in bulk SDPE solutions,adsorption behaviors of SDPE in the vicinity of a single dielectric surface,and surface forces between two charged surfaces mediated by SDPE solutions.
基金the National Natural Science Foundation of China(22178243 and 22038008).
文摘Direct coal liquefaction products offer a considerable quantity of cycloalkanes, which are the valuable candidates for making the high energy density fuels. The creation of such fuels depends on designing molecular structures and calculating their properties, which can be expedited with computer-aided techniques. In this study, a dataset containing 367 fuel molecules was constructed based on the analysis of direct coal liquefied oil. Three convolutional neural network property prediction models have been created based on molecular structure-physical and chemical property data from the library. All the models have good fitting ability with R2 values above 0.97. Then, a variational autoencoder generation model has been established using the molecular structures from the library, focusing on the structure of saturated cycloalkanes. The structure-property prediction model was then applied to the newly generated molecules, assessing their density, volumetric calorific value, and melting point. As a result, 70000 novel molecular structures were generated, and 25 molecular structures meeting the criteria for high energy density fuels were identified. The established variational autoencoder model in this study effectively assimilates the structural information from the sample set and autonomously generates novel high energy density fuels, which is difficult to achieve in traditional experimental methods.
基金Project supported by the National Natural Science Foundation of China(21301107,21501109)the Excellent Young Scientists Fund from NSFC(21622106)+3 种基金the Taishan Scholar Project of Shandong Province of China,China Postdoctoral Science Foundation(2014M551891,2015T80706)Doctoral Funding of Shandong Province of China(BS2014CL008)Specialized Research Fund for the Doctoral Program of Higher Education(20130131120009)Postdoctoral Innovation Project Foundation of Shandong Province(201301008)
文摘Copper-ceria sheets catalysts with different loadings of copper（2 wt.%, 5 wt.% and 10 wt.%） supported on ceria nanosheets were synthesized via a depositioneprecipitation（DP） method. The prepared catalysts were systematically characterized with various structural and textural detections including X-ray diffraction（XRD）, Raman spectra, transmission electron microscopy（TEM）, X-ray absorption fine structure（XAFS）, and temperature-programmed reduction by hydrogen（H2-TPR）, and tested for the CO oxidation reaction. Notably, the sample containing 5 wt.% of Cu exhibited the best catalytic performance as a result of the highest number of active CuO species on the catalyst surface. Further increase of copper content strongly affects the dispersion of copper and thus leads to the formation of less active bulk CuO phase, which was verified by XRD and H2-TPR analysis. Moreover, on the basis of in-situ diffuse reflectance infrared Fourier transform spectroscopy（in-situ DRIFTS） results, the surface Cu~＋ species, which are derived from the reduction of Cu^（2＋）, are likely to play a crucial role in the catalyzing CO oxidation.Consequently, the superior catalytic performance of the copper-ceria sheets is mainly attributed to the highly dispersed CuOx cluster rather than Cu-[Ox]-Ce structure, while the bulk CuO phase is adverse to the catalytic activity of CO oxidation.
基金Supported by Industrialization Cultivation Projects in Colleges and Universities of Hunan Province(13CY030)Natural Science Foundation of Hunan Province(12JJ6026)Colleges and Universities Open Innovation Platform Fund of Hunan Province(14K053,15K066)~~
文摘In order to solve the problem of poor interpretability of support vector re- gression （SVR） applied in quantitative structure-property relationship （QSPR）, a com- plete set of explanatory system for SVR was established based on F-test, The nov- el explanatory system includes significance tests of model and single-descriptor im- portance, single-descriptor effect and sensitivity analysis, and significance tests of interaction between two descriptors, etc. The results of example indicated that the explanatory results of the new system were consistent well with those of stepwise linear regression model and quadratic polynomial stepwise regression model. The explanatory SVR model will play an important role in regression analysis such as QSPR.
基金Supported by the National Natural Science Foundation of China(21676152)
文摘Extractive distillation is an effective method for separating azeotropic or close boiling point mixtures by adding a third component.Various technologies for performing the extractive distillation process have been explored to protect the environment and save resources.This paper focuses on the improvement of these advanced technologies in recent years.Extractive distillation is retrieved and analyzed from the view of phase equilibrium,selection of solvent in extractive distillation,process design,energy conservation,and dynamic control.The quantitative structure–property relationship used in extractive distillation is discussed,and the future development of extractive distillation is proposed to determine how the solvent affects the relative volatility of the separated mixture.In the steady state design,the relationship between the curvature of the residue curve and parameters of the optimal steady state is also highlighted as another field worthy of further study to simplify the distillation process.
基金financially supported by the Natural Science Foundation of Shanghai(No.20ZR1419200)the National Natural Science Foundation of China(No.51972089)the Program for Professor of Special Appointment(Eastern Scholar)by Shanghai Municipal Education Commission(No.TP2015040)。
文摘Recent technical progress in the industry has led to an urgent requirement on new materials with enhanced multi-properties.To meet this multi-property requirement,the materials consisting of three and more elements have attracted increasing attention.However,facing to the nearly unknown huge multi-component materials system,the traditional trial and error method cannot provide sufficient data efficiently.Therefore,an efficient material innovation strategy is significant.The first-principles calculation based on the density functional theory is a powerful tool for both the accurate prediction of material properties and the identification of its underlying thermodynamics and dynamics.At the same time,the advances of computational methods and computer calculation abilities that are orders of magnitude faster than before make the high throughput first-principles calculations popular.At present,the simulation-assisted material design has become a main branch in the material research field and a great many successes have been made.In this article,the advances of the high throughput first-principles calculations are reviewed to show the achievements of the first-principles calculations and guide the future directions of its applications in ceramics.
文摘An oil-in-water (O/W) solvent evaporation method was used to prepare biodegradable microspheresbased on poly(D,L-lactic acid) (PLA). Nifedipine, a hydrophobic drug, was chosen as a model molecule in the studyof drug entrapment and release. Effect of preparation conditions on the size, morphology, drug loading, and releaseprofiles of micropheres was investigated. Based on in vitro release experimental findings, a diffusion/dissolutionmodel was presented for quantitative description of the resulting release behaviors and drug release kinetics fromPLA microspheres analyzed. The mathematical models were used to predict the effect of microstructure on theresulting drug release. It provided an approach to determine the suitable structure parameters for microspheres toachieve desired drug release behaviors.
基金supported by the National Natural Science Foundation of China(Nos.21771021 and 21822501)the Beijing Nova Program(No.xx2018115)+1 种基金the Fundamental Research Funds for the Central UniversitiesAnalytical and Measurements Fund of Beijing Normal University
文摘Recently,molecule-based luminescent materials have been drawing extensive attention due to their desirable properties and promising applications in the fields of sensors,lighting display and cell imaging.Crystalline polymorph is an intriguing phenomenon that the presence of multiple packing and aggregate architectures of the same molecular system.The studies on polymorphs for molecule-based fluorophores provide the opportunities to adjust the mode of molecular packing and photophysical properties,which will help to illustrate the structure-property relationship.In this review,we focus on the recent progress in various feasible methods of molecule-based crystalline polymorphism growth and their adjustable photofunctional properties,which will open up possibilities of variant optical applications.Firstly,several effective ways to prepare and screen polymorphs are sorted out.And then,we discuss the discrepant properties and multifunctional applications(such as sensors,laser and OFET).Finally,the development trends and future prospects of these polymorphs are also briefly introduced.
基金supported by the National Natural Science Foundation of China(grant number 51872157)Shenzhen Technical Plan Project(grant number KQJSCX20160226191136 and JCYJ20170412170911187)Research Grants Council of the Hong Kong Special Administrative Region,China[grant number PF17-10186]。
文摘In nature,the properties of matter are ultimately governed by the electronic structures.Quantum chemistry(QC)at electronic level matches well with a few simple physical assumptions in solving simple problems.To date,machine learning(ML)algorithm has been migrated to this field to simplify calculations and improve fidelity.This review introduces the basic information on universal electron structures of emerging energy materials and ML algorithms involved in the prediction of material properties.Then,the structure-property relationships based on ML algorithm and QC theory are reviewed.Especially,the summary of recently reported applications on classifying crystal structure,modeling electronic structure,optimizing experimental method,and predicting performance is provided.Last,an outlook on ML assisted QC calculation towards identifying emerging energy materials is also presented.
基金This work was financially supported by the National Basic Research Program of China (2003CB415002), the China Postdoctoral Science Foundation (No. 2003033486) and the Natural Science Research Fund of University in Jiangsu (04KJB150149)
文摘Twenty eight alkyl(1-phenylsulfonyl) cycloalkane carboxylates were computed at the B3LYP/6-31G* level. Based on linear solvation energy theory, two quantitative correlation equations of the molecular structures of alkyl(1-phenylsulfonyl) cycloalkane carboxylate com- pounds to their chromatographic retention (capacity factor lgKW) and the toxicity for photo- bacterium phosphoreum (–lgEC50) were developed by using the molecular structural parameters as theoretical descriptors (r2 = 0.9501, 0.9488). The two quantitative correlation equations were consequently cross validated by leave-one-out (LOO) validation method with q2 of 0.9113 and 0.9281, respectively. The result showed that the two equations achieved in this work by B3LYP/6-31G* are both more advantageous than those from AM1, and can be used to predict the lgKW and –lgEC50 of congeneric organics.
基金Supported by the National Natural Science Foundation of China(No.21673207)Special Fundamental Research Fund for the Central Public Scientific Research Institutes(No.562018Y-5983)Zhejiang Provincial Collaborative Innovation Center of Food Safety and Nutrition(No.2017SICR115,2017SICR101)
文摘The extensive utilization of the low-energy dipeptide sweetener aspartame in foods leads to various studies on searching for new sweeteners in series. However, the real mechanistic cause of their sweetness power is still not completely known owing to their complex interactions with human sweet receptor, which may be different from that of other sweeteners to some extent. In this contribution, predictive quantitative structure-property relationship(QSPR) models have been developed for diverse aspartame analogues using Materials Studio 5.0 software. The optimal QSPR model(r2 = 0.913, r2 CV = 0.881 and r2 pred = 0.730) constructed by the genetic function approximation method has been validated by the tests of cross validation, randomization, external prediction and other statistical criteria, which shows that their sweetness power is mainly governed by their electrotopological-state indices(SssCH and SsNH), spatial descriptors(Shadow length: LX, ellipsoidal volume and Connolly surface occupied volume) and topological descriptors(Chi(3): cluster and Chi(0)(valence modified)), which partially supports both multipoint attachment theory proposed by Nofre and Tinti et al. and B-X theory proposed by Kier et al.. Present exploited results provide the key structural features for the sweetness power of aspartame analogues, supplement the mechanistic understanding of the sweet perception, and would be also helpful for the design of potent sweetener analogs prior to their synthesis.
基金This work was supported by the National Natural Science Foundation of China (No. 20737001)
文摘The n-octanol/water partition coefficients （lgKow） of 18 substituted anilines were determined at 25 ℃ by shake-flask method. The geometrical optimization of substituted anilines has been performed at B3LYP/6-311G^＊＊ level with Gaussian98 program, and the molecular surface areas of substituted anilines were calculated using ChemOffice 2004 program. The calculated structural parameters of substituted anilines were used as theoretical descriptors and the two-parameter （molecular surface area （MA） and the energy of the highest occupied molecular orbital （EaoMo）） quantitative structure-property relationship （QSPR） model of lgKow for substituted aniline with molecular structural parameters was developed by multi-linear regression method. The regression coefficient square （r^2） is 0.990 and the standard deviation SE 0.109. The model was validated by variance inflation factors （VIF） and t-test, and the results show that there exists small self-correlation between variables of the model with perfect stability. The model gives results in good qualitative agreement with experimental data. At last, the model was applied to predict lgKow values of five substituted anilines whose lgKow values have not been determined experimentally.
基金This work was supported by the National Natural Science Foundation of China (No. 20737001)(2003CB415002)China Postdoctoral Science Foundation (No. 2003033486)
文摘Optimized calculations of 75 PCDDs and their parent DD were carded out at the B3LYP/6-31G＊ level by density functional theory （DFT） method. The structural parameters were obtained and significant correlation between the C1 substitution position and some structural parameters was found. Consequently, the number of C1 substitution positions was taken as theoretical descriptors to establish two novel QSPR models for predicting lgKow and -lgSw of all PCDD congeners. The two models achieved in this work contain two variables （Na and Nβ）, of which r = 0.9312, 0.9965 and SD = 0.27, 0.12 respectively, and t values are all large. The variation inflation factors （VIF） of variables in the two models herein are both less than 5.0, suggesting high accuracy of the lgKow and -lgSw predicting models, and the results of cross-validation test also show that the two models exhibit optimum stability and good predictive power. By comparison, the correlation and predictive ability of the present work are more advantageous than those obtained using semi-empirical AM1 and GC-RI methods.
文摘There is an ever-growing demand for lightweighting of steel for structural applications,particularly for automobile and transportation applications.It is mainly to improve the fuel efficiency,reduce the CO_(2) emissions and cater the increased passenger safety.Hence,the main focus is to reduce the density of the steel structure without affecting other properties.This can be achieved by down-gauging of the conventional steel by replacing the steel with higher strength,however,it is limited by dent resistance and stiffness.So,the novel idea is to reduce the density of the steel itself.It is well-known that addition of Al to steel reduces the density of the steel.About 1wt% of Al addition to steel can reduce the density by 1.3%,decreases the elastic modulus by 2% and it improves the strength by about 40 MPa.There is a new class of low-density/lightweight steel with addition of about 6-9 wt% Al to steel.Addition of higher than 9 wt%of Al in steel leads to embrittlement issues due to ordering and environmental effect.These disordered Fe-Al lightweight steels have raised considerable interest due to their low-density,high ductility,costeffectiveness and feasibility for bulk production.The low-density steels are envisaged in the development of an advanced lightweight ground transportation system,huge structures and also for certain defence applications and in thermal power plants.
