Chemical process design as an important part of industrial production, its own safety problems affect the industrial process to a great extent. Therefore, in order to better improve the industrial production efficienc...Chemical process design as an important part of industrial production, its own safety problems affect the industrial process to a great extent. Therefore, in order to better improve the industrial production efficiency and increase economic benefits, we must find out the safety hazards in chemical process design in time, and effectively solve the safety problems in process design process. Based on this, this paper mainly discusses the safety problems in chemical process design and puts forward the control strategy.展开更多
Development of piezoelectric materials through chemical design meets the requirement of the nextgeneration electronic devices,yet the sensitive piezoelectricity to both chemical components and operational environment ...Development of piezoelectric materials through chemical design meets the requirement of the nextgeneration electronic devices,yet the sensitive piezoelectricity to both chemical components and operational environment call for the trial and error method during material preparation.In order to give an atomic-level understanding about functional unit and assist the chemical design,deep learning was applied to train a novelmodel based on themost popular BaTiO3 system,as a case study in this work.Through training the atomic force field of calcium and stannum doped solid-solution with Deep Potential method,3D structure of chemical distribution and corresponding polarization configuration can be constructed for different compositions under different temperatures,which exhibits a high degree of consistency with the local structure quantitatively analyzed from HAADF STEM and reverse Monte Carlo refinement of neutron total scattering data,especially for the critical composition with ultrahigh piezoelectricity of d33~860 pC/N.Systemic analysis reveals that variations in chemical bond length among various elements with oxygen elements are the primary factors influencing ferroelectric activity and leading to structural evolution.The results and methodology can facilitate the discovery of new ferroelectrics and the design of high-performance piezo/ferroelectrics with atomic-level insights.展开更多
Under the background of the continuous combination of science and technology and modern production, the national macro requirements for enterprise construction have been adjusted and changed more obviously than in the...Under the background of the continuous combination of science and technology and modern production, the national macro requirements for enterprise construction have been adjusted and changed more obviously than in the past. It is not simply based on quantitative production, but more emphasis on the upgrading and progress of technology. This change also provides new ideas and ways for enterprise innovation. As an important basis for leading the development trend of the times, chemical enterprises should also receive more attention and attention in this case, especially in terms of chemical design, we should especially emphasize the significance of the application of computer software technology.展开更多
In many circumstances, chemical process design can be formulated as a multi-objective optimization （MOO） problem. Examples include bi-objective optimization problems, where the economic objective is maximized and en...In many circumstances, chemical process design can be formulated as a multi-objective optimization （MOO） problem. Examples include bi-objective optimization problems, where the economic objective is maximized and environmental impact is minimized simultaneously. Moreover, the random behavior in the process,property, market fluctuation, errors in model prediction and so on would affect the performance of a process. Therefore, it is essential to develop a MOO methodology under uncertainty. In this article, the authors propose a generic and systematic optimization methodology for chemical process design under uncertainty. It aims at identifying the optimal design from a number of candidates. The utility of this methodology is demonstrated by a case study based on the design of a condensate treatment unit in an ammonia plant.展开更多
Rational architecture design has turned out to be an effective strategy in improving the electrochemical performance of electrode materials for batteries.However,an elaborate structure that could simultaneously endow ...Rational architecture design has turned out to be an effective strategy in improving the electrochemical performance of electrode materials for batteries.However,an elaborate structure that could simultaneously endow active materials with promoted reaction reversibility,accelerated kinetic and restricted volume change still remains a huge challenge.Herein,a novel chemical interaction motivated structure design strategy has been proposed,and a chemically bonded Co(CO_(3))_(0.5)OH·0.11 H_(2)O@MXene(CoCH@MXene)layered-composite was fabricated for the first time.In such a composite,the chemical interaction between Co^(2+)and MXene drives the growth of smaller-sized CoCH crystals and the subsequent formation of interwoven CoCH wires sandwiched in-between MXene nanosheets.This unique layered structure not only encourages charge transfer for faster reaction dynamics,but buffers the volume change of CoCH during lithiation-delithiation process,owing to the confined crystal growth between conductive MXene layers with the help of chemical bonding.Besides,the sandwiched interwoven CoCH wires also prevent the stacking of MXene layers,further conducive to the electrochemical performance of the composite.As a result,the as-prepared CoCH@MXene anode demonstrates a high reversible capacity(903.1 mAh g^(-1)at 100 mA g^(-1))and excellent cycling stability(maintains 733.6 mAh g^(-1)at1000 mA g^(-1)after 500 cycles)for lithium ion batteries.This work highlights a novel concept of layerby-layer chemical interaction motivated architecture design for futuristic high performance electrode materials in energy storage systems.展开更多
A process-oriented knowledge-sharing platform is studied to improve knowledge sharing and project management of chemical engineering design enterprises. First, problems and characteristics of knowledge sharing in mult...A process-oriented knowledge-sharing platform is studied to improve knowledge sharing and project management of chemical engineering design enterprises. First, problems and characteristics of knowledge sharing in multi-projects of chemical engineering design are analyzed. Then based on theories of project management, process management, and knowledge management, a process-oriented knowledge-sharing platform is proposed. The platform has three characteristics: knowledge is divided into professional knowledge and project management knowledge; knowledge sharing is integrated with the project process, which makes knowledge sharing a necessary part of the project process and ensures the quantity of knowledge shared; the platform provides quantitative measurements of incentive mechanisms for knowledge providers and users which ensures the quality of knowledge shared. This knowledge-sharing platform uses two knowledge management tools, a knowledge map and a knowledge base, to support the platform.展开更多
During the early days of New China, to support the domestic construction of those projects aided by the former Soviet Union, the design institution formed a chemical engineering production installation design team. Du...During the early days of New China, to support the domestic construction of those projects aided by the former Soviet Union, the design institution formed a chemical engineering production installation design team. During the 1950s, this team designed an ammonia synthesis unit with an annual capacity of 75000 tons, set up the Sichuan Chemical Plant and worked out a展开更多
Methods of constructing the optimum chemical balance weighing designs from symmetric balanced incomplete block designs are proposed with illustration. As a by-product pairwise efficiency and variance balanced designs ...Methods of constructing the optimum chemical balance weighing designs from symmetric balanced incomplete block designs are proposed with illustration. As a by-product pairwise efficiency and variance balanced designs are also obtained.展开更多
The development of China's chemical industry in recent years tends to a good level, and the public is more and more dependent on chemical products. But with the increase of production intensity, the probability of...The development of China's chemical industry in recent years tends to a good level, and the public is more and more dependent on chemical products. But with the increase of production intensity, the probability of accidents is also rising. Once a chemical accident occurs, it will not only directly affect the production of the whole chemical products, but also seriously threaten the lives and health of workers. Therefore, it is necessary to introduce comprehensive measures in advance to prevent and deal with various safety problems, and implement targeted safety design in chemical production, so as to effectively deal with potential safety hazards and ensure the smooth progress of the whole production activities. Next, the article discusses the importance of chemical safety design in the prevention of chemical accidents.展开更多
The zebra mussel is an important aquatic pest that causes great damage to freshwater-dependent industries, due to biofouling. The main goal of the project discussed here is to develop improved solutions to control thi...The zebra mussel is an important aquatic pest that causes great damage to freshwater-dependent industries, due to biofouling. The main goal of the project discussed here is to develop improved solutions to control this species. Three approaches have been explored in an attempt to design innovative application strategies for existing biocides： （i） encapsulation of toxins; （ii） combination of toxins; （iii） investigation of the seasonal variation of the species＇ tolerance to toxins. In this paper, the principles behind these approaches and the major results on each topic are presented. The benefits of adopting a chemical product engineering approach in conducting this project are also discussed.展开更多
Small-molecule drugs are essential for maintaining human health. The objective of this study is to identify a molecule that can inhibit the Factor Xa protein and be easily procured. An optimization-based de novo drug ...Small-molecule drugs are essential for maintaining human health. The objective of this study is to identify a molecule that can inhibit the Factor Xa protein and be easily procured. An optimization-based de novo drug design framework, Drug CAMD, that integrates a deep learning model with a mixed-integer nonlinear programming model is used for designing drug candidates. Within this framework, a virtual chemical library is specifically tailored to inhibit Factor Xa. To further filter and narrow down the lead compounds from the designed compounds, comprehensive approaches involving molecular docking,binding pose metadynamics(BPMD), binding free energy calculations, and enzyme activity inhibition analysis are utilized. To maximize efficiency in terms of time and resources, molecules for in vitro activity testing are initially selected from commercially available portions of customized virtual chemical libraries. In vitro studies assessing inhibitor activities have confirmed that the compound EN300-331859shows potential Factor Xa inhibition, with an IC_(50)value of 34.57 μmol·L^(-1). Through in silico molecular docking and BPMD, the most plausible binding pose for the EN300-331859-Factor Xa complex are identified. The estimated binding free energy values correlate well with the results obtained from biological assays. Consequently, EN300-331859 is identified as a novel and effective sub-micromolar inhibitor of Factor Xa.展开更多
Designing optimal formulations is a major challenge in developing electrolytes for the next generation of rechargeable batteries due to the vast combinatorial design space and complex interplay between multiple consti...Designing optimal formulations is a major challenge in developing electrolytes for the next generation of rechargeable batteries due to the vast combinatorial design space and complex interplay between multiple constituents.Machine learning(ML)offers a powerful tool to uncover underlying chemical design rules and accelerate the process of formulation discovery.In this work,we present an approach to design new formulations that can achieve target performance,using a generalizable chemical foundation model.The chemical foundation model is fine-tuned on an experimental dataset of 13,666 ionic conductivity values curated from the lithium-ion battery literature.The fine-tuned model is used to discover 7 novel high conductivity electrolyte formulations through generative screening,improving the conductivity of LiFSI-and LiDFOB-based electrolytes by 82%and 172%,respectively.These findings highlight a generalizable workflow that is highly adaptable to the discovery of chemical mixtures with tailored properties to address challenges in energy storage and beyond.展开更多
Polymer circularity has received increasing attention due to ecological benefits,by which plastic waste should be reused or converted into high-value products in an economic framework balanced with virgin polymer prod...Polymer circularity has received increasing attention due to ecological benefits,by which plastic waste should be reused or converted into high-value products in an economic framework balanced with virgin polymer production.From a chemical engineering point of view,the understanding of reaction kinetics and chemical modifications plays a crucial role in improving the process towards polymer circularity.This reaction kinetics is connected to molecular variations for which(micro)kinetic models are essential.In this perspective,the main kinetic simulation methods are summarized,focusing on their respective characteristics and challenges,besides differentiating between deterministic and stochastic methods.The application of kinetic simulations in polymer circularity processes is clarified in the form of three case studies,including(i)mechanical recycling with deliberate chemical modification by reactive extrusion,(ii)chemical recycling aiming at monomer recovery,and(iii)recycling-by-design aiming at vitrimer molecular design.Attention is also paid to the relevance of benchmarking the methods applied.展开更多
A new paradigm driven by artificial intelligence(AI)and machine learning(ML)is significantly accelerating the iterative pace of polymer materials research.Traditional experimental approaches to polymer discovery have ...A new paradigm driven by artificial intelligence(AI)and machine learning(ML)is significantly accelerating the iterative pace of polymer materials research.Traditional experimental approaches to polymer discovery have long relied on trial and error,requiring extensive time and resources while offering limited access to the vast chemical design space.In contrast,ML-assisted strategies provide a transformative framework for efficiently navigating this complex landscape.This paper focuses specifically on polymer design at the molecular level.By integrating data-driven methodologies,researchers can extract structure−property relationships,predict polymer properties,and optimize molecular architectures with unprecedented speed.ML-driven polymer design follows a structured approach:(1)database construction,(2)structural representation and feature engineering,(3)development of ML-based property prediction models,(4)virtual screening of potential candidates,and(5)validation through experiments and/or numerical simulations.This workflow faces two central challenges.First is the limited availability of high-quality polymer datasets,particularly for advanced materials with specialized properties.Second is the generation of virtual polymer structures.Unlike small-molecule drug discovery,where vast libraries of candidate compounds exist,polymer chemistry lacks an equivalent repository of hypothetical structures.Recent efforts have leveraged rule-based polymerization reactions and generative models to create large-scale databases of hypothetical polymers,significantly expanding the design space.Additionally,the diversity of polymer structures,the broad range of their properties,and the limited availability of training samples add complexity to developing accurate predictive models.Addressing these challenges requires innovative ML techniques,such as transfer learning,multitask learning,and generative models,to extract meaningful insights from sparse data and improve prediction reliability.This data-driven approach has enabled the discovery of novel,high-performance polymers for applications in aerospace,electronics,energy storage,and biomedical engineering.Despite these advancements,several hurdles remain.The interpretability of ML models,particularly deep neural networks,is a pressing concern.While black-box models can achieve remarkable predictive accuracy,understanding their decision-making processes remains challenging.Explainable AI methods are increasingly being explored to provide insights into feature importance,model uncertainty,and the underlying chemistry driving polymer properties.Additionally,the synthesizability and processability of ML-generated candidates must be carefully considered to ensure practical experimental validation and real-world application.In this paper,we review recent progress in ML-assisted molecular design of polymer materials,focusing on database development,feature representation,predictive modeling,and virtual polymer generation.We highlight emerging methodologies,including transformer-based language models,physics-informed neural networks,and closed-loop discovery frameworks,which collectively enhance the efficiency and accuracy of polymer informatics.Finally,we discuss the future outlook of ML-driven polymer research,emphasizing the need for collaborative efforts between data scientists,chemists,and engineers to refine predictive models,integrate experimental validation,and accelerate the development of next-generation polymeric materials.By leveraging the synergy between computational modeling and experimental insights,ML-assisted design is poised to revolutionize polymer discovery,enabling the rapid development of sustainable,high-performance materials tailored for diverse applications.展开更多
Particle coating is an important method that can be used to expand particle-technology applications. Coated-particle design and preparation for nuclear fuel-element trajectory tracing were focused on in this paper. Pa...Particle coating is an important method that can be used to expand particle-technology applications. Coated-particle design and preparation for nuclear fuel-element trajectory tracing were focused on in this paper. Particles that contain elemental cobalt were selected because of the characteristic gamma ray spectra of 60Co. A novel particle-structure design was proposed by coating particles that contain elemental cobalt with a high-density silicon-carbide （SiC） layer. During the coating process with the high-density SiC layer, cobalt metal was formed and diffused towards the coating, so an inner SiC–CoxSi layer was designed and obtained by fluidized-bed chemical vapor deposition coupled with in-situ chemical reaction. The coating layers were studied by X-ray diffractometry, scanning electron microscopy, and energy dispersive X-ray spectroscopy techniques. The chemical composition was also determined by inductively coupled plasma optical emission spectrometry. The novel particle design can reduce the formation of metallic cobalt and prevent cobalt diffusion in the coating process, which can maintain safety in a nuclear reactor for an extended period. The experimental results also validated that coated particles maintain their structural integrity at extremely high temperatures （～1950 °C）, which meets the requirements of next-generation nuclear reactors.展开更多
The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers b...The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.展开更多
Janus hydrogels have recently emerged as promising bioadhesives for efficient wet-tissue adhesion and anti-postoperative adhesion.However,existing Janus hydrogel adhesives normally need varied chemical designs of diff...Janus hydrogels have recently emerged as promising bioadhesives for efficient wet-tissue adhesion and anti-postoperative adhesion.However,existing Janus hydrogel adhesives normally need varied chemical designs of different layers to achieve asymmetric adhesive/anti-adhesive properties on either side.Here,we present a new strategy to construct an adhesive/anti-adhesive Janus hydrogel tissue patch accomplished by switching the charge-balance of the hydrogel layers with similar compositions(anionic carboxyl polymer and cationicε-polylysine,EPL).The bottom layer(AL)is formed under acidic condition(pH 2.85),featuring abundant-COOH and-NH3+residues,which provide rapid&robust adhesion to diverse wet tissues(up to 100.4 kPa)with high bursting pressure(362.5 mmHg),while the top layer(MLT)is formed under neutral condition,achieving a balanced charge between-COOH/-NH2 and-COO/NH3+groups,which mimic the overall electroneutral structure of zwitterionic materials for efficient anti-postoperative tissue adhesion(up to 6 weeks).Further in vivo studies validated that the integrated AL/MLT hydrogel patch is biodegradable(within 10 weeks),exhibits broad-spectrum antibacterial activity(up to 99.8%),and outperforms the commercial fibrin gel in sutureless wound sealing,rat gastric tissue repair,and anti-postoperative adhesion.This strategy may open a new avenue to develop adhesive/anti-adhesive Janus bioadhesives for efficient non-invasive internal tissue sealing and promoted wound healing.展开更多
Nonlinear optical(NLO)crystals capable of controlling and manipulating light to generate coherent radiation at a variety of difficult-to-access wavelengths are essentially crucial for many high-tech applications,yet t...Nonlinear optical(NLO)crystals capable of controlling and manipulating light to generate coherent radiation at a variety of difficult-to-access wavelengths are essentially crucial for many high-tech applications,yet the rational design of NLO crystals with high-performance remains a great challenge.Herein,inspired by two facts,namely,hetero-anionic structures can effectively integrate the diverse property superiorities of single-anions,and T2-type supertetrahedra can exhibit enhanced polarizability compared to simple tetrahedra.We assembled multiple different[TS_(4)](T=Zn,Sn)tetrahedra to form the hybrid T2-type supertetrahedra and successfully synthesized new hybrid T2-type supertetrahedral IR NLO crystals,Ae_(5)Zn_(3)Ga_(2)Sn_(2)S_(15)(Ae=Sr and Ba),both of which exhibit intriguing NLO properties,including strong second harmonic generation responses(2.8×AgGaS_(2)-3.0×AgGaS_(2)),wide band-gaps(2.81-2.89 eV),high laser-induced damage thresholds(~15×AgGaS_(2)),a broad IR transmission range(up to 14μm),and suitable birefringence(0.048-0.051@1064 nm).More significantly,both exhibit congruent melting behavior,and a high-quality single crystal of Ba_(5)Zn_(3)Ga_(2)Sn_(2)S_(15)with centimeter-level has been successfully grown using the Bridgman method.These findings strongly suggest that Ba_(5)Zn_(3)Ga_(2)Sn_(2)S_(15)holds great promise as an IR NLO crystal,and the strategy for constructing hybrid T2-type supertetrahedra is effective for designing novel high-performance NLO crystals.展开更多
Antimicrobial resistance(AMR)poses a huge threat to human health.It is urgent to explore efficient ways to suppress the spread of AMR.Antibacterial nanozymes have become one of the powerful weapons to combat AMR due t...Antimicrobial resistance(AMR)poses a huge threat to human health.It is urgent to explore efficient ways to suppress the spread of AMR.Antibacterial nanozymes have become one of the powerful weapons to combat AMR due to their enzyme-like catalytic activity with a broad-spectrum antibacterial performance.However,the inherent low catalytic activity of nanozymes limits their expansion into antibacterial applications.In this regard,a variety of advanced chemical design strategies have been developed to improve the antimicrobial activity of nanozymes.In this review,we have summarized the recent progress of advanced strategies to engineer efficient nanozymes for fighting against AMR,which can be mainly classified as catalytic activity improvement,external stimuli,bacterial affinity enhancement,and multifunctional platform construction according to the basic principles of engineering efficient nanocatalysts and the mechanism of nanozyme catalysis.Moreover,the deep insights into the effects of these enhancing strategies on the nanozyme structures and properties are highlighted.Finally,current challenges and future perspectives of antibacterial nanozymes are discussed for their future clinical potential.展开更多
What is the most favorite and original chemistry developed in your research group?We originally proposed the design principle for molecular ferroelectrics:ferroelectrochemistry,including quasi-spherical theory,the int...What is the most favorite and original chemistry developed in your research group?We originally proposed the design principle for molecular ferroelectrics:ferroelectrochemistry,including quasi-spherical theory,the introduction of homochirality,and H/F substitution.Ferroelectrochemistry changed the blind search for molecular ferroelectrics into targeted chemical design,which will develop into a new discipline.展开更多
文摘Chemical process design as an important part of industrial production, its own safety problems affect the industrial process to a great extent. Therefore, in order to better improve the industrial production efficiency and increase economic benefits, we must find out the safety hazards in chemical process design in time, and effectively solve the safety problems in process design process. Based on this, this paper mainly discusses the safety problems in chemical process design and puts forward the control strategy.
基金supported by the National Key R&D Program of China(Grant No.2023YFB3508200)the Outstanding Young Scientist Program of Beijing Colleges and Universities(JWZQ20240101015)the National Natural Science Foundation of China(Grant Nos.92370104,22235002 and 52172181).We acknowledge the computational resource from Beijing PARATERA Tech Corp,LTD.
文摘Development of piezoelectric materials through chemical design meets the requirement of the nextgeneration electronic devices,yet the sensitive piezoelectricity to both chemical components and operational environment call for the trial and error method during material preparation.In order to give an atomic-level understanding about functional unit and assist the chemical design,deep learning was applied to train a novelmodel based on themost popular BaTiO3 system,as a case study in this work.Through training the atomic force field of calcium and stannum doped solid-solution with Deep Potential method,3D structure of chemical distribution and corresponding polarization configuration can be constructed for different compositions under different temperatures,which exhibits a high degree of consistency with the local structure quantitatively analyzed from HAADF STEM and reverse Monte Carlo refinement of neutron total scattering data,especially for the critical composition with ultrahigh piezoelectricity of d33~860 pC/N.Systemic analysis reveals that variations in chemical bond length among various elements with oxygen elements are the primary factors influencing ferroelectric activity and leading to structural evolution.The results and methodology can facilitate the discovery of new ferroelectrics and the design of high-performance piezo/ferroelectrics with atomic-level insights.
文摘Under the background of the continuous combination of science and technology and modern production, the national macro requirements for enterprise construction have been adjusted and changed more obviously than in the past. It is not simply based on quantitative production, but more emphasis on the upgrading and progress of technology. This change also provides new ideas and ways for enterprise innovation. As an important basis for leading the development trend of the times, chemical enterprises should also receive more attention and attention in this case, especially in terms of chemical design, we should especially emphasize the significance of the application of computer software technology.
基金Supported by Dalian University of Technology, the US National Science Foundation （No.CTS-0407494） and the Texas Advanced Technology program （No.003581-0044-2003）
文摘In many circumstances, chemical process design can be formulated as a multi-objective optimization （MOO） problem. Examples include bi-objective optimization problems, where the economic objective is maximized and environmental impact is minimized simultaneously. Moreover, the random behavior in the process,property, market fluctuation, errors in model prediction and so on would affect the performance of a process. Therefore, it is essential to develop a MOO methodology under uncertainty. In this article, the authors propose a generic and systematic optimization methodology for chemical process design under uncertainty. It aims at identifying the optimal design from a number of candidates. The utility of this methodology is demonstrated by a case study based on the design of a condensate treatment unit in an ammonia plant.
基金financially supported by the National Natural Science Foundation of China(No.51933007,No.51673123 and No.22005346)the National Key R&D Program of China(No.2017YFE0111500)+1 种基金the State Key Laboratory of Polymer Materials Engineering(Grant No.:sklpme2020-1-02)Financial support provided by the Fundamental Research Funds for the Central Universities(No.YJ202118)。
文摘Rational architecture design has turned out to be an effective strategy in improving the electrochemical performance of electrode materials for batteries.However,an elaborate structure that could simultaneously endow active materials with promoted reaction reversibility,accelerated kinetic and restricted volume change still remains a huge challenge.Herein,a novel chemical interaction motivated structure design strategy has been proposed,and a chemically bonded Co(CO_(3))_(0.5)OH·0.11 H_(2)O@MXene(CoCH@MXene)layered-composite was fabricated for the first time.In such a composite,the chemical interaction between Co^(2+)and MXene drives the growth of smaller-sized CoCH crystals and the subsequent formation of interwoven CoCH wires sandwiched in-between MXene nanosheets.This unique layered structure not only encourages charge transfer for faster reaction dynamics,but buffers the volume change of CoCH during lithiation-delithiation process,owing to the confined crystal growth between conductive MXene layers with the help of chemical bonding.Besides,the sandwiched interwoven CoCH wires also prevent the stacking of MXene layers,further conducive to the electrochemical performance of the composite.As a result,the as-prepared CoCH@MXene anode demonstrates a high reversible capacity(903.1 mAh g^(-1)at 100 mA g^(-1))and excellent cycling stability(maintains 733.6 mAh g^(-1)at1000 mA g^(-1)after 500 cycles)for lithium ion batteries.This work highlights a novel concept of layerby-layer chemical interaction motivated architecture design for futuristic high performance electrode materials in energy storage systems.
基金The National Natural Science Foundation of China (No.70501030,70621001)Natural Science Foundation of Beijing (No.9073020)
文摘A process-oriented knowledge-sharing platform is studied to improve knowledge sharing and project management of chemical engineering design enterprises. First, problems and characteristics of knowledge sharing in multi-projects of chemical engineering design are analyzed. Then based on theories of project management, process management, and knowledge management, a process-oriented knowledge-sharing platform is proposed. The platform has three characteristics: knowledge is divided into professional knowledge and project management knowledge; knowledge sharing is integrated with the project process, which makes knowledge sharing a necessary part of the project process and ensures the quantity of knowledge shared; the platform provides quantitative measurements of incentive mechanisms for knowledge providers and users which ensures the quality of knowledge shared. This knowledge-sharing platform uses two knowledge management tools, a knowledge map and a knowledge base, to support the platform.
文摘During the early days of New China, to support the domestic construction of those projects aided by the former Soviet Union, the design institution formed a chemical engineering production installation design team. During the 1950s, this team designed an ammonia synthesis unit with an annual capacity of 75000 tons, set up the Sichuan Chemical Plant and worked out a
文摘Methods of constructing the optimum chemical balance weighing designs from symmetric balanced incomplete block designs are proposed with illustration. As a by-product pairwise efficiency and variance balanced designs are also obtained.
文摘The development of China's chemical industry in recent years tends to a good level, and the public is more and more dependent on chemical products. But with the increase of production intensity, the probability of accidents is also rising. Once a chemical accident occurs, it will not only directly affect the production of the whole chemical products, but also seriously threaten the lives and health of workers. Therefore, it is necessary to introduce comprehensive measures in advance to prevent and deal with various safety problems, and implement targeted safety design in chemical production, so as to effectively deal with potential safety hazards and ensure the smooth progress of the whole production activities. Next, the article discusses the importance of chemical safety design in the prevention of chemical accidents.
基金the Portuguese Foundation for Science and Technology (scholarship SFRH/BD/18731/2004 and Research Project Grant POCI/EQU/59305/2004).
文摘The zebra mussel is an important aquatic pest that causes great damage to freshwater-dependent industries, due to biofouling. The main goal of the project discussed here is to develop improved solutions to control this species. Three approaches have been explored in an attempt to design innovative application strategies for existing biocides： （i） encapsulation of toxins; （ii） combination of toxins; （iii） investigation of the seasonal variation of the species＇ tolerance to toxins. In this paper, the principles behind these approaches and the major results on each topic are presented. The benefits of adopting a chemical product engineering approach in conducting this project are also discussed.
基金financial supports of the National Natural Science Foundation of China (22078041, 22278053,22208042)Dalian High-level Talents Innovation Support Program (2023RQ059)“the Fundamental Research Funds for the Central Universities (DUT20JC41, DUT22YG218)”。
文摘Small-molecule drugs are essential for maintaining human health. The objective of this study is to identify a molecule that can inhibit the Factor Xa protein and be easily procured. An optimization-based de novo drug design framework, Drug CAMD, that integrates a deep learning model with a mixed-integer nonlinear programming model is used for designing drug candidates. Within this framework, a virtual chemical library is specifically tailored to inhibit Factor Xa. To further filter and narrow down the lead compounds from the designed compounds, comprehensive approaches involving molecular docking,binding pose metadynamics(BPMD), binding free energy calculations, and enzyme activity inhibition analysis are utilized. To maximize efficiency in terms of time and resources, molecules for in vitro activity testing are initially selected from commercially available portions of customized virtual chemical libraries. In vitro studies assessing inhibitor activities have confirmed that the compound EN300-331859shows potential Factor Xa inhibition, with an IC_(50)value of 34.57 μmol·L^(-1). Through in silico molecular docking and BPMD, the most plausible binding pose for the EN300-331859-Factor Xa complex are identified. The estimated binding free energy values correlate well with the results obtained from biological assays. Consequently, EN300-331859 is identified as a novel and effective sub-micromolar inhibitor of Factor Xa.
文摘Designing optimal formulations is a major challenge in developing electrolytes for the next generation of rechargeable batteries due to the vast combinatorial design space and complex interplay between multiple constituents.Machine learning(ML)offers a powerful tool to uncover underlying chemical design rules and accelerate the process of formulation discovery.In this work,we present an approach to design new formulations that can achieve target performance,using a generalizable chemical foundation model.The chemical foundation model is fine-tuned on an experimental dataset of 13,666 ionic conductivity values curated from the lithium-ion battery literature.The fine-tuned model is used to discover 7 novel high conductivity electrolyte formulations through generative screening,improving the conductivity of LiFSI-and LiDFOB-based electrolytes by 82%and 172%,respectively.These findings highlight a generalizable workflow that is highly adaptable to the discovery of chemical mixtures with tailored properties to address challenges in energy storage and beyond.
基金support from the National Natural Science Foundation of China(21625603,22078195,22222807,22238005)support from FWO Vlaanderen(G.0H52.16 N and G027122 N).
文摘Polymer circularity has received increasing attention due to ecological benefits,by which plastic waste should be reused or converted into high-value products in an economic framework balanced with virgin polymer production.From a chemical engineering point of view,the understanding of reaction kinetics and chemical modifications plays a crucial role in improving the process towards polymer circularity.This reaction kinetics is connected to molecular variations for which(micro)kinetic models are essential.In this perspective,the main kinetic simulation methods are summarized,focusing on their respective characteristics and challenges,besides differentiating between deterministic and stochastic methods.The application of kinetic simulations in polymer circularity processes is clarified in the form of three case studies,including(i)mechanical recycling with deliberate chemical modification by reactive extrusion,(ii)chemical recycling aiming at monomer recovery,and(iii)recycling-by-design aiming at vitrimer molecular design.Attention is also paid to the relevance of benchmarking the methods applied.
基金support from the Air Force Office of Scientific Research through the Air Force’s Young Investigator Research Program(FA9550-20-1-0183,Program Manager:Dr.Ming-Jen Pan and Capt.Derek Barbee)Air Force Research Laboratory/UES Inc.(FA8650-20-S-5008,PICASSO program)the National Science Foundation(CMMI-2332276,CMMI-2316200,and CAREER-2323108).
文摘A new paradigm driven by artificial intelligence(AI)and machine learning(ML)is significantly accelerating the iterative pace of polymer materials research.Traditional experimental approaches to polymer discovery have long relied on trial and error,requiring extensive time and resources while offering limited access to the vast chemical design space.In contrast,ML-assisted strategies provide a transformative framework for efficiently navigating this complex landscape.This paper focuses specifically on polymer design at the molecular level.By integrating data-driven methodologies,researchers can extract structure−property relationships,predict polymer properties,and optimize molecular architectures with unprecedented speed.ML-driven polymer design follows a structured approach:(1)database construction,(2)structural representation and feature engineering,(3)development of ML-based property prediction models,(4)virtual screening of potential candidates,and(5)validation through experiments and/or numerical simulations.This workflow faces two central challenges.First is the limited availability of high-quality polymer datasets,particularly for advanced materials with specialized properties.Second is the generation of virtual polymer structures.Unlike small-molecule drug discovery,where vast libraries of candidate compounds exist,polymer chemistry lacks an equivalent repository of hypothetical structures.Recent efforts have leveraged rule-based polymerization reactions and generative models to create large-scale databases of hypothetical polymers,significantly expanding the design space.Additionally,the diversity of polymer structures,the broad range of their properties,and the limited availability of training samples add complexity to developing accurate predictive models.Addressing these challenges requires innovative ML techniques,such as transfer learning,multitask learning,and generative models,to extract meaningful insights from sparse data and improve prediction reliability.This data-driven approach has enabled the discovery of novel,high-performance polymers for applications in aerospace,electronics,energy storage,and biomedical engineering.Despite these advancements,several hurdles remain.The interpretability of ML models,particularly deep neural networks,is a pressing concern.While black-box models can achieve remarkable predictive accuracy,understanding their decision-making processes remains challenging.Explainable AI methods are increasingly being explored to provide insights into feature importance,model uncertainty,and the underlying chemistry driving polymer properties.Additionally,the synthesizability and processability of ML-generated candidates must be carefully considered to ensure practical experimental validation and real-world application.In this paper,we review recent progress in ML-assisted molecular design of polymer materials,focusing on database development,feature representation,predictive modeling,and virtual polymer generation.We highlight emerging methodologies,including transformer-based language models,physics-informed neural networks,and closed-loop discovery frameworks,which collectively enhance the efficiency and accuracy of polymer informatics.Finally,we discuss the future outlook of ML-driven polymer research,emphasizing the need for collaborative efforts between data scientists,chemists,and engineers to refine predictive models,integrate experimental validation,and accelerate the development of next-generation polymeric materials.By leveraging the synergy between computational modeling and experimental insights,ML-assisted design is poised to revolutionize polymer discovery,enabling the rapid development of sustainable,high-performance materials tailored for diverse applications.
基金This work was supported by the Natural Science Foundation of China （Grant Nos. S1302148, 21306097）, the Research Fund for Independent Research Projects of Tsinghua University （Grant Nos. 20131089217, 20121088038）, the Specialized Research Fund for the Doctoral Program of Higher Education （Grant No. 20110002120023）, and the Higher Education Young Elite Teacher Project of Beijing （Grant No. YETP0155）.
文摘Particle coating is an important method that can be used to expand particle-technology applications. Coated-particle design and preparation for nuclear fuel-element trajectory tracing were focused on in this paper. Particles that contain elemental cobalt were selected because of the characteristic gamma ray spectra of 60Co. A novel particle-structure design was proposed by coating particles that contain elemental cobalt with a high-density silicon-carbide （SiC） layer. During the coating process with the high-density SiC layer, cobalt metal was formed and diffused towards the coating, so an inner SiC–CoxSi layer was designed and obtained by fluidized-bed chemical vapor deposition coupled with in-situ chemical reaction. The coating layers were studied by X-ray diffractometry, scanning electron microscopy, and energy dispersive X-ray spectroscopy techniques. The chemical composition was also determined by inductively coupled plasma optical emission spectrometry. The novel particle design can reduce the formation of metallic cobalt and prevent cobalt diffusion in the coating process, which can maintain safety in a nuclear reactor for an extended period. The experimental results also validated that coated particles maintain their structural integrity at extremely high temperatures （～1950 °C）, which meets the requirements of next-generation nuclear reactors.
基金Projects(71301115,71271150,71101102)supported by the National Natural Science Foundation of ChinaProject(20130032120009)supported by Specialized Research Fund for the Doctoral Program of Higher Education of China
文摘The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.
基金supports from the Six Talent Peaks Project in Jiangsu Province(SWYY-060)Changzhou City Major Technology De-mand"Unveiling and Leading"Science and Technology Research Project(S11090B42215)the Postdoctoral Fellowship Program of CPSF under Grant Number GZC20231142.
文摘Janus hydrogels have recently emerged as promising bioadhesives for efficient wet-tissue adhesion and anti-postoperative adhesion.However,existing Janus hydrogel adhesives normally need varied chemical designs of different layers to achieve asymmetric adhesive/anti-adhesive properties on either side.Here,we present a new strategy to construct an adhesive/anti-adhesive Janus hydrogel tissue patch accomplished by switching the charge-balance of the hydrogel layers with similar compositions(anionic carboxyl polymer and cationicε-polylysine,EPL).The bottom layer(AL)is formed under acidic condition(pH 2.85),featuring abundant-COOH and-NH3+residues,which provide rapid&robust adhesion to diverse wet tissues(up to 100.4 kPa)with high bursting pressure(362.5 mmHg),while the top layer(MLT)is formed under neutral condition,achieving a balanced charge between-COOH/-NH2 and-COO/NH3+groups,which mimic the overall electroneutral structure of zwitterionic materials for efficient anti-postoperative tissue adhesion(up to 6 weeks).Further in vivo studies validated that the integrated AL/MLT hydrogel patch is biodegradable(within 10 weeks),exhibits broad-spectrum antibacterial activity(up to 99.8%),and outperforms the commercial fibrin gel in sutureless wound sealing,rat gastric tissue repair,and anti-postoperative adhesion.This strategy may open a new avenue to develop adhesive/anti-adhesive Janus bioadhesives for efficient non-invasive internal tissue sealing and promoted wound healing.
基金supported by the National Natural Science Foundation of China(52322202,22071179,52172006,51972230,51890864,51890865)the Natural Science Foundation of Tianjin Municipality(21JCJQJC00090,20JCJQJC00060).
文摘Nonlinear optical(NLO)crystals capable of controlling and manipulating light to generate coherent radiation at a variety of difficult-to-access wavelengths are essentially crucial for many high-tech applications,yet the rational design of NLO crystals with high-performance remains a great challenge.Herein,inspired by two facts,namely,hetero-anionic structures can effectively integrate the diverse property superiorities of single-anions,and T2-type supertetrahedra can exhibit enhanced polarizability compared to simple tetrahedra.We assembled multiple different[TS_(4)](T=Zn,Sn)tetrahedra to form the hybrid T2-type supertetrahedra and successfully synthesized new hybrid T2-type supertetrahedral IR NLO crystals,Ae_(5)Zn_(3)Ga_(2)Sn_(2)S_(15)(Ae=Sr and Ba),both of which exhibit intriguing NLO properties,including strong second harmonic generation responses(2.8×AgGaS_(2)-3.0×AgGaS_(2)),wide band-gaps(2.81-2.89 eV),high laser-induced damage thresholds(~15×AgGaS_(2)),a broad IR transmission range(up to 14μm),and suitable birefringence(0.048-0.051@1064 nm).More significantly,both exhibit congruent melting behavior,and a high-quality single crystal of Ba_(5)Zn_(3)Ga_(2)Sn_(2)S_(15)with centimeter-level has been successfully grown using the Bridgman method.These findings strongly suggest that Ba_(5)Zn_(3)Ga_(2)Sn_(2)S_(15)holds great promise as an IR NLO crystal,and the strategy for constructing hybrid T2-type supertetrahedra is effective for designing novel high-performance NLO crystals.
基金This work was financially supported by the National Natural Science Foundation of China(No.82160421)Natural Science Foundation of Jiangsu Province(BK20211322)+5 种基金China Postdoctoral Science Foundation(No.2021M691331)Postdoctoral Fund of Jiangsu Province(No.2021K371C)This work was also supported by Research Fellow(Grant No.328933)Solution for Health Profile(336355)InFLAMES Flagship(337531)grants from Academy of FinlandFinland China Food and Health International Pilot Project funded by the Finnish Ministry of Education and Culture.
文摘Antimicrobial resistance(AMR)poses a huge threat to human health.It is urgent to explore efficient ways to suppress the spread of AMR.Antibacterial nanozymes have become one of the powerful weapons to combat AMR due to their enzyme-like catalytic activity with a broad-spectrum antibacterial performance.However,the inherent low catalytic activity of nanozymes limits their expansion into antibacterial applications.In this regard,a variety of advanced chemical design strategies have been developed to improve the antimicrobial activity of nanozymes.In this review,we have summarized the recent progress of advanced strategies to engineer efficient nanozymes for fighting against AMR,which can be mainly classified as catalytic activity improvement,external stimuli,bacterial affinity enhancement,and multifunctional platform construction according to the basic principles of engineering efficient nanocatalysts and the mechanism of nanozyme catalysis.Moreover,the deep insights into the effects of these enhancing strategies on the nanozyme structures and properties are highlighted.Finally,current challenges and future perspectives of antibacterial nanozymes are discussed for their future clinical potential.
基金supported by the National Natural Science Foundation of China(21991142,21831004,91856114,and 22175082)。
文摘What is the most favorite and original chemistry developed in your research group?We originally proposed the design principle for molecular ferroelectrics:ferroelectrochemistry,including quasi-spherical theory,the introduction of homochirality,and H/F substitution.Ferroelectrochemistry changed the blind search for molecular ferroelectrics into targeted chemical design,which will develop into a new discipline.
