A5034392151- Energetic Materials and Combustion
- Thermal and Kinetic Analysis
- Crystallography and molecular interactions
- Advanced Photocatalysis Techniques
- Machine Learning in Materials Science
- Rocket and propulsion systems research
- Covalent Organic Framework Applications
- Boron and Carbon Nanomaterials Research
- Electronic and Structural Properties of Oxides
- Fullerene Chemistry and Applications
- High-pressure geophysics and materials
- MXene and MAX Phase Materials
- Molecular spectroscopy and chirality
- Metal-Organic Frameworks: Synthesis and Applications
- Catalysis and Oxidation Reactions
- ZnO doping and properties
- Chemical Thermodynamics and Molecular Structure
- Advanced Nanomaterials in Catalysis
- Electrocatalysts for Energy Conversion
- Computational Drug Discovery Methods
- Copper-based nanomaterials and applications
- Gas Sensing Nanomaterials and Sensors
- Crystallization and Solubility Studies
Microbiology Institute of Shaanxi
2021-2024
Xi’an University
2024
Xi'an Jiaotong University
2021-2023
Chang'an University
2021
Domain-related knowledge promoted high-throughput cage scaffold screening from the ZINC15 database containing over 130 000 scaffolds and cooperated with combinatorial design to alleviate lack of energetic materials. A dozen candidates were discovered that show excellent energy safety performance, confirming effectiveness our strategy.
Aiming to balance the pertinence and universality of energetic materials, this study proposes a new concept bionic inspired multifunctional modular materials seeks out potential monomers via high-throughput screening strategy.
Layered energetic materials (LEMs) can effectively balance energy and mechanical sensitivity, making them a current research focus in the field of materials. However, influence layered stacking pattern on impact sensitivity is still unclear, leading to lack advanced design strategies for high-energy low-sensitivity LEMs. Herein, we first utilize novel indicators such as maximum plane separation hydrogen bond dimension perform high-throughput screening over 106 candidate structures, resulting...
We give a new answer to the old puzzle of crystal density TTTO (tetrazino-tetrazine 1,3,6,8-tetraoxide) and its isomer via tailor-made polarizable force fields, an evolutionary algorithm, ab initio molecular dynamics simulation. The densities are predicted be over 2.0 g/cm3, making them still "holy grail" CHON-based energetic materials.
In this paper, we report the first attempt to quantify impact sensitivity using second-order incremental approach based on structural features of explosives. It has been found that height (h50) can be expressed via a multiplicative exponential form, in which exponents are characteristic coefficients increments multiplied by their numbers molecule. The method was developed large array experimental data (450 molecules and salts) different energetic materials, namely, nitro compounds,...
Main observation and conclusion Important progress has been made in the development of energetic molecules with high performance by computer‐aided molecular design recent years, but structural novelty organic scaffolds is insufficient. In this work, we propose an intra‐ring bridging strategy inspired known nitramines to novel polycyclic cage molecules. More than 100 structures were designed introducing C—C bridges increasing ring size. The synthesis difficulty considered besides two most...
We proposed a crystal structure prediction strategy based on tailor-made polarizable force field and an evolutionary algorithm, showing good accuracy efficiency in the of three CL-20 polymorphs.
Machine learning is an emerging approach to predict thermal decomposition temperature in the field of energetic materials, while assessment descriptor applicability still lacking. In this work, we have systematically established 5 general sets for 1091 compounds and combined them with 9 algorithms construct a suite predictive models mean absolute error ranging 41-29°C, which comparable cutting-edge endeavors. Our study emphasizes significant influence multi-level structural interactions on...
ConspectusIn this Account, we present a comprehensive overview of recent advancements in applying data-driven combinatorial design for developing novel high-energy-density materials. Initially, outline the progress energetic materials (EMs) development within framework four scientific paradigms, with particular emphasis on opportunities afforded by evolution computer and data science, which has propelled theoretical EMs into new era development. We then discuss structural features typical...
Strontium titanate (SrTiO3) is one of the most promising photocatalysts for overall water splitting (OWS). Strains can be commonly introduced in SrTiO3 during synthetic processes, example, pulsed laser deposition. However, effect strains on catalytic performance OWS still unclear to date. Herein, first-principles calculations were performed evaluate impact biaxial applied (001) surface oxygen evolution reaction (OER), bottleneck OWS. It was found that strains, especially compressive...
In the ZINC20 database, with aid of maximum substructure searches, common substructures were obtained from molecules high-strain-energy and combustion heat values, further provided domain knowledge on how to design high-energy-density hydrocarbon (HEDH) fuels. Notably, quadricyclane syntin could be topologically assembled through these substructures, corresponding schemes guided 20 fuel (ZD-1 ZD-20). The properties evaluated by using group-contribution methods density functional theory (DFT)...