Related papers: BEAST DB: Grand-Canonical Database of Electrocatal…
We present a new velocity-gauge real-time, time-dependent density functional tight-binding (VG-rtTDDFTB) implementation in the open-source DFTB+ software package (https://dftbplus.org) for probing electronic excitations in large, condensed…
CO2 reduction requires efficient catalysts, yet materials discovery remains bottlenecked by 10-20 year development cycles requiring deep domain expertise. This paper demonstrates how large language models can assist the catalyst discovery…
Heterogeneous gas and solid catalyst reactions occur at the atomic level, and understanding and controlling complex catalytic reactions at this level is crucial for the development of improved processes and materials. There are postulations…
Deep learning models were developed and implemented to aid the search for new heavy fermion compounds. For the purpose of these calculations a database of more than 200 heavy fermions was compiled from the literature. The deep learning…
Quantum mechanical methods like Density Functional Theory (DFT) are used with great success alongside efficient search algorithms for studying kinetics of reactive systems. However, DFT is prohibitively expensive for large scale…
Accurately determining the crystallographic structure of a material, organic or inorganic, is a critical primary step in material development and analysis. The most common practices involve analysis of diffraction patterns produced in…
The exponential growth of data is making query processing increasingly critical for modern computing infrastructure, yet the environmental impact of database operations remains poorly understood and largely overlooked. This paper presents…
Several electrochemical and electrical energy storage devices are reported every day, with the claim of outperforming the established ones. The use of newer materials and recent advanced techniques to synthesize and/or assemble them into a…
The B-Pt alloy system contains several Pt-rich phases exhibiting complex structures, many with partial site occupation. It also exhibits a deep (nearly 1000 degrees C) eutectic. We evaluate the ab-initio total energies of the crystalline…
The immersed boundary method (IB) is an elegant way to fully couple the motion of a fluid and deformations of an immersed elastic structure. In that vein, the IB2d software allows for expedited explorations of fluid-structure interaction…
We perform extensive density functional theory (DFT) calculations to determine the stability and elementary properties of 4249 previously unexplored monolayer crystals. The monolayers comprise the most stable subset (energy within 0.1…
In deep active learning, it is especially important to choose multiple examples to markup at each step to work efficiently, especially on large datasets. At the same time, existing solutions to this problem in the Bayesian setup, such as…
Heterogeneous catalysts are the most important catalysts in industrial reactions. Nanocatalysts, with size ranging from hundreds of nanometers to the atomic scale, possess activities that are closely connected to their structural…
Density functional theory (DFT) is one of the main methods in Quantum Chemistry that offers an attractive trade off between the cost and accuracy of quantum chemical computations. The electron density plays a key role in DFT. In this work,…
Video aesthetic assessment, a vital area in multimedia computing, integrates computer vision with human cognition. Its progress is limited by the lack of standardized datasets and robust models, as the temporal dynamics of video and…
We present the design and the status of the database for detector description parameters in ATLAS experiment. The ATLAS Primary Numbers are the parameters defining the detector geometry and digitization in simulations, as well as certain…
We systematically compare an event-by-event heavy-ion collision model to data from the Large Hadron Collider. Using a general Bayesian method, we probe multiple model parameters including fundamental quark-gluon plasma properties such as…
We create synthetic biometric databases to study general, fundamental, biometric principles. First, we check the validity of the synthetic database design by comparing it to real data in terms of biometric performance. The real data used…
High performance materials, from natural bone over ancient damascene steel to modern superalloys, typically possess a complex structure at the microscale. Their properties exceed those of the individual components and their knowledge-based…
A new family of Intensional RDBs (IRDBs), introduced in [1], extends the traditional RDBs with the Big Data and flexible and 'Open schema' features, able to preserve the user-defined relational database schemas and all preexisting user's…