A5035056140- Advancements in Battery Materials
- Advanced Battery Materials and Technologies
- Molecular Communication and Nanonetworks
- Metaheuristic Optimization Algorithms Research
- Graphene research and applications
- Zeolite Catalysis and Synthesis
- Machine Learning in Materials Science
- Spacecraft Design and Technology
- Quantum Computing Algorithms and Architecture
- Gold and Silver Nanoparticles Synthesis and Applications
- Advanced Battery Technologies Research
Fritz Haber Institute of the Max Planck Society
2024-2025
University of Southampton
2022-2024
The Faraday Institution
2022-2023
Swarm intelligence-based algorithms have proven successful in exploring a potential energy surfaces (PESs) of chemical systems. One the major limitations to recent implementations these is that they been implemented serially. To overcome this limitation we present our asynchronously parallel global optimisations (GO) artificial bee colony (ABC) methodology: pyGlobOpt. Furthermore, demonstrate methodologies properly tune and enhance pyGlobOpt for system specific character by developing...
Abstract Computational modelling is a vital tool in the research of batteries and their component materials. Atomistic models are key to building truly physics-based form foundation multiscale chain, leading more robust predictive models. These can be applied fundamental questions with high accuracy. For example, they used predict new behaviour not currently accessible by experiment, for reasons cost, safety, or throughput. useful quantifying evaluating trends experimental data, explaining...
Swarm intelligence-based algorithms have proven successful in exploring a potential energy surfaces (PESs) of chemical systems. One the major limitations to recent implementations these is that they been implemented serially. To overcome this limitation we present our asynchronously parallel global optimisations (GO) artificial bee colony (ABC) methodology: pyGlobOpt. Furthermore, demonstrate methodologies properly tune and enhance pyGlobOpt for system specific character by developing...
Ab initio workflow for prediction of Li intercalation, with minimal calculations, in anode-like graphite nanoparticles using linear-scaling DFT. The is able to reproduce key experimental data including staging, charge transfer, and OCVs.
Swarm intelligence-based algorithms have proven successful in exploring a potential energy surfaces (PESs) of chemical systems. One the major limitations to recent implementations these is that they been implemented serially. To overcome this limitation we present our asynchronously parallel global optimisations (GO) artificial bee colony (ABC) methodology: pyGlobOpt. Furthermore, demonstrate methodologies properly tune and enhance pyGlobOpt for system specific character by developing...
With the ever-increasing demand for atomistic structures representative of real-life systems as well ad-vent exascale computers, it has now become necessary and possible to use advanced global optimization (GO) techniques intelligently sample potential energy surface (PES). Given previous studies demonstrating relative efficiency artificial bee colony (ABC) swarm intelligence algorithm chemical systems, we turn focus on maximizing this tool. This is achieved by producing a new software;...
Experimental and theoretical works have, to date, been unable uncover the ground state configuration of prominent solid electrolyte candidate cubic Li$_7$La$_3$Zr$_2$O$_{12}$ (c-LLZO). Computational studies rely on an initial low-energy structure as a reference point. In this study, we present methodology identify energetically favourable configurations c-LLZO, enabling isolation structures, for crystallographically predicted structure. We begin by eliminating structures that involve...
To date, experimental and theoretical works have been unable to uncover the ground-state configuration of solid electrolyte cubic Li7La3Zr2O12 (c-LLZO). Computational studies rely on an initial low-energy structure as a reference point. Here, we present methodology for identifying energetically favorable configurations c-LLZO crystallographically predicted structure. We begin by eliminating structures that involve overlapping Li atoms based nearest neighbor counts. further reduce space...