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
A novel quantitative structure-property relationship （QSPR） model for estimating the solution surface tension of 92 organic compounds at 20℃ was developed based on newly introduced atom-type topological indices. Th...A novel quantitative structure-property relationship （QSPR） model for estimating the solution surface tension of 92 organic compounds at 20℃ was developed based on newly introduced atom-type topological indices. The data set contained non-polar and polar liquids, and saturated and unsaturated compounds. The regression analysis shows that excellent result is obtained with multiple linear regression. The predictive power of the proposed model was discussed using the leave-one-out （LOO） cross-validated （CV） method. The correlation coefficient （R） and the leave-one-out cross-validation correlation coefficient （Rcv） of multiple linear regression model are 0.991 4 and 0.991 3, respectively. The new model gives the average absolute relative deviation of 1.81% for 92 substances. The result demonstrates that novel topological indices based on the equilibrium electro-negativity of atom and the relative bond length are useful model parameters for QSPR analysis of compounds.展开更多
The ring-opening polymerization of heterocyclic monomers and the reversed ring-closing depolymerization of corresponding polymers with neutral thermodynamics are broadly explored to establish a circular economy of nex...The ring-opening polymerization of heterocyclic monomers and the reversed ring-closing depolymerization of corresponding polymers with neutral thermodynamics are broadly explored to establish a circular economy of next-generation plastics.Polythioesters(PTEs),analogues of polyesters,are emerging materials for this purpose due to their high refractive index,high crystallinity,dynamic property and responsiveness.In this work,we synthesize and polymerize a series of D-penicillamine-derivedβ-thiolactones(NRPenTL)with varied side chain alkyl groups,and study the structure-property relationship of the resulting polymers.The obtained PTEs exhibit tunable glass transition temperature in a wide range of 130–50℃,and melting temperature of 90–105℃.In addition,copolymerizations of monomers with different side chains are effective in modulating material properties.The obtained homo and copolymers can be fully depolymerized to recycle monomers.This work provides a robust molecular platform and detailed structure-property relationship of PTEs with potential of achieving sustainable plastics.展开更多
As the scaling down of semiconductor devices, it would be necessary to discover the structure-property relationship of semiconductor nanomaterials at nanometer scale. In this review, the quantitative characterization ...As the scaling down of semiconductor devices, it would be necessary to discover the structure-property relationship of semiconductor nanomaterials at nanometer scale. In this review, the quantitative characterization technique off-axis electron holography is introduced in details, followed by its applications in various semiconductor nanomaterials including group IV, compound and two-dimensional semiconductor nanostructures in static states as well as under various stimuli. The advantages and disadvantages of off-axis electron holography in material analysis are discussed, the challenges facing in-situ electron holographic study of semiconductor devices at working conditions are presented, and all the possible influencing factors need to be considered to achieve the final goal of fulfilling quantitative characterization of the structure-property relationship of semiconductor devices at their working conditions.展开更多
In recent twenty years,aggregation-induced emission(AIE),due to its excellent application prospect,has aroused widespread interests.The development of novel and easy to make AIE luminogens(AIEgens)is an attractive sub...In recent twenty years,aggregation-induced emission(AIE),due to its excellent application prospect,has aroused widespread interests.The development of novel and easy to make AIE luminogens(AIEgens)is an attractive subject.For this purpose,it is very important to study the structure-property relationship of AIEgens.Because azine derivatives are easy to synthesis and some of them have nice AIE properties,herein,a series of azine derivatives(ADs)were employed as models to study the influence of different functional groups,electronic effects and structures on the AIE properties of azine derivatives.The AIE mechanism were studied by single crystal analysis,density functional theory(DFT)calculations and so on.The results indicated that the o-hydroxyl aryl substituted azine compounds could show good AIE properties.Meanwhile,the AIE properties of o-hydroxyl aryl substituted azine compounds were also influenced by the electronic effects of the aryl groups in the azine compounds.The o-hydroxyl groups could form intramolecular hydrogen bond with imine group,which play key role to restrict the intramolecular rotation of the aryl groups and act as base stone for the AIE process of this kind compounds.The HOMO-LUMO energy gaps of o-hydroxyl substituted azine are smaller than other homologous compounds,which is agree with the proposed AIE mechanism.Finally,thanks to the AIE properties,the o-hydroxy-substituted azines could be used as efficient Al^(3+)and Cu^(2+)fluorescent chemosensors in different conditions.In addition,test strips based on AD10 has been prepared,which can conveniently detect Cu^(2+)in industrial wastewater.This research supplied a way for the design of novel easy to make AIEgens through simple azine derivatives.展开更多
A quantitative structure-property relationship (QSPR) study has been made for the prediction of the surface tension of nonionic surfactants in aqueous solution. The regressed model includes a topological descriptor, ...A quantitative structure-property relationship (QSPR) study has been made for the prediction of the surface tension of nonionic surfactants in aqueous solution. The regressed model includes a topological descriptor, the Kier & Hall index of zero order (KH0) of the hydrophobic segment of surfactant and a quantum chemical one, the heat of formation (fHD) of surfactant molecules. The established general QSPR between the surface tension and the descriptors produces a correlation coefficient of multiple determination, 2r=0.9877, for 30 studied nonionic surfactants.展开更多
X-ray crystal structures of 2,2',3,3'-and 3, 3',4,4'-biphenyltetracarboxylic dianhydride (2,2',3,3'- and 3,3',4,4'-BPDA) were determined. The dianhydride isomers have different symmetr...X-ray crystal structures of 2,2',3,3'-and 3, 3',4,4'-biphenyltetracarboxylic dianhydride (2,2',3,3'- and 3,3',4,4'-BPDA) were determined. The dianhydride isomers have different symmetry caused by difference in two anhydride group positions and the dihedral angles between the two phenyl rings are 62.9°for 2,2',3,3',-BPDA and 0°for 3,3',4,4'-BPDA respectively. The polyimides from 2,2',3,3'-BPDA exhibit enhanced solubility, higher thermal stability, and higher glasstransition temperature (Tg) compared with those from 3,3',4,4'-BPDA.展开更多
Efficient removal of^(137)Cs and^(90)Sr from radioactive waste liquids is challenging due to their strong radioactivity,solubility,and mobility.Herein,the efficient Cs^(+)/Sr^(2+)capture has been achieved by layered t...Efficient removal of^(137)Cs and^(90)Sr from radioactive waste liquids is challenging due to their strong radioactivity,solubility,and mobility.Herein,the efficient Cs^(+)/Sr^(2+)capture has been achieved by layered thioniobates and thiotantalate with radiation resistance,namely K_(0.36)NbS_(2)·0.54H_(2)O(K-NbS_(2)),Rb_(0.36)NbS_(2)·0.54H_(2)O(Rb-NbS_(2)),and K_(0.33)TaS_(2)·0.75H_2O(K-TaS_(2)).In particular,K-NbS_(2)exhibits high adsorption capacities,fast kinetics,and fantastic p H durability.K-NbS_(2)is an unprecedented scavenger for selective Sr^(2+)capture in acidic solutions containing excess Na^(+)/Mg^(2+)ions.They show successful cleanup for acidic^(90)Sr-liquid-waste generated during industrial production.Importantly,the removal mechanism is revealed as the ion exchange between Cs^(+)/Sr^(2+)and interlayer K^(+)in thioniobates and thiotantalate due to their appropriate interlayer distances,flexible and adjustable frameworks,and strong affinity of soft basic S^(2-)for Cs^(+)/Sr^(2+).Further,the structure-property relationship study indicates that there is an inverted U-curve rule for the relationship between interlayer distances of layered metal sulfides and ion exchange performance.The rule combined with the factors affecting interlayer distance can be used to direct the structural design and predict properties for the specific recognition and separation of radionuclides.This is a pioneering work on the development of thioniobates/thiotantalate ion exchangers with a deep insight into structure-property relationship for radionuclide remediation.展开更多
Spinels have been widely concerned as a promising class of electrocatalysts due to their appealing catalytic properties and the tunability of their compositions and structures.Ligand field theory(LFT),which describes ...Spinels have been widely concerned as a promising class of electrocatalysts due to their appealing catalytic properties and the tunability of their compositions and structures.Ligand field theory(LFT),which describes the origins and the consequences of metal-ligand interactions,offers crucial insights for the design of spinel-type electrocatalysts.In this review,we timely summarize the research progress of spinel electrocatalysts that leverage LFT for structure-property insights,providing a pioneering perspective in this field.This review explores how LFT plays a pivotal role in optimizing the electrocatalytic properties of spinels.It covers important aspects such as identifying the origin of the catalytic properties,tuning the number of active sites,manipulating the eg-filling and the spin state of metal cations,and modulating the 2p band of ligands.We anticipate that this review will provide valuable theoretical guidance and inspire creative spinel designs that excel in electrocatalytic applications.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
The enthalpies of vaporization for the series of pyridinium-based ionic liquids with bis（trifluoromethylsulfonyl）imide anion [CnPy][NTfz] （n = 2, 3, 4, 5, and 6） have been determined with the quartz crystal microb...The enthalpies of vaporization for the series of pyridinium-based ionic liquids with bis（trifluoromethylsulfonyl）imide anion [CnPy][NTfz] （n = 2, 3, 4, 5, and 6） have been determined with the quartz crystal microbalance technique combined with the Langmuir evaporation. The linear dependence of vaporization enthalpies on the chain length has been revealed. New approach based on volumetric, surface tension, and speed of sound measurements has been developed for estimation of heat capacity differences between gas and liquid phase, which were required for adjustment of measured vaporization enthalpies to the ref- erence temperature 298 K.展开更多
Chemical industry is always seeking opportunities to efficiently and economically convert raw materials to commodity chemicals and higher value-added chemicalbased products.The life cycles of chemical products involve...Chemical industry is always seeking opportunities to efficiently and economically convert raw materials to commodity chemicals and higher value-added chemicalbased products.The life cycles of chemical products involve the procedures of conceptual product designs,experimental investigations,sustainable manufactures through appropriate chemical processes and waste disposals.During these periods,one of the most important keys is the molecular property prediction models associating molecular structures with product properties.In this paper,a framework combining quantum mechanics and quantitative structure-property relationship is established for fast molecular property predictions,such as activity coefficient,and so forth.The workflow of framework consists of three steps.In the first step,a database is created for collections of basic molecular information;in the second step,quantum mechanics-based calculations are performed to predict quantum mechanics-based/derived molecular properties(pseudo experimental data),which are stored in a database and further provided for the developments of quantitative structure-property relationship methods for fast predictions of properties in the third step.The whole framework has been carried out within a molecular property prediction toolbox.Two case studies highlighting different aspects of the toolbox involving the predictions of heats of reaction and solid-liquid phase equilibriums are presented.展开更多
Quantitative structure-property relationship(QSPR)models were developed for prediction of photolysis half-life(t_(1/2))of polychlorinated biphenyls(PCBs)in water under ultraviolet(UV)radiation.Quantum chemical descrip...Quantitative structure-property relationship(QSPR)models were developed for prediction of photolysis half-life(t_(1/2))of polychlorinated biphenyls(PCBs)in water under ultraviolet(UV)radiation.Quantum chemical descriptors computed by the PM3 Hamiltonian software were used as independent variables.The cross-validated Q^(2)_(cum)value for the optimal QSPR model is 0.966,indicating good prediction capability for lg t_(1/2)values of PCBs in water.The QSPR results show that the largest negative atomic charge on a carbon atom(Q-C)and the standard heat of formation(ΔH_(f))have a dominant effect on t_(1/2)values of PCBs.Higher Q_(C)^(-)values or lowerΔHf values of the PCBs leads to higher lg t_(1/2)values.In addition,the lg t_(1/2)values of PCBs increase with the increase in the energy of the highest occupied molecular orbital values.Increasing the largest positive atomic charge on a chlorine atom and the most positive net atomic charge on a hydrogen atom in PCBs leads to the decrease of lg t_(1/2)values.展开更多
In order to predict the critical micelle concentration (cmc) of nonionic surfactants in aqueous solution,a quantitative structure-property relationship (QSPR) was found for 77 nonionic surfactants belonging to eight s...In order to predict the critical micelle concentration (cmc) of nonionic surfactants in aqueous solution,a quantitative structure-property relationship (QSPR) was found for 77 nonionic surfactants belonging to eight series. The best-regressed model contained four quantum-chemical descriptors,the heat of formation (ΔH),the molecular dipole moment (D),the energy of the lowest unoccupied molecular orbital (E_ LUMO ) and the energy of the highest occupied molecular orbital (E_ HOMO ) of the surfactant molecule; two constitutional descriptors,the molecular weight of surfactant (M) and the number of oxygen and nitrogen atoms (n_ ON ) of the hydrophilic fragment of surfactant molecule; and one topological descriptor,the Kier & Hall index of zero order (KH0) of the hydrophobic fragment of the surfactant. The established general QSPR between lg(cmc) and the descriptors produced a relevant coefficient of multiple determination:R 2=0.986. When cross terms were considered,the corresponding best model contained five descriptors E_ LUMO ,D,KH0,M and a cross term n_ ON ·KH0,which also produced the same coefficient as the seven-parameter model.展开更多
Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatical...Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.展开更多
Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy cl...Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.展开更多
During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 202...During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.展开更多
The banding and electronic structures of a series of long-chain macromolecules of cellu- lose,2-,3-,6-mononitrocellulose,2,3-,2,6-,3,6-dinitrocellulose and trinitrocellulose as well as their structural units(i.e.singl...The banding and electronic structures of a series of long-chain macromolecules of cellu- lose,2-,3-,6-mononitrocellulose,2,3-,2,6-,3,6-dinitrocellulose and trinitrocellulose as well as their structural units(i.e.single-,double-or three-ring systems)have been calculated by both the EH and CNDO/2 methods.The increase of molecular total energies is consistent with the decrease of their stabilities at the three conformations of gg,gt and tg.The Mulliken bond order of O—NO_2 bond is the samllest in each molecule at any of the three conformations,which indicates that this bond is the weakest,and supports the view of initial homolytic cleavage of O—NO_2 bond on slow thermal decomposition.The band gap at the edge of the first Brillouin zone far surpasses 5 eV for cellu- lose,and is less than 3 eV for mono-,di-,and trinitrocellulose.The results show that cellulose is a typical insulator,as we know,and it can be predicted that nitrocellulose has electric conductivity similar to that of semiconductor.展开更多
Collecting amounts of distorted/clean image pairs in the real world is non-trivial,which severely limits the practical application of these supervised learning-based methods to real-world image super-resolution(RealSR...Collecting amounts of distorted/clean image pairs in the real world is non-trivial,which severely limits the practical application of these supervised learning-based methods to real-world image super-resolution(RealSR).Previous works usually address this problem by leveraging unsupervised learning-based technologies to alleviate the dependency on paired training samples.However,these methods typically suffer from unsatisfactory texture synthesis due to the lack of supervision of clean images.To overcome this problem,we are the first to take a close look at the under-explored direction for RealSR,i.e.,few-shot real-world image super-resolution,which aims to tackle the challenging RealSR problem with few-shot distorted/clean image pairs.Under this brand-new scenario,we propose distortion relation guided transfer learning(DRTL)for the few-shot RealSR by transferring the rich restoration knowledge from auxiliary distortions(i.e.,synthetic distortions)to the target RealSR under the guidance of the distortion relation.Concretely,DRTL builds a knowledge graph to capture the distortion relation between auxiliary distortions and target distortion(i.e.,real distortions in RealSR).Based on the distortion relation,DRTL adopts a gradient reweighting strategy to guide the knowledge transfer process between auxiliary distortions and target distortions.In this way,DRTL is able to quickly learn the most relevant knowledge from the synthetic distortions for the target distortion.We instantiate DRTL with two commonly-used transfer learning paradigms,including pretraining and meta-learning pipelines,to realize a distortion relation-aware few-shot RealSR.Extensive experiments on multiple benchmarks and thorough ablation studies demonstrate the effectiveness of our DRTL.展开更多
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Projects(20775010,21075011) supported by the National Natural Science Foundation of ChinaProject(2008AA05Z405) supported by the National High Technology Research and Development Program of China+2 种基金Project(09JJ3016) supported by Hunan Provincial Natural Science Foundation,ChinaProject(09C066) supported by Scientific Research Fund of Hunan Provincial Education Department,ChinaProject(2010CL01) supported by the Foundation of Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation,China
文摘A novel quantitative structure-property relationship （QSPR） model for estimating the solution surface tension of 92 organic compounds at 20℃ was developed based on newly introduced atom-type topological indices. The data set contained non-polar and polar liquids, and saturated and unsaturated compounds. The regression analysis shows that excellent result is obtained with multiple linear regression. The predictive power of the proposed model was discussed using the leave-one-out （LOO） cross-validated （CV） method. The correlation coefficient （R） and the leave-one-out cross-validation correlation coefficient （Rcv） of multiple linear regression model are 0.991 4 and 0.991 3, respectively. The new model gives the average absolute relative deviation of 1.81% for 92 substances. The result demonstrates that novel topological indices based on the equilibrium electro-negativity of atom and the relative bond length are useful model parameters for QSPR analysis of compounds.
基金supported by the National Science Fund for Distinguished Young Scholars(No.22125101).
文摘The ring-opening polymerization of heterocyclic monomers and the reversed ring-closing depolymerization of corresponding polymers with neutral thermodynamics are broadly explored to establish a circular economy of next-generation plastics.Polythioesters(PTEs),analogues of polyesters,are emerging materials for this purpose due to their high refractive index,high crystallinity,dynamic property and responsiveness.In this work,we synthesize and polymerize a series of D-penicillamine-derivedβ-thiolactones(NRPenTL)with varied side chain alkyl groups,and study the structure-property relationship of the resulting polymers.The obtained PTEs exhibit tunable glass transition temperature in a wide range of 130–50℃,and melting temperature of 90–105℃.In addition,copolymerizations of monomers with different side chains are effective in modulating material properties.The obtained homo and copolymers can be fully depolymerized to recycle monomers.This work provides a robust molecular platform and detailed structure-property relationship of PTEs with potential of achieving sustainable plastics.
基金supported by the National Natural Science Foundation of China (51871104)the Fundamental Research Funds for the Central Universities (No.2019kfy RCPY074)。
文摘As the scaling down of semiconductor devices, it would be necessary to discover the structure-property relationship of semiconductor nanomaterials at nanometer scale. In this review, the quantitative characterization technique off-axis electron holography is introduced in details, followed by its applications in various semiconductor nanomaterials including group IV, compound and two-dimensional semiconductor nanostructures in static states as well as under various stimuli. The advantages and disadvantages of off-axis electron holography in material analysis are discussed, the challenges facing in-situ electron holographic study of semiconductor devices at working conditions are presented, and all the possible influencing factors need to be considered to achieve the final goal of fulfilling quantitative characterization of the structure-property relationship of semiconductor devices at their working conditions.
基金supported by the National Natural Science Foundation of China(NSFC,No.22065031)the Key R&D Program of Gansu Province(No.21YF5GA066)+4 种基金Gansu Province College Industry Support Plan Project(No.2022CYZC-18)Natural Science Foundation of Gansu Province(Nos.2020-0405-JCC-630,20JR10RA088)Fundamental Research Funds for the Central Universities(Nos.31920190041,31920200002,31920190018,31920190013)Young Doctor Foundation of Gansu Province(No.2021QB-148)The Science and Technology Project Funded by Social Capital in Longnan City of Gansu Province(No.2021-SZ-01)。
文摘In recent twenty years,aggregation-induced emission(AIE),due to its excellent application prospect,has aroused widespread interests.The development of novel and easy to make AIE luminogens(AIEgens)is an attractive subject.For this purpose,it is very important to study the structure-property relationship of AIEgens.Because azine derivatives are easy to synthesis and some of them have nice AIE properties,herein,a series of azine derivatives(ADs)were employed as models to study the influence of different functional groups,electronic effects and structures on the AIE properties of azine derivatives.The AIE mechanism were studied by single crystal analysis,density functional theory(DFT)calculations and so on.The results indicated that the o-hydroxyl aryl substituted azine compounds could show good AIE properties.Meanwhile,the AIE properties of o-hydroxyl aryl substituted azine compounds were also influenced by the electronic effects of the aryl groups in the azine compounds.The o-hydroxyl groups could form intramolecular hydrogen bond with imine group,which play key role to restrict the intramolecular rotation of the aryl groups and act as base stone for the AIE process of this kind compounds.The HOMO-LUMO energy gaps of o-hydroxyl substituted azine are smaller than other homologous compounds,which is agree with the proposed AIE mechanism.Finally,thanks to the AIE properties,the o-hydroxy-substituted azines could be used as efficient Al^(3+)and Cu^(2+)fluorescent chemosensors in different conditions.In addition,test strips based on AD10 has been prepared,which can conveniently detect Cu^(2+)in industrial wastewater.This research supplied a way for the design of novel easy to make AIEgens through simple azine derivatives.
基金the National Natural Science Foundation of China(to grant No.29903006 and 29973023)the Visiting Scholar Foundation of Key Laboratory in University of China for their financial support
文摘A quantitative structure-property relationship (QSPR) study has been made for the prediction of the surface tension of nonionic surfactants in aqueous solution. The regressed model includes a topological descriptor, the Kier & Hall index of zero order (KH0) of the hydrophobic segment of surfactant and a quantum chemical one, the heat of formation (fHD) of surfactant molecules. The established general QSPR between the surface tension and the descriptors produces a correlation coefficient of multiple determination, 2r=0.9877, for 30 studied nonionic surfactants.
文摘X-ray crystal structures of 2,2',3,3'-and 3, 3',4,4'-biphenyltetracarboxylic dianhydride (2,2',3,3'- and 3,3',4,4'-BPDA) were determined. The dianhydride isomers have different symmetry caused by difference in two anhydride group positions and the dihedral angles between the two phenyl rings are 62.9°for 2,2',3,3',-BPDA and 0°for 3,3',4,4'-BPDA respectively. The polyimides from 2,2',3,3'-BPDA exhibit enhanced solubility, higher thermal stability, and higher glasstransition temperature (Tg) compared with those from 3,3',4,4'-BPDA.
基金supported by the National Natural Science Foundation of China(22325605,U21A20296,22076185,22406185)the Natural Science Foundation of Fujian Province(2024J08105)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB1170000)。
文摘Efficient removal of^(137)Cs and^(90)Sr from radioactive waste liquids is challenging due to their strong radioactivity,solubility,and mobility.Herein,the efficient Cs^(+)/Sr^(2+)capture has been achieved by layered thioniobates and thiotantalate with radiation resistance,namely K_(0.36)NbS_(2)·0.54H_(2)O(K-NbS_(2)),Rb_(0.36)NbS_(2)·0.54H_(2)O(Rb-NbS_(2)),and K_(0.33)TaS_(2)·0.75H_2O(K-TaS_(2)).In particular,K-NbS_(2)exhibits high adsorption capacities,fast kinetics,and fantastic p H durability.K-NbS_(2)is an unprecedented scavenger for selective Sr^(2+)capture in acidic solutions containing excess Na^(+)/Mg^(2+)ions.They show successful cleanup for acidic^(90)Sr-liquid-waste generated during industrial production.Importantly,the removal mechanism is revealed as the ion exchange between Cs^(+)/Sr^(2+)and interlayer K^(+)in thioniobates and thiotantalate due to their appropriate interlayer distances,flexible and adjustable frameworks,and strong affinity of soft basic S^(2-)for Cs^(+)/Sr^(2+).Further,the structure-property relationship study indicates that there is an inverted U-curve rule for the relationship between interlayer distances of layered metal sulfides and ion exchange performance.The rule combined with the factors affecting interlayer distance can be used to direct the structural design and predict properties for the specific recognition and separation of radionuclides.This is a pioneering work on the development of thioniobates/thiotantalate ion exchangers with a deep insight into structure-property relationship for radionuclide remediation.
基金support of the Shanghai Young Outstanding Academic Leaders Plan(Overseas)the Shanghai Pujiang Program(23PJ1409300)+2 种基金the National key research and development program(2023YFB250400)the National Natural Science Foundation of China(52271222)the Science and Technology Commission of Shanghai Municipal(23DZ1202500 and 21010503100).
文摘Spinels have been widely concerned as a promising class of electrocatalysts due to their appealing catalytic properties and the tunability of their compositions and structures.Ligand field theory(LFT),which describes the origins and the consequences of metal-ligand interactions,offers crucial insights for the design of spinel-type electrocatalysts.In this review,we timely summarize the research progress of spinel electrocatalysts that leverage LFT for structure-property insights,providing a pioneering perspective in this field.This review explores how LFT plays a pivotal role in optimizing the electrocatalytic properties of spinels.It covers important aspects such as identifying the origin of the catalytic properties,tuning the number of active sites,manipulating the eg-filling and the spin state of metal cations,and modulating the 2p band of ligands.We anticipate that this review will provide valuable theoretical guidance and inspire creative spinel designs that excel in electrocatalytic applications.
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 German Science Foundation (DFG) in frame of the priority program SPP 1191 "Ionic Liquids" (VE 265/5-3)
文摘The enthalpies of vaporization for the series of pyridinium-based ionic liquids with bis（trifluoromethylsulfonyl）imide anion [CnPy][NTfz] （n = 2, 3, 4, 5, and 6） have been determined with the quartz crystal microbalance technique combined with the Langmuir evaporation. The linear dependence of vaporization enthalpies on the chain length has been revealed. New approach based on volumetric, surface tension, and speed of sound measurements has been developed for estimation of heat capacity differences between gas and liquid phase, which were required for adjustment of measured vaporization enthalpies to the ref- erence temperature 298 K.
基金The authors are grateful for the financial supports of the National Natural Science Foundation of China(Grant Nos.22078041 and 21808025)the Fundamental Research Funds for the Central Universities(Grant No.DUT20JC41).
文摘Chemical industry is always seeking opportunities to efficiently and economically convert raw materials to commodity chemicals and higher value-added chemicalbased products.The life cycles of chemical products involve the procedures of conceptual product designs,experimental investigations,sustainable manufactures through appropriate chemical processes and waste disposals.During these periods,one of the most important keys is the molecular property prediction models associating molecular structures with product properties.In this paper,a framework combining quantum mechanics and quantitative structure-property relationship is established for fast molecular property predictions,such as activity coefficient,and so forth.The workflow of framework consists of three steps.In the first step,a database is created for collections of basic molecular information;in the second step,quantum mechanics-based calculations are performed to predict quantum mechanics-based/derived molecular properties(pseudo experimental data),which are stored in a database and further provided for the developments of quantitative structure-property relationship methods for fast predictions of properties in the third step.The whole framework has been carried out within a molecular property prediction toolbox.Two case studies highlighting different aspects of the toolbox involving the predictions of heats of reaction and solid-liquid phase equilibriums are presented.
基金The research was supported by the Open Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering(No.2009490511)the special fund of State Key Joint Laboratory of Environment Simulation and Pollution Control(No.10Y08ESPCN)the National High Technology Research and Development Program of China(No.2009AA05Z306).
文摘Quantitative structure-property relationship(QSPR)models were developed for prediction of photolysis half-life(t_(1/2))of polychlorinated biphenyls(PCBs)in water under ultraviolet(UV)radiation.Quantum chemical descriptors computed by the PM3 Hamiltonian software were used as independent variables.The cross-validated Q^(2)_(cum)value for the optimal QSPR model is 0.966,indicating good prediction capability for lg t_(1/2)values of PCBs in water.The QSPR results show that the largest negative atomic charge on a carbon atom(Q-C)and the standard heat of formation(ΔH_(f))have a dominant effect on t_(1/2)values of PCBs.Higher Q_(C)^(-)values or lowerΔHf values of the PCBs leads to higher lg t_(1/2)values.In addition,the lg t_(1/2)values of PCBs increase with the increase in the energy of the highest occupied molecular orbital values.Increasing the largest positive atomic charge on a chlorine atom and the most positive net atomic charge on a hydrogen atom in PCBs leads to the decrease of lg t_(1/2)values.
文摘In order to predict the critical micelle concentration (cmc) of nonionic surfactants in aqueous solution,a quantitative structure-property relationship (QSPR) was found for 77 nonionic surfactants belonging to eight series. The best-regressed model contained four quantum-chemical descriptors,the heat of formation (ΔH),the molecular dipole moment (D),the energy of the lowest unoccupied molecular orbital (E_ LUMO ) and the energy of the highest occupied molecular orbital (E_ HOMO ) of the surfactant molecule; two constitutional descriptors,the molecular weight of surfactant (M) and the number of oxygen and nitrogen atoms (n_ ON ) of the hydrophilic fragment of surfactant molecule; and one topological descriptor,the Kier & Hall index of zero order (KH0) of the hydrophobic fragment of the surfactant. The established general QSPR between lg(cmc) and the descriptors produced a relevant coefficient of multiple determination:R 2=0.986. When cross terms were considered,the corresponding best model contained five descriptors E_ LUMO ,D,KH0,M and a cross term n_ ON ·KH0,which also produced the same coefficient as the seven-parameter model.
文摘Given the scarcity of Satellite Frequency and Orbit(SFO)resources,it holds paramount importance to establish a comprehensive knowledge graph of SFO field(SFO-KG)and employ knowledge reasoning technology to automatically mine available SFO resources.An essential aspect of constructing SFO-KG is the extraction of Chinese entity relations.Unfortunately,there is currently no publicly available Chinese SFO entity Relation Extraction(RE)dataset.Moreover,publicly available SFO text data contain numerous NA(representing for“No Answer”)relation category sentences that resemble other relation sentences and pose challenges in accurate classification,resulting in low recall and precision for the NA relation category in entity RE.Consequently,this issue adversely affects both the accuracy of constructing the knowledge graph and the efficiency of RE processes.To address these challenges,this paper proposes a method for extracting Chinese SFO text entity relations based on dynamic integrated learning.This method includes the construction of a manually annotated Chinese SFO entity RE dataset and a classifier combining features of SFO resource data.The proposed approach combines integrated learning and pre-training models,specifically utilizing Bidirectional Encoder Representation from Transformers(BERT).In addition,it incorporates one-class classification,attention mechanisms,and dynamic feedback mechanisms to improve the performance of the RE model.Experimental results show that the proposed method outperforms the traditional methods in terms of F1 value when extracting entity relations from both balanced and long-tailed datasets.
基金funded by the Research Project:THTETN.05/24-25,VietnamAcademy of Science and Technology.
文摘Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex,high-dimensional data that single-view methods cannot capture.Traditional fuzzy clustering techniques,such as Fuzzy C-Means(FCM),face significant challenges in handling uncertainty and the dependencies between different views.To overcome these limitations,we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data,aiming to enhance clustering accuracy and robustness,termed Multi-view Picture Fuzzy Clustering(MPFC).In particular,the picture fuzzy set theory extends the capability to represent uncertainty by modeling three membership levels:membership degrees,neutral degrees,and refusal degrees.This allows for a more flexible representation of uncertain and conflicting data than traditional fuzzy models.Meanwhile,dual-anchor graphs exploit the similarity relationships between data points and integrate information across views.This combination improves stability,scalability,and robustness when handling noisy and heterogeneous data.Experimental results on several benchmark datasets demonstrate significant improvements in clustering accuracy and efficiency,outperforming traditional methods.Specifically,the MPFC algorithm demonstrates outstanding clustering performance on a variety of datasets,attaining a Purity(PUR)score of 0.6440 and an Accuracy(ACC)score of 0.6213 for the 3 Sources dataset,underscoring its robustness and efficiency.The proposed approach significantly contributes to fields such as pattern recognition,multi-view relational data analysis,and large-scale clustering problems.Future work will focus on extending the method for semi-supervised multi-view clustering,aiming to enhance adaptability,scalability,and performance in real-world applications.
文摘During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.
文摘The banding and electronic structures of a series of long-chain macromolecules of cellu- lose,2-,3-,6-mononitrocellulose,2,3-,2,6-,3,6-dinitrocellulose and trinitrocellulose as well as their structural units(i.e.single-,double-or three-ring systems)have been calculated by both the EH and CNDO/2 methods.The increase of molecular total energies is consistent with the decrease of their stabilities at the three conformations of gg,gt and tg.The Mulliken bond order of O—NO_2 bond is the samllest in each molecule at any of the three conformations,which indicates that this bond is the weakest,and supports the view of initial homolytic cleavage of O—NO_2 bond on slow thermal decomposition.The band gap at the edge of the first Brillouin zone far surpasses 5 eV for cellu- lose,and is less than 3 eV for mono-,di-,and trinitrocellulose.The results show that cellulose is a typical insulator,as we know,and it can be predicted that nitrocellulose has electric conductivity similar to that of semiconductor.
基金supported by the National Natural Science Foundation of China(623B2098,62021001,62371434)the Postdoctoral Fellowship Program of CPSF(GZC20252293)+1 种基金the China Postdoctoral Science Foundation–Anhui Joint Support Program(2024T017AH)Anhui Postdoctoral Scientific Research Program Foundation(2025A1015).
文摘Collecting amounts of distorted/clean image pairs in the real world is non-trivial,which severely limits the practical application of these supervised learning-based methods to real-world image super-resolution(RealSR).Previous works usually address this problem by leveraging unsupervised learning-based technologies to alleviate the dependency on paired training samples.However,these methods typically suffer from unsatisfactory texture synthesis due to the lack of supervision of clean images.To overcome this problem,we are the first to take a close look at the under-explored direction for RealSR,i.e.,few-shot real-world image super-resolution,which aims to tackle the challenging RealSR problem with few-shot distorted/clean image pairs.Under this brand-new scenario,we propose distortion relation guided transfer learning(DRTL)for the few-shot RealSR by transferring the rich restoration knowledge from auxiliary distortions(i.e.,synthetic distortions)to the target RealSR under the guidance of the distortion relation.Concretely,DRTL builds a knowledge graph to capture the distortion relation between auxiliary distortions and target distortion(i.e.,real distortions in RealSR).Based on the distortion relation,DRTL adopts a gradient reweighting strategy to guide the knowledge transfer process between auxiliary distortions and target distortions.In this way,DRTL is able to quickly learn the most relevant knowledge from the synthetic distortions for the target distortion.We instantiate DRTL with two commonly-used transfer learning paradigms,including pretraining and meta-learning pipelines,to realize a distortion relation-aware few-shot RealSR.Extensive experiments on multiple benchmarks and thorough ablation studies demonstrate the effectiveness of our DRTL.
