Cargando…

Prediction and Construction of Energetic Materials Based on Machine Learning Methods

Energetic materials (EMs) are the core materials of weapons and equipment. Achieving precise molecular design and efficient green synthesis of EMs has long been one of the primary concerns of researchers around the world. Traditionally, advanced materials were discovered through a trial-and-error pr...

Descripción completa

Detalles Bibliográficos
Autores principales:	Zang, Xiaowei, Zhou, Xiang, Bian, Haitao, Jin, Weiping, Pan, Xuhai, Jiang, Juncheng, Koroleva, M. Yu., Shen, Ruiqi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821915/ https://www.ncbi.nlm.nih.gov/pubmed/36615516 http://dx.doi.org/10.3390/molecules28010322

Ejemplares similares

Applying machine learning techniques to predict the properties of energetic materials
por: Elton, Daniel C., et al.
Publicado: (2018)

The Art of Framework Construction: Core–Shell Structured Micro-Energetic Materials
por: Duan, Binghui, et al.
Publicado: (2021)

The prediction of distant metastasis risk for male breast cancer patients based on an interpretable machine learning model
por: Zhao, Xuhai, et al.
Publicado: (2023)

Molecular design and properties of bridged energetic pyridines derivatives
por: Zhai, Diandian, et al.
Publicado: (2019)

Synthesis, thermal behaviors, and energetic properties of asymmetrically substituted tetrazine-based energetic materials
por: Wang, Shenghui, et al.
Publicado: (2022)

Center-environment feature models for materials image segmentation based on machine learning
por: Han, Yuexing, et al.
Publicado: (2022)

Design and Development of Lubricating Material Database and Research on Performance Prediction Method of Machine Learning
por: Jia, Dan, et al.
Publicado: (2019)

Transferring chemical and energetic knowledge between molecular systems with machine learning
por: Heydari, Sajjad, et al.
Publicado: (2023)

Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials
por: Chun, Sehyun, et al.
Publicado: (2020)

Research on Insurance Method for Energetic Materials on Information Self-Destruction Chips
por: Feng, Hengzhen, et al.
Publicado: (2022)

Theoretical Study on CL-20-Based Cocrystal Energetic Compounds in an External Electric Field
por: Hao, Lina, et al.
Publicado: (2020)

Theoretical Studies on the Performance of HMX with Different Energetic Groups
por: Hao, Lina, et al.
Publicado: (2020)

Identification of heavy, energetic, hadronically decaying particles using machine-learning techniques
por: Sirunyan, Albert M, et al.
Publicado: (2020)

Use of Machine Learning and Wearable Sensors to Predict Energetics and Kinematics of Cutting Maneuvers
por: Zago, Matteo, et al.
Publicado: (2019)

Forecasting molecular dynamics energetics of polymers in solution from supervised machine learning
por: Andrews, James, et al.
Publicado: (2022)

Experimental Investigation of the Self-Ignition and Jet Flame of Hydrogen Jets Released under Different Conditions
por: Pan, Xuhai, et al.
Publicado: (2019)

Research on Electromagnetic Radiation Mechanism during Detonation of Energetic Material
por: Cui, Yuanbo, et al.
Publicado: (2022)

Design of Energetic Materials Based on Asymmetric Oxadiazole
por: Jin, Xinghui, et al.
Publicado: (2019)

Facile Fabrication of Energetic Nanocomposite Materials by Polydopamine
por: Song, Zhanxin, et al.
Publicado: (2023)

Energetic Glaucoma Segmentation and Classification Strategies Using Depth Optimized Machine Learning Strategies
por: Elizabeth Jesi, V., et al.
Publicado: (2021)

Preparation of a superfine RDX/Al composite as an energetic material by mechanical ball-milling method and the study of its thermal properties
por: Xiao, Lei, et al.
Publicado: (2018)

Preparation, Characterization and Application of Nano-Graphene-Based Energetic Materials
por: Fu, Xiaolong, et al.
Publicado: (2021)

Effect of addition of HTa to Al/PTFE under quasi-static compression on the properties of the developed energetic composite material
por: Ren, Xinxin, et al.
Publicado: (2021)

Current Self-Healing Binders for Energetic Composite Material Applications
por: Yang, Jing, et al.
Publicado: (2023)

Application of Machine Learning in Intelligent Medical Image Diagnosis and Construction of Intelligent Service Process
por: Gao, Zhihong, et al.
Publicado: (2022)

Insensitive ionic bio-energetic materials derived from amino acids
por: Zhang, Lei, et al.
Publicado: (2017)

Benzimidazole Derivatives as Energetic Materials: A Theoretical Study
por: Sarlauskas, Jonas, et al.
Publicado: (2021)

Nitroacetonitrile as a versatile precursor in energetic materials synthesis
por: Creegan, Shannon E., et al.
Publicado: (2020)

Noncovalent Interactions and Crystal Structure Prediction of Energetic Materials
por: Liu, Yan, et al.
Publicado: (2022)

The exon junction complex senses energetic stress and regulates contractility and cell architecture in cardiac myocytes
por: Pierrat, Olivier A., et al.
Publicado: (2017)

Prediction of the Compressive Strength for Cement-Based Materials with Metakaolin Based on the Hybrid Machine Learning Method
por: Huang, Jiandong, et al.
Publicado: (2022)

Fundamentals of building construction: materials and methods
por: Allen, Edward, et al.
Publicado: (2009)

Topological representations of crystalline compounds for the machine-learning prediction of materials properties
por: Jiang, Yi, et al.
Publicado: (2021)

Investigation on the Extraction Methods of Timbre Features in Vocal Singing Based on Machine Learning
por: Zang, Lu
Publicado: (2022)

Unraveling the energetic significance of chemical events in enzyme catalysis via machine-learning based regression approach
por: Song, Zilin, et al.
Publicado: (2020)

Textile materials for lightweight constructions: technologies, methods, materials, properties
por: Cherif, Chokri
Publicado: (2016)

Classification and Prediction of Skyrmion Material Based on Machine Learning
por: Liu, Dan, et al.
Publicado: (2023)

Midpalatal Suture CBCT Image Quantitive Characteristics Analysis Based on Machine Learning Algorithm Construction and Optimization
por: Gao, Lu, et al.
Publicado: (2022)

Automating Construction of Machine Learning Models With Clinical Big Data: Proposal Rationale and Methods
por: Luo, Gang, et al.
Publicado: (2017)

Forecasting induced seismicity in Oklahoma using machine learning methods
por: Qin, Yan, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_3o4oqmhkm47c0nmhc4biamreer