The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF str...The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.展开更多
Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the pot...Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the potential to combine the low cost of Li Fe PO_(4)(LFP)with the high theoretical energy density of LiMnPO_(4)(LMP).However,quantitative investigation of the intricate coupling between the Fe/Mn ratio and the resulting energy density is challenging due to the parametric complexity.It is crucial to develop a universal approach for the rapid construction of multi-parameter mapping.In this work,we propose an active learning-guided high-throughput workflow for quantitatively predicting the Fe/Mn ratio and the energy density mapping of LMFP.An optimal composition(LiMn_(0.66)Fe_(0.34)PO_(4))was effectively screened from 81 cathode materials via only 5 samples.Model-guided electrochemical analysis revealed a nonlinear relationship between the Fe/Mn ratio and electrochemical properties,including ion mobility and impedance,elucidating the quantitative chemical composition-energy density map of LMFP.The results demonstrated the efficacy of the method in high-throughput screening of LiBs cathode materials.展开更多
The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combinat...The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).展开更多
For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered tr...For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.展开更多
Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of m...Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of medicine,food,and agriculture.However,efficiently screening AMPs from natural sources poses several challenges,including low efficiency and high antibiotic resistance.This review focuses on the action mechanisms of AMPs,both through membrane and non-membrane routes.We thoroughly examine various highly efficient AMP screening methods,including whole-bacterial adsorption binding,cell membrane chromatography(CMC),phospholipid membrane chromatography binding,membranemediated capillary electrophoresis(CE),colorimetric assays,thin layer chromatography(TLC),fluorescence-based screening,genetic sequencing-based analysis,computational mining of AMP databases,and virtual screening methods.Additionally,we discuss potential developmental applications for enhancing the efficiency of AMP discovery.This review provides a comprehensive framework for identifying AMPs within complex natural product systems.展开更多
Single-atom catalysts(SACs)have been widely utilized in electrochemical nitrogen reduction reactions(NRR)due to their high atomic utilization and selectivity.Owing to the unique sp/sp^(2)co-hybridization,graphyne mate...Single-atom catalysts(SACs)have been widely utilized in electrochemical nitrogen reduction reactions(NRR)due to their high atomic utilization and selectivity.Owing to the unique sp/sp^(2)co-hybridization,graphyne materials can offer stable adsorption sites for single metal atoms.To investigate the influence of the sp/sp^(2)hybrid carbon ratio on the electrocatalytic NRR performance of graphyne,a high-throughput screening of 81 catalysts,with27 transition metals loaded on graphyne(GY1),graphdiyne(GY2),and graphtriyne(GY3),was conducted using firstprinciples calculations.The results of the screening revealed that Ti@GY3 exhibits the lowest energy barrier for the rate-determining step(0.32 eV)in NRR.Further,to explore the impact of different sp/sp^(2)-hybridized carbon ratios on the catalytic activity of SACs,the mechanism of nitrogen(N_(2))adsorption,activation,and the comprehensive pathway of NRR on Ti@GY1,Ti@GY2,and Ti@GY3 was systematically investigated.It was found that the ratio of sp/sp^(2)-hybridized carbon can significantly modulate the d-band center of the metal,thus affecting the energy barrier of the rate-determining step in NRR,decreasing from Ti@GY1(0.59 eV)to Ti@GY2(0.49 eV);and further to Ti@GY3(0.32 eV).Additionally,the Hall conductance was found to increase with the bias voltage in the range of 0.4-1 V,as calculated by Nanodcal software,demonstrating an improvement in the conductivity of the SAC.In summary,this work provides theoretical guidance for modulating the electrocatalytic nitrogen reduction activity of SACs by varying the ratio of sp/sp^(2)hybrid carbon,with Ti@GY3 showing potential as an excellent NRR catalyst.展开更多
Recent years have witnessed significant advances in the development of novel techniques and methodologies for identifying active ingredients in traditional Chinese medicine(TCM),substantially advancing research and de...Recent years have witnessed significant advances in the development of novel techniques and methodologies for identifying active ingredients in traditional Chinese medicine(TCM),substantially advancing research and development efforts.Spectrum-effect correlation analysis,affinity ultrafiltration,high-content screening(HCS)imaging,and cell membrane chromatography(CMC)have emerged as essential tools,effectively linking TCM chemical constituents to their biological effects,thereby enabling efficient active ingredient screening.Additionally,molecular interaction analysis provides deeper insights into TCM-biomolecule interaction mechanisms,enhancing understanding of its therapeutic potential.Computer-aided techniques facilitate TCM active ingredient identification,optimizing the screening process for efficiency and cost-effectiveness.Molecular probe technology,as an emerging methodology,enables precise and rapid screening for novel therapeutic drug discovery.Ongoing technological advancement in this field indicates promising future developments,potentially leading to more effective and targeted TCM-based therapies.展开更多
Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is...Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.展开更多
Understanding the correlation between the fundamental descriptors and catalytic performance is meaningful to guide the design of high-performance electrochemical catalysts.However,exploring key factors that affect cat...Understanding the correlation between the fundamental descriptors and catalytic performance is meaningful to guide the design of high-performance electrochemical catalysts.However,exploring key factors that affect catalytic performance in the vast catalyst space remains challenging for people.Herein,to accurately identify the factors that affect the performance of N2 reduction,we apply interpretable machine learning(ML)to analyze high-throughput screening results,which is also suited to other surface reactions in catalysis.To expound on the paradigm,33 promising catalysts are screened from 168 carbon-supported candidates,specifically single-atom catalysts(SACs)supported by a BC_(3)monolayer(TM@V_(B/C)-N_(n)=_(0-3)-BC_(3))via high-throughput screening.Subsequently,the hybrid sampling method and XGBoost model are selected to classify eligible and non-eligible catalysts.Through feature interpretation using Shapley Additive Explanations(SHAP)analysis,two crucial features,that is,the number of valence electrons(N_(v))and nitrogen substitution(N_(n)),are screened out.Combining SHAP analysis and electronic structure calculations,the synergistic effect between an active center with low valence electron numbers and reasonable C-N coordination(a medium fraction of nitrogen substitution)can exhibit high catalytic performance.Finally,six superior catalysts with a limiting potential lower than-0.4 V are predicted.Our workflow offers a rational approach to obtaining key information on catalytic performance from high-throughput screening results to design efficient catalysts that can be applied to other materials and reactions.展开更多
Tuberculosis(TB)is a chronic infectious disease,which is caused by the pathogen Mycobacterium tuberculosis(Mtb)and reemerged as a global health risk with a significant proportion of multi-drug resistant and extensivel...Tuberculosis(TB)is a chronic infectious disease,which is caused by the pathogen Mycobacterium tuberculosis(Mtb)and reemerged as a global health risk with a significant proportion of multi-drug resistant and extensively drug resistant TB cases.It is very urgent to find some novel high-confidence drug targets in Mtb for discovering the effective anti-TB agents.Thioredoxin reductase(TrxR)has been identified to be a highly viable target for anti-TB drugs for its important role in protecting the pathogen from thiol-specific oxidizing stress,regulating intracellular dithiol/disulfide homeostasis and DNA replication and repair.In the present work,a near-infrared(NIR)fluorescent probe DDAT was developed for the detection of TrxR activity and used to high-throughput screen the TrxR inhibitors from natural products.Two screened TrxR inhibitors from Sappan Lignum and microbial metabolites that were further used to inhibit Mycobacterium tuberculosis.All the results indicate that DDAT is a practical fluorescent molecular tool for the discovery of potential anti-TB drugs.展开更多
Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due ...Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.展开更多
One of the main diseases that adversely impacts the global citrus industry is citrus bacterial canker(CBC),caused by the bacteria Xanthomonas citri subsp.citri(Xcc).Response to CBC is a complex process,with both prote...One of the main diseases that adversely impacts the global citrus industry is citrus bacterial canker(CBC),caused by the bacteria Xanthomonas citri subsp.citri(Xcc).Response to CBC is a complex process,with both proteinDNA as well as protein–protein interactions for the regulatory network.To detect such interactions in CBC resistant regulation,a citrus high-throughput screening system with 203 CBC-inducible transcription factors(TFs),were developed.Screening the upstream regulators of target by yeast-one hybrid(Y1H)methods was also performed.A regulatory module of CBC resistance was identified based on this system.One TF(CsDOF5.8)was explored due to its interactions with the 1-kb promoter fragment of CsPrx25,a resistant gene of CBC involved in reactive oxygen species(ROS)homeostasis regulation.Electrophoretic mobility shift assay(EMSA),dual-LUC assays,as well as transient overexpression of CsDOF5.8,further validated the interactions and transcriptional regulation.The CsDOF5.8–CsPrx25 promoter interaction revealed a complex pathway that governs the regulation of CBC resistance via H2O2homeostasis.The high-throughput Y1H/Y2H screening system could be an efficient tool for studying regulatory pathways or network of CBC resistance regulation.In addition,it could highlight the potential of these candidate genes as targets for efforts to breed CBC-resistant citrus varieties.展开更多
Barrett's esophagus(BE) is a change in the esophageal lining and is known to be the major precursor lesion for most cases of esophageal adenocarcinoma(EAC).Despite an understanding of its association with BE for m...Barrett's esophagus(BE) is a change in the esophageal lining and is known to be the major precursor lesion for most cases of esophageal adenocarcinoma(EAC).Despite an understanding of its association with BE for many years and the falling incidence rates of squamous cell carcinoma of the esophagus, the incidence for EAC continues to rise exponentially. In association with this rising incidence, if the delay in diagnosis of EAC occurs after the onset of symptoms,then the mortality at 5 years is greater than 80%. Appropriate diagnosis and surveillance strategies are therefore vital for BE. Multiple novel optical technologies and other advanced approaches are being utilized to assist in making screening and surveillance more cost effective. We review the current guidelines and evolving techniques that are currently being evaluated.展开更多
Effective prevention and management of osteoporosis would require suitable methods for population screenings and early diagnosis. Current clinicallyavailable diagnostic methods are mainly based on the use of either X-...Effective prevention and management of osteoporosis would require suitable methods for population screenings and early diagnosis. Current clinicallyavailable diagnostic methods are mainly based on the use of either X-rays or ultrasound(US). All X-ray based methods provide a measure of bone mineral density(BMD), but it has been demonstrated that other structural aspects of the bone are important in determining fracture risk, such as mechanical features and elastic properties, which cannot be assessed using densitometric techniques. Among the most commonly used techniques, dual X-ray absorptiometry(DXA) is considered the current 'gold standard' for osteoporosis diagnosis and fracture risk prediction. Unfortunately, as other X-ray based techniques, DXA has specific limitations(e.g., use of ionizing radiation, large size of the equipment, high costs, limited availability) that hinder its application for population screenings and primary care diagnosis. This has resulted in an increasing interest in developing reliable pre-screening tools for osteoporosis such as quantitative ultrasound(QUS) scanners, which do not involve ionizing radiation exposure and represent a cheaper solution exploiting portable and widely available devices. Furthermore, the usefulness of QUS techniques in fracture risk prediction has been proven and, with the last developments, they are also becoming a more and more reliable approach for assessing bone quality. However, the US assessment of osteoporosis is currently used only as a pre-screening tool, requiring a subsequent diagnosis confirmation by means of a DXA evaluation. Here we illustrate the state of art in the early diagnosis of this 'silent disease' and show up recent advances for its prevention and improved management through early diagnosis.展开更多
Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and...Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.展开更多
Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening （HTS） data for 3 762 distinct global gene knockout （KO） mouse lines with viable adult hom...Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening （HTS） data for 3 762 distinct global gene knockout （KO） mouse lines with viable adult homozygous mice generated using either gene-trap or homologous recombination technologies. Bone mass was determined from DEXA scans of male and female mice at 14 weeks of age and by microCT analyses of bones from male mice at 16 weeks of age. Wild-type （WT） cagemates/littermates were examined for each gene KO. Lethality was observed in an additional 850 KO lines. Since primary HTS are susceptible to false positive findings, additional cohorts of mice from KO lines with intriguing HTS bone data were examined. Aging, ovariectomy, histomorphometry and bone strength studies were performed and possible non-skeletal phenotypes were explored. Together, these screens identified multiple genes affecting bone mass： 23 previously reported genes （Calcr, Cebpb, Crtap, Dcstamp, Dkkl, Duoxa2, Enppl, Fgf23, Kissl/Kisslr, Kl （Klotho）, Lrp5, Mstn, Neol, Npr2, Ostml, Postn, Sfrp4, S1c30a5, Sic39a13, Sost, Sumf1, Src, Wnt10b）, five novel genes extensively characterized （Cldn18, Fam20c, Lrrkl, Sgpll, Wnt16）, five novel genes with preliminary characterization （Agpat2, RassfS, Slc10a7, Stc26a7, Slc30a10） and three novel undisclosed genes coding for potential osteoporosis drug targets.展开更多
Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compound...Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compounds for dyslipidaemia drug from the chemical library. Methods cDNA encoding the human FXR ligand binding domain （LBD） was amplified by RT-PCR from a human liver total mRNA and fused to the DNA binding domain （DBD） of yeast GAL4 of pBIND to construct a GAL4-FXR （LBD） chimera expression plasmid. Five copies of the GAL4 DNA binding site were synthesized and inserted into upstream of the SV40 promoter of pGL3-promoter vector to construct a reporter plasmid pG5-SV40 Luc. The assay was developed by transient co-transfection with pG5-SV40 Luc reporter plasmid and pBIND-FXR-LBD （189-472） chimera expression plasmid. Results After optimization, CDCA, a FXR natural agonist, could induce expression of the luciferase gene in a dose-dependent manner, and had a signal/noise ratio of 10 and Z＇ factor value of 0.65, Conclusion A stable and sensitive cell-based high-throughput screening model can be used in high-throughput screening for FXR agonists from the synthetic and natural compound library.展开更多
Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite thei...Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite their relevance in diseases and the variety of physiological functions they are involved in, ion channels still remain underexploited as drug targets. This, to a large extent, is attributed to the absence of screening technologies that ensure both the quality and the throughput of data. However, an increasing number of assays and technologies have evolved rapidly in the past decades. In this review, we summarized the currently available high-throughput screening technologies in ion channel drug discovery.展开更多
Efficient parallel screening of combinatorial libraries is one of the most challenging aspects of the high- throughput （HT） heterogeneous catalysis workflow. Today, a number of methods have been used in HT catalyst ...Efficient parallel screening of combinatorial libraries is one of the most challenging aspects of the high- throughput （HT） heterogeneous catalysis workflow. Today, a number of methods have been used in HT catalyst studies, including various optical, mass-spectrometry, and gas- chromatography techniques. Of these, rapid-scanning Fourier-transform infrared （FTIR） imaging is one of the fastest and most versatile screening techniques. Here, the new design of the 16-channel HT reactor is presented and test results for its accuracy and reproducibility are shown. The performance of the system was evaluated through the oxidation of CO over commercial Pd/AI203 and cobalt oxide nanoparticles synthesized with different reducer-reductant molar ratios, surfactant types, metal and surfactant concentrations, synthesis temperatures, and ramp rates.展开更多
The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carb...The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.展开更多
基金financial support from the National Key Research and Development Program of China(2021YFB 3501501)the National Natural Science Foundation of China(No.22225803,22038001,22108007 and 22278011)+1 种基金Beijing Natural Science Foundation(No.Z230023)Beijing Science and Technology Commission(No.Z211100004321001).
文摘The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design platform.High-throughput screening of catalytic performance is feasible since the large MOF structure database is available.In this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition reaction.The descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification criterion.The feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were discovered.Among them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.
基金supported by the National Key Research and Development Program of China(No.2021YFB3702102)support from the“Initiation Program for New Teachers”(No.AF0500207)+1 种基金Shanghai Jiao Tong Universitysupport from the Changsha Science and Technology Plan International and Regional Cooperation Project(No.kh2304002)。
文摘Lithium-ion batteries(LiBs)with high energy density have gained significant popularity in smart grids and portable electronics.LiMn_(1-x)Fe_(x)PO_(4)(LMFP)is considered a leading candidate for the cathode,with the potential to combine the low cost of Li Fe PO_(4)(LFP)with the high theoretical energy density of LiMnPO_(4)(LMP).However,quantitative investigation of the intricate coupling between the Fe/Mn ratio and the resulting energy density is challenging due to the parametric complexity.It is crucial to develop a universal approach for the rapid construction of multi-parameter mapping.In this work,we propose an active learning-guided high-throughput workflow for quantitatively predicting the Fe/Mn ratio and the energy density mapping of LMFP.An optimal composition(LiMn_(0.66)Fe_(0.34)PO_(4))was effectively screened from 81 cathode materials via only 5 samples.Model-guided electrochemical analysis revealed a nonlinear relationship between the Fe/Mn ratio and electrochemical properties,including ion mobility and impedance,elucidating the quantitative chemical composition-energy density map of LMFP.The results demonstrated the efficacy of the method in high-throughput screening of LiBs cathode materials.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11304079,11404094,and 11504088)Science and Technology Research Project of Henan Science and Technology Department(Grant No.182102410076)。
文摘The capture of CO_(2)from CO_(2)/H_(2)gas mixtures in syngas is a crucial issue for hydrogen production from steam methane reforming in industry,as the presence of CO_(2)directly affects the purity of H_(2).A combination of a high-throughput screening method and grand canonical Monte Carlo simulation was utilized to evaluate and screen 1725 metal–organic frameworks(MOFs)in detail as a means of determining their adsorption performance for CO_(2)/H_(2)gas mixtures.The adsorption and separation performance of double-linker MOFs was comprehensively evaluated using eight evaluation indicators,namely,the largest cavity diameter,accessible surface area,pore occupied accessible volume,porosity,adsorption selectivity,working capacity,adsorbent performance score and percent regeneration.Six optimal performance frameworks were screened to further study their single-component adsorption and binary competitive adsorption of CO_(2)/H_(2)respectively.The CO_(2)adsorption selectivity at different CO_(2)/H_(2)feed ratios was also evaluated,which indicated their excellent adsorption and separation performance.The microscopic adsorption mechanisms for CO_(2)and H_(2)at the molecular level were investigated by analyzing the radial distribution function and density distribution.This study may provide directional guidance and reference for subsequent experiments on the adsorption and separation of CO_(2)/H_(2).
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2022R1F1A1074339)。
文摘For the advancement of fast-charging sodium-ion batteries(SIBs),the synthesis of cutting-edge cathode materials with superior structural stability and enhanced Na+diffusion kinetics is imperative.Multiphase layered transition metal oxides(LTMOs),which leverage the synergistic properties of two distinct monophasic LTMOs,have garnered significant attention;however,their efficacy under fast-charging conditions remains underexplored.In this study,we developed a high-throughput computational screening framework to identify optimal dopants that maximize the electrochemical performance of LTMOs.Specifically,we evaluated the efficacy of 32 dopants based on P2/O3-type Mn/Fe-based Na_(x)Mn_(0.5)Fe_(0.5)O_(2)(NMFO)cathode material.Multiphase LTMOs satisfying criteria for thermodynamic and structural stability,minimized phase transitions,and enhanced Na^(+)diffusion were systematically screened for their suitability in fast-charging applications.The analysis identified two dopants,Ti and Zr,which met all predefined screening criteria.Furthermore,we ranked and scored dopants based on their alignment with these criteria,establishing a comprehensive dopant performance database.These findings provide a robust foundation for experimental exploration and offer detailed guidelines for tailoring dopants to optimize fast-charging SIBs.
基金supported by the National Natural Science Foundation of China(Grant Nos.:82373835,82304437,and 82173781)Regional Joint Fund Project of Guangdong Basic and Applied Basic Research Fund,China(Grant Nos.:2023A1515110417 and 2023A1515140131)+2 种基金Regional Joint Fund-Key Project of Guangdong Basic and Applied Basic Research Fund,China(Grant No.:2020B1515120033)the Key Field Projects of General Universities in Guangdong Province,China(Grant Nos.:2020ZDZX2057 and 2022ZDZX2056)Medical Scientific Research Foundation of Guangdong Province of China(Grant No.:A2022061).
文摘Natural antimicrobial peptides(AMPs)are promising candidates for the development of a new generation of antimicrobials to combat antibiotic-resistant pathogens.They have found extensive applications in the fields of medicine,food,and agriculture.However,efficiently screening AMPs from natural sources poses several challenges,including low efficiency and high antibiotic resistance.This review focuses on the action mechanisms of AMPs,both through membrane and non-membrane routes.We thoroughly examine various highly efficient AMP screening methods,including whole-bacterial adsorption binding,cell membrane chromatography(CMC),phospholipid membrane chromatography binding,membranemediated capillary electrophoresis(CE),colorimetric assays,thin layer chromatography(TLC),fluorescence-based screening,genetic sequencing-based analysis,computational mining of AMP databases,and virtual screening methods.Additionally,we discuss potential developmental applications for enhancing the efficiency of AMP discovery.This review provides a comprehensive framework for identifying AMPs within complex natural product systems.
基金financially supported by the National Natural Science Foundation of China(Nos.52301011,52231008,52142304,52177220,52101182 and U23A200767)Hainan Provincial Natural Science Foundation of China(No.524QN226)+2 种基金the Key research and development program of Hainan province(No.ZDYF2022GXJS006)the Starting Research Fund from the Hainan University(No.KYQD(ZR)23026)the International Science&Technology Cooperation Program of Hainan Province(No.GHYF2023007)。
文摘Single-atom catalysts(SACs)have been widely utilized in electrochemical nitrogen reduction reactions(NRR)due to their high atomic utilization and selectivity.Owing to the unique sp/sp^(2)co-hybridization,graphyne materials can offer stable adsorption sites for single metal atoms.To investigate the influence of the sp/sp^(2)hybrid carbon ratio on the electrocatalytic NRR performance of graphyne,a high-throughput screening of 81 catalysts,with27 transition metals loaded on graphyne(GY1),graphdiyne(GY2),and graphtriyne(GY3),was conducted using firstprinciples calculations.The results of the screening revealed that Ti@GY3 exhibits the lowest energy barrier for the rate-determining step(0.32 eV)in NRR.Further,to explore the impact of different sp/sp^(2)-hybridized carbon ratios on the catalytic activity of SACs,the mechanism of nitrogen(N_(2))adsorption,activation,and the comprehensive pathway of NRR on Ti@GY1,Ti@GY2,and Ti@GY3 was systematically investigated.It was found that the ratio of sp/sp^(2)-hybridized carbon can significantly modulate the d-band center of the metal,thus affecting the energy barrier of the rate-determining step in NRR,decreasing from Ti@GY1(0.59 eV)to Ti@GY2(0.49 eV);and further to Ti@GY3(0.32 eV).Additionally,the Hall conductance was found to increase with the bias voltage in the range of 0.4-1 V,as calculated by Nanodcal software,demonstrating an improvement in the conductivity of the SAC.In summary,this work provides theoretical guidance for modulating the electrocatalytic nitrogen reduction activity of SACs by varying the ratio of sp/sp^(2)hybrid carbon,with Ti@GY3 showing potential as an excellent NRR catalyst.
基金supported by the National Natural Science Foundation of China (Nos. 22175078, 52373287, 82404846, and 22467002)the Natural Science Foundation of Jiangsu Province of China (No. BK20241597)the Fundamental Research Funds for the Central Universities (No. 2632024TD05)
文摘Recent years have witnessed significant advances in the development of novel techniques and methodologies for identifying active ingredients in traditional Chinese medicine(TCM),substantially advancing research and development efforts.Spectrum-effect correlation analysis,affinity ultrafiltration,high-content screening(HCS)imaging,and cell membrane chromatography(CMC)have emerged as essential tools,effectively linking TCM chemical constituents to their biological effects,thereby enabling efficient active ingredient screening.Additionally,molecular interaction analysis provides deeper insights into TCM-biomolecule interaction mechanisms,enhancing understanding of its therapeutic potential.Computer-aided techniques facilitate TCM active ingredient identification,optimizing the screening process for efficiency and cost-effectiveness.Molecular probe technology,as an emerging methodology,enables precise and rapid screening for novel therapeutic drug discovery.Ongoing technological advancement in this field indicates promising future developments,potentially leading to more effective and targeted TCM-based therapies.
基金The authors are grateful for financial support from the National Key Projects for Fundamental Research and Development of China(2021YFA1500803)the National Natural Science Foundation of China(51825205,52120105002,22102202,22088102,U22A20391)+1 种基金the DNL Cooperation Fund,CAS(DNL202016)the CAS Project for Young Scientists in Basic Research(YSBR-004).
文摘Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors.
基金supported by the National Key R&D Program of China(2022YFA1503103)the National Natural Science Foundation of China(22033002,92261112,22203046)+2 种基金the Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant No.NY221128)the Six Talent Peaks Project in Jiangsu Province(XCL-104)the open research fund of Key Laboratory of Quantum Materials and Devices(Southeast University)
文摘Understanding the correlation between the fundamental descriptors and catalytic performance is meaningful to guide the design of high-performance electrochemical catalysts.However,exploring key factors that affect catalytic performance in the vast catalyst space remains challenging for people.Herein,to accurately identify the factors that affect the performance of N2 reduction,we apply interpretable machine learning(ML)to analyze high-throughput screening results,which is also suited to other surface reactions in catalysis.To expound on the paradigm,33 promising catalysts are screened from 168 carbon-supported candidates,specifically single-atom catalysts(SACs)supported by a BC_(3)monolayer(TM@V_(B/C)-N_(n)=_(0-3)-BC_(3))via high-throughput screening.Subsequently,the hybrid sampling method and XGBoost model are selected to classify eligible and non-eligible catalysts.Through feature interpretation using Shapley Additive Explanations(SHAP)analysis,two crucial features,that is,the number of valence electrons(N_(v))and nitrogen substitution(N_(n)),are screened out.Combining SHAP analysis and electronic structure calculations,the synergistic effect between an active center with low valence electron numbers and reasonable C-N coordination(a medium fraction of nitrogen substitution)can exhibit high catalytic performance.Finally,six superior catalysts with a limiting potential lower than-0.4 V are predicted.Our workflow offers a rational approach to obtaining key information on catalytic performance from high-throughput screening results to design efficient catalysts that can be applied to other materials and reactions.
基金the National Natural Science Foundation of China(Nos.81930112 and 82225048)Open Research Fund of the School of Chemistry and Chemical Engineering,Henan Normal University for support(No.2021YB07)Research on National Reference Material and Product Development of Natural Products(No.SG030801,Beijing Polytechnic)。
文摘Tuberculosis(TB)is a chronic infectious disease,which is caused by the pathogen Mycobacterium tuberculosis(Mtb)and reemerged as a global health risk with a significant proportion of multi-drug resistant and extensively drug resistant TB cases.It is very urgent to find some novel high-confidence drug targets in Mtb for discovering the effective anti-TB agents.Thioredoxin reductase(TrxR)has been identified to be a highly viable target for anti-TB drugs for its important role in protecting the pathogen from thiol-specific oxidizing stress,regulating intracellular dithiol/disulfide homeostasis and DNA replication and repair.In the present work,a near-infrared(NIR)fluorescent probe DDAT was developed for the detection of TrxR activity and used to high-throughput screen the TrxR inhibitors from natural products.Two screened TrxR inhibitors from Sappan Lignum and microbial metabolites that were further used to inhibit Mycobacterium tuberculosis.All the results indicate that DDAT is a practical fluorescent molecular tool for the discovery of potential anti-TB drugs.
文摘Gastric cancers are caused primarily due to the activation and amplification of the EGFR or HER2 kinases resulting in cell proliferation,adhesion,angiogenesis,and metastasis.Conventional therapies are ineffective due to the intra-tumoral heterogeneity and concomitant genetic mutations.Hence,dual inhibition strategies are recommended to increase potency and reduce cytotoxicity.In this study,we have conducted computational high-throughput screening of the ChemBridge library followed by in vitro assays and identified novel selective inhibitors that have a dual impediment of EGFR/HER2 kinase activities.Diversity-based High-throughput Virtual Screening(D-HTVS)was used to screen the whole ChemBridge small molecular library against EGFR and HER2.The atomistic molecular dynamic simulation was conducted to understand the dynamics and stability of the protein-ligand complexes.EGFR/HER2 kinase enzymes,KATOIII,and Snu-5 cells were used for in vitro validations.The atomistic Molecular Dynamics simulations followed by solvent-based Gibbs binding free energy calculation of top molecules,identified compound C3(5-(4-oxo-4H-3,1-benzoxazin-2-yl)-2-[3-(4-oxo-4H-3,1-benzoxazin-2-yl)phenyl]-1H-isoindole-1,3(2H)-dione)to have a good affinity for both EGFR and HER2.The predicted compound,C3,was promising with better binding energy,good binding pose,and optimum interactions with the EGFR and HER2 residues.C3 inhibited EGFR and HER2 kinases with IC50 values of 37.24 and 45.83 nM,respectively.The GI50 values of C3 to inhibit KATOIII and Snu-5 cells were 84.76 and 48.26 nM,respectively.Based on these findings,we conclude that the identified compound C3 showed a conceivable dual inhibitory activity on EGFR/HER2 kinase,and therefore can be considered as a plausible lead-like molecule for treating gastric cancers with minimal side effects,though testing in higher models with pharmacokinetic approach is required.
基金funded by the National Key Research and Development Program of China(2022YFD1201600)the earmarked fund for the China Agriculture Research System(CARS-26)+1 种基金the Fundamental Research Funds for the Central Universities,China(SWU-XDJH202308)the Science and Technology Research Program of Chongqing Municipal Education Commission,China(KJQN202001418)。
文摘One of the main diseases that adversely impacts the global citrus industry is citrus bacterial canker(CBC),caused by the bacteria Xanthomonas citri subsp.citri(Xcc).Response to CBC is a complex process,with both proteinDNA as well as protein–protein interactions for the regulatory network.To detect such interactions in CBC resistant regulation,a citrus high-throughput screening system with 203 CBC-inducible transcription factors(TFs),were developed.Screening the upstream regulators of target by yeast-one hybrid(Y1H)methods was also performed.A regulatory module of CBC resistance was identified based on this system.One TF(CsDOF5.8)was explored due to its interactions with the 1-kb promoter fragment of CsPrx25,a resistant gene of CBC involved in reactive oxygen species(ROS)homeostasis regulation.Electrophoretic mobility shift assay(EMSA),dual-LUC assays,as well as transient overexpression of CsDOF5.8,further validated the interactions and transcriptional regulation.The CsDOF5.8–CsPrx25 promoter interaction revealed a complex pathway that governs the regulation of CBC resistance via H2O2homeostasis.The high-throughput Y1H/Y2H screening system could be an efficient tool for studying regulatory pathways or network of CBC resistance regulation.In addition,it could highlight the potential of these candidate genes as targets for efforts to breed CBC-resistant citrus varieties.
文摘Barrett's esophagus(BE) is a change in the esophageal lining and is known to be the major precursor lesion for most cases of esophageal adenocarcinoma(EAC).Despite an understanding of its association with BE for many years and the falling incidence rates of squamous cell carcinoma of the esophagus, the incidence for EAC continues to rise exponentially. In association with this rising incidence, if the delay in diagnosis of EAC occurs after the onset of symptoms,then the mortality at 5 years is greater than 80%. Appropriate diagnosis and surveillance strategies are therefore vital for BE. Multiple novel optical technologies and other advanced approaches are being utilized to assist in making screening and surveillance more cost effective. We review the current guidelines and evolving techniques that are currently being evaluated.
基金Supported by Partially funded by FESR P.O.Apulia Region 2007-2013-Action 1.2.4,No.3Q5AX31
文摘Effective prevention and management of osteoporosis would require suitable methods for population screenings and early diagnosis. Current clinicallyavailable diagnostic methods are mainly based on the use of either X-rays or ultrasound(US). All X-ray based methods provide a measure of bone mineral density(BMD), but it has been demonstrated that other structural aspects of the bone are important in determining fracture risk, such as mechanical features and elastic properties, which cannot be assessed using densitometric techniques. Among the most commonly used techniques, dual X-ray absorptiometry(DXA) is considered the current 'gold standard' for osteoporosis diagnosis and fracture risk prediction. Unfortunately, as other X-ray based techniques, DXA has specific limitations(e.g., use of ionizing radiation, large size of the equipment, high costs, limited availability) that hinder its application for population screenings and primary care diagnosis. This has resulted in an increasing interest in developing reliable pre-screening tools for osteoporosis such as quantitative ultrasound(QUS) scanners, which do not involve ionizing radiation exposure and represent a cheaper solution exploiting portable and widely available devices. Furthermore, the usefulness of QUS techniques in fracture risk prediction has been proven and, with the last developments, they are also becoming a more and more reliable approach for assessing bone quality. However, the US assessment of osteoporosis is currently used only as a pre-screening tool, requiring a subsequent diagnosis confirmation by means of a DXA evaluation. Here we illustrate the state of art in the early diagnosis of this 'silent disease' and show up recent advances for its prevention and improved management through early diagnosis.
基金the Science Challenge Project(TZ2018004)the National Natural Science Foundation of China(21875228 and 21702195)for financial support。
文摘Finding energetic materials with tailored properties is always a significant challenge due to low research efficiency in trial and error.Herein,a methodology combining domain knowledge,a machine learning algorithm,and experiments is presented for accelerating the discovery of novel energetic materials.A high-throughput virtual screening(HTVS)system integrating on-demand molecular generation and machine learning models covering the prediction of molecular properties and crystal packing mode scoring is established.With the proposed HTVS system,candidate molecules with promising properties and a desirable crystal packing mode are rapidly targeted from the generated molecular space containing 25112 molecules.Furthermore,a study of the crystal structure and properties shows that the good comprehensive performances of the target molecule are in agreement with the predicted results,thus verifying the effectiveness of the proposed methodology.This work demonstrates a new research paradigm for discovering novel energetic materials and can be extended to other organic materials without manifest obstacles.
文摘Screening gene function in vivo is a powerful approach to discover novel drug targets. We present high-throughput screening （HTS） data for 3 762 distinct global gene knockout （KO） mouse lines with viable adult homozygous mice generated using either gene-trap or homologous recombination technologies. Bone mass was determined from DEXA scans of male and female mice at 14 weeks of age and by microCT analyses of bones from male mice at 16 weeks of age. Wild-type （WT） cagemates/littermates were examined for each gene KO. Lethality was observed in an additional 850 KO lines. Since primary HTS are susceptible to false positive findings, additional cohorts of mice from KO lines with intriguing HTS bone data were examined. Aging, ovariectomy, histomorphometry and bone strength studies were performed and possible non-skeletal phenotypes were explored. Together, these screens identified multiple genes affecting bone mass： 23 previously reported genes （Calcr, Cebpb, Crtap, Dcstamp, Dkkl, Duoxa2, Enppl, Fgf23, Kissl/Kisslr, Kl （Klotho）, Lrp5, Mstn, Neol, Npr2, Ostml, Postn, Sfrp4, S1c30a5, Sic39a13, Sost, Sumf1, Src, Wnt10b）, five novel genes extensively characterized （Cldn18, Fam20c, Lrrkl, Sgpll, Wnt16）, five novel genes with preliminary characterization （Agpat2, RassfS, Slc10a7, Stc26a7, Slc30a10） and three novel undisclosed genes coding for potential osteoporosis drug targets.
基金supported by the Ministry of Science and Technology, PRC in Mega-projects of Science Research During the 10th Five-Year Plan Period (No. 2004AA2Z38784)National Natural Science Foundation of China (No. 30472026).
文摘Objective To develop a high-throughput screening assay for Farnesoid X receptor （FXR） agonists based on mammalian one-hybrid system （a chimera receptor gene system） for the purpose of identifying new lead compounds for dyslipidaemia drug from the chemical library. Methods cDNA encoding the human FXR ligand binding domain （LBD） was amplified by RT-PCR from a human liver total mRNA and fused to the DNA binding domain （DBD） of yeast GAL4 of pBIND to construct a GAL4-FXR （LBD） chimera expression plasmid. Five copies of the GAL4 DNA binding site were synthesized and inserted into upstream of the SV40 promoter of pGL3-promoter vector to construct a reporter plasmid pG5-SV40 Luc. The assay was developed by transient co-transfection with pG5-SV40 Luc reporter plasmid and pBIND-FXR-LBD （189-472） chimera expression plasmid. Results After optimization, CDCA, a FXR natural agonist, could induce expression of the luciferase gene in a dose-dependent manner, and had a signal/noise ratio of 10 and Z＇ factor value of 0.65, Conclusion A stable and sensitive cell-based high-throughput screening model can be used in high-throughput screening for FXR agonists from the synthetic and natural compound library.
基金supported by the State Key Laboratory of Natural and Biomimetic Drugs, Peking University。
文摘Ion channels are attractive targets for drug discovery as an increasing number of new ion channel targets have been uncovered in diseases, such as pain, cardiovascular disease, and neurological disorders. Despite their relevance in diseases and the variety of physiological functions they are involved in, ion channels still remain underexploited as drug targets. This, to a large extent, is attributed to the absence of screening technologies that ensure both the quality and the throughput of data. However, an increasing number of assays and technologies have evolved rapidly in the past decades. In this review, we summarized the currently available high-throughput screening technologies in ion channel drug discovery.
基金the South Carolina Smart State Center for Strategic Approaches to the Generation of Electricity (SAGE) for funding
文摘Efficient parallel screening of combinatorial libraries is one of the most challenging aspects of the high- throughput （HT） heterogeneous catalysis workflow. Today, a number of methods have been used in HT catalyst studies, including various optical, mass-spectrometry, and gas- chromatography techniques. Of these, rapid-scanning Fourier-transform infrared （FTIR） imaging is one of the fastest and most versatile screening techniques. Here, the new design of the 16-channel HT reactor is presented and test results for its accuracy and reproducibility are shown. The performance of the system was evaluated through the oxidation of CO over commercial Pd/AI203 and cobalt oxide nanoparticles synthesized with different reducer-reductant molar ratios, surfactant types, metal and surfactant concentrations, synthesis temperatures, and ramp rates.
基金supported by the Natural Science Foundation of China (Nos.21706106,21536001 and 21322603)the National Key Basic Research Program of China ("973") (No.2013CB733503)+1 种基金the Natural Science Foundation of Jiangsu Normal University(16XLR011)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.
