86 citations · 174 across the 29 of their papers we have counts for
8 papers · 1 filter
The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture
Anuroop Sriram, Logan M. Brabson, Xiaohan Yu +12
Identifying useful sorbent materials for direct air capture (DAC) from humid air remains a challenge. We present the Open DAC 2025 (ODAC25) dataset, a significant expansion and imp…
Comparing classical and machine learning force fields for modeling deformation of solid sorbents relevant for direct air capture
Logan M. Brabson, Andrew J. Medford, David S. Sholl
Direct air capture (DAC) with solid sorbents such as metal-organic frameworks (MOFs) is a promising approach for negative carbon emissions. Computational materials screening can he…
Ab initio study of strain-driven vacancy clustering in aluminum
Sayan Bhowmik, Abhiraj Sharma, Andrew J. Medford +2
We present a first principles investigation of strain-driven vacancy clustering in aluminum. Specifically, we perform Kohn-Sham density functional theory calculations to study the…
The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture
Anuroop Sriram, Sihoon Choi, Xiaohan Yu +6
New methods for carbon dioxide removal are urgently needed to combat global climate change. Direct air capture (DAC) is an emerging technology to capture carbon dioxide directly fr…
Self-consistent convolutional density functional approximations: Application to adsorption at metal surfaces
Sushree Jagriti Sahoo, Qimen Xu, Xiangyun Lei +5
The exchange-correlation (XC) functional in density functional theory is used to approximate multi-electron interactions. A plethora of different functionals is available, but near…
The phase stability of large-size nanoparticle alloy catalysts at ab initio quality using a nearsighted force-training approach
Cheng Zeng, Sushree Jagriti Sahoo, Andrew J. Medford +1
CoPt nanoparticle catalysts are integral to commercial fuel cells. Such systems are prohibitive to fully characterize with electronic structure calculations. Machine-learned potent…
Ab-initio investigation of finite size effects in rutile titania nanoparticles with semilocal and nonlocal density functionals
Sushree Jagriti Sahoo, Xin Jing, Phanish Suryanarayana +1
In this work, we employ hybrid and generalized gradient approximation (GGA) level density functional theory (DFT) calculations to investigate the convergence of surface properties…
Application of DFTB and machine learning to evaluate the stability of biomass intermediates on the Rh(111) surface
Chaoyi Chang, Andrew J. Medford
Biomass compounds adsorbed on surfaces are challenging to study due to the large number of possible species and adsorption geometries. In this work, possible intermediates of eryth…