Research
Research
Research
Research
190+ open-access research outputs.
Machine-learned interatomic potentials hold the promise to enable the modeling of highly concentrated liquids over meaningful timescales, far from reach for current ab initio electronic structure meth…
Quantum chemistry is a foundational enabling tool for the fields of chemistry, materials science, computational biology and others. Despite of its power, the practical application of quantum chemistry…
The use of bioceramics as hard tissue substitutes is extensive due to their excellent biocompatible and osteogenic behaviors. Among various bioceramics, Ca-Mg silicates are unique from the viewpoints …
X-ray absorption near edge structure (XANES) is an essential tool for elucidating the atomic-scale, local three-dimensional (3D) structure of given materials and molecules. The rapid computation of XA…
Ten high resolution Fourier transform spectra of the pentad region near 3.3 {\mu}m of methane diluted in carbon dioxide at total pressures up to 800 hPa have been recorded at 296.5(5) K. Including a h…
Attosecond science is an emerging topic where chirality plays a central role. Here we demonstrate subjecting iodoacetylene, a geometrically achiral molecule, to a pair of simulated non-ionizing ultraf…
Silicate bioceramics have attracted significant attention in medical applications, particularly in hard tissue regeneration, because of their controllable chemical, physical, and biological functional…
Robust model predictive control (MPC) aims to preserve performance under model-plant mismatch, yet robust formulations for nonlinear MPC (NMPC) with data-driven surrogates remain limited. This work pr…
Biomass-derived hard carbon has become the most promising anode material for sodium-ion batteries (SIBs) due to its high capacity and excellent cycling stability. However, the effects of synthesis par…
Physics-informed machine learning (PIML) represents an emerging paradigm that integrates various forms of physical knowledge into machine learning (ML) components, thereby enhancing the physical consi…
We study many-body correlation functions within various Fundamental Measure Theory (FMT) formulations and compare their predictions to Monte Carlo simulations of hard-sphere fluids. FMT accurately cap…
As a result of the wide span of uncertainties and input variables considered in recent peer-reviewed studies on hydrogen supply chains, consensus and generalized insight are hard to derive. This work …
MOF/polymer composites have been widely investigated in the past decade for gas separation applications. However, the impact of MOF nanoparticle morphology and size in gas separation have not yet been…
We have observed the signatures of valence electron rearrangement in photoexcited ammonia using ultrafast hard X-ray scattering. Time-resolved X-ray scattering is a powerful tool for imaging structura…
Neural operators are capable of capturing nonlinear mappings between infinite-dimensional functional spaces, offering a data-driven approach to modeling complex functional relationships in classical d…
Coarse-grained (CG) force field methods for molecular systems are a crucial tool to simulate large biological macromolecules and are therefore essential for characterisations of biomolecular systems. …
Singlet fission and triplet-triplet annihilation (TTA) are spin-dependent phenomena critical to optoelectronics. The dynamics of spin populations during geminate triplet pair separation are crucial fo…
Molecular Dynamics simulations are essential tools for understanding the dynamic behavior of biomolecules, yet extracting meaningful molecular pathways from these simulations remains challenging due t…
Coarse-grained (CG) modeling has gained significant attention in recent years due to its wide applicability in enhancing the spatiotemporal scales of molecular simulations. While CG simulations, often…
CuInS2 quantum dots have been studied in a broad range of applications, but despite this, the fine details of their charge carrier dynamics remain a subject of intense debate. Two of the most relevant…
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