Rationalizing the role of structural motif and underlying electronic structure in the finite temperature behavior of atomic clusters - Susan, Anju; Joshi, Kavita (Journal of Chemical Physics, 2014)
Melting in finite size systems is an interesting but complex phenomenon. Many factors affect melting and owing to their interdependencies it is a challenging task to rationalize their roles in the phase transition. In this work, we demonstrate how structural motif of the ground state influences melting transition in small clusters. Here, we report a case with clusters of aluminum and gallium having same number of atoms, valence electrons, and similar structural motif of the ground state but drastically different melting temperatures. We have employed Born-Oppenheimer molecular dynamics to simulate the solid-like to liquid-like transition in these clusters. Our simulations have reproduced the experimental trends fairly well. Further, the detailed analysis of isomers has brought out the role of the ground state structure and underlying electronic structure in the finite temperature behavior of these clusters. For both clusters, isomers accessible before cluster melts have striking similarities and does have strong influence of the structural motif of the ground state. Further, the shape of the heat capacity curve is similar in both the cases but the transition is more spread over for Al-36 which is consistent with the observed isomerization pattern. Our simulations also suggest a way to characterize transition region on the basis of accessibility of the ground state at a specific temperature. (C) 2014 AIP Publishing LLC.

Role of facet in the competitive pathway of ethylene epoxidation - Nair, Aathira; Kenge, Nivedita; Joshi, Kavita (Surface Science, 2022)
Ethylene epoxide (EtO) is used as raw material for a broad range of products from pharmaceuticals and plastics to paints and adhesives. Although the reaction of ethylene interacting with preadsorbed oxygen on Ag surface is known for decades, the underlying mechanism of EtO formation is not completely understood. Successful investigation of oxametallacycle (OMC) intermediate common to selective as well as non-selective pathways has ensured at least 50% selectivity. The current study brings out the electronic signatures of distinct conformers of OMC stabilised on two different facets of Ag viz. (100) and (111). There are subtle differences between OMC conformers observed on these two facets with near-eclipsed on Ag(100) and near-staggered on Ag(111). A detailed analysis of Ag-O, C-O, C-C, and Ag-C interactions along with projected Density of States (pDOS) and projected Crystal Orbital Hamilton Population (pCOHP) imply towards ring closure on Ag(100) and hydrogen transfer on Ag(111). Finally, our understanding based on electronic and structural signatures are backed up by activation barriers computed through NEB calculations. Activation barrier for EtO is lower on (100) as compared to (111) facet. Thus, our study sheds light on how these differences between OMC affect the selectivity towards EtO.
Keywords: Ag(100); Ag(111); DFT; epoxidation; Ethylene Oxide (EtO); OMC

Remarkable SO2 and H2S resistant ability on CO oxidation by unique Pd/WO3 3D hollow sphere nanocatalyst: correlating structure-activity relationships on SO2 exposure - Jeyavani, Vijayakrishnan; Kondhekar, Deepali; Bhati, Meema; Dev, Sahil; Joshi, Kavita; Devi, R. Nandini; Mukherjee, Shatabdi Porel (ACS Applied Energy Materials, 2024)
We report a simple inorganic route for synthesizing a Pd/WO3 3D hollow sphere nanocatalyst, where Pd nanoparticles are encapsulated and well distributed on porous tungsten oxide nanospheres. The synthesis protocol has advantages, as it requires no surfactant or stabilizing agent, Pd loading is easily tuned, and the as-synthesized nanomaterials can be directly used as catalysts for the CO oxidation reaction. The synthesized nanocatalyst exhibited 100% CO to CO2 conversion efficiency at 260 degrees C. In addition, the nanocatalyst demonstrated remarkable SO2 (3 ppm) tolerance during the CO oxidation reaction for prolonged SO2 sulfation of 1-21 h at 260-400 degrees C. This represents the longest SO2 exposure time reported to date based on a single metal Pd/support-based nanocatalyst. No decrement in CO conversion efficiency was observed even after SO2 (3 ppm) treatment for 21 h for the first time based on a single metal Pd-based nanocatalyst. Moreover, the synthesized nanocatalyst shows H2S (4 ppm), even in situ H2S tolerance during the CO oxidation reaction at 260 degrees C for 1-3 h and exhibited less sensitivity to prolonged and stringent sulfur exposure, with the highest H2S concentration and maximum 100% CO to CO2 conversion efficiency obtained after H2S treatment for the first time based on a Pd-based nanocatalyst to the best of our knowledge. The composition and structure of the R-Pd/WO3 nanocatalyst were not much influenced, even after the prolonged SO2 and H2S exposure during the CO oxidation reaction, as verified from spent catalyst analysis. Finally, our DFT-based model provides insights into understanding the observed sulfur resistance on Pd/WO3 by analyzing the underlying electronic structure. Therefore, our strategic synthesis methodology will open up many opportunities to select Pd/metal oxide-based nanomaterials for designing highly efficient, stable, and SO2/H2S-resistant nanocomposite catalyst.
Keywords: CO oxidation; DFT calculation; nanocatalyst; palladium (Pd); SO2 andH(2)S resistant ability; structure-activityrelationships; tungstenoxide (WO3)

Retrieval augmented generation for building datasets from scientific literature - Maharana, Piyush Ranjan; Verma, Ashwini; Joshi, Kavita (Journal of Physics-Materials, 2025)
In this work, we show that employing retrieval augmented generation (RAG) with a large language model (LLM) enables us to extract accurate data from scientific literature and construct datasets. The rapid growth in publications necessitates the automation of extraction of structured data as it is crucial for training machine learning(ML) models. The pipeline developed is simple and can be adjusted accordingly with natural language as input. Quantization enables us to run LLMs on consumer hardware and remove the reliance on closed-source models. Both Llama3-8B and Gemma2-9B with RAG give structured output consistently and with high accuracy as compared to direct prompting. Using the newly developed protocol, we created a data set of metal hydrides for solid-state hydrogen storage from paper abstracts. The accuracy of the generated dataset was >88% in the cases tested. Further, we demonstrate that the generated dataset is ready-to-use for ML models by testing it with HYST to predict the H(2)wt% at a given temperature. Thus, we demonstrate a pipeline to create datasets from scientific literature at minimal computational cost and high accuracy.
Keywords: dataset building; Hydrogen storage; LLM; materials; RAG