A property-oriented adaptive design framework for rapid discovery of energetic molecules based on small-scale labeled datasets
暂无分享,去创建一个
Xuemei Pu | Yunhao Xie | Yijing Liu | Renling Hu | Xu Lin | Jing Hu | X. Pu | Yunhao Xie | Yijing Liu | Jing Hu | Renling Hu | Xu Lin
[1] Dennis Fischer,et al. Dense energetic nitraminofurazanes. , 2014, Chemistry.
[2] David Rogers,et al. Extended-Connectivity Fingerprints , 2010, J. Chem. Inf. Model..
[3] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[4] Tian Lu,et al. Multiwfn: A multifunctional wavefunction analyzer , 2012, J. Comput. Chem..
[5] S. Broderick,et al. Prediction of optical band gap of β-(AlxGa1-x)2O3 using material informatics , 2018 .
[6] Radha Shivaramaiah,et al. Direct calorimetric verification of thermodynamic instability of lead halide hybrid perovskites , 2016, Proceedings of the National Academy of Sciences.
[7] M. Göbel,et al. Nitrotetrazolate-2N-oxides and the strategy of N-oxide introduction. , 2010, Journal of the American Chemical Society.
[8] S. Verevkin,et al. Imidazolium-based ionic liquids containing FAP anion: Thermodynamic study , 2019, Journal of Molecular Liquids.
[9] M. Fathollahi,et al. QSPR modeling of decomposition temperature of energetic cocrystals using artificial neural network , 2018, Journal of Thermal Analysis and Calorimetry.
[10] D. Comaniciu,et al. Artificial Intelligence in Cardiovascular Imaging: JACC State-of-the-Art Review. , 2019, Journal of the American College of Cardiology.
[11] W. Li,et al. Construction of a Thermally Stable and Highly Energetic Metal–Organic Framework as Lead-Free Primary Explosives , 2018 .
[12] Daniel C Elton,et al. Applying machine learning techniques to predict the properties of energetic materials , 2018, Scientific Reports.
[13] S. J. Jacobs,et al. Chemistry of Detonations. I. A Simple Method for Calculating Detonation Properties of C–H–N–O Explosives , 1968 .
[14] Lauren A. Mitchell,et al. N-functionalized nitroxy/azido fused-ring azoles as high-performance energetic materials , 2016 .
[15] T. Klapötke,et al. Energetic derivatives of 5-(5-amino-2H-1,2,3-triazol-4-yl)-1H-tetrazole. , 2015, Dalton transactions.
[16] Hieu A. Doan,et al. Quantum Chemistry-Informed Active Learning to Accelerate the Design and Discovery of Sustainable Energy Storage Materials , 2020, Chemistry of Materials.
[17] R. Peng,et al. Novel strategies for synthesizing energetic materials based on BTO with improved performances. , 2019, Dalton transactions.
[18] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[19] L. Curtiss,et al. Assessment of Gaussian-2 and density functional theories for the computation of enthalpies of formation , 1997 .
[20] Kazushi Ikeda,et al. Predicting the band gap of ZnO quantum dots via supervised machine learning models , 2020 .
[21] Lionel M. Ni,et al. Generalizing from a Few Examples , 2020, ACM Comput. Surv..
[22] William G. Mallard,et al. The NIST Chemistry WebBook: A Chemical Data Resource on the Internet† , 2001 .
[23] V. P. Sinditskii,et al. Thermal decomposition peculiarities and combustion behavior of nitropyrazoles , 2017 .
[24] F. Roland,et al. Global CO2 emissions from dry inland waters share common drivers across ecosystems , 2020, Nature Communications.
[25] Z. Algamal,et al. A penalized quantitative structure–property relationship study on melting point of energetic carbocyclic nitroaromatic compounds using adaptive bridge penalty , 2018, SAR and QSAR in environmental research.
[26] Geun Ho Gu,et al. Thermochemistry of gas-phase and surface species via LASSO-assisted subgraph selection , 2018 .
[27] A DFT theoretical study of heats of formation and detonation properties of nitrogen-rich explosives. , 2010, Journal of hazardous materials.
[28] M. Rahimi-Gorji,et al. Synthesis and characterization of a novel hydride polymer P-DSBT/ZnO nano-composite for optoelectronic applications , 2019, Journal of Molecular Liquids.
[29] Michael J. Zdilla,et al. Properties and Promise of Catenated Nitrogen Systems As High-Energy-Density Materials. , 2020, Chemical reviews.
[30] Ming Lu,et al. [N-N=N-N]-linked fused triazoles with π-π stacking and hydrogen bonds: Towards thermally stable, Insensitive, and highly energetic materials , 2021 .
[31] M. Keshavarz,et al. New and reliable model for prediction of autoignition temperature of organic compounds containing energetic groups , 2018 .
[32] N. Zohari,et al. Using the QSPR Approach for Estimating the Density of Azole‐based Energetic Compounds , 2017 .
[33] J. Murray,et al. Some Perspectives on Estimating Detonation Properties of C, H, N, O Compounds , 2011 .
[34] Lemont B. Kier,et al. Electrotopological State Indices for Atom Types: A Novel Combination of Electronic, Topological, and Valence State Information , 1995, J. Chem. Inf. Comput. Sci..
[35] J. Shreeve,et al. Energetic dinitromethyl group functionalized azofurazan and its azofurazanates , 2016 .
[36] J. Murray,et al. Relationships between dissociation energies and electrostatic potentials of CNO2 bonds: applications to impact sensitivities , 1996 .
[37] Xiaotong Shen,et al. Journal of the American Statistical Association Likelihood-based Selection and Sharp Parameter Estimation Likelihood-based Selection and Sharp Parameter Estimation , 2022 .
[38] J. Shreeve,et al. Intermolecular weak hydrogen-bonding (Het-H-N/O): an effective strategy for the synthesis of monosubstituted 1,2,4,5-tetrazine-based energetic materials with excellent sensitivity. , 2019, The Journal of organic chemistry.
[39] T. Klapötke,et al. 1,1'-Nitramino-5,5'-bitetrazoles. , 2016, Chemistry.
[40] G. Schneider,et al. Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery. , 2019, Chemical reviews.
[41] Chaoyang Zhang,et al. Review of the molecular and crystal correlations on sensitivities of energetic materials. , 2020, Journal of hazardous materials.
[42] Yong Tian,et al. Accelerating the discovery of insensitive high-energy-density materials by a materials genome approach , 2018, Nature Communications.
[43] K. Müller,et al. Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space , 2015, The journal of physical chemistry letters.
[44] Jun Yang,et al. 1,2,4,5-Dioxadiazine-functionalized [N-NO2]- furazan energetic salts. , 2016, Dalton transactions.
[45] Monica C. Concha,et al. An electrostatic interaction correction for improved crystal density prediction , 2009 .
[46] Hongzhen Li,et al. Furazans with Azo Linkages: Stable CHNO Energetic Materials with High Densities, Highly Energetic Performance, and Low Impact and Friction Sensitivities. , 2016, Chemistry.
[47] Z. Jianguo,et al. Gem-diol and Ketone Crystal-to-crystal Transition Phenomena , 2017, Scientific Reports.
[48] Turab Lookman,et al. Machine learning assisted design of high entropy alloys with desired property , 2019, Acta Materialia.
[49] J. Moxnes,et al. Models for predicting impact sensitivity of energetic materials based on the trigger linkage hypothesis and Arrhenius kinetics , 2020, Journal of Molecular Modeling.
[50] Heming Xiao,et al. Quantum Chemistry Derived Criteria for Impact Sensitivity , 2014 .
[51] T. Lookman,et al. Accelerated Discovery of Large Electrostrains in BaTiO3‐Based Piezoelectrics Using Active Learning , 2018, Advanced materials.
[52] A. Christofferson. Asymmetric ligand binding in homodimeric Enterobacter cloacae nitroreductase yields the Michaelis complex for nitroaromatic substrates , 2020, Journal of Molecular Modeling.
[53] Edward R. Dougherty,et al. Optimal experimental design for materials discovery , 2017 .
[54] C. Campbell,et al. Adsorbed Hydroxyl and Water on Ni(111): Heats of Formation by Calorimetry , 2018 .
[55] Ahmad Alzghoul,et al. Experimental and Computational Prediction of Glass Transition Temperature of Drugs , 2014, J. Chem. Inf. Model..