Sheena Agarwal
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MLIPX: machine-learned interatomic potential eXploration Open
The rapid advancement in machine-learned interatomic potentials (MLIPs) and the proliferation of universal MLIPs ( u MLIPs) have significantly broadened their application scope. Community benchmarks and leaderboard rankings are frequently …
MLIPX: Machine Learned Interatomic Potential eXploration Open
The rapid advancement in machine-learned interatomic potentials (MLIPs) and the proliferation of uni- versal MLIPs (uMLIPs) have significantly broadened their application scope. Community benchmarks and leaderboard rankings are frequently …
Copper Gallium Aluminum Mixed Metal Oxides as new Alternative Catalyst Candidates for Efficient Conversion of Carbon Dioxide to Methanol and Dimethyl Ether Open
Converting CO2 with renewable hydrogen requires high-value products to be economically viable due to its inherent energy intensity and associated renewable energy costs. Direct hydrogenation of CO2 via exothermic reactions is appealing giv…
Episodic Obsessive–Compulsive and Related Disorder Symptoms and Pica in Recurrent Depressive Disorder Open
INTRODUCTION The prevalence of obsessive–compulsive symptoms (OCSs) is common in major depression, and it impacts the quality of life and outcome.[1,2] Although the episodic nature of obsessive–compulsive disorder (OCD) is reported, it is …
Electroconvulsive Therapy in Patients With Cardiac Implantable Electronic Devices: A Case Report and Systematic Review of Published Cases. Open
Electroconvulsive therapy is a safe and efficacious treatment for major psychiatric disorders, and the presence of CIEDs should not delay or deter the use of ECT in these patients.
An Analytical Study of Economic & Demographic Factors affecting the Awareness & Purchase of Organic Foods in Meerut City. Open
Purpose- The purpose of this paper is to analyze the impact of various economic and demographic factors (income, gender, educational background & occupation) on the awareness and purchase of organic food products (F&V, Dairy Foods, Groceri…
Looking Beyond Adsorption Energies to Understand Interactions at Surface Using Machine Learning Open
Identifying factors that influence interactions at the surface is still an active area of research. In this study, we present the importance of analyzing bondlength activation, while interpreting Density Functional Theory (DFT) results, as…
Looking Beyond Adsorption Energies to Understand Interactions at Surface Using Machine Learning Open
Identifying factors that influence interactions at the surface is still an active area of research. In this study, we present the importance of analyzing bondlength activation, while interpreting Density Functional Theory (DFT) results, as…
DART: Deep Learning Enabled Topological Interaction Model for Energy Prediction of Metal Clusters and its Application in Identifying Unique Low Energy Isomers Open
Recently, Machine Learning (ML) has proven to yield fast and accurate predictions of chemical properties to accelerate the discovery of novel molecules and materials. The majority of the work is on organic molecules, and much more work nee…
DART: Deep Learning Enabled Topological Interaction Model for Energy Prediction of Metal Clusters and its Application in Identifying Unique Low Energy Isomers Open
Recently, Machine Learning (ML) has proven to yield fast and accurate predictions of chemical properties to accelerate the discovery of novel molecules and materials. The majority of the work is on organic molecules, and much more work nee…
Catching the essence of Hohenberg-Kohn's first theorem with machine learning Open
To date, density functional theory (DFT) is one of the most accurate and yet practical theory to gain insight about materials properties. Although successful, the computational cost is the main hurdle even today. In recent years, there has…
Combining DFT with ML to study size specific interactions between metal clusters and adsorbates Open
To date, density functional theory (DFT) is one of the most accurate and yet practical theory to gain insight about materials properties. Although successful, the computational cost is the main hurdle even today. A way out is combining DFT…