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Design Principles and Mechanistic Understandings of Non-Noble-Metal Bifunctional Electrocatalysts for Zinc-Air Batteries

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Nano-Micro Letters 2024年第9期16卷 13-48页

作者： Yunnan Gao Ling Liu Yi Jiang Dexin Yu xiaomei Zheng Jiayi Wang Jingwei Liu Dan Luo Yongguang Zhang Zhenjia Shi Xin Wang Ya‑Ping deng Zhongwei Chen Power Battery and Systems Research Center State Key Laboratory of CatalysisDalian Institute of Chemical PhysicsDalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023People’s Republic of China Department of Chemical Engineering University of WaterlooWaterlooON N2L 3G1Canada Institute of Carbon Neutrality Zhejiang Wanli UniversityNingbo 315100People’s Republic of China College of Materials and Chemistry China Jiliang UniversityHangzhou 310018People’s Republic of China

Zinc-air batteries(ZABs)are promising energy storage systems because of high theoretical energy density,safety,low cost,and abundance of zinc.However,the slow multi-step reaction of oxygen and heavy reliance on noble-metal catalysts hinder the practical applications of ZABs.Therefore,feasible and advanced non-noble-metal elec-trocatalysts for air cathodes need to be identified to promote the oxygen catalytic reaction.In this review,we initially introduced the advancement of ZABs in the past two decades and provided an overview of key developments in this field.Then,we discussed the work-ing mechanism and the design of bifunctional electrocatalysts from the perspective of morphology design,crystal structure tuning,interface strategy,and atomic engineering.We also included theoretical studies,machine learning,and advanced characterization technologies to provide a comprehensive understanding of the structure-performance relationship of electrocatalysts and the reaction pathways of the oxygen redox reactions.Finally,we discussed the challenges and prospects related to designing advanced non-noble-metal bifunctional electrocatalysts for ZABs.

关键词： Zinc-air batteries Bifunctional electrocatalysts Design principles Mechanistic understandings

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Prediction of Molecular Conformation Using Deep Generative Neural Networks

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Chinese Journal of Chemistry 2023年第24期41卷 3684-3688页

作者： Congsheng Xu Yi Lu xiaomei deng Peiyuan Yu School of Chemistry and Chemical Engineering Harbin Institute of TechnologyHarbinHeilongjiang150001 China Department of Chemistry and Shenzhen Grubbs Institute Guangdong Provincial Key Laboratory of CatalysisSouthern University of Science and TechnologyShenzhenGuangdong518055 China

The accurate prediction of molecular conformations with high efficiency is crucial in various fields such as materials science,computational chemistry and computer-aided drug design,as the three-dimensional structures accessible at a given condition usually determine the specific physical,chemical,and biological properties of a molecule.Traditional approaches for the conformational sampling of molecules such as molecular dynamics simulations and Markov chain Monte Carlo methods either require an exponentially increasing amount of time as the degree of freedom of the molecule increases or suffer from systematic errors that fail to obtain important conformations,thus presenting significant challenges for conformation sampling with both high efficiency and high accuracy.Recently,deep learning-based generative models have emerged as a promising solution to this problem.These models can generate a large number of molecular conformations in a short time,and their accuracy is comparable and,in some cases,even better than that of current popular open-source and commercial software.This Emerging Topic introduces the recent progresses of using deep learning for predicting molecular conformations and briefly discusses the potential and challenges of this emerging field.

关键词： Conformation generation Machine learning Deep Generative Neural Networks Drug design Reaction mechanisms

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限定域关系抽取技术研究综述

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计算机科学 2024年第1期51卷 252-265页

作者：侯景邓晓梅汉鹏武中国科学院空间应用工程与技术中心北京100094 中国科学院大学北京100094

限定域关系抽取技术是在预定义实体类型和关系类型的前提下,从文本中捕获关键信息的技术,多采用由头尾实体和关系构成的三元组作为信息表示形式。作为信息抽取领域的重要研究方向之一,其在知识问答、信息检索等任务中被广泛应用。文中... 详细信息

限定域关系抽取技术是在预定义实体类型和关系类型的前提下,从文本中捕获关键信息的技术,多采用由头尾实体和关系构成的三元组作为信息表示形式。作为信息抽取领域的重要研究方向之一,其在知识问答、信息检索等任务中被广泛应用。文中在介绍相关概念和任务范式的基础上,分析了深度学习背景下限定域关系抽取任务的研究进展,根据句中实体是否可见,分为关系分类任务和三元组抽取任务,依据任务表现特征,前者可细分为有监督条件下的关系分类任务、小样本关系分类任务和远程监督条件下的关系分类任务。文中探讨和分析了以上任务中常用的技术方法及其优缺点,最后归纳总结了关系抽取技术在低资源、多模态等更为接近真实情景下的发展潜力和现存的挑战。

关键词：限定域关系抽取深度学习关系分类三元组远程监督

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Lambda-cyhalothrin disrupts the up-regulation effect of 17β-estradiol on post-synaptic density 95 protein expression via estrogen receptor α-dependent Akt pathway

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Journal of Environmental Sciences 2016年第3期28卷 252-260页

作者： Qunan Wang Xin Xia xiaomei deng Nian Li Daji Wu Long Zhang Chengwei Yang Fangbiao Tao Jiangning Zhou Chinese Academy of Science Key Laboratory of Brain Function and Diseases School of Life SciencesUniversity of Science and Technology of China Department of Toxicology College of Public HealthAnhui Medical University Department of Pharmacy Affiliated Anhui Provincial HospitalAnhui Medical University Department of Maternal and Child health College of Public HealthAnhui Medical University

Lambda-cyhalothrin（LCT）,one of the type II pyrethroids,has been widely used throughout the world.The estrogenic effect of LCT to increase cell proliferation has been well established.However,whether the estrogenic effect of LCT will influence neurodevelopment has not been investigated.In addition,17β-Estradiol（E2）plays a crucial role in neurodevelopment and induces an increase in synaptic proteins.The post-synaptic density 95（PSD95）protein,which is involved in the development of the structure and function of new spines and localized with estrogen receptor α（ERα）at the post-synaptic density（PSD）,was detected in our study by using hippocampal neuron cell line HT22.We found that LCT up-regulated PSD95 and ERα expression,estrogen receptor（ER）antagonist ICI182,780 and phosphatidylinositol-4;5-bisphosphate 3-kinase（PI3K）inhibitor LY294,002 blocked this effect.In addition,LCT disrupted the promotion effect of E2 on PSD95.To investigate whether the observed changes are caused by ERα-dependent signaling activation,we next detected the effects of LCT on the ERα-mediated PI3K-Protein kinase B（PKB/Akt）-eukaryotic initiation factor（e IF）4E-binding protein 1（4E-BP1）pathway.There existed an activation of Akt and the downstream factor 4E-BP1 after LCT treatment.In addition,LCT could disrupt the activation effect of E2 on the Akt pathway.However,no changes in c AMP response element-binding protein（CREB）activation and PSD95 messenger ribonucleic acid（m RNA）were observed.Our findings demonstrated that LCT could increase the PSD95 protein level via the ERα-dependent Akt pathway,and LCT might disrupt the up-regulation effect of E2 on PSD95 protein expression via this signaling pathway.

关键词： 17β-Estradiol Akt pathway Interference Lambda-cyhalothrin Post-synaptic density 95

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Machine learning and high-throughput computational screening of hydrophobic metal–organic frameworks for capture of formaldehyde from air

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Green Energy & Environment 2021年第5期6卷 759-770页

作者： Xueying Yuan xiaomei deng Chengzhi Cai Zenan Shi Hong Liang Shuhua Li Zhiwei Qiao Guangzhou Key Laboratory for New Energy and Green Catalysis School of Chemistry and Chemical EngineeringGuangzhou UniversityGuangzhou510006China

Aiming to efficiently capture the formaldehyde(HCHO)with low content in the air exceeding the standard,31,399 hydrophobic metal–organic frameworks(MOFs)were first selected from 137,953 hypothetical MOFs to calculate their formaldehyde adsorption performance,namely,adsorption capacity(NHCHO)and selectivity(SHCHO=N^(2+)O_(2))by molecular simulation and machine learning(ML).To combine the SHCHO=N^(2+)O_(2) and NHCHO,a new performance metric,the tradeoff between selectivity and capacity(TSC)was proposed to identify more reasonably the top-performing MOFs.The MOFs were divided into three datasets(i.e.,all of the MOFs(AM),MOFs with top 5%of SHCHO=N^(2+)O_(2)(PS)and MOFs with top 5%of NHCHO(PN))to scrutinize and explore the characteristics of different materials capturing formaldehyde from the air(N2 and O_(2)).Furthermore,after four ML algorithms(the back propagation neural network(BPNN),support vector machine(SVM),extreme learning machine(ELM),and random forest(RF))are applied to quantitatively assess the prediction effects of performance indexes in different datasets,RF algorithm with the most accurate prediction revealed that the TSC has strong correlations with the MOF descriptors in PS dataset.In view of 14.10%of the promising MOFs occupied PN,the design paths of excellent adsorbents for six MOF descriptors were quantitatively determined,especially for the Henry's coefficient(KHCHO)and heat of adsorption of formaldehyde(Q0 st).Their probabilities of obtaining excellent MOFs could reach 100%and 77.42%,respectively,and both the relative importance and the trends of univariate analysis coherently confirm the important positions of KHCHO and Q0 st.Finally,20 best MOFs were identified for the single-step separation of formaldehyde with low concentration.The microscopic insights and structure-performance relationship predictions from this computational and ML study are useful toward the development of new MOFs for the capture of formaldehyde from air.

关键词： Molecular simulation Adsorption Metal–organic framework Formaldehyde

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米老排优树组培技术体系优化研究

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南京林业大学学报（自然科学版） 2024年第2期48卷 69-78页

作者：孙旭高陶家璐谢微石洁张宝津邓小梅华南农业大学林学与风景园林学院广东省森林植物种质创新与应用重点实验室广东广州510642

【目的】建立米老排(Mytilaria laosensis)优良单株组培再生体系,为今后其无性化推广提供技术支撑。【方法】以米老排优树基部半木质化萌芽为外植体,采用丛芽发生途径,通过初代腋芽诱导、继代增殖培养、生根培养等过程,研究筛选最适的... 详细信息

【目的】建立米老排(Mytilaria laosensis)优良单株组培再生体系,为今后其无性化推广提供技术支撑。【方法】以米老排优树基部半木质化萌芽为外植体,采用丛芽发生途径,通过初代腋芽诱导、继代增殖培养、生根培养等过程,研究筛选最适的外植体采集时间、继代及生根培养的基本培养基以及植物生长调节剂的种类及浓度配比等。【结果】10月采集的外植体诱导效果最好,存活率为32.38%;米老排腋芽诱导最适配方为MS+6-BA 0.5 mg/L+NAA 0.02 mg/L,诱导率为100%,萌发时间为4.07 d;最适增殖培养基为MX(改良WPM)+6-BA 1.0 mg/L+NAA 0.05 mg/L,增殖系数达4.94,芽生长旺盛;最适生根培养基为MX+NAA 0.3 mg/L,生根率100%,平均根数13.18,根生长健壮,移栽成活率可达92.3%。【结论】米老排外植体诱导成活率与取材地点、时间相关,广东地区10月的米老排外植体材料最佳;在使用MS基本培养基增殖系数低的情况下,改用MX(改良WPM)培养基能够显著提高米老排增殖继代倍数;本研究还对米老排诱导培养基、增殖培养基、生根培养基进行了优化,有助于建立米老排优树组培体系,有效提高组培质量和效率。

关键词：米老排基本培养基丛生芽组织培养

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任豆组培再生研究

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林业与环境科学 2024年第2期40卷 122-127页

作者：张晓明邓小梅华南农业大学林学与风景园林学院/广东省森林植物种质创新与应用重点实验室广东广州510642 广州崇耀企业管理顾问有限公司广东广州510700

为完善任豆Zenia insignis组培快繁技术,研究采用微枝扦插的组培再生方式,探讨了基本培养基中NO-3、K+、Ca2+不同含量,以及不同植物生长调节剂种类与浓度对任豆组培芽增殖与生根效果的影响,结果表明:(1)任豆种子用75%酒精、0.1%升汞分... 详细信息

为完善任豆Zenia insignis组培快繁技术,研究采用微枝扦插的组培再生方式,探讨了基本培养基中NO-3、K+、Ca2+不同含量,以及不同植物生长调节剂种类与浓度对任豆组培芽增殖与生根效果的影响,结果表明:(1)任豆种子用75%酒精、0.1%升汞分别浸泡灭菌10,30 min,再用始温为85℃无菌水浸种24 h效果最好,种子萌芽快,种子发芽率可达92.16%;(2)RD基本培养基中NO^(-)_(3)、K^(+)、Ca^(2+)含量分别以600,360,330mg/L为最优配比,最佳继代培养基配比为RD+6-BA 0.2 mg/L+NAA 0.01 mg/L,20 d增殖系数可达3.32;(3)NAA对任豆组培芽生根以及生长有极显著的影响,最佳生根培养基配比为1/2 MS+NAA 0.5 mg/L+AC 1.0 g/L,生根率可达100%,且根系粗壮发达,组培苗生长健壮,叶片浓绿舒展。

关键词：任豆组培微枝扦插

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3种芒果品种不同成熟度的营养指标聚类和主成分分析

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现代食品科技 2024年第6期40卷 198-205页

作者：邓浩吴广陈小妹郭莉尹青春海南省热带果蔬冷链研究重点实验室农业农村部热带果蔬遗传资源评价利用重点实验室(部省共建)海南省农业科学院农产品加工设计研究所海南海口571100 国家市场监管重点实验室(热带果蔬质量与安全) 海南省食品检验检测中心海南海口570311

芒果为呼吸跃变型水果,不同采收成熟度的芒果色泽、理化、营养指标差异较大。该实验在对3种不同成熟度的贵妃(GF)、台农(TN)和金煌(JH)芒果主要品质指标对比的基础上,利用聚类分析和主成分分析对其进行了综合评价。结果表明:GF和JH芒果... 详细信息

芒果为呼吸跃变型水果,不同采收成熟度的芒果色泽、理化、营养指标差异较大。该实验在对3种不同成熟度的贵妃(GF)、台农(TN)和金煌(JH)芒果主要品质指标对比的基础上,利用聚类分析和主成分分析对其进行了综合评价。结果表明:GF和JH芒果综合色泽指数为-0.01到-0.35,说明果皮以绿色为主,转色不如TN芒果明显。3种芒果在成熟过程中硬度分别降低了56.05%,48.58%,69.69%。可滴定酸分别降低了30.61%,61.29%,85.06%,而可溶性固形物、pH值、固酸比则逐渐增大。起主导作用的糖是蔗糖,主导有机酸为柠檬酸、己二酸、丁二酸,主导氨基酸为丙氨酸、谷氨酰胺、赖氨酸、精氨酸、天冬氨酸。对以上15个关键品质指标进行聚类分析将其可分为3类。主成分分析表明:3个主成分代表了以上指标的91.361%的信息。进一步的数学模型评价表明:十成熟的芒果综合品质排序为:GF>TN>JH。因此,十成熟的GF芒果品质最佳,且比九成熟的GF芒果综合得分提升了154.29%,适宜做“树上熟”农场采摘体验项目主推品种。

关键词：成熟度芒果营养主成分分析品质

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跨境电商赋能珠海市外贸转型升级的战略研究

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对外经贸实务 2024年第2期42卷 53-58页

作者：邓宁君李晓媚广东理工学院肇庆526100

珠海市是粤港澳大湾区的经济枢纽之一,为了推动珠海市对外贸易的高质量发展,珠海市政府实施了多项促进外贸转型升级的措施,发展跨境电商是重要举措之一。立足珠海现有的产业结构,珠海市大力发展跨境电商具有重要意义。通过引进头部跨境... 详细信息

珠海市是粤港澳大湾区的经济枢纽之一,为了推动珠海市对外贸易的高质量发展,珠海市政府实施了多项促进外贸转型升级的措施,发展跨境电商是重要举措之一。立足珠海现有的产业结构,珠海市大力发展跨境电商具有重要意义。通过引进头部跨境电商平台,传统外贸企业借助跨境电商完成转型升级,在复杂多变的全球贸易新格局下,实现珠海市对外贸易的高质量发展。文章分析了珠海市外贸的现状、跨境电商发展情况以及跨境电商对珠海外贸转型升级的影响,提出针对性的对策建议以供参考。

关键词：跨境电商外贸转型开放经济

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Nitrification performance evaluation of activated sludge under high potassium ion stress during high-ammonia nitrogen organic wastewater treatment

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Journal of Environmental Sciences 2022年第1期34卷 84-92页

作者： xiaomei Jiang Heng Wang PeikeWu Hong Wang Liangwei deng Wenguo Wang Key Laboratory of Development and Application of Rural Renewable Energy Biogas Institute of Ministry of Agriculture and Rural AffairsChengdu 610041China Sichuan Academy of Environmental Policy and Planning Chengdu 610041China Institute of Urban Agriculture Chinese Academy of Agricultural SciencesChengdu 610213China

The recycling reverse osmosis(RO)membrane concentrate of some high-ammonia nitrogen(NH_(4)^(+)-N)organic wastewater to the biological unit could cause potassium ion(K^(+))accumulation,thereby affecting the removal of NH_(4)^(+)-N by activated sludge.Thus,the effects of high K^(+) stress on activated sludge nitrification performance was studied.The results showed that the high K^(+) stress promoted the floc sludge to produce more extracellular polymers(EPS),which accelerated the sludge sedimentation and enriched the biomass in sequential batch reactors(SBRs).The ammonia oxidation process and nitrite(NO_(2)^(-)-N)oxidation process were further analyzed in the nitrification process.High K^(+) stress enriched ammonia oxidizing bacteria(AOB),which ensured the efficient ammonia oxidation process in SBRs,and ensured the removal rate of NH_(4)^(+)-N was maintained above 93%.However,high K^(+) stress(15g/L KCl)inhibited the activity of NO_(2)^(-)-N oxidizing bacteria(NOB)and reduced the abundance of NOB,thus leading to the accumulation of NO_(2)^(-)-N,and finally worsened the nitrification performance of activated sludge.In short,the performance of activated sludge will not be inhibited when the K^(+) in the wastewater does not exceed 5.23 g/L.The results could provide a reference for the optimization of the biological performance in treating high-NH_(4)^(+)-N organic wastewater with activated sludge coupled RO membrane treatment process.

关键词： Potassium ion(K^(+)) Activated sludge Nitrification High-ammonia nitrogen organic wastewater Microbial community

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