Related papers: Bayesian Optimization of High-Entropy Alloy Compos…
Orbital-free density functional theory (OF-DFT) constitutes a computationally highly effective tool for modeling electronic structures of systems ranging from room-temperature materials to warm dense matter. Its accuracy critically depends…
We derive an exact representation of the exchange-correlation energy within density functional theory (DFT) which spawns a class of approximations leading to correct long-range asymptotic behavior. In what amounts to be the simplest…
Accurate computational predictions of metal-organic frameworks (MOFs) and their properties is crucial for discovering optimal compositions and applying them in relevant technological areas. This work benchmarks density functional theory…
Density functional theory (DFT) is used to rationalize magnetic parameters of hydrated electron trapped in alkaline glasses as observed using Electron Paramagnetic Resonance (EPR) and Electron Spin Echo Envelope Modulation (ESEEM)…
Locality of compact one-electron orbitals expanded strictly in terms of local subsets of basis functions can be exploited in density functional theory (DFT) to achieve linear growth of computation time with systems size, crucial in…
Here we describe a computational study undertaken in an effort to elucidate the reaction mechanisms behind the experimentally observed oxidations and hydrations catalyzed by graphene oxide (GO). Using the oxidation of benzyl alcohol to…
The predictive accuracy of density functional theory (DFT) for alloy formation enthalpies is often limited by intrinsic energy resolution errors, particularly in ternary phase stability calculations. In this work, we present a machine…
Density functional theory (DFT) embedding provides a formally exact framework for interfacing correlated wave-function theory (WFT) methods with lower-level descriptions of electronic structure. Here, we report techniques to improve the…
A central problem of materials science is to determine whether a hypothetical material is stable without being synthesized, which is mathematically equivalent to a global optimization problem on a highly non-linear and multi-modal potential…
High-entropy alloys are characterized by high configurational entropy. Since the discovery of high-entropy alloys (HEA) in 2004, entropy engineering has provided a promising direction for exploiting composition, lattice disorder, band…
High-entropy alloys (HEAs) are a new class of materials constructed from multiple principal elements statistically arranged on simple crystallographic lattices. Due to the large amount of disorder present, they are excellent model systems…
Pt-based electrocatalysts are the primary choice for fuel cells due to their superior oxygen reduction reaction (ORR) activity. To enhance ORR performance and durability, extensive studies have investigated transition metal alloying,…
Efficient optimization of molecules with targeted properties remains a significant challenge due to the vast size and discrete nature of chemical compound space. Conventional machine-learning-based optimization approaches typically require…
The development of oxidation-resistant high-entropy alloy (HEA) bond coats is restricted by the limited understanding of how multi-principal element interactions govern scale formation across temperatures. This study uncovers new oxidation…
The design of high-entropy alloys (HEA) with desired properties is challenging due to their large compositional space. While various machine learning (ML) models can predict specific HEA solid-solution phases (SS), predicting high-entropy…
High entropy alloys (HEAs) are multicomponent compounds whose high configurational entropy allows them to solidify into a single phase, with a simple crystal lattice structure. Some HEA's exhibit desirable properties, such as high specific…
Order versus disorder in the structure of materials plays a key role in the theoretical prediction of their properties. However, this structural description appears to be ineffective for new families of materials such as high entropy alloys…
Accelerated discovery in materials science demands autonomous systems capable of dynamically formulating and solving design problems. In this work, we introduce a novel framework that leverages Bayesian optimization over a problem…
Density functional theory (DFT) has been used as an important tool for studying activity of oxygen reduction reaction (ORR) catalysts. The dispersion effects, which are not encountered in many of the previous DFT studies for periodic…
High-entropy alloys are widely modeled as homogeneously mixed surfaces, yet the validity of this assumption for catalytic prediction remains unclear. Here, we reproduce high-throughput experimental measurements using thermodynamic…