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This paper studies the long-term energy management of a microgrid coordinating hybrid hydrogen-battery energy storage. We develop an approximate semi-empirical hydrogen storage model to accurately capture the power-dependent efficiency of…
Due to their abundant use in all-solid-state lasers, nonlinear optical (NLO) crystals are needed for many applications across diverse fields such as medicine and communication. However, because of conflicting requirements, the design of…
Recently, machine learning Hamiltonian (MLH) models have gained traction as fast approximations of electronic structures such as orbitals and electron densities, while also enabling direct evaluation of energies and forces from their…
DFT+U is a widely used treatment in the density functional theory (DFT) to deal with correlated materials that contain open-shell elements, whereby the quantitative and sometimes even qualitative failures of local and semilocal…
Accurate and predictive computations of the quantum-mechanical behavior of many interacting electrons in realistic atomic environments are critical for the theoretical design of materials with desired properties, and require solving the…
A new database of collisional rate coefficients for transitions between the rotational states of H$_2$O collided with H$_2$ background gas is developed. The goal is to expand over the other existing databases in terms of the rotational…
Understanding the behavior of materials under irradiation is crucial for the design and safety of nuclear reactors, spacecraft, and other radiation environments. The threshold displacement energy (Ed) is a critical parameter for…
Machine learning has emerged as a novel tool for the efficient prediction of materials properties, and claims have been made that machine-learned models for the formation energy of compounds can approach the accuracy of Density Functional…
Hydrogen incorporation in native surface oxides of metal alloys often controls the onset of metal hydriding, with implications for materials corrosion and hydrogen storage. A key representative example is titania, which forms as a…
Estimation of division and death rates of lymphocytes in different conditions is vital for quantitative understanding of the immune system. Deuterium, in the form of deuterated glucose or heavy water, can be used to measure rates of…
In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3D heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural…
The appropriateness of including Hg among the transition metals has been debated for a long time. Although the synthesis of HgF$_{4}$ molecules in gas phase was reported before, the molecules show strong instabilities and dissociate.…
The proposed model concerns the 'confluent shrinking core' scenario and reproduces the desorption kinetic after the complete decay of the stoichiometric hydride ($\beta$-phase). The exact analytical solution is obtained, the numerical…
Hydrogen is deemed as an attractive energy carrier alternative to fossil fuels, and it is required to store for many applications. Physisorption is one of the promising ways to store H$_2$ for its practical applications. Covalent Organic…
Oxyhydrides have drawn attention because of their fast ion conductivity and strong reducing properties. Recently, hydride ion migration in SrTiO$_{3-x}$H$_{x}$ oxyhydride crystals has been investigated, showing that hydride ion migration is…
Machine learning has the potential to accelerate materials discovery by accurately predicting materials properties at a low computational cost. However, the model inputs remain a key stumbling block. Current methods typically use…
Recently, superhydrides have been computationally identified and subsequently synthesized with a variety of metals at very high pressures. In this work, we evaluate the possibility of synthesizing superhydrides by uniquely combining…
We present equation of state data of shock compressed hydrogen and deuterium. These have been calculated in the physical picture by using {\it ab initio} molecular dynamics simulations based on finite temperature density functional theory…
Since hydrogen has many advantages (e.g., free pollution, extensive sources, convenient storage and transportation), hydrogen-based multi-energy systems (HMESs) have received wide attention. However, existing works on the optimal operation…
Thermoelectric materials can achieve direct energy conversion between electricity and heat, thus can be applied to waste heat harvesting and solid-state cooling. The discovery of new thermoelectric materials is mainly based on experiments…