Conference: Artificial Intelligence for Multidisciplinary Exploration and Discovery (AIMED) in Heterogeneous Catalysis: A Workshop

会议:多相催化中的多学科探索和发现人工智能(AIMED):研讨会

基本信息

项目摘要

The Artificial Intelligence for Multidisciplinary Exploration and Discovery in Heterogeneous Catalysis Workshop (AIMED CWS) is co-organized by Hongliang Xin (Virginia Tech), John Kitchin (Carnegie Mellon University), Neil Schweitzer (Northwestern University), and Núria López (Institute of Chemical Research of Catalonia). This workshop explores the evolving role of AI for accelerating scientific exploration and discovery in heterogeneous catalysis. Special emphasis is placed on the multidisciplinary nature of AI endeavors in tackling the complexities underpinning catalytic processes at interfaces and material behaviors under relevant conditions. The primary objectives are to evaluate AI’s current state in this field and to identify challenges and potential growth opportunities. The workshop will delve deep into the intersection of AI and catalysis and will cover a broad spectrum of topics from AI’s historical development in catalysis and recent advancements in algorithms for the rise of self-driving labs, to the intricacies and best practices in data management, sharing, utilization, and repurposing. This workshop is committed to a bold vision for AI in heterogeneous catalysis, highlighting the integration of AI across the research spectrum, in educational and workforce training settings, and in practical applications.The AIMED CWS will unite students, early-career researchers, and senior-level technical experts from academe, industry, and national laboratories to investigate the opportunities and challenges in leveraging AI to expedite scientific exploration and discovery. Heterogeneous catalysis plays a vital role in a wide array of chemical synthesis and manufacturing processes, particularly in the growing fields of clean energy and sustainable chemical technologies. The diverse and intricate nature of catalytic environments, encompassing interfacial processes and material design challenges, often eludes traditional experimental or purely theoretical approaches. AI has emerged as a comprehensive suite of methods that, when combined with experimental and computational strategies, significantly enhances catalyst development across synthesis, characterization, to deployment. The workshop will unfold in three phases: 1) Community Engagement, gathering insights and recommendations from the catalysis community; 2) In-Person Workshop, featuring keynote lectures, panel discussions, and poster presentations by early career researchers to explore AI’s role in catalysis; and 3) Follow-Up Activities, focusing on creating and disseminating educational materials, including an AIMED Webinar Series in Catalysis. Collectively, the AIMED CWS will engage a broad catalysis research community in discussions and hands-on sessions, encouraging multidisciplinary collaborations that drive the field towards new horizons in the age of AI.This workshop is jointly funded by ENG/CBET and MPS/CHE.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
多相催化多学科探索与发现人工智能研讨会(AIMED CWS)由辛洪亮(弗吉尼亚理工大学)、John Kitchin(卡内基梅隆大学)、Neil Schweitzer(西北大学)和 Núria López(化学研究所)共同组织加泰罗尼亚研究)本研讨会探讨了人工智能在加速多相催化科学探索和发现方面的不断发展的作用。重点关注人工智能在解决相关条件下界面催化过程和材料行为的复杂性方面的多学科性质,主要目标是评估人工智能在该领域的现状,并确定挑战和潜在的增长机会。深入研究人工智能和催化的交叉点,涵盖广泛的主题,从人工智能在催化方面的历史发展和自动驾驶实验室兴起的算法的最新进展,到数据的复杂性和最佳实践该研讨会致力于实现人工智能在异质催化领域的大胆愿景,强调人工智能在整个研究领域、教育和劳动力培训环境以及实际应用中的整合。AIMED CWS 将联合起来。来自学术界、工业界和国家实验室的学生、早期职业研究人员和高级技术专家共同研究利用人工智能加速科学探索和发现的机遇和挑战。多相催化在广泛的领域中发挥着至关重要的作用。一系列化学合成和制造工艺,特别是在不断发展的清洁能源和可持续化学技术领域,催化环境的多样性和复杂性,包括界面过程和材料设计挑战,往往难以解决传统的实验或纯理论方法的问题。作为一套综合方法,与实验和计算策略相结合,可以显着增强从合成、表征到部署的催化剂开发。研讨会将分三个阶段进行:1) 社区参与,收集催化社区的见解和建议; 2)面对面研讨会,由早期职业研究人员进行主题演讲、小组讨论和海报展示,探讨人工智能在催化中的作用;3) 后续活动,重点是创建和传播教育材料,包括 AIMED 催化网络研讨会系列。总的来说,AIMED CWS 将让广泛的催化研究界参与讨论和实践会议,鼓励多学科合作,推动该领域在人工智能时代迈向新视野。本次研讨会由共同资助由 ENG/CBET 和 MPS/CHE 颁发。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Hongliang Xin其他文献

Ophthalmic Delivery of Brinzolamide by Liquid Crystalline Nanoparticles: In Vitro and In Vivo Evaluation
液晶纳米颗粒布林佐胺的眼科给药:体外和体内评价
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    3.3
  • 作者:
    Weijun Wu;Jing Li;Lin Wu;Baoyan Wang;Zhongyuan Wang;Qunwei Xu;Hongliang Xin
  • 通讯作者:
    Hongliang Xin
A potential carrier based on liquid crystal nanoparticles for ophthalmic delivery of pilocarpine nitrate.
一种基于液晶纳米粒子的潜在载体,用于硝酸毛果芸香碱的眼科递送。
  • DOI:
    10.1016/j.ijpharm.2013.07.057
  • 发表时间:
    2013-10-15
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jing Li;Lin Wu;Weijun Wu;Baoyan Wang;Zhongyuan Wang;Hongliang Xin;Qunwei Xu
  • 通讯作者:
    Qunwei Xu
Toward a stable and active catalyst for proton-exchange membrane water electrolysis
用于质子交换膜水电解的稳定且活性的催化剂
  • DOI:
    10.1016/j.checat.2023.100869
  • 发表时间:
    2024-01-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Siwen Wang;Liping Liu;Hongliang Xin;Chen Ling
  • 通讯作者:
    Chen Ling
Enhanced anti-tumor effect of 9-nitro-camptothecin complexed by hydroxypropyl-β-cyclodextrin and safety evaluation.
羟丙基-β-环糊精复合9-硝基喜树碱的增强抗肿瘤作用及安全性评价。
  • DOI:
    10.1016/j.ijpharm.2011.05.056
  • 发表时间:
    2011-08-30
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ye Jiang;Xinyi Jiang;K. Law;Yanzuo Chen;Jijin Gu;Wei Zhang;Hongliang Xin;X. Sha;Xiaoling Fang
  • 通讯作者:
    Xiaoling Fang
Enhanced anti-glioblastoma efficacy by PTX-loaded PEGylated poly(ɛ-caprolactone) nanoparticles: In vitro and in vivo evaluation.
负载 PTX 的聚乙二醇化聚己内酯纳米颗粒增强抗胶质母细胞瘤功效:体外和体内评估。
  • DOI:
    10.1016/j.ijpharm.2010.10.005
  • 发表时间:
    2010-12-15
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hongliang Xin;Liangcen Chen;Jijin Gu;Xiaoqing Ren;Zhangao Wei;Jieqi Luo;Yanzuo Chen;Xinyi Jiang
  • 通讯作者:
    Xinyi Jiang

Hongliang Xin的其他文献

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{{ truncateString('Hongliang Xin', 18)}}的其他基金

Collaborative Research: CDS&E: Theory-infused Neural Network (TinNet) for Nonadiabatic Molecular Simulations
合作研究:CDS
  • 批准号:
    2245402
  • 财政年份:
    2023
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
CAREER: Bayesian Model of Chemisorption for Adsorbate-Specific Tuning of Electrocatalysis
职业:用于电催化吸附质特异性调节的化学吸附贝叶斯模型
  • 批准号:
    1845531
  • 财政年份:
    2019
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
Accelerating Multimetallic Catalyst Design for Electrochemical CO2 Reduction using Quantum Chemical Modeling and Machine Learning
使用量子化学建模和机器学习加速电化学二氧化碳还原的多金属催化剂设计
  • 批准号:
    1604984
  • 财政年份:
    2016
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant

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