2023 Industry 4.0: Digital Transformation Conference (IDTC23) October 3-4, 2023 Hyatt Lodge Oak Brook, Oak Brook, IL
International Congress on Particle Technology September 26-28, 2023 Nürnberg Convention Center, Nürnberg, Germany
A Case Study in Using JMP Statistical Tools to Tackle Chemical Engineering Challenges – Session 2 September 28, 2023
University of Louisville Student Process Safety Bootcamp September 29-30, 2023 University of Louisville
2023 Industry 4.0: Digital Transformation Conference (IDTC23) October 3-4, 2023 Hyatt Lodge Oak Brook, Oak Brook, IL
2023 Indonesia Student Regional Conference October 7, 2023 Universitas Pertamina, South Jakarta, Jakarta, Indonesia
Archived Webinar Want to be an Entrepreneur? Personal Stories From Three Successful Entrepreneurs Who Have Traveled This Path.
Aditya Nandy Citation name Nandy, A. Affiliation Massachusetts Institute of Technology State MA Country USA Authored(710b) Strategies and Software for Accelerating Inorganic Molecular DesignJon Paul JanetHeather KulikChenru DuanAditya NandyStefan Gugler2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)(699g) Accelerating Inorganic Discovery with Machine Learning and AutomationHeather KulikJon Paul JanetAditya NandyChenru DuanStefan Gugler2018 AIChE Annual Meeting (ISBN: 978-0-8169-1108-0)(162b) Exploiting Electronic Structure and Machine Learning Models for Discovery in Transition Metal ChemistryHeather KulikJon Paul JanetFang LiuAditya NandyChenru Duan2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)(443e) Using Data Driven Models to Gain Insight on Spin- and Oxidation-State Dependent Behavior of Reaction Energetics for Light Alkane OxidationHeather KulikJon Paul JanetChenru DuanAditya Nandy2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)(246e) Machine Learning and Transition Metal Chemistry: Data-Driven Comparisons of First and Second Row ComplexesJon Paul JanetDaniel HarperChenru DuanNaveen ArunachalamAditya NandyHeather Kulik2019 AIChE Annual Meeting (ISBN: 978-0-8169-1112-7)(427c) Breaking the Rules: Open Shell Systems Break Strong Scaling Relations and Allow Discovery of Materials with Improved Multiple Property TargetingAditya NandyChenru DuanHeather Kulik2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)(285e) A Database with Automated Quantum Chemistry Calculations and Machine Learning for Functional Transition Metal Complex DiscoveryMichael TaylorChenru DuanDaniel HarperAditya NandyNaveen ArunachalamFang LiuHeather Kulik2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)(346m) Navigating Combinatorial Challenges in High-Throughput Transition Metal Complex DiscoveryNaveen ArunachalamAditya NandyChenru DuanMichael TaylorDaniel HarperHeather Kulik2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)(106a) Molecular Design Blueprints: Catalysts and Principles from New Simulation and Machine Learning ToolsHeather KulikAditya NandyDaniel HarperMichael TaylorChenru DuanFang LiuNaveen ArunachalamJon Paul Janet2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)(477b) Leveraging Experimental Transition Metal Complex Information to Improve Generalizability of Machine Learning ModelsMichael TaylorChenru DuanNaveen ArunachalamAditya NandyDaniel HarperHeather Kulik2020 Virtual AIChE Annual Meeting (ISBN: 978-0-8169-1114-1)(118d) Semi-Supervised Learning Detects Safe Islands Where Density Functional Theory Is Applicable for Chemical DiscoveryChenru DuanAditya NandyFang LiuHeather Kulik2021 Annual Meeting (ISBN: 978-0-8169-1116-5)(265f) When does the choice of DFT functional matter in computational catalysis? The case of methane-to-methanolAditya NandyVyshnavi VennelakantiHeather Kulik2021 Annual Meeting (ISBN: 978-0-8169-1116-5)(152j) Machine-Learning Enabled Screening of MOFs for Ion Selective MembranesShuwen YueAditya NandyHeather Kulik2022 Annual Meeting (ISBN: 978-0-8169-1118-9)(360ac) Using Text-Mining and Community Knowledge to Quantify and Engineer Stability in MOFsAditya NandyHeather Kulik2022 Annual Meeting (ISBN: 978-0-8169-1118-9)(477b) Finding Needles in a Haystack: Sifting through 16M Catalysts for Optimal Methane-to-Methanol Catalyst Design Under Weak Thermodynamic ScalingAditya NandyHeather Kulik2022 Annual Meeting (ISBN: 978-0-8169-1118-9)(191i) Accelerating the Design of Single-Site Materials for Catalysis Using Computational Data, Experimental Data, and Machine LearningAditya NandyHeather Kulik2022 Annual Meeting (ISBN: 978-0-8169-1118-9) Associated proceedings 2018 AIChE Annual Meeting 2019 AIChE Annual Meeting 2020 Virtual AIChE Annual Meeting 2021 Annual Meeting 2022 Annual Meeting
