Chenru Duan

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 37

Top Topics

Density Functional Theory

Machine Learning

Silver Nanoparticles

Top Venues

Nature computational science

Journal of chemical theory and computation

The journal of physical chemistry letters

Chemical science

This page only lists publications with an associated author ORCID identifier.

Publications

Vyshnavi Vennelakanti, Irem B Kilic, Gianmarco G Terrones, Chenru Duan, Heather J Kulik
Machine Learning Prediction of the Experimental Transition Temperature of Fe(II) Spin-Crossover Complexes. The journal of physical chemistry. A 128 (1) (2023)
Chenru Duan, Yuanqi Du, Haojun Jia, Heather J Kulik
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. Nature computational science 3 (12) (2023)
Chenru Duan, Yuanqi Du, Haojun Jia, Heather J Kulik
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. Nature computational science 3 (12) (2023)
Yael Cytter, Aditya Nandy, Chenru Duan, Heather J Kulik
Insights into the deviation from piecewise linearity in transition metal complexes from supervised machine learning models. Physical chemistry chemical physics : PCCP (2023)
Vyshnavi Vennelakanti, Irem B Kilic, Gianmarco G Terrones, Chenru Duan, Heather J Kulik
Machine Learning Prediction of the Experimental Transition Temperature of Fe(II) Spin-Crossover Complexes. The journal of physical chemistry. A (2023)
Ilia Kevlishvili, Chenru Duan, Heather J Kulik
Classification of Hemilabile Ligands Using Machine Learning. The journal of physical chemistry letters (2023)
Gianmarco G Terrones, Chenru Duan, Aditya Nandy, Heather J Kulik
Low-cost machine learning prediction of excited state properties of iridium-centered phosphors. Chemical science 14 (6) (2023)
Yael Cytter, Aditya Nandy, Chenru Duan, Heather J Kulik
Insights into the deviation from piecewise linearity in transition metal complexes from supervised machine learning models. Physical chemistry chemical physics : PCCP 25 (11) (2023)
Gianmarco G Terrones, Chenru Duan, Aditya Nandy, Heather J Kulik
Low-cost machine learning prediction of excited state properties of iridium-centered phosphors. Chemical science 14 (6) (2023)
Chenru Duan, Yuanqi Du, Haojun Jia, Heather J Kulik
Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model. Nature computational science 3 (12) (2023)
Chenru Duan, Daniel B K Chu, Aditya Nandy, Heather J Kulik
Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost. Chemical science 13 (17) (2022)
Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J Kulik
A transferable recommender approach for selecting the best density functional approximations in chemical discovery. Nature computational science 3 (1) (2022)
Chenru Duan, Aditya Nandy, Husain Adamji, Yuriy Roman-Leshkov, Heather J Kulik
Machine Learning Models Predict Calculation Outcomes with the Transferability Necessary for Computational Catalysis. Journal of chemical theory and computation 18 (7) (2022)
Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J Kulik
A transferable recommender approach for selecting the best density functional approximations in chemical discovery. Nature computational science 3 (1) (2022)
Chenru Duan, Aditya Nandy, Gianmarco G Terrones, David W Kastner, Heather J Kulik
Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores. JACS Au 3 (2) (2022)
Chenru Duan, Adriana J Ladera, Julian C-L Liu, Michael G Taylor, Isuru R Ariyarathna, Heather J Kulik
Exploiting Ligand Additivity for Transferable Machine Learning of Multireference Character across Known Transition Metal Complex Ligands. Journal of chemical theory and computation 18 (8) (2022)
Chenru Duan, Aditya Nandy, Gianmarco G Terrones, David W Kastner, Heather J Kulik
Active Learning Exploration of Transition-Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores. JACS Au 3 (2) (2022)
Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J Kulik
A transferable recommender approach for selecting the best density functional approximations in chemical discovery. Nature computational science 3 (1) (2022)
Aditya Nandy, Chenru Duan, Conrad Goffinet, Heather J Kulik
New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts. JACS Au 2 (5) (2022)
Yeongsu Cho, Aditya Nandy, Chenru Duan, Heather J Kulik
DFT-Based Multireference Diagnostics in the Solid State: Application to Metal-Organic Frameworks. Journal of chemical theory and computation (2022)
Chenru Duan, Aditya Nandy, Ralf Meyer, Naveen Arunachalam, Heather J Kulik
A transferable recommender approach for selecting the best density functional approximations in chemical discovery. Nature computational science 3 (1) (2022)
Yeongsu Cho, Aditya Nandy, Chenru Duan, Heather J Kulik
DFT-Based Multireference Diagnostics in the Solid State: Application to Metal-Organic Frameworks. Journal of chemical theory and computation 19 (1) (2022)
Chenru Duan, Fang Liu, Aditya Nandy, Heather J Kulik
Putting Density Functional Theory to the Test in Machine-Learning-Accelerated Materials Discovery. The journal of physical chemistry letters 12 (19) (2021)
Chenru Duan, Shuxin Chen, Michael G Taylor, Fang Liu, Heather J Kulik
Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles. Chemical science 12 (39) (2021)
Jon Paul Janet, Chenru Duan, Aditya Nandy, Fang Liu, Heather J Kulik
Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design. Accounts of chemical research 54 (3) (2021)
Aditya Nandy, Chenru Duan, Michael G Taylor, Fang Liu, Adam H Steeves, Heather J Kulik
Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning. Chemical reviews 121 (16) (2021)
Aditya Nandy, Chenru Duan, Heather J Kulik
Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworks. Journal of the American Chemical Society 143 (42) (2021)
Chenru Duan, Fang Liu, Aditya Nandy, Heather J Kulik
Semi-supervised Machine Learning Enables the Robust Detection of Multireference Character at Low Cost. The journal of physical chemistry letters 11 (16) (2020)
Fang Liu, Chenru Duan, Heather J Kulik
Rapid Detection of Strong Correlation with Machine Learning for Transition-Metal Complex High-Throughput Screening. The journal of physical chemistry letters 11 (19) (2020)
Chenru Duan, Chang-Yu Hsieh, Junjie Liu, Jianlan Wu, Jianshu Cao
Unusual Transport Properties with Noncommutative System-Bath Coupling Operators. The journal of physical chemistry letters 11 (10) (2020)
Michael G Taylor, Tzuhsiung Yang, Sean Lin, Aditya Nandy, Jon Paul Janet, Chenru Duan, Heather J Kulik
Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions. The journal of physical chemistry. A 124 (16) (2020)
Chenru Duan, Fang Liu, Aditya Nandy, Heather J Kulik
Data-Driven Approaches Can Overcome the Cost-Accuracy Trade-Off in Multireference Diagnostics. Journal of chemical theory and computation 16 (7) (2020)
Qianlong Wang, Zhihao Gong, Chenru Duan, Zhoufei Tang, Jianlan Wu
Dynamical scaling in the Ohmic spin-boson model studied by extended hierarchical equations of motion. The Journal of chemical physics 150 (8) (2019)
Jon Paul Janet, Chenru Duan, Tzuhsiung Yang, Aditya Nandy, Heather J Kulik
A quantitative uncertainty metric controls error in neural network-driven chemical discovery. Chemical science 10 (34) (2019)
Chenru Duan, Jon Paul Janet, Fang Liu, Aditya Nandy, Heather J Kulik
Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models. Journal of chemical theory and computation 15 (4) (2019)
Jon Paul Janet, Fang Liu, Aditya Nandy, Chenru Duan, Tzuhsiung Yang, Sean Lin, Heather J Kulik
Designing in the Face of Uncertainty: Exploiting Electronic Structure and Machine Learning Models for Discovery in Inorganic Chemistry. Inorganic chemistry 58 (16) (2019)
Chenru Duan, Qianlong Wang, Zhoufei Tang, Jianlan Wu
The study of an extended hierarchy equation of motion in the spin-boson model: The cutoff function of the sub-Ohmic spectral density. The Journal of chemical physics 147 (16) (2018)