Related references
Note: Only part of the references are listed.Multiple comparisons: a tutorial. Part 1. Understanding hypothesis testing
Michael T. Lawson et al.
BJOG-AN INTERNATIONAL JOURNAL OF OBSTETRICS AND GYNAECOLOGY (2021)
Sensitivity of energetic materials: Evidence of thermodynamic factor on a large array of CHNOFCl compounds
Nikita V. Muravyev et al.
CHEMICAL ENGINEERING JOURNAL (2021)
Transfer learning with graph neural networks for optoelectronic properties of conjugated oligomers
Chee-Kong Lee et al.
JOURNAL OF CHEMICAL PHYSICS (2021)
Transfer learning for solvation free energies: From quantum chemistry to experiments
Florence H. Vermeire et al.
CHEMICAL ENGINEERING JOURNAL (2021)
Sources of Variation in Drop-Weight Impact Sensitivity Testing of the Explosive Pentaerythritol Tetranitrate
Frank W. Marrs et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2021)
Epigenetic Target Profiler: A Web Server to Predict Epigenetic Targets of Small Molecules
Norberto Sanchez-Cruz et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2021)
Predicting Energetics Materials' Crystalline Density from Chemical Structure by Machine Learning
Phan Nguyen et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2021)
A Short Review of Nitric Esters and Their Role in Energetic Materials
Jesse J. Sabatini et al.
ACS OMEGA (2021)
Highly accurate protein structure prediction with AlphaFold
John Jumper et al.
NATURE (2021)
Practical Active Learning with Model Selection for Small Data
Maryam Pardakhti et al.
20TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2021) (2021)
Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data
Vishu Gupta et al.
NATURE COMMUNICATIONS (2021)
Some Observations About the Drop-weight Explosive Sensitivity Test
P. J. Rae et al.
JOURNAL OF DYNAMIC BEHAVIOR OF MATERIALS (2021)
Autonomous Discovery in the Chemical Sciences Part I: Progress
Connor W. Coley et al.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2020)
Boosting Tree-Assisted Multitask Deep Learning for Small Scientific Datasets
Jian Jiang et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Models for predicting impact sensitivity of energetic materials based on the trigger linkage hypothesis and Arrhenius kinetics
Tomas L. Jensen et al.
JOURNAL OF MOLECULAR MODELING (2020)
Modeling Sensitivities of Energetic Materials using the Python Language and Libraries
Didier Mathieu
PROPELLANTS EXPLOSIVES PYROTECHNICS (2020)
Neural Message Passing for NMR Chemical Shift Prediction
Youngchun Kwon et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Rapid Assembly and Preparation of Energetic Microspheres LLM-105/CL-20
Yuanping Zhang et al.
PROPELLANTS EXPLOSIVES PYROTECHNICS (2020)
Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials
Joshua L. Lansford et al.
NATURE COMMUNICATIONS (2020)
Data Augmentation and Pretraining for Template-Based Retrosynthetic Prediction in Computer-Aided Synthesis Planning
Michael E. Fortunato et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Prediction of Energetic Material Properties from Electronic Structure Using 3D Convolutional Neural Networks
Alex D. Casey et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences
Jinchao Feng et al.
SCIENCE ADVANCES (2020)
Deep Learning for Energetic Material Detonation Performance
Brian C. Barnes
SHOCK COMPRESSION OF CONDENSED MATTER - 2019 (2020)
Deep Learning in Protein Structural Modeling and Design
Wenhao Gao et al.
PATTERNS (2020)
Deep learning for automated classification and characterization of amorphous materials
Kirk Swanson et al.
SOFT MATTER (2020)
Machine learning regressors for solar radiation estimation from satellite data
L. Cornejo-Bueno et al.
SOLAR ENERGY (2019)
Analyzing Learned Molecular Representations for Property Prediction
Kevin Yang et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2019)
Accurate Thermochemistry with Small Data Sets: A Bond Additivity Correction and Transfer Learning Approach
Colin A. Grambow et al.
JOURNAL OF PHYSICAL CHEMISTRY A (2019)
Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning
Justin S. Smith et al.
NATURE COMMUNICATIONS (2019)
A robotic platform for flow synthesis of organic compounds informed by AI planning
Connor W. Coley et al.
SCIENCE (2019)
Predicting Materials Properties with Little Data Using Shotgun Transfer Learning
Hironao Yamada et al.
ACS CENTRAL SCIENCE (2019)
Text-mined dataset of inorganic materials synthesis recipes
Olga Kononova et al.
SCIENTIFIC DATA (2019)
Void collapse generated meso-scale energy localization in shocked energetic materials: Non-dimensional parameters, regimes, and criticality of hotspots
N. K. Rai et al.
PHYSICS OF FLUIDS (2019)
Deep learning for molecular design-a review of the state of the art
Daniel C. Elton et al.
MOLECULAR SYSTEMS DESIGN & ENGINEERING (2019)
Machine Learning in Computer-Aided Synthesis Planning
Connor W. Coley et al.
ACCOUNTS OF CHEMICAL RESEARCH (2018)
Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition
Sabrina Jaeger et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)
Understanding the shock and detonation response of high explosives at the continuum and meso scales
C. A. Handley et al.
APPLIED PHYSICS REVIEWS (2018)
Multi-scale shock-to-detonation simulation of pressed energetic material: A meso-informed ignition and growth model
O. Sen et al.
JOURNAL OF APPLIED PHYSICS (2018)
Machine learning for molecular and materials science
Keith T. Butler et al.
NATURE (2018)
Drop hammer with high-speed thermal imaging
Zhiwei Men et al.
REVIEW OF SCIENTIFIC INSTRUMENTS (2018)
Sensitivity of Energetic Materials: Theoretical Relationships to Detonation Performance and Molecular Structure
Didier Mathieu
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2017)
Effect of Sandpaper and Grain Size on Non-Shock Initiated Reactions in HMX
John G. Reynolds et al.
PROPELLANTS EXPLOSIVES PYROTECHNICS (2017)
A General Guidebook for the Theoretical Prediction of Physicochemical Properties of Chemicals for Regulatory Purposes
Carlos Nieto-Draghi et al.
CHEMICAL REVIEWS (2015)
Recent Developments in the Synthesis of Supported Catalysts
Peter Munnik et al.
CHEMICAL REVIEWS (2015)
Impact sensitivities of energetic materials: Exploring the limitations of a model based only on structural formulas
Didier Mathieu et al.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING (2015)
Activity cliffs in drug discovery: Dr Jekyll or Mr Hyde?
Maykel Cruz-Monteagudo et al.
DRUG DISCOVERY TODAY (2014)
Preparation and Properties of Submicrometer-Sized LLM-105 via Spray-Crystallization Method
Juan Zhang et al.
PROPELLANTS EXPLOSIVES PYROTECHNICS (2014)
Theoretical evaluation of sensitivity and thermal stability for high explosives based on quantum chemistry methods: A brief review
Qi-Long Yan et al.
INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY (2013)
Preparation and Properties of An Insensitive Booster Explosive Based on LLM-105
Wenzheng Xu et al.
PROPELLANTS EXPLOSIVES PYROTECHNICS (2013)
Review of Existing QSAR/QSPR Models Developed for Properties Used in Hazardous Chemicals Classification System
Flor A. Quintero et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2012)
Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
Lars Ruddigkeit et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2012)
Prediction of Impact Sensitivity of Nonheterocyclic Nitroenergetic Compounds Using Genetic Algorithm and Artificial Neural Network
Rui Wang et al.
JOURNAL OF ENERGETIC MATERIALS (2012)
QSPR studies of impact sensitivity of nitro energetic compounds using three-dimensional descriptors
Jie Xu et al.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING (2012)
Density functionals for surface science: Exchange-correlation model development with Bayesian error estimation
Jess Wellendorff et al.
PHYSICAL REVIEW B (2012)
An investigation into pharmaceutically relevant mutagenicity data and the influence on Ames predictive potential
Patrick McCarren et al.
JOURNAL OF CHEMINFORMATICS (2011)
Chemical Substitutions That Introduce Activity Cliffs Across Different Compound Classes and Biological Targets
Anne Mai Wassermann et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2010)
Extended-Connectivity Fingerprints
David Rogers et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2010)
Prediction of impact sensitivity of nitro energetic compounds by neural network based on electrotopological-state indices
Rui Wang et al.
JOURNAL OF HAZARDOUS MATERIALS (2009)
Structure-activity landscape index: Identifying and quantifying activity cliffs
Rajarshi Guha et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2008)
Development of quantitative structure-property relationships for predictive modeling and design of energetic materials
Jason A. Morrill et al.
JOURNAL OF MOLECULAR GRAPHICS & MODELLING (2008)
Shear-strain-induced chemical reactivity of layered molecular crystals
Maija M. Kuklja et al.
APPLIED PHYSICS LETTERS (2007)
A quantum mechanical investigation of the relation between impact sensitivity and the charge distribution in energetic molecules
BM Rice et al.
JOURNAL OF PHYSICAL CHEMISTRY A (2002)
Important aspects of behaviour of organic energetic compounds: a review
AK Sikder et al.
JOURNAL OF HAZARDOUS MATERIALS (2001)
Share Paper
