Related papers: Ab initio random structure searching for battery c…
The large number of possible structures of metal-organic frameworks (MOFs) and their limitless potential applications has motivated molecular modelers and researchers to develop methods and models to efficiently assess MOF performance. Some…
The growing demand for efficient, high-capacity energy storage systems has driven extensive research into advanced materials for lithium-ion batteries. Among the various candidates, Wadsley-Roth (WR) niobates have emerged as a promising…
We discover many new crystalline solid materials with fast single crystal Li ion conductivity at room temperature, discovered through density functional theory simulations guided by machine learning-based methods. The discovery of new solid…
Silicon materials play a key role in many technologically relevant fields, ranging from the electronic to the photovoltaic industry. A systematic search for silicon allotropes was performed by employing a modified ab initio minima hopping…
The increasing relevance of energy storage technologies demands high-capacity cathode materials for Li-ion batteries. Recently, Li-rich defect anti-fluorite Li$_5$FeO$_4$ has emerged as a high-capacity cathode material exhibiting…
The discovery and design of new materials are paramount in the development of green technologies. High entropy oxides represent one such group that has only been tentatively explored, mainly due to the inherent problem of navigating vast…
The efficiency of active learning (AL) approaches to identify materials with desired properties relies on the knowledge of a few parameters describing the property. However, these parameters are unknown if the property is governed by a high…
Challenges associated with in-service mechanical degradation of Li-ion battery cathodes has prompted a transition from polycrystalline to single crystal cathode materials. Whilst for single crystal materials, dislocation-assisted crack…
Li-ion battery (LIB) research has continuing importance for the entire range of applications from consumer products to vehicle electrification and grid stabilization. In many cases, standard electrochemical methods only provide an overall…
Generative modeling of crystal structures is significantly challenged by the complexity of input data, which constrains the ability of these models to explore and discover novel crystals. This complexity often confines de novo design…
Structurally and chemically complex materials such as amorphous metallosilicates underpin major catalytic and separation technologies, yet their intrinsic complexity challenges reliable atomistic modeling under realistic conditions.…
Metal anodes provide the highest energy density in batteries. However, they still suffer from electrode/electrolyte interface side reactions and dendrite growth, especially under fast-charging conditions. In this paper, we consider a…
LiNi0.5Mn1.5O4, which has a spinel framework structure, is a promising candidate for the cathode material of next-generation lithium-ion batteries with high energy density. We investigate the structural transition in LixNi0.5Mn1.5O4 (0 <= x…
Machine learning force fields (MLFFs), which employ neural networks to map atomic structures to system energies, effectively combine the high accuracy of first-principles calculation with the computational efficiency of empirical force…
We have studied hydrogen/lithium complexes in crystalline silicon using density-functional-theory methods and the ab initio random structure searching (AIRSS) method for predicting structures. A method based on the Maxwell construction and…
Crystal structures are indispensable across various domains, from batteries to solar cells, and extensive research has been dedicated to predicting their properties based on their atomic configurations. However, prevailing Crystal Structure…
In this paper, we introduce an approach for the prediction of capacity for over 100,000 spinel compounds relevant for battery materials, from which we propose the 20 most promising candidate materials. In the design of batteries, selecting…
As battery technologies advance toward higher stability and energy density, the need for extensive cell-level testing across various component configurations becomes critical. To evaluate performance and understand the operating principles…
Through its capability for 3D mapping of Li at the nanoscale, atom probe tomography (APT) is poised to play a key role in understanding the microstructural degradation of lithium-ion batteries (LIB) during successive charge and discharge…
High quality scanning transmission electron microscopy (STEM) data acquisition and analysis has become increasingly important due to the commercial demand for investigating the properties of complex materials such as battery cathodes;…