In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honey...In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.展开更多
Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop spec...Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop species,is a promising source forβ-ionone production.This study aimed to modify CCD4 activity to increaseβ-ionone yield in tobacco.We identified two isoforms of CCD4 in N.tabacum,NtCCD4a and NtCCD4b,with NtCCD4a exhibiting significantly higher expression levels than NtCCD4b.Using solid-phase microextraction gas chromatography-mass spectrometry(SPME-GC–MS),we demonstrated that NtCCD4a effectively catalyzes the cleavage ofβ-carotene to produceβ-ionone.To improve its enzymatic activity,we applied structure-based rational design to reconstruct the active pocket of NtCCD4a,followed by high-throughput screening of mutant variants.Three single base mutants,F181G,F184L,and F337M,in NtCCD4a showed enhancedβ-ionone production compared to the wild-type,with F337M yielding the highest amount.No synergistic effects were observed among the three mutants.Transgenic tobacco plants expressing the F181G,F184L,and F337M mutations had acceleratedβ-carotene cleavage and increasedβ-ionone production relative to the wild-type NtCCD4a.Our results establish a framework for the design of CCD4 in major crop species through genome editing technology.展开更多
Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalyst...Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalysts.This review synthesizes advances that recast these processes as engineering targets and proposes a conceptual roadmap that bridges synthetic symbioses with the synthetic biology of enzymes and pathways.For BNF,progress spans cross-kingdom strategies—from refactoring nif gene sets and targeting nitrogenase assembly to eukaryotic organelles,to engineering plant-associated diazotrophs,rhizosphere control circuits,and emerging nodule-like microenvironments.For carbon assimilation,new-to-nature CO_(2)-fixation modules and photorespiratory bypasses illustrate how pathway redesign and alternative carboxylases can circumvent key Calvin–Benson–Bassham limitations,and expanding photosynthetic light capture offers additional leverage.Across these domains,we extract common design principles:(i)nitrogenase output is increasingly governed by carbon/energy supply and electron delivery as much as by oxygen protection;(ii)robust function requires compartment-aware enzyme–chassis coordination,substrate channeling,and dynamic regulation using sensors and control circuits;and(iii)scalable implementation may benefit from distributing metabolic labor across engineered consortia rather than forcing all functions into a single host.We discuss enabling technologies—including AI-guided protein design and directed evolution,cell-free prototyping,chassis toolkits,and materials/bioelectrochemical interfaces—that can accelerate design–build–test–learn cycles and reduce barriers to deployment.Together,these insights define a path toward integrated nitrogen and carbon fixation systems for low-emission agriculture and biomanufacturing.展开更多
Biomass-based hydrocarbon fuels,as one of the alternatives to traditional fossil fuels,have attracted considerable attention in the energy field due to their renewability and environmental benefits.This article provid...Biomass-based hydrocarbon fuels,as one of the alternatives to traditional fossil fuels,have attracted considerable attention in the energy field due to their renewability and environmental benefits.This article provides a systematic review of recent research progress in the chemical synthesis of biomass-based hydrocarbon fuels.It outlines the conversion pathways using feedstocks such as lipids,terpenoids,cellulose/hemicellulose,and lignin.Depending on the feedstock,various products with distinct structural characteristics can be prepared through reactions such as cyclization,condensation,and catalytic hydrogenation.Throughout the synthesis process,three key factors play a critical role:efficient catalyst development,production process optimization,and computational-chemistry-based molecular design.Finally,the article discusses future perspectives for biomass-based hydrocarbon fuel synthesis research.展开更多
Filters,as a key component in the photoelectric detection system,can simplify the optical system and improve detection efficiency.Based on the usage requirements,a visible/near-infrared filter film with up to 5 waveba...Filters,as a key component in the photoelectric detection system,can simplify the optical system and improve detection efficiency.Based on the usage requirements,a visible/near-infrared filter film with up to 5 wavebands needs to be designed and prepared,while simultaneously satisfying high reflection in 2 wave-bands and high transmittance in 3 wavebands.Therefore,we have conducted a systematic study on the film design,thin film preparation process,and control accuracy of film layer thickness.In this work,the short-wave pass film system is superimposed with the long-wave pass film system,and the number of cycles and matching coefficient of the film system are tuned to meet the requirements of cut-off band.Additionally,Smith method was used to match bandpass film system to optimize the transmission band and complete the visible/near infrared multiband laser filter film design.In the preparation process,combined with the sensitiv-ity of the film layer,inverse analysis is used to invert the film layer monitored by each optical monitoring chip.The optical control scheme with weak optical signal in the monitoring process is simulated and correc-ted,and the monitoring wavelength with stronger optical signal is matched,resulting in an improvement of the control accuracy for the film thickness and the transmittance in the specified wavelength range.Ulti-mately,the actual physical thickness is 9.66μm,and the error with the theoretical design thickness is less than 0.4%,and the transmittance of the specified 3 wavebands exceeds 99%.The average transmittance of the cut-off bands at the 455−500 nm and 910−1000 nm is 0.45% and 0.16%,respectively.展开更多
Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon...Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.展开更多
Evaluating Adherence to Safety Standards for Physical Space Design, Equipment, and Patient and Staff Protection in Magnetic Resonance Imaging Centers:A Descriptive Cross-sectional Study Amirreza Sadeghinasab1, Jafar F...Evaluating Adherence to Safety Standards for Physical Space Design, Equipment, and Patient and Staff Protection in Magnetic Resonance Imaging Centers:A Descriptive Cross-sectional Study Amirreza Sadeghinasab1, Jafar Fatahiasl2, Mahmoud Mohammadi-Sadr1, Masoud Heydari Kahkesh3, and Marziyeh Tahmasbi2(1.Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran;2.Department of Radiologic Technology, School of Allied Medical Sciences, Ahvaz, Jundishapur University of Medical Sciences, Ahvaz, Iran;3.Department of Radiology and Radiotherapy, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran)Abstract:Magnetic resonance imaging(MRI) has revolutionized disease diagnosis and treatment.However, the technology poses safety risks, such as exposure to magnetic fields, RF pulses, and cryogens, necessitating strict adherence to safety protocols to protect patients and healthcare workers.展开更多
The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,effic...The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,efficiency,and catalyst stability are strongly dependent on the electrolyte pH environment.Under alkaline conditions,high OH−concentration facilitates preferential aldehyde group oxidation and efficient deprotonation,enabling highly efficient synthesis of 2,5-furandicarboxylic acid,but simultaneously induces HMF self-degradation and complicates product separation.As pH decreases,the reaction mechanism shifts toward enhanced hydroxymethyl oxidation,leading to intermediate accumulation(such as 5-hydroxymethyl-2-furancarboxylic acid,2,5-diformylfuran,and 5-formyl-2-furancarboxylic acid)with challenging selectivity control and significantly slowed reaction kinetics.This review comprehensively examines the systematic differences in HMF oxidation pathways and surface catalytic mechanisms across the full pH range from alkaline to acidic conditions.Addressing the distinct reaction characteristics and core challenges in alkaline,near-neutral,and acidic media,we systematically evaluate design strategies for high-efficiency electrocatalysts and explore reactor design aspects.Future research should focus on process integration(with tailored reactor design)for energy consumption reduction in alkaline systems,targeted synthesis of diverse oxidation products in near-neutral systems,and innovative catalyst development for acidic systems,thereby advancing the efficiency,selectivity,and practical application of HMF electrooxidation technologies across the entire pH spectrum through synergistic optimization of catalyst,reactor,and process.展开更多
With the rapid growth of cloud computing,the number of data centers(DCs)continuously increases,leading to a high-energy consumption dilemma.Cooling,apart from IT equipment,represents the largest energy consumption in ...With the rapid growth of cloud computing,the number of data centers(DCs)continuously increases,leading to a high-energy consumption dilemma.Cooling,apart from IT equipment,represents the largest energy consumption in DCs.Passive design(PD)and active design(AD)are two important approaches in architectural design to reduce energy consumption.However,for DC cooling,few studies have summarized AD,and there are almost no studies on PD.Based on existing international research(2005-2024),this paper summarizes the current state of cooling strategies for DCs.PD encompasses floors,ceilings,and layout and zoning of racks.Additionally,other passive strategies not yet studied in DCs are critically examined.AD includes air,liquid,free,and two-phase cooling.This paper systematically compares the performance of different AD technologies on various KPIs,including energy,economic,and environmental indicators.This paper also explores the application of different cooling design strategies through best-practice examples and presents advanced algorithms for energy management in operational DCs.This study reveals that free cooling is widely employed,with Artificial Neural Networks emerging as the most popular algorithm for managing cooling energy.Finally,this paper suggests four future directions for reducing cooling energy in DCs,with a focus on the development of passive strategies.This paper provides an overview and guide to DC energy-consumption issues,emphasizes the importance of implementing passive and active design strategies to reduce DC cooling energy consumption,and provides directions and references for future energy-efficient DC designs.展开更多
Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a cruc...Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a crucial part of managing any construction project-but particularly important for high-speed railway projects that often have several contractual parties and stakeholders,very long project timelines and huge upfront cost overlays.This paper discusses how various project interfaces were managed during the design and construction of the civil engineering infrastructure for the High Speed Two(HS2)project in the United Kingdom.Design/methodology/approach-The paper uses the case study methodology.Key interfaces on the HS2 project are grouped into various categories and the paper discusses how they were managed within the Area North Integrated Project Team(IPT)of the HS2 project made up of contractor Balfour Beatty VINCI(BBV),the Mott MacDonald SYSTRA Design Joint Venture(DJV)and client HS2 Ltd.3 different case studies drawn from across the IPT are used,each of them highlighting different interfaces and how these interfaces were managed.Findings-The paper shows how innovative technical designs and modern methods of construction were used to address some of the unique and peculiar challenges of designing a brand-new railway in the United Kingdom.Addressing the contrasting and often competing requirements of different stakeholders,coupled with challenging physical constraints of the very limited land available for the project and the use of a rarely used Act of Parliament in the delivery of the project required different approach to interface management.Collaboration and proactive stakeholder engagement are necessary for successful interface management on megaprojects.The authors posit that adopting an integrated approach to engineering and construction management is an essential ingredient for the successful delivery of high-speed railway projects.Originality/value-With many high-speed railway projects around the world coming up in the next few years,understanding the context and challenges for each country will help engineering and design managers adopt appropriate approaches for their projects.The lessons learned on the HS2 project are also transferable to other mega infrastructure projects with complex project interfaces.展开更多
In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of ...In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of mixture experiments that involve process variables.Prior research has extensively delved into optimal orthogonal block designs for some classic mixture models with process variables.Based on the framework of general blending models,this paper proposes a class of symmetric linear mixture models,which can be regarded as a generalization of many existing ones.Under the orthogonal blocking conditions,orthogonal block designs are devised through Latin squares in the presence of process variables.TheD-,A-,and E-optimality criteria are utilized to obtain optimal designs at the boundary of the simplex in the case of 3 components.As the values of the exponents change,numerically derived optimal design points are presented to illustrate the pattern of their variations,and to verify the consistency of the results with previous research on some specific symmetric general blending models.展开更多
Both large-scale prospective randomized controlled trials(RCTs)and smaller investigator-initiated trials are essential for evaluating the efficacy and safety of medical interventions.Robust protocols and statistical d...Both large-scale prospective randomized controlled trials(RCTs)and smaller investigator-initiated trials are essential for evaluating the efficacy and safety of medical interventions.Robust protocols and statistical designs ensure the reliability of trial outcomes and improve the credibility of research findings.By reviewing the statistical approaches used in the TORCHLIGHT,NCC2167,and NeoTENNIS trials,this article illustrates the principles underlying large-sample confirmatory RCTs,small-sample exploratory adaptive designs,and single-arm two-stage designs.This discussion is aimed at helping researchers apply these design methods more effectively,to increase the likelihood of success in clinical studies.展开更多
Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent...Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent,and metastatic malignancies.Mechanistically,ferroptosis induction not only directly eliminates tumor cells but also promotes immunogenic cell death(ICD),eliciting damage-associated molecular patterns(DAMPs)release to activate partial antitumor immunity.However,standalone ferroptosis therapy fails to initiate robust systemic antitumor immune responses due to inherent limitations:low tumor immunogenicity,immunosuppressive microenvironment constraints,and tumor microenvironment(TME)-associated physiological barriers(e.g.,hypoxia,dense extracellular matrix).To address these challenges,synergistic approaches have been developed to enhance immune cell infiltration and reestablish immunosurveillance,encompassing(1)direct amplification of antitumor immunity,(2)disruption of immunosuppressive tumor niches,and(3)biophysical hallmark remodeling in TME.Rational nanocarrier design has emerged as a critical enabler for overcoming biological delivery barriers and optimizing therapeutic efficacy.Unlike prior studies solely addressing ferroptosis or nanotechnology in tumor therapy,this work first systematically outlines the synergistic potential of nanoparticles in combined ferroptosis-immunotherapy strategies.It advances multidimensional nanoplatform design principles for material selection,structural configuration,physicochemical modulation,multifunctional integration,and artificial intelligence-enabled design,providing a scientific basis for efficacy optimization.Moreover,it examines translational challenges of ferroptosis-immunotherapy nanoplatforms across preclinical and clinical stages,proposing actionable solutions while envisioning future onco-immunotherapy directions.Collectively,it provides systematic insights into advanced nanomaterial design principles and therapeutic optimization strategies,offering a roadmap for accelerating clinical translation in onco-immunotherapy research.展开更多
Health monitoring is becoming increasingly critical for disease prevention,early diagnosis,and highquality living.Polymeric materials,with their mechanical flexibility,biocompatibility,and tunable biochemical properti...Health monitoring is becoming increasingly critical for disease prevention,early diagnosis,and highquality living.Polymeric materials,with their mechanical flexibility,biocompatibility,and tunable biochemical properties,offer unique advantages for creating next-generation personalized devices.In recent years,flexible polymer-based platforms have shown remarkable potential to capture diverse physiological signals in both daily and clinical contexts,including electrophysiological,biochemical,mechanical,and thermal indicators.In this review,we introduce a safety-leveloriented framework to evaluate material and device strategies for health monitoring,spanning the continuum from noninvasive wearables to deeply embedded implants.Physiological signals are systematically classified by use case,and application-specific requirements such as stability,comfort,and long-term compatibility are highlighted as critical factors guiding the selection of polymers,interfacial designs,and device architectures.Special emphasis is placed on mapping material types—including hydrogels,elastomers,and conductive composites—to their most suitable applications.Finally,we propose design principles for developing safe,functional,and adaptive polymer-based systems,aiming at reliable integration with the human body and enabling personalized,preventive healthcare.展开更多
In this paper,we provide a comprehensive examination of the evolution of graphics Application Programming Interfaces(APIs).We begin by exploring traditional graphics APIs,elucidating their distinct features and inhere...In this paper,we provide a comprehensive examination of the evolution of graphics Application Programming Interfaces(APIs).We begin by exploring traditional graphics APIs,elucidating their distinct features and inherent challenges.This sets the stage for a detailed exploration of modern graphics APIs,with a focus on four critical design principles.These principles are further analyzed through specific case studies and categorical examinations.The paper then introduces MoerEngine,a bespoke rendering engine,as a practical case to demonstrate the real-world application of these modern principles in software engineering.In conclusion,the study offers insights into the potential future trajectory of graphics APIs,spotlighting emerging design patterns and technological innovations.It also ventures to predict the development trends and capabilities of next-generation graphics APIs.展开更多
Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,...Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,and knee,caused by echinococ cosis.Artificial intelligence(AI)was used to develop a targeted surgical plan and to design a personalized prosthesis.Finite element analysis(FEA)was used to optimize the mechanical effectiveness of a customized integrated replacement prosthesis and to model stress distribution in the surrounding bone.Three-dimensional(3 D)printing was used to fabricate a customized prosthesis.With the assistance of AI,FEA,and 3 D printing technology,a personalized surgical plan and customized prosthesis were successfully constructed based on the patient’s disease.This approach achieved a successful therapeutic effect,demonstrating that AI-assisted personalized medicine holds great promise for the future.展开更多
Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The app...Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The applications span across non-volatile memory,neuromorphic computing,hardware security,and beyond,prompting memristors to become a versatile solution for next-generation computing and data storage systems.Despite enormous potential of memristors,the transition from laboratory prototypes to large-scale applications is challenging in terms of material stability,device reproducibility,and array scalability.This review systematically explores recent advancements in high-performance memristor technologies,focusing on performance enhancement strategies through material engineering,structural design,pulse protocol optimization,and algorithm control.We provide an in-depth analysis of key performance metrics tailored to specific applications,including non-volatile memory,neuromorphic computing,and hardware security.Furthermore,we propose a co-design framework that integrates device-level optimizations with operational-level improvements,aiming to bridge the gap between theoretical models and practical implementations.展开更多
Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a disti...Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a distinct ability to trigger the nonradical pathway in advance oxidation processes(AOPs),promising a stable,rapid and selective degradation of persistent contaminants.However,due to the inherent“black box”nature and limitations of input features,results and conclusions derived from ML may not always be intuitively understood or comprehensively validated.To tackle this challenge,we linked the front-point interpretable analysis approaches with back-point density functional theory(DFT)calculations to form a chained learning strategy for deeper sight into the intrinsic activation mechanism of BCs in AOPs.At the front point,we conducted an easy-to-interpret meta-analysis to validate two strategies for enhancing nonradical pathways by increasing oxygen content and specific surface area(SSA),and prepared oxidized biochar(OBC500)and SSA-increased biochar(SBC900)by controlling pyrolysis conditions and modification methods.Subsequently,experimental results showed that OBC500 and SBC900 had distinct dominant degradation pathways for 1O2 generation and electron transfer,respectively.Finally,at the end point,DFT calculations revealed their active sites and degradation mechanisms.This chained learning strategy elucidates fundamental principles for BC inverse design and showcases the exceptional capacity to integrate computational techniques to accelerate catalyst inverse design.展开更多
基金the financial supports from National Key R&D Program for Young Scientists of China(Grant No.2022YFC3080900)National Natural Science Foundation of China(Grant No.52374181)+1 种基金BIT Research and Innovation Promoting Project(Grant No.2024YCXZ017)supported by Science and Technology Innovation Program of Beijing institute of technology under Grant No.2022CX01025。
文摘In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.
基金funded High-Level Talents project of Henan Agricultural University(111-30501301)Project of the National key R&D Program of China(2021YFA0909600)+3 种基金Natural Science Foundation of Henan Province(242300420141)the China Postdoctoral Science Foundation(2020M672308)Cultivation Program for Young Backbone Teachers at Henan University of Technology(DC 11)Science Project 110202101042(JY 19)/2022530000241007,110202102033,110202202038.
文摘Carotenoid cleavage dioxygenase 4(CCD4)controls the rate-limiting step ofβ-ionone biosynthesis,making it a valuable target for healthcare and pharmaceutical applications.Nicotiana tabacum,a carotenoid-richd crop species,is a promising source forβ-ionone production.This study aimed to modify CCD4 activity to increaseβ-ionone yield in tobacco.We identified two isoforms of CCD4 in N.tabacum,NtCCD4a and NtCCD4b,with NtCCD4a exhibiting significantly higher expression levels than NtCCD4b.Using solid-phase microextraction gas chromatography-mass spectrometry(SPME-GC–MS),we demonstrated that NtCCD4a effectively catalyzes the cleavage ofβ-carotene to produceβ-ionone.To improve its enzymatic activity,we applied structure-based rational design to reconstruct the active pocket of NtCCD4a,followed by high-throughput screening of mutant variants.Three single base mutants,F181G,F184L,and F337M,in NtCCD4a showed enhancedβ-ionone production compared to the wild-type,with F337M yielding the highest amount.No synergistic effects were observed among the three mutants.Transgenic tobacco plants expressing the F181G,F184L,and F337M mutations had acceleratedβ-carotene cleavage and increasedβ-ionone production relative to the wild-type NtCCD4a.Our results establish a framework for the design of CCD4 in major crop species through genome editing technology.
基金supported by the funds of the Ministry of Science and Technology of China(2019YFA0904700)the National Natural Science Foundation of China(32471477)to Cheng Qi.
文摘Biological nitrogen fixation(BNF)and photosynthetic carbon fixation underpin food production and climate mitigation,yet natural systems are constrained by oxygen sensitivity,high energy demand,and inefficient catalysts.This review synthesizes advances that recast these processes as engineering targets and proposes a conceptual roadmap that bridges synthetic symbioses with the synthetic biology of enzymes and pathways.For BNF,progress spans cross-kingdom strategies—from refactoring nif gene sets and targeting nitrogenase assembly to eukaryotic organelles,to engineering plant-associated diazotrophs,rhizosphere control circuits,and emerging nodule-like microenvironments.For carbon assimilation,new-to-nature CO_(2)-fixation modules and photorespiratory bypasses illustrate how pathway redesign and alternative carboxylases can circumvent key Calvin–Benson–Bassham limitations,and expanding photosynthetic light capture offers additional leverage.Across these domains,we extract common design principles:(i)nitrogenase output is increasingly governed by carbon/energy supply and electron delivery as much as by oxygen protection;(ii)robust function requires compartment-aware enzyme–chassis coordination,substrate channeling,and dynamic regulation using sensors and control circuits;and(iii)scalable implementation may benefit from distributing metabolic labor across engineered consortia rather than forcing all functions into a single host.We discuss enabling technologies—including AI-guided protein design and directed evolution,cell-free prototyping,chassis toolkits,and materials/bioelectrochemical interfaces—that can accelerate design–build–test–learn cycles and reduce barriers to deployment.Together,these insights define a path toward integrated nitrogen and carbon fixation systems for low-emission agriculture and biomanufacturing.
基金Support by National Natural Science Foundation of China(22127802,22573091)the HY Action(62402010305)。
文摘Biomass-based hydrocarbon fuels,as one of the alternatives to traditional fossil fuels,have attracted considerable attention in the energy field due to their renewability and environmental benefits.This article provides a systematic review of recent research progress in the chemical synthesis of biomass-based hydrocarbon fuels.It outlines the conversion pathways using feedstocks such as lipids,terpenoids,cellulose/hemicellulose,and lignin.Depending on the feedstock,various products with distinct structural characteristics can be prepared through reactions such as cyclization,condensation,and catalytic hydrogenation.Throughout the synthesis process,three key factors play a critical role:efficient catalyst development,production process optimization,and computational-chemistry-based molecular design.Finally,the article discusses future perspectives for biomass-based hydrocarbon fuel synthesis research.
文摘Filters,as a key component in the photoelectric detection system,can simplify the optical system and improve detection efficiency.Based on the usage requirements,a visible/near-infrared filter film with up to 5 wavebands needs to be designed and prepared,while simultaneously satisfying high reflection in 2 wave-bands and high transmittance in 3 wavebands.Therefore,we have conducted a systematic study on the film design,thin film preparation process,and control accuracy of film layer thickness.In this work,the short-wave pass film system is superimposed with the long-wave pass film system,and the number of cycles and matching coefficient of the film system are tuned to meet the requirements of cut-off band.Additionally,Smith method was used to match bandpass film system to optimize the transmission band and complete the visible/near infrared multiband laser filter film design.In the preparation process,combined with the sensitiv-ity of the film layer,inverse analysis is used to invert the film layer monitored by each optical monitoring chip.The optical control scheme with weak optical signal in the monitoring process is simulated and correc-ted,and the monitoring wavelength with stronger optical signal is matched,resulting in an improvement of the control accuracy for the film thickness and the transmittance in the specified wavelength range.Ulti-mately,the actual physical thickness is 9.66μm,and the error with the theoretical design thickness is less than 0.4%,and the transmittance of the specified 3 wavebands exceeds 99%.The average transmittance of the cut-off bands at the 455−500 nm and 910−1000 nm is 0.45% and 0.16%,respectively.
基金Supported by the National Key Research and Development Program of China(2023YFB4104500,2023YFB4104502)the National Natural Science Foundation of China(22138013)the Taishan Scholar Project(ts201712020).
文摘Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.
文摘Evaluating Adherence to Safety Standards for Physical Space Design, Equipment, and Patient and Staff Protection in Magnetic Resonance Imaging Centers:A Descriptive Cross-sectional Study Amirreza Sadeghinasab1, Jafar Fatahiasl2, Mahmoud Mohammadi-Sadr1, Masoud Heydari Kahkesh3, and Marziyeh Tahmasbi2(1.Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran;2.Department of Radiologic Technology, School of Allied Medical Sciences, Ahvaz, Jundishapur University of Medical Sciences, Ahvaz, Iran;3.Department of Radiology and Radiotherapy, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran)Abstract:Magnetic resonance imaging(MRI) has revolutionized disease diagnosis and treatment.However, the technology poses safety risks, such as exposure to magnetic fields, RF pulses, and cryogens, necessitating strict adherence to safety protocols to protect patients and healthcare workers.
基金supported by the National Key R&D Program of China(2023YFA1507400)the National Natural Science Foundation of China(Grant No.22325805,22441010,22408203)+2 种基金Beijing Natural Science Foundation(Grant No.JQ22003)the Haihe Laboratory of Sustainable Chemical Transformations(24HHWCSS00007)Tsinghua University Dushi Program,and Sinopec Group(PR20232572).
文摘The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,efficiency,and catalyst stability are strongly dependent on the electrolyte pH environment.Under alkaline conditions,high OH−concentration facilitates preferential aldehyde group oxidation and efficient deprotonation,enabling highly efficient synthesis of 2,5-furandicarboxylic acid,but simultaneously induces HMF self-degradation and complicates product separation.As pH decreases,the reaction mechanism shifts toward enhanced hydroxymethyl oxidation,leading to intermediate accumulation(such as 5-hydroxymethyl-2-furancarboxylic acid,2,5-diformylfuran,and 5-formyl-2-furancarboxylic acid)with challenging selectivity control and significantly slowed reaction kinetics.This review comprehensively examines the systematic differences in HMF oxidation pathways and surface catalytic mechanisms across the full pH range from alkaline to acidic conditions.Addressing the distinct reaction characteristics and core challenges in alkaline,near-neutral,and acidic media,we systematically evaluate design strategies for high-efficiency electrocatalysts and explore reactor design aspects.Future research should focus on process integration(with tailored reactor design)for energy consumption reduction in alkaline systems,targeted synthesis of diverse oxidation products in near-neutral systems,and innovative catalyst development for acidic systems,thereby advancing the efficiency,selectivity,and practical application of HMF electrooxidation technologies across the entire pH spectrum through synergistic optimization of catalyst,reactor,and process.
文摘With the rapid growth of cloud computing,the number of data centers(DCs)continuously increases,leading to a high-energy consumption dilemma.Cooling,apart from IT equipment,represents the largest energy consumption in DCs.Passive design(PD)and active design(AD)are two important approaches in architectural design to reduce energy consumption.However,for DC cooling,few studies have summarized AD,and there are almost no studies on PD.Based on existing international research(2005-2024),this paper summarizes the current state of cooling strategies for DCs.PD encompasses floors,ceilings,and layout and zoning of racks.Additionally,other passive strategies not yet studied in DCs are critically examined.AD includes air,liquid,free,and two-phase cooling.This paper systematically compares the performance of different AD technologies on various KPIs,including energy,economic,and environmental indicators.This paper also explores the application of different cooling design strategies through best-practice examples and presents advanced algorithms for energy management in operational DCs.This study reveals that free cooling is widely employed,with Artificial Neural Networks emerging as the most popular algorithm for managing cooling energy.Finally,this paper suggests four future directions for reducing cooling energy in DCs,with a focus on the development of passive strategies.This paper provides an overview and guide to DC energy-consumption issues,emphasizes the importance of implementing passive and active design strategies to reduce DC cooling energy consumption,and provides directions and references for future energy-efficient DC designs.
文摘Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a crucial part of managing any construction project-but particularly important for high-speed railway projects that often have several contractual parties and stakeholders,very long project timelines and huge upfront cost overlays.This paper discusses how various project interfaces were managed during the design and construction of the civil engineering infrastructure for the High Speed Two(HS2)project in the United Kingdom.Design/methodology/approach-The paper uses the case study methodology.Key interfaces on the HS2 project are grouped into various categories and the paper discusses how they were managed within the Area North Integrated Project Team(IPT)of the HS2 project made up of contractor Balfour Beatty VINCI(BBV),the Mott MacDonald SYSTRA Design Joint Venture(DJV)and client HS2 Ltd.3 different case studies drawn from across the IPT are used,each of them highlighting different interfaces and how these interfaces were managed.Findings-The paper shows how innovative technical designs and modern methods of construction were used to address some of the unique and peculiar challenges of designing a brand-new railway in the United Kingdom.Addressing the contrasting and often competing requirements of different stakeholders,coupled with challenging physical constraints of the very limited land available for the project and the use of a rarely used Act of Parliament in the delivery of the project required different approach to interface management.Collaboration and proactive stakeholder engagement are necessary for successful interface management on megaprojects.The authors posit that adopting an integrated approach to engineering and construction management is an essential ingredient for the successful delivery of high-speed railway projects.Originality/value-With many high-speed railway projects around the world coming up in the next few years,understanding the context and challenges for each country will help engineering and design managers adopt appropriate approaches for their projects.The lessons learned on the HS2 project are also transferable to other mega infrastructure projects with complex project interfaces.
基金supported by the National Natural Science Foundation of China[grant numbers 12071329,12471246].
文摘In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of mixture experiments that involve process variables.Prior research has extensively delved into optimal orthogonal block designs for some classic mixture models with process variables.Based on the framework of general blending models,this paper proposes a class of symmetric linear mixture models,which can be regarded as a generalization of many existing ones.Under the orthogonal blocking conditions,orthogonal block designs are devised through Latin squares in the presence of process variables.TheD-,A-,and E-optimality criteria are utilized to obtain optimal designs at the boundary of the simplex in the case of 3 components.As the values of the exponents change,numerically derived optimal design points are presented to illustrate the pattern of their variations,and to verify the consistency of the results with previous research on some specific symmetric general blending models.
基金supported by a grant from the National Science and Technology Major Project(Grant No.2024ZD0519800).
文摘Both large-scale prospective randomized controlled trials(RCTs)and smaller investigator-initiated trials are essential for evaluating the efficacy and safety of medical interventions.Robust protocols and statistical designs ensure the reliability of trial outcomes and improve the credibility of research findings.By reviewing the statistical approaches used in the TORCHLIGHT,NCC2167,and NeoTENNIS trials,this article illustrates the principles underlying large-sample confirmatory RCTs,small-sample exploratory adaptive designs,and single-arm two-stage designs.This discussion is aimed at helping researchers apply these design methods more effectively,to increase the likelihood of success in clinical studies.
基金supported by the National Natural Science Foundation of China(Nos.82302373,81903846)Natural Science Foundation of Sichuan Province(No.2022NSFSC1925)+1 种基金Chengdu Technology Innovation Research and Development Project(No.2022-YF05-01546-SN)the Introduction of Talents Research Project of Chengdu University(No.2081921049)。
文摘Emerging ferroptosis-immunotherapy strategies,integrating functionalized nanoplatforms with ferroptosis-inducing agents and immunomodulatory therapeutics,demonstrate significant potential in managing primary,recurrent,and metastatic malignancies.Mechanistically,ferroptosis induction not only directly eliminates tumor cells but also promotes immunogenic cell death(ICD),eliciting damage-associated molecular patterns(DAMPs)release to activate partial antitumor immunity.However,standalone ferroptosis therapy fails to initiate robust systemic antitumor immune responses due to inherent limitations:low tumor immunogenicity,immunosuppressive microenvironment constraints,and tumor microenvironment(TME)-associated physiological barriers(e.g.,hypoxia,dense extracellular matrix).To address these challenges,synergistic approaches have been developed to enhance immune cell infiltration and reestablish immunosurveillance,encompassing(1)direct amplification of antitumor immunity,(2)disruption of immunosuppressive tumor niches,and(3)biophysical hallmark remodeling in TME.Rational nanocarrier design has emerged as a critical enabler for overcoming biological delivery barriers and optimizing therapeutic efficacy.Unlike prior studies solely addressing ferroptosis or nanotechnology in tumor therapy,this work first systematically outlines the synergistic potential of nanoparticles in combined ferroptosis-immunotherapy strategies.It advances multidimensional nanoplatform design principles for material selection,structural configuration,physicochemical modulation,multifunctional integration,and artificial intelligence-enabled design,providing a scientific basis for efficacy optimization.Moreover,it examines translational challenges of ferroptosis-immunotherapy nanoplatforms across preclinical and clinical stages,proposing actionable solutions while envisioning future onco-immunotherapy directions.Collectively,it provides systematic insights into advanced nanomaterial design principles and therapeutic optimization strategies,offering a roadmap for accelerating clinical translation in onco-immunotherapy research.
基金the financial support from the National University of Singapore(Grant No.A-001002800-00)the Singapore Ministry of Education(Grant No.A-8003587-00-00)。
文摘Health monitoring is becoming increasingly critical for disease prevention,early diagnosis,and highquality living.Polymeric materials,with their mechanical flexibility,biocompatibility,and tunable biochemical properties,offer unique advantages for creating next-generation personalized devices.In recent years,flexible polymer-based platforms have shown remarkable potential to capture diverse physiological signals in both daily and clinical contexts,including electrophysiological,biochemical,mechanical,and thermal indicators.In this review,we introduce a safety-leveloriented framework to evaluate material and device strategies for health monitoring,spanning the continuum from noninvasive wearables to deeply embedded implants.Physiological signals are systematically classified by use case,and application-specific requirements such as stability,comfort,and long-term compatibility are highlighted as critical factors guiding the selection of polymers,interfacial designs,and device architectures.Special emphasis is placed on mapping material types—including hydrogels,elastomers,and conductive composites—to their most suitable applications.Finally,we propose design principles for developing safe,functional,and adaptive polymer-based systems,aiming at reliable integration with the human body and enabling personalized,preventive healthcare.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20230921014。
文摘In this paper,we provide a comprehensive examination of the evolution of graphics Application Programming Interfaces(APIs).We begin by exploring traditional graphics APIs,elucidating their distinct features and inherent challenges.This sets the stage for a detailed exploration of modern graphics APIs,with a focus on four critical design principles.These principles are further analyzed through specific case studies and categorical examinations.The paper then introduces MoerEngine,a bespoke rendering engine,as a practical case to demonstrate the real-world application of these modern principles in software engineering.In conclusion,the study offers insights into the potential future trajectory of graphics APIs,spotlighting emerging design patterns and technological innovations.It also ventures to predict the development trends and capabilities of next-generation graphics APIs.
基金partially supported by the National Natural Science Foundation of China(Nos.32471474 and 82102574)the Precision Medicine Project of People’s Hospital of Xinjiang Uygur Autonomous Region(No.20220305)+4 种基金Chengdu Advanced Metal Materials Industry Technology Research Institute Co.,Ltd.Support Project(No.24H0802)Sichuan Science and Technology Program(Nos.2025YFHZ0086,2023YFS0053,2024YFHZ0125,and 2025ZNSFSC0381)Project of Tianfu Jincheng Laboratory(No.2025ZH009)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515220102)Xinjiang Autonomous Region Science and Technology Support Project Plan(Directive)Project(No.2024E02049)。
文摘Cases of widespread bone hydatid infection are relatively rare in clinical practice.In this study,we reported for the first time a validated integrated repair therapy for multiple bone tissues,including the hip,femur,and knee,caused by echinococ cosis.Artificial intelligence(AI)was used to develop a targeted surgical plan and to design a personalized prosthesis.Finite element analysis(FEA)was used to optimize the mechanical effectiveness of a customized integrated replacement prosthesis and to model stress distribution in the surrounding bone.Three-dimensional(3 D)printing was used to fabricate a customized prosthesis.With the assistance of AI,FEA,and 3 D printing technology,a personalized surgical plan and customized prosthesis were successfully constructed based on the patient’s disease.This approach achieved a successful therapeutic effect,demonstrating that AI-assisted personalized medicine holds great promise for the future.
基金supported by the National Key R&D Project from the Minister of Science and Technology(2024YFA1211500)the National Natural Science Foundation of China(Grant Nos.62304130,62405158 and 62574123)+1 种基金the Shanghai youth science and technology star project(24QA2702800)Shanghai Key Laboratory of Chips and Systems for Intelligent Connected Vehicle。
文摘Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The applications span across non-volatile memory,neuromorphic computing,hardware security,and beyond,prompting memristors to become a versatile solution for next-generation computing and data storage systems.Despite enormous potential of memristors,the transition from laboratory prototypes to large-scale applications is challenging in terms of material stability,device reproducibility,and array scalability.This review systematically explores recent advancements in high-performance memristor technologies,focusing on performance enhancement strategies through material engineering,structural design,pulse protocol optimization,and algorithm control.We provide an in-depth analysis of key performance metrics tailored to specific applications,including non-volatile memory,neuromorphic computing,and hardware security.Furthermore,we propose a co-design framework that integrates device-level optimizations with operational-level improvements,aiming to bridge the gap between theoretical models and practical implementations.
基金supported by Project of National and Local Joint Engineering Research Center for Biomass Energy Development and Utilization(Harbin Institute of Technology,No.2021A004).
文摘Machine learning(ML)is recognized as a potent tool for the inverse design of environmental functional material,particularly for complex entities like biochar-based catalysts(BCs).Thus,the tailored BCs can have a distinct ability to trigger the nonradical pathway in advance oxidation processes(AOPs),promising a stable,rapid and selective degradation of persistent contaminants.However,due to the inherent“black box”nature and limitations of input features,results and conclusions derived from ML may not always be intuitively understood or comprehensively validated.To tackle this challenge,we linked the front-point interpretable analysis approaches with back-point density functional theory(DFT)calculations to form a chained learning strategy for deeper sight into the intrinsic activation mechanism of BCs in AOPs.At the front point,we conducted an easy-to-interpret meta-analysis to validate two strategies for enhancing nonradical pathways by increasing oxygen content and specific surface area(SSA),and prepared oxidized biochar(OBC500)and SSA-increased biochar(SBC900)by controlling pyrolysis conditions and modification methods.Subsequently,experimental results showed that OBC500 and SBC900 had distinct dominant degradation pathways for 1O2 generation and electron transfer,respectively.Finally,at the end point,DFT calculations revealed their active sites and degradation mechanisms.This chained learning strategy elucidates fundamental principles for BC inverse design and showcases the exceptional capacity to integrate computational techniques to accelerate catalyst inverse design.
