Correlation between the variation in observed melting temperatures and structural motifs of the global minima of gallium clusters: an ab initio study - Susan, Anju; Kibey, Aniruddha; Kaware, Vaibhav; Joshi, Kavita (Journal of Chemical Physics, 2013)
We have investigated the correlation between the variation in the melting temperature and the growth pattern of small positively charged gallium clusters. Significant shift in the melting temperatures was observed for a change of only few atoms in the size of the cluster. Clusters with size between 31-42 atoms melt between 500-600 K whereas those with 46-48 atoms melt around 800 K. Density functional theory based first principles simulations have been carried out on Ga-n(+) clusters with n = 31, ... , 48. At least 150 geometry optimizations have been performed towards the search for the global minima for each size resulting in about 3000 geometry optimizations. For gallium clusters in this size range, the emergence of spherical structures as the ground state leads to higher melting temperature. The well-separated core and surface shells in these clusters delay isomerization, which results in the enhanced stability of these clusters at elevated temperatures. The observed variation in the melting temperature of these clusters therefore has a structural origin. (C) 2013 American Institute of Physics. [http://dx.doi.org/10.1063/1.4772470]

Design and engineering of organic molecules for customizable terahertz tags - Ray, Shaumik; Dash, Jyotirmayee; Nallappan, Kathirvel; Kaware, Vaibhav; Basutkar, Nitin; Ambade, Ashootosh; Joshi, Kavita; Pesala, Bala (Terahertz, RF, Millimeter, and Submillimeter-Wave Technology and Applications VII, 2014)
Terahertz (THz) frequency band lies between the microwave and infrared region of the electromagnetic spectrum. Molecules having strong resonances in this frequency range are ideal for realizing "Terahertz tags" which can be easily incorporated into various materials. THz spectroscopy of molecules, especially at frequencies below 10 THz, provides valuable information on the low frequency vibrational modes, viz. intermolecular vibrational modes, hydrogen bond stretching, torsional vibrations in several chemical and biological compounds. So far there have been very few attempts to engineer molecules which can demonstrate customizable resonances in the THz frequency region. In this paper, Diamidopyridine (DAP) based molecules are used as a model system to demonstrate engineering of THz resonances (< 10 THz) by fine-tuning the molecular mass and bond strengths. Density Functional Theory (DFT) simulations have been carried out to explain the origin of THz resonances and factors contributing to the shift in resonances due to the addition of various functional groups. The design approach presented here can be easily extended to engineer various organic molecules suitable for THz tags application.

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.

Scaling up the shape: a novel growth pattern of gallium clusters - Kaware, Vaibhav; Joshi, Kavita (Journal of Chemical Physics, 2014)
Putative global minima for Ga+N clusters with size ``N'' ranging from 49 to 70 are found by employing the Kohn-Sham formulation of the density functional theory, and their evolution is described and discussed in detail. We have discovered a unique growth pattern in these clusters, all of which are hollow core-shell structures. They evolve with size from one spherical core-shell to the next spherical core-shell structure mediated by prolate geometries, with an increase in overall diameter of the core, as well as the shell, without putting on new layers of atoms. We also present a complete picture of bonding in gallium clusters by critically analyzing the molecular orbitals, the electron localization function, and Bader charges. Bonding in these clusters is a mixture of metallic and covalent type that leans towards covalency, accompanied by marginal charge transfer from the surface to the core. Most molecular orbitals of Ga clusters are non-jellium type. Covalency of bonding is supported by a wide localization window of electron localization function, and joining of its basins along the bonds. (C) 2014 AIP Publishing LLC.

Multifaceted thermodynamics of Pb-n (n=16-24) clusters: a case study - Susan, Anju; Kaware, Vaibhav; Joshi, Kavita (Journal of Physical Chemistry C, 2015)
Thermodynamic response of small clusters is a challenging area of exploration, both experimentally and theoretically. In this article, we study the thermodynamic behavior of small Pb clusters (size 16-24) using Born-Oppenheimer molecular dynamics. A new ground state structure is reported for Pb-20. Except for Pb-21, all clusters fragment at temperatures above T-m[bulk] and show no signs of melting. Characteristic behavior like restricted diffusion and solid solid transition is discussed in detail. Variation in the isomerization temperature of these clusters is explained using the bond length analysis. Root mean square bond length fluctuations (delta(rms)) along with distribution of atoms about center of mass of the cluster as a function of time and distance-energy (DE) plots are used to bring out the essential features of Pb cluster thermodynamics. Analysis carried out using these parameters, and their interpretation regarding state of the system, are discussed in detail. We highlight that it is not possible to define ``liquid state'' for these small clusters, in the conventional frame of understanding.

Partial ionic bonding in homogeneous sodium clusters - Kaware, Vaibhav; Joshi, Kavita (Condensed Matter Physics, 2015)
In this work, we report an interesting observation of partial ionic bonding due to charge transfer in homogeneous sodium clusters. The charge transfer causes the electronic charge to accumulate on the surface, and the resulting charges on atoms range between +0.4 to -1.0 |e^-|. We also demonstrate that this disparity among effective charges on atoms is geometry dependent, such that atoms experiencing similar surrounding, have equal effective charge. It is speculated that this phenomenon will occur among other homogeneous clusters as well, and its extent will be defined by the valence electron delocalization.

Pt-nanoparticle functionalized carbon nano-onions for ultra-high energy supercapacitors and enhanced field emission behaviour - Suryawanshi, Sachin R.; Kaware, Vaibhav; Chakravarty, Disha; Walke, Pravin S.; More, Mahendra A.; Joshi, Kavita; Rout, Chandra Sekhar; Late, Dattatray J. (RSC Advances, 2015)
In the present work, we have investigated the charge storage capacitive response and field emission behaviour of platinum (Pt) nanoparticles decorated on carbon nano onions (CNOs) and compared them with those of pristine carbon nano onions. The specific capacitance observed for Pt-CNOs is 342.5 F g(-1), about six times higher than that of pristine CNOs, at a scan rate of 100 mV s(-1). The decoration with Pt nanoparticles, without any binder or polymer separator on the CNO, leading to enhanced supercapacitance is due to easy accessibility of Na2SO4 electrolyte in the active material. The Density Functional Theory (DFT) calculations of these systems reveal enhancement in the Density of States (DOS) near the Fermi energy (E-F) on account of platinum decoration on the CNOs. Furthermore, the field emission current density of similar to 0.63 mA cm(-2) has been achieved from the Pt-CNOs emitter at an applied electric field of similar to 4.5 V mu m(-1) and from the pristine CNOs sample current density of similar to 0.4 mA cm(-2) has been achieved at an applied electric field of similar to 6.6 V mu m(-1). The observed enhanced field emission behavior has been attributed to the improved electrical conductivity and increased emitting sites of the Pt-CNO emitter. The field emission current stability of the Pt-CNO emitter over a longer duration is found to be good. The observed results imply multifunctional potential of Pt-CNOs, as supercapacitor material in various next generation hybrid energy storage devices, and field emitters for next generation vacuum nano/microelectronic devices.

Terahertz spectroscopy and solid-state density functional theory calculations of cyanobenzaldehyde isomers - Dash, Jyotirmayee; Ray, Shaurnik; Nallappan, Kathirvel; Kaware, Vaibhav; Basutkar, Nitin B.; Gonnade, Rajesh G.; Ambade, Ashootosh V.; Joshi, Kavita; Pesala, Bala (Journal of Physical Chemistry A, 2015)
Spectral signatures in the terahertz (THz) frequency region are mainly due to bulk vibrations of the molecules. These resonances are highly sensitive to the relative position of atoms in a molecule as well as the crystal packing arrangement. To understand the variation of THz resonances, THz spectra (2-10 THz) of three structural isomers: 2-, 3-, and 4-cyanobenzaldehyde have been studied. THz spectra obtained from Fourier transform infrared (FTIR) spectrometry of these isomers show that the resonances are distinctly different especially below 5 THz. For understanding the intermolecular interactions due to hydrogen bonds, four molecule cluster simulations of each of the isomers have been carried out using the B3LYP density functional with the 6-31G(d,p) basis set in Gaussian09 software and the compliance constants are obtained. However, to understand the exact reason behind the observed resonances, simulation of each isomer considering the full crystal structure is essential. The crystal structure of each isomer has been determined using X-ray diffraction (XRD) analysis for carrying out crystal structure simulations. Density functional theory (DFT) simulations using CRYSTAL14 software, utilizing the hybrid density functional B3LYP, have been carried out to understand the vibrational modes. The bond lengths and bond angles from the optimized structures are compared with the XRD results in terms of root-mean-square-deviation (RMSD) values. Very low RMSD values confirm the overall accuracy of the results. The simulations are able to predict most of the spectral features exhibited by the isomers. The results show that low frequency modes (<3 THz) are mediated through hydrogen bonds and are dominated by intermolecular vibrations.

Nature of electrophilic oxygen: insights from periodic density functional theory investigations - Kenge, Nivedita; Pitale, Sameer; Joshi, Kavita (Surface Science, 2019)
Increasing demand of ethylene oxide and the cost of versatile chemical ethene has been a driving force for understanding mechanism of epoxidation to develop highly selective catalytic process. Direct epoxidation is a proposed mechanism which in theory provides 100% selectivity. A key aspect of this mechanism is an electrophilic oxygen (O-ele) species forming on the Ag surface. In the past two and half decades, large number of theoretical and experimental investigations have tried to elucidate formation of O-ele, on Ag surface with little success. Equipped with this rich literature on Ag-O interactions, we investigate the same using periodic DFT calculations to further understand how silver surface and oxygen interact with each other from a chemical standpoint. Based on energetics, Lowdin charges, topologies and pdos data described in this study, we scrutinize the established notions of O-ele. Our study provides no evidence in support of O-ele, being an atomic species nor a diatomic molecular species. In fact, a triatomic molecular species described in this work bears multiple signatures which are very convincing evidence for considering it as the most sought for electrophilic entity.
Keywords: Ag(100); DFT; Electrophilic; epoxidation; Nucleophilic oxygen

Agro-waste extracted cellulose supported silver phosphate nanostructures as a green photocatalyst for improved photodegradation of RhB dye and industrial fertilizer effluents - Dwivedi, Pravin K.; Nair, Aathira; Mehare, Rupali S.; Chaturvedi, Vikash; Joshi, Kavita; Shelke, V. Manjusha (Nanoscale Advances, 2020)
The efficiency and reusability of photocatalysts are the dominant factors for their pragmatic use. The visible light induced semiconductor silver phosphate is a superior photocatalyst effective under visible light but its stability is still an undiscussed issue. To overcome this stability issue in this present manuscript, eco-friendly agro-waste extracted cellulose supported silver phosphate nanostructures have been designed for the first time through a simple chemical process. At first, silver phosphate nanostructures were synthesized by the co-precipitation method. Then, different weights of cellulose were added to the silver nitrate solution to form cellulose supported silver phosphate nanostructures. The photodegradation efficiency for each weight ratio was examined in which the photocatalyst Ag-8 nanostructures showed a high rate (0.024 min(-1)) for degradation of Rhodamine B (RhB) using a low intensity tungsten bulb. Real sample analysis has also been carried out using this photocatalyst for the degradation of industrial fertilizer effluents. The degradation rate of all the nanostructures was found to be high in comparison to pristine silver phosphate as well as the extracted bare cellulose. The photocatalytic activity is enhanced because of the participation of cellulose as a support which makes an interface for silver phosphate and assists it in delaying the charge recombination period under visible light. To understand the photochemical reaction of electrons and holes, scavenger studies were also performed.

Experimental and theoretical investigations of the effect of heteroatom-doped carbon microsphere supports on the stability and storage capacity of nano-Co3O4 conversion anodes for application in lithium-ion batteries - Dwivedi, Pravin K.; Nair, Aathira; Mehare, Rupali S.; Chaturvedi, Vikash; Joshi, Kavita; Shelke, V, Manjusha (Nanoscale Advances, 2020)
Conversion-type anode materials have been intensely studied for application in Li-ion batteries (LIBs) due to their potentially higher capacities than current graphite-based anodes. This work reports the development of a high-capacity and stable anode from a nanocomposite of N and S co-doped carbon spheres (NSCSs) with Co3O4 (NSCS-Co3O4). A hydrothermal reaction of saccharose withl-cysteine was carried out, followed by its carbonization. CSs when used as supports for conversion-type materials provide efficient electron/ion transfer channels, enhancing the overall electrochemical performance of the electrodes. Additionally, the heteroatoms doped in a carbon matrix alter the electronic properties, often increasing the reactivity of the carbon surface, and they are reported to be effective for anchoring metal oxide nanoparticles. Consequently, the NSCS-Co3O4 nanocomposites developed in this work exhibit enhanced and stable reversible specific capacity over several cycles. Stable cycling behavior was observed at 1 A g(-1)with 1285 mA h g(-1) of specific capacity retained after 350 cycles along with more than 99% of coulombic efficiency. This material shows excellent rate capability with a specific capacity of 745 mA h g(-1) retained even at a high current density of 5 A g(-1). Detailed DFT-based calculations revealed the role of doped supports in controlling the volume expansion upon lithiation.

Mixed metal oxide: a new class of catalyst for methanol activation - Mehta, Shweta; Agarwal, Sheena; Kenge, Nivedita; Mekala, Siva Prasad; Patil, Vipul; Raja, T.; Joshi, Kavita (Applied Surface Science, 2020)
In this work, we propose a mixed metal oxide as a catalyst and demonstrate it's ability to not only activate the MeOH molecule upon adsorption but also dissociate O-H and one of it's C-H bonds. MeOH activation is compared on two prominent facets of ZnAl(2)O(4 )viz. (2 2 0) and (31 1). While spontaneous O-H bond dissociation is observed on both facets, C-H bond dissociates only on the (3 1 1) surface. Multiple factors like atomic arrangement and steps on the surface, coordination of surface atoms, and their effective charges have a combined effect on MeOH activation. The (3 1 1) surface offers higher catalytic activity in comparison with (2 2 0) surface. Having a stepped surface, availability of multiple sites, and variation in the charge distribution are some of the reasons for better catalytic performance of (3 1 1) facet. Effect of orientation of MeOH with respect to the surface adds both, information and complexity to the problem. Observations pertinent to understanding this effect are also reported. A detailed analysis of atomic arrangement on the two surfaces provides a rationale as to why MeOH gets dissociated spontaneously on the mixed metal oxide. The promising results reported here opens up a new class of catalyst for research.
Keywords: DFT; MeOH; Spontaneous dissociation; ZnAl2O4

Understanding the ML black box with simple descriptors to predict cluster-adsorbate interaction energy - Agarwal, Sheena; Mehta, Shweta; Joshi, Kavita (New Journal of Chemistry, 2020)
Density functional theory (DFT) is currently one of the most accurate and yet practical theories used to gain insight into the properties of materials. Although successful, the computational cost required is still the main hurdle even today. In recent years, there has been a trend of combining DFT with Machine Learning (ML) to reduce the computational cost without compromising accuracy. Finding the right set of descriptors that are simple to understand in terms of giving insights about the problem at hand, lies at the heart of any ML problem. In this work, we demonstrate the use of nearest neighbor (NN) distances as descriptors to predict the interaction energy between the cluster and an adsorbate. The model is trained over a size range of 5 to 75 atom clusters. When the training and testing is carried out on mutually exclusive cluster sizes, the mean absolute error (MAE) in predicting the interaction energy is similar to 0.24 eV. MAE reduces to 0.1 eV when testing and training sets include information from the complete range. Furthermore, when the same set of descriptors are tested over individual sizes, the MAE further reduces to similar to 0.05 eV. We bring out the correlation between dispersion in the nearest neighbor distances and variation in MAE for individual sizes. Our detailed and extensive DFT calculations provide a rationale as to why nearest neighbor distances work so well. Finally, we also demonstrate the transferability of the ML model by applying the same recipe of descriptors to systems of different elements like (Na-10), bimetallic systems (Al6Ga6, Li4Sn6, and Au40Cu40) and also different adsorbates (N-2, O-2, and CO).

Copolymers of bipyridinium and metal (Zn & Ni) porphyrin derivatives; theoretical insights and electrochemical activity towards CO2 - Kochrekar, Sachin; Kalekar, Ajit; Mehta, Shweta; Damlin, Pia; Salomaki, Mikko; Granroth, Sari; Meltola, Niko; Joshi, Kavita; Kvarnstrom, Carita (RSC Advances, 2021)
This study reports the electropolymerization of novel keto functionalized octaethyl metal porphyrins (Zn2+ and Ni2+) in the presence of 4,4 `-bipyridine (4,4 `-bpy) as a bridging nucleophile. The polymer films were characterized by electrochemical, spectroscopic (UV-Vis, XPS, FT-IR and Raman spectroscopy) and imaging (AFM and SEM) techniques. The absorption and electronic spectra confirm the presence of both porphyrin and 4,4 `-bipyridine units in the film. The surface morphology reveals homogeneous film deposition with average roughness values of approx. 8 nm. The theoretical studies performed offered insights into the interplay of different metal centres (Zn2+ and Ni2+) and the keto functionality of the porphyrin unit in the formation of copolymer films. The electrochemical interaction of polymer films with CO2 suggests a reversible trap and release of CO2 with low energy barriers for both the polymers.

DART: deep learning enabled topological interaction model for energy prediction of metal clusters and its application in identifying unique low energy isomers - Modee, Rohit; Agarwal, Sheena; Verma, Ashwini; Joshi, Kavita; Priyakumar, U. Deva (Physical Chemistry Chemical Physics, 2021)
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 needs to be done for inorganic molecules, especially clusters. In the present work, we introduce a simple topological atomic descriptor called TAD, which encodes chemical environment information of each atom in the cluster. TAD is a simple and interpretable descriptor where each value represents the atom count in three shells. We also introduce the DART deep learning enabled topological interaction model, which uses TAD as a feature vector to predict energies of metal clusters, in our case gallium clusters with sizes ranging from 31 to 70 atoms. The DART model is designed based on the principle that the energy is a function of atomic interactions and allows us to model these complex atomic interactions to predict the energy. We further introduce a new dataset called GNC_31-70, which comprises structures and DFT optimized energies of gallium clusters with sizes ranging from 31 to 70 atoms. We show how DART can be used to accelerate the process of identification of low energy structures without geometry optimization. Albeit using a topological descriptor, DART achieves a mean absolute error (MAE) of 3.59 kcal mol(-1) (0.15 eV) on the test set. We also show that our model can distinguish core and surface atoms in the Ga-70 cluster, which the model has never encountered earlier. Finally, we demonstrate the transferability of the DART model by predicting energies for about 6k unseen configurations picked up from molecular dynamics (MD) data for three cluster sizes (46, 57, and 60) within seconds. The DART model was able to reduce the load on DFT optimizations while identifying unique low energy structures from MD data.

Disordered but efficient: understanding the role of structure and composition of the Co-Pt alloy on the electrocatalytic methanol oxidation reaction - Dalavi, Shankar B.; Agarwal, Sheena; Deshpande, Pooja; Joshi, Kavita; Bhagavatula L. V. Prasad (Journal of Physical Chemistry C, 2021)
A systematic investigation of the electrocatalytic Methanol Oxidation Reaction (MOR) was carried out using a model Co:Pt alloy system with different compositions and structural arrangements of the Co and Pt atoms. The structural variations with the same alloy composition included those with disordered arrangement of Co and Pt atoms in a face-centered cubic (fcc) lattice and ordered arrangements in face-centered tetragonal (fct) lattices. Our investigations clearly show that structures with disordered arrangements with Co:Pt atomic ratios near to 1:1 display better electrocatalytic efficiencies even when compared to pure Pt. These experimental findings were then rationalized by means of Density Functional Theory (DFT) calculations. Electronic level signatures in terms of charge transfer and relative shift in the peaks of the d band for surface metal atoms are proposed to be the reasons for the superior catalytic activity of a particular composition over the others. An increase in the number of inequivalent sites for methanol adsorption in disordered systems appears to result in better catalytic performance in comparison with ordered systems.

Lowering the C-H bond activation barrier of methane by means of SAC@Cu(111): periodic DFT investigations - Bhati, Meema; Dhumal, Jignesh; Joshi, Kavita (New Journal of Chemistry, 2021)
Methane has long captured the world's attention for being the simplest yet one of the most notorious hydrocarbons. Exploring its potential to be converted into value-added products has raised compelling interest. In the present work, we have studied the efficiency of single-atom catalysts (SACs) for methane activation employing density functional theory (DFT). The climbing image-nudged elastic band (CI-NEB) method is used in tandem with the improved dimer (ID) method to determine the minimum energy pathway for the first C-H bond dissociation of methane. Our study reported that the transition-metal doped Cu(111) surfaces enhance the adsorption, activate the C-H bond, and reduce the activation barrier for first C-H bond cleavage of methane. The results suggest Ru-/Co-/Rh-doped Cu(111) as promising candidates for methane activation with a minimal activation barrier and a less endothermic reaction. For these SACs, the calculated activation barriers for the first C-H bond cleavage are 0.17 eV, 0.24 eV, and 0.26 eV respectively, which is substantially lower than 1.13 eV, the activation barrier for Cu(111).

From molecular adsorption to decomposition of methanol on various ZnO facets: a periodic DFT study - Mehta, Shweta; Joshi, Kavita (Applied Surface Science, 2022)
Methanol is an interesting and important molecule to study because of its potential to replace existing fuels. It is also a prominent hydrogen source which can be used to generate hydrogen in-situ. ZnO is widely used as catalyst in synthesis of methanol from CO2 at industrial scale. In this work, we demonstrate that the same catalyst could be used for MeOH decomposition. We have investigated interaction of methanol with various flat and stepped facets of ZnO by employing Density Functional Theory (DFT). Two flat [(10(1)overbar 0) and (11(2)overbar 0)] and two stepped [(10(1)overbar 3) and (11(2)overbar 2)] facets are studied in detail for methanol adsorption. Chemisorption of MeOH with varying strength is common to all four facets. Most importantly spontaneous dissociation of O-H bond of methanol is observed on all facets except (11(2)overbar 0). Our DFT calculations reveal that molecular adsorption is favored on flat facets, while dissociation is favored on step facets. Also, (10(1)overbar 0) facet undergoes substantial reconstruction upon MeOH adsorption. Activation of C-H bond along with strengthening of C-O bond on ZnO facets suggest partial oxidation of methanol. With our DFT investigations, we dig deeper into the underlying electronic structure of various facets of ZnO and provide rationale for the observed facet dependent interaction of ZnO with MeOH.
Keywords: DFT; MeOH; Surface interactions; ZnO

Looking beyond adsorption energies to understand interactions at surface using machine learning - Agarwal, Sheena; Joshi, Kavita (ChemistrySelect, 2022)
Identifying factors that influence interactions at the surface is still an active area of research. In this work, the importance of analyzing bond length activations (BLact) along with adsorption energies (E-a) while interpreting Density Functional Theory (DFT) results is emphasized. Investigating adsorption of different small molecules, such as O-2, N-2, CO, and CO2, on commonly studied facets ((100), (110), and (111)) of seven fcc transition metal surfaces (M=Ag, Au, Cu, Ir, Rh, Pt, and Pd) demonstrates the missing linear correlation between E-a and BLact. Further, tree based Machine Learning (ML) models reinforce the missing linear correlation between the two parameters and also highlight the importance of analyzing both to develop a better understanding of adsorption at surfaces. The best performing Random Forest models have a mean absolute error (MAE) of 0.19 eV for E-a prediction, and even lower MAE of 0.012 angstrom for BLact prediction. While often d-band center is correlated with E-a, our observations show that infact the d-band center has a better correlation with BLact. These observations emphasizes the role of BLact in gaining a fuller picture for catalysis. The fact that the factors responsible for BLact is a lesser-explored subject adds to the novelty of the findings.
Keywords: Adsorption energy; Bondlength activation; catalysis; DFT; machine learning

Predicting the redox potentials of phenazine derivatives using DFT-assisted machine learning - Ghule, Siddharth; Dash, Soumya Ranjan; Bagchi, Sayan; Joshi, Kavita; Vanka, Kumar (ACS Omega, 2022)
This study investigates four machine-learning (ML) models to predict the redox potentials of phenazine derivatives in dimethoxyethane using density functional theory (DFT). A small data set of 151 phenazine derivatives having only one type of functional group per molecule (20 unique groups) was used for the training. Prediction accuracy was improved by a combined strategy of feature selection and hyperparameter optimization, using the external validation set. Models were evaluated on the external test set containing new functional groups and diverse molecular structures. High prediction accuracies of R2 > 0.74 were obtained on the external test set. Despite being trained on the molecules with a single type of functional group, models were able to predict the redox potentials of derivatives containing multiple and different types of functional groups with good accuracies (R2 > 0.7). This type of performance for predicting redox potential from such a small and simple data set of phenazine derivatives has never been reported before. Redox flow batteries (RFBs) are emerging as promising candidates for energy storage systems. However, new green and efficient materials are required for their widespread usage. We believe that the hybrid DFT-ML approach demonstrated in this report would help in accelerating the virtual screening of phenazine derivatives, thus saving computational and experimental costs. Using this approach, we have identified promising phenazine derivatives for green energy storage systems such as RFBs.

Pseudo-boehmite AlOOH supported NGr composite-based air electrode for mechanically rechargeable Zn-air battery applications - Kharabe, Geeta Pandurang; Manna, Narugopal; Nadeema, Ayasha; Singh, Santosh K.; Mehta, Shweta; Nair, Aathira; Joshi, Kavita; Kurungot, Sreekumar (Journal of Materials Chemistry A, 2022)
Both mechanically and electrically rechargeable zinc-air batteries (ZABs) have received much interest due to their high energy density and suitability for mobile and stationary applications. However, their commercialization has been impeded by the lack of robust, low-cost and environmentally benign catalyst materials that can be easily scaled up. In this context, the present work introduces a new type of transition metal-free catalytic material (AlOOH/NGr) by anchoring the pseudo-boehmite phase of aluminium oxyhydroxide (AlOOH) nanosheets over nitrogen-doped graphene (NGr) via a single-step and straightforward hydrothermal process. Furthermore, density functional theory (DFT) based computation demonstrates that the nucleation of AlOOH starts from the N-sites and points towards the strong surface interaction between AlOOH and NGr via doped nitrogen. AlOOH/NGr consisting of thin layered pseudo-boehmite sheets uniformly distributed over NGr has displayed an oxygen reduction reaction onset potential of 0.83 V and a half-wave potential of 0.72 V, along with good catalytic durability in alkaline medium. With this, AlOOH/NGr, when used as an air electrode for fabricating a primary Zn-air battery, the system has exhibited an open circuit voltage of similar to 1.27 V with a flat discharge profile at a current rate of 10 mA cm(-2). The fabricated system delivered a specific capacity of similar to 720 mA h g(-1) and a high power density of 204 mW cm(-2) and is comparable to the counterpart system based on the state-of-the-art Pt/C (20 wt% Pt) cathode. Additionally, the homemade battery was able to maintain its performance after 4 times of mechanical recharging of the battery, which lasted for more than 35 h at a discharge current density of 10 mA cm(-2). Thus, we have uncovered the potential of an earth-abundant metal-based catalytic system for fabricating and demonstrating a robust mechanically rechargeable zinc-air battery.

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

Baby step in assembling and integrating the components of an artificial photosynthesis device with forced heterojunctions towards improved efficiency - Salgaonkar, Kranti N.; Bajpai, Himanshu; Mhamane, Nitin B.; Nalajala, Naresh; Chauhan, Inderjeet; Thakkar, Kavita; Joshi, Kavita; Gopinath, Chinnakonda S. (Journal of Materials Chemistry A, 2023)
How to achieve unassisted, economical, scalable, and sustainable artificial photosynthesis for liquid fuels/products with improved solar-to-fuel efficiency (STFE) to address a carbon-neutral economy remains a big question. To a large degree, the extent of charge separation at heterojunction interfaces and charge utilization determine the STFE. Towards this, BiVO3 is assembled from ionic-precursors into TiO2 pores, and integrated structurally and electronically with TiO2 on calcination as BiVO4 quantum dots (BVQDs). BVQDs in TiO2 (BVT) pores lead to an all-inorganic system with a sub-quadrillion number of heterojunctions in a 1 cm(2) device (contains similar to 25 mu g of BiVO4 (similar to 2.5 wt%) in the nanopores of similar to 975 mu g of TiO2 (similar to 97.5 wt%)) and facilitate artificial photosynthesis. We demonstrate 31-38% STFE with a photon to chemical conversion turn over frequency (ToF(P2C)) of 2.73 s(-1) with a 1 cm(2) wireless BiVO4-TiO2 artificial leaf (BVT-AL) device for HCHO and CH3OH. The sequential nature of CO2 reduction to HCHO and then to CH3OH is evident from the reaction results. (CO2)-C-13 isotopic labeling experiments confirm that the input CO2 is the source for product formation. A large increase in the photocurrent density and incident photon-to-current efficiency (IPCE) of BVT, over 100% for the BiVO4 photoanode in visible light, demonstrates and supports efficient visible light absorption, charge separation and migration to the redox sites. A device has been demonstrated to show sustainable activity in direct sunlight, and addresses scalability from 1 to 9 cm(2). Assuming no change (50% decrease) in the STFE, a 6.74 m(2) device is expected to convert 1 (0.5) kg h(-1) CO2 into C1-oxygenates in sunlight. DFT calculations carried out with anatase TiO2 (101) and BiVO4 (121) interfaces support many of the experimental findings, including electron flow from the latter to the former, and interaction of the oxygen of TiO2 with BiVO4 and vice versa at the interface towards forced heterojunctions.

Electronic fingerprints for diverse interactions of methanol with various Zn-based systems - Mehta, Shweta; Joshi, Kavita (Surface Science, 2023)
We have investigated various Zn-based catalysts for their interaction with methanol (MeOH). MeOH is one of the most critical molecules being studied extensively, and Zn-based catalysts are widely used in many industrially relevant reactions involving MeOH. We note that the same element (Zn and O, in the present study) exhibits different catalytic activity in different environments. The changing environment is captured in the underlying electronic structure of the catalysts. In the present work, we compared the electronic structure of Zn-based systems, i.e., ZnAl2O4 and ZnO along with oxygen preadsorbed Zn (O-Zn) and metallic Zn. We demonstrate the one-to-one correlation between the pDOS of the bare facet and the outcome of that facet's interaction (i.e. either adsorption or dissociation of MeOH) with MeOH. These findings would pave the way towards the in-silico design of catalysts.
Keywords: DFT; Electronic properties; Methanol; Zn-based systems; ZnO

Hydrogen from catalytic non-thermal plasma-assisted steam methane reforming reaction - Bajpai, Abhinav; Mehta, Shweta; Joshi, Kavita; Kumar, Sushant (International Journal of Hydrogen Energy, 2023)
Steam methane reforming reaction was carried out in a dielectric barrier plasma reactor. A systematic study is conducted to understand the influence of input power, flow rate, and water for the conversion, yield, and selectivity of the reaction over strategically designed catalysts. In particular, the production rate and selectivity of the products (H2, CO and C2 hydrocarbons) are monitored. CeO2 was used as packing material, mixed with oxides of manganese or copper and their combination. The optimum Cu/CeO2 catalyst illustrated the production rate of 248.7 mmolg-1h-1 and 11.25 mmolg-1h-1 for H2, and CO, respectively at specific energy input of 19.8 JL-1. DFT calculations exhibit apparent change in electronic structure of the CeO2 after inclusion of oxides of manganese and copper that enhance interaction with methane. Based on these findings, a plausible mechanism is elucidatedSteam methane reforming reaction was carried out in a dielectric barrier plasma reactor. A systematic study is conducted to understand the influence of input power, flow rate, and water for the conversion, yield, and selectivity of the reaction over strategically designed catalysts. In particular, the production rate and selectivity of the products (H2, CO and C2 hydrocarbons) are monitored. CeO2 was used as packing material, mixed with oxides of manganese or copper and their combination. The optimum Cu/CeO2 catalyst illustrated the production rate of 248.7 mmolg-1h-1 and 11.25 mmolg-1h-1 for H2, and CO, respectively at specific energy input of 19.8 JL-1. DFT calculations exhibit apparent change in electronic structure of the CeO2 after inclusion of oxides of manganese and copper that enhance interaction with methane. Based on these findings, a plausible mechanism is elucidated which can help to design catalyst for other applications in non-thermal plasma atmosphere. & COPY; 2023 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Keywords: DFT; Dielectric barrier discharge; Non-thermal plasma; selectivity; Specific energy input; Steam methane reforming

MeGen-generation of gallium metal clusters using reinforcement learning - Modee, Rohit; Verma, Ashwini; Joshi, Kavita; Priyakumar, U. Deva (Machine Learning-Science and Technology, 2023)
The generation of low-energy 3D structures of metal clusters depends on the efficiency of the search algorithm and the accuracy of inter-atomic interaction description. In this work, we formulate the search algorithm as a reinforcement learning (RL) problem. Concisely, we propose a novel actor-critic architecture that generates low-lying isomers of metal clusters at a fraction of computational cost than conventional methods. Our RL-based search algorithm uses a previously developed DART model as a reward function to describe the inter-atomic interactions to validate predicted structures. Using the DART model as a reward function incentivizes the RL model to generate low-energy structures and helps generate valid structures. We demonstrate the advantages of our approach over conventional methods for scanning local minima on potential energy surface. Our approach not only generates isomer of gallium clusters at a minimal computational cost but also predicts isomer families that were not discovered through previous density-functional theory (DFT)-based approaches.
Keywords: gallium clusters; reinforcement learning; structure generation

Photoinduced CO2 and N2 reductions on plasmonically enabled gallium oxide - Ojha, Niwesh; Thakkar, Kavita; Bajpai, Abhinav; Joshi, Kavita; Kumar, Sushant (Journal of Colloid and Interface Science, 2023)
Ag-containing ZnO/ b-Ga2O3 semiconductor, which exhibit reduced bandgap, increased light absorption, and hydrophilicity, have been found to be useful for photocatalytic CO2 reduction and N2 fixation by water. The charge-separation is facilitated by the new interfaces and inherent vacancies. The Ag@GaZn demonstrated the highest photocurrent response, about 20-and 2.27-folds that of the Ga and GaZn sam-ples, respectively. CO, CH4, and H2 formed as products for photo-reduction of CO2. Ag@GaZn catalyst exhibited the highest AQY of 0.121 % at 400 nm (31.2 W/m2). Also, Ag@GaZn generated 740 lmolg-1 of NH4+ ions, which was about 18-folds higher than Ga sample. In situ DRIFTS for isotopic-labelled 13CO2 and 15N2 reaffirmed the photo-activity of as-synthesized catalysts. Density functional theory pro-vided insight into the relative affinity of different planes of heterostructures towards H2O, CO2 and N2 molecules. The structure-photoactivity rationale behind the intriguing Ag@GaZn sample offers a funda-mental insight into the role of plasmonic Ag and design principle of heterostructure with improved pho-toactivity and stability.(c) 2022 Elsevier Inc. All rights reserved.
Keywords: CO2 reduction; DRIFTS density functional theory; hydrophilicity; Photocurrent response

Aluminium, nitrogen-dual-doped reduced graphene oxide Co-existing with cobalt-encapsulated graphitic carbon nanotube as an activity modulated electrocatalyst for oxygen electrocatalyst for oxygen electrochemistry applications - Kharabe, Geeta Pandurang; Barik, Sidharth; Veeranmaril, Sudheesh Kumar; Nair, Aathira; Illathvalappil, Rajith; Yoyakki, Athira; Joshi, Kavita; Vinod, Chathakudath Prabhakaran; Kurungot, Sreekumar (Small, 2024)
There is a rising need to create high-performing, affordable electrocatalysts in the new field of oxygen electrochemistry. Here, a cost-effective, activity-modulated electrocatalyst with the capacity to trigger both the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) in an alkaline environment is presented. The catalyst (Al, Co/N-rGCNT) is made up of aluminium, nitrogen-dual-doped reduced graphene oxide sheets co-existing with cobalt-encapsulated carbon nanotube units. Based on X-ray Absorption Spectroscopy (XAS) studies, it is established that the superior reaction kinetics in Al, Co/N-rGCNT over their bulk counterparts can be attributed to their electronic regulation. The Al, Co/N-rGCNT performs as a versatile bifunctional electrocatalyst for zinc-air battery (ZAB), delivering an open circuit potential approximate to 1.35 V and peak power density of 106.3 mW cm-2, which are comparable to the system based on Pt/C. The Al, Co/N-rGCNT-based system showed a specific capacity of 737 mAh gZn-1 compared to 696 mAh gZn-1 delivered by the system based on Pt/C. The DFT calculations indicate that the adsorption of Co in the presence of Al doping in NGr improves the electronic properties favoring ORR. Thus, the Al, Co/N-rGCNT-based rechargeable ZAB (RZAB) emerges as a highly viable and affordable option for the development of RZAB for practical applications. This manuscript reports the development of a new bifunctional catalyst that exhibits high activity and stability under practical operating conditions. The catalyst (Al, Co/N-rGCNT) is made up of aluminium, nitrogen-dual-doped reduced graphene oxide sheets co-existing with the in situ formed cobalt-encapsulated CNT units is synthesized by a scalable pyrolysis method in an inert Ar atmosphere. The developed electrocatalyst achieved enhanced the oxygen reduction reaction (ORR) and the oxygen evolution reaction OER activity as a result of the favorable synergistic modulations and the system can serve as a process-friendly air-electrode for rechargeable zinc-air battery (RZAB). image
Keywords: Al; Bifunctional catalyst; DFT study; encapsulated structure; N-dual doping; Oxygen Evolution Reaction; oxygen reduction reaction; rechargeable zinc-air battery; X-ray absorption spectroscopy

Exploring the catalytic potential of Mg-Cu alloys for enhanced activity toward CO2 hydrogenation - Thakkar, Kavita; Joshi, Kavita (Molecular Catalysis, 2024)
CO2, a well-known greenhouse gas, is a potential raw material that can produce various chemicals. Dissociation of CO2 to CO or hydrogenation to formate (HCOO*) or carboxyl (COOH*) intermediate is crucial in determining the reaction pathway for CO2 conversion. In this work, we demonstrate that alloys of Mg-Cu exhibit greater activity toward activation and hydrogenation of CO2 than transition metal alloys reported so far. Two different compositions of Mg-Cu, namely Mg2Cu and MgCu2, have been studied using periodic Density Functional Theory (DFT). Our investigations reveal that CO2 chemisorbs on both intermetallic alloys. Coadsorption of CO2 with H2O leads to the spontaneous formation of COOH* over Mg2Cu(224), whereas a negligible barrier (0.04 eV) is observed for MgCu2(311). HCOO* formation has a barrier of 0.34 eV and 0.42 eV on Mg2Cu(224) and MgCu2(311), respectively. Dissociation of CO2 to CO is kinetically unfavourable on both compositions of Mg-Cu. We provide a rationale for the observed activity by analyzing the electronic structure. Notably, the spontaneous hydrogenation of CO2 makes earth -abundant metals suitable candidates for alloying that await experimental verification.
Keywords: CO2 hydrogenation; DFT; Mg2Cu; MgCu2

From digital blueprint to chemical reality: methanol to formaldehyde at ambient conditions - Mehta, Shweta; Kasabe, Mirabai; Umbarkar, Shubhangi B.; Joshi, Kavita (Applied Surface Science, 2024)
Partial oxidation of methanol to value added product presents an intriguing yet challenging process. Among these products, formaldehyde is the simplest and one of the most vital aliphatic aldehydes, which has extensive application across various domains. Industrially, silver and iron-molybdenum oxides are used as catalysts for the conversion of methanol to formaldehyde at elevated temperatures (600 degrees C and 250-400 degrees C, respectively). However, in this computational and experimental study, we have demonstrated the efficacy of ZnO as a catalyst. Notably, in the presence of ZnO, methanol readily converts to formaldehyde even under ambient conditions. We employed periodic density functional theory (DFT) to explore (10 1 1) facet of ZnO to elucidate its interaction with methanol. Our comprehensive analysis identified the most active facet (10 1 1) involved in the spontaneous conversion of methanol to formaldehyde. Subsequently, experimental validation supported our theoretical findings, demonstrating the conversion of methanol to formaldehyde with 100% selectivity at room temperature and atmospheric pressure in the presence of ZnO. This study exemplifies the pivotal role of theory in catalyst design.
Keywords: DFT; Formaldehyde; MeOH; ZnO

HyStor: an experimental database of hydrogen storage properties for various metal alloy classes - Wilson, Nikhil; Verma, Ashwini; Maharana, Piyush Ranjan; Sahoo, Ameeya Bhusan; Joshi, Kavita (International Journal of Hydrogen Energy, 2024)
In this work, we introduce the HyStor database, consisting of 1282 metal alloys along with their maximum hydrogen storage capacity (H2wt%) at a given absorption temperature. The curated HydPark database consist of 831 entries. We sourced compositions from research articles and various patent documents, resulting in addition of 451 compositions to the HydPark database. The addition is reflected in the data across all existing classes of alloys. Further, low entropy alloys (LEA), medium entropy alloys (MEA) and high entropy alloys (HEA) have been newly included classes. This has broadened the scope of the database to encompass the latest materials of interest for hydrogen storage. HyStor contains representation of 54 elements, with a temperature range of 200-800 K, and H2wt% ranging from 0.1 to 7.19. We conducted thorough checks for duplicate entries, erroneous data, and conflicting compositions within the database to ensure data quality. Furthermore, we conducted multiple tests to identify potential outlier compositions. The data curation and updation reflects into slight improved error metrics of the HYST model, reducing the Mean Absolute Error (MAE) from 0.31 to 0.29 and increasing the R2 score from 0.77 to 0.79.
Keywords: Databases; machine learning; Metal hydrides; Solid-state hydrogen storage

Insights on prussian blue analogue cathode material engineered with polypyrrole surface protection layer for aqueous rechargeable zinc metal battery - Puthiyaveetil, Priyanka Pandinhare; Nair, Aathira; Dilwale, Swati; Kurian, Maria; Joshi, Kavita; Kurungot, Sreekumar (Small, 2024)
One of the key intricacies against using Prussian blue analogues (PBAs) in aqueous batteries is their gradual dissolution in aqueous electrolytes, resulting in inadequate cycling stability. Besides, the rate capability of PBAs is limited due to their poor electrical conductivity. To overcome these challenges, it is essential to tune the physical and chemical properties of PBAs at the nano regime without affecting the inherent charge storage properties, especially at high-voltage operating conditions. Through this work, a strategy is demonstrated to enhance the electrochemical performance of vanadium-based PBA (V-PBA) by surface engineering using a conducting polymer nano-skin (V-PBA/PPy) for aqueous zinc metal batteries. The polypyrrole (PPy) nano-skin over the V-PBA nanoparticles acts as an electron percolation path to ameliorate the poor electronic conductivity of the otherwise pristine V-PBA. Interestingly, the V-PBA with an optimized polypyrrole coating (V-PBA/PPy-2) exhibits an enhanced specific capacity (173 mAh g-1 at 0.10 A g-1) than the pristine V-PBA counterpart (80 mAh g-1) and 85% capacity retention up to 500 cycles. The DFT calculation confirms the synergistic interaction between PPy and V-PBA and the presence of PPy favors the adsorption of Zn.
Keywords: aqueous rechargeable zinc metal battery; DFT; polypyrrole coating; Prussian blue analogue; surface protection layer

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)

Single-atom alloys of Cu(211) with earth-abundant metals for enhanced activity towards CO2 dissociation - Thakkar, Kavita; Joshi, Kavita (Journal of Molecular Graphics and Modelling, 2024)
CO2, a byproduct from various industrial reactions, must not be released into the atmosphere and should be managed through capture, conversion, and utilization. The first step in converting CO2 into valuable products is to break the C-O bond. This work focuses on designing Single Atom Catalysts (SACs) by doping Cu(211) surface with 13 different s, p, and d block elements with an aim to minimize the activation barrier for C-O bond cleavage. Our work demonstrates that SACs of Mg/Al/Pt@Cu(211) favor CO2 chemisorption compared to Cu(211) where CO2 physisorbs. The barrier for CO2 dissociation is lowest for Mg@Cu(211) and it increases in the order Mg@Cu(211) < Al@Cu(211) < Pt@Cu(211) < Zn@Cu(211) < Ga@Cu(211) < Cu@Cu(211) < Pd@Cu(211). These findings suggest that doping Cu(211) with earth-abundant metal like Mg can potentially be a viable catalyst for CO2 conversion, providing a promising solution to reduce carbon footprint and mitigate climate change.
Keywords: CO2; Cu(211); DFT; Single atom catalysts

Solid state hydrogen storage: Decoding the path through machine learning - Verma, Ashwini; Wilson, Nikhil; Joshi, Kavita (International Journal of Hydrogen Energy, 2024)
We present a machine learning (ML) framework HEART (HydrogEn storAge propeRty predicTor) for identifying suitable families of metal alloys for hydrogen storage under ambient conditions. Our framework includes two ML models that predict the hydrogen storage capacity (HYST) and the enthalpy of hydride formation (THOR) of multi-component metal alloys. We demonstrate that a chemically diverse set of features effectively describes the hydrogen storage properties of the alloys. In HYST, we use absorption temperature as a feature which improved H2wt% prediction significantly. For out-of-the-bag samples, HYST predicted H2wt% with R2 score of 0.81 and mean absolute error (MAE) of 0.45 wt% whereas R2 score is 0.89 and MAE is 4.53 kJ/molH2 for THOR. These models are further employed to predict H2wt% and Delta H for similar to 6.4 million multi-component metal alloys. We have identified 6480 compositions with superior storage properties (H2wt% > 2.5 at room temperature and Delta H < 60 kJ/molH2). We have also discussed in detail the interesting trends picked up by these models like temperature dependent variation in the rate of hydrogenation and alloying effect on H2wt% and Delta H in different families of alloys. Importantly certain elements like Al, Si, Sc, Cr, and Mn when mixed in small fractions with hydriding elements like Mg, Ti, V etc. systematically reduce Delta H without significantly compromising the storage capacity. Further upon increasing the number of elements in the alloy i.e from binary to ternary to quaternary, the number of compositions with lower enthalpies also increases. From the 6.4 million compositions, we have reported new alloy families having potential for hydrogen storage at room temperature. Finally, we demonstrate that HEART has the potential to scan vast chemical spaces by narrowing down potential materials for hydrogen storage.
Keywords: Enthalpy of hydride formation; Hydrogen storage capacity; Metal hydrides; Predictive machine learning models; Solid-state hydrogen storage

What leads to direct epoxidation? an exhaustive DFT investigation of electrophilic oxygen mediated epoxidation of ethylene on Ag(100) - Nair, Aathira; Joshi, Kavita (Computational Materials Science, 2024)
Extensive research has contributed to a better understanding of the commercially important epoxidation reaction. Selectivity, a crucial aspect of this reaction, has received significant attention in both experimental and theoretical investigations. However, a consensus regarding the role of electrophilic oxygen in epoxidation is yet to be reached. The present study is a theoretical examination of the prerequisites necessary for direct epoxidation to occur on the Ag(100) surface, at varied monolayer concentrations. Additionally, the study investigates the characteristics of various oxygen species interacting with ethylene to promote the direct epoxidation pathway. Based on the effective charges and projected density of states (pDOS) analysis, three oxygen variants were identified on the Ag(100) surface: atomic oxygen, dissociatively adsorbed molecular oxygen, and O 3 . The investigation reveals that all oxygen species, despite their physical and electronic differences, are electrophilic and undergo direct epoxidation. This work provides insights into the complex nature of epoxidation reaction and discusses electronic factors influencing the selective oxidation route on different Ag-O complexes.
Keywords: Ag(100); DFT; Direct epoxidation; Electrophilic oxygen; Ethylene Oxide (EtO); OMC

Chlorophobic iron hydrogen phosphite as OER-active electrocatalyst in anion exchange membrane (sea)water electrolysis - Das, Chandni; Sinha, Nibedita; Nair, Aathira; Pal, Santanu; Joshi, Kavita; Roy, Poulomi (Small, 2025)
Seawater electrolysis is recognized as a promising technology to cater to the worldwide drive for sustainable hydrogen production; however, its practical viability is often hindered by the inevitable anode corrosion arising from the electrode side reactions owing to the presence of high chloride content which eventually degrade the electrode performance eventually. Herein, the design of unprecedented ammonium iron hydrogen phosphite (FeHPhi) along with a trace amount of Cu, is reported as the unique and much desired electrode material for seawater electrolysis due to its special chloride repellant nature along with great electrocatalytic activity toward water oxidation. The [HPO3](2-) oxoanion as Lewis base in the structure effectively restricts chloride ions, while the Fe center acts as Lewis acid offering an active site for water oxidation, also well-supported theoretically. Leveraging this frustrated Lewis pair combination, the electrocatalyst achieves a high current density of 500 mA cm(-2) at 344 mV overpotential in alkaline real seawater with impressive robustness to sustain for 200 h when operated under chlorine evolution reaction dominating region (>2 V). The electrocatalyst also demonstrates superior performance in anion exchange membrane freshwater and seawater electrolysis, demonstrating its potential applicability.
Keywords: AEM electrolyzer; chloride repellant; electrocatalyst; hydrogen production; seawater oxidation

MH-PCTpro: a machine learning model for rapid prediction of pressure-composition-temperature (PCT) isotherms - Verma, Ashwini; Joshi, Kavita (Iscience, 2025)
We present a machine-learning powered Metal Hydride's Pressure-Composition-Temperature isotherm Predictor (MH-PCTpro) for metal compositions. To train the MH-PCTpro, an experimental database of PCT isotherms is built from published literature. The database comprises over 14,000 data points extracted from 237 PCT isotherms representing 138 distinct compositions. The dataset encompasses more than 25 elements and spans a broad spectrum of absorption temperatures (263-653 K) and hydrogen pressures (0.001-40 MPa). The model is validated on a wide range of alloy families and its predictions are consistent with experimental results. The model also captures temperature-dependent variations in plateau pressure, enabling determination of enthalpy and entropy of hydride formation through Van't Hoff plots. Hence, MH-PCTpro can be used as an ML tool for guiding PCT experiments, offering PCT isotherm predictions and valuable thermodynamic insights into materials suitable for solid-state hydrogen storage.

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

Sequential nitro-michael addition and reductive cyclization cascade reaction for diastereoselective synthesis of multifunctionalized 3,3′-pyrrolidinyl-spirooxindoles - Nichinde, Chandrakant B.; Bhati, Meema; Girase, Amardipsing S.; Patil, Baliram R.; Chaudhari, Suryakant S.; Gamidi, Rama Krishna; Joshi, Kavita; Kinage, Anil K. (European Journal of Organic Chemistry, 2025)
In this investigation, we elucidated, one-pot two stage efficient synthesis of multifuctionalized spiro[oxindole -3,3 `-pyrrolidine]. The methodology proceeds via organocatalyzed nitro-Michael addition reaction between indolylidenecyanoesters and nitroalkanes to formed nitro-Michael adduct which transformed into multifunctionalized 3,3 `-pyrrolidinyl-spirooxindoles by metal catalyzed reductive cyclization cascade. DFT investigations were conducted to elucidate the mechanism underlying the preferential reduction of the nitro group, with subsequent attack on the nitrile and ester groups remain inert throughout the reaction process. The approach is operationally simple, easily scalable, exhibits compatibility with readily accessible starting material and catalysts, thereby emphasizing cost-effectiveness.
Keywords: 3 `-pyrrolidinyl spirooxindoles; DFT study for regioselective cyclization; Diastereoselective 3; organocatalysis; Pd/C catalysed partial reductive spirocyclization

Potential tuneable glucose oxidation to selective C6 molecules and CC cleavage, and parallel green H2 production: sustainable high current density electrolysis - Chauhan, Inderjeet; Patra, Kshirodra Kumar; Vijay, Pothoppurathu M.; Nalajala, Naresh; Mehta, Shweta; Joshi, Kavita; Ravindranathan, Sapna; Gopinath, Chinnakonda S. (Chemical Engineering Journal, 2026)
Current study elucidates the electrocatalytic efficacy of palladium-nanocubes (Pd-NCs) for the selective oxidation of glucose to value-added chemicals with concomitant hydrogen evolution. The Pd-NC catalyst demonstrated exceptional activity and product selectivity, achieving nearly quantitative glucose conversion (>99 %) with high gluconic and glucaric acid yield at low anodic overpotential (0.6 V vs. RHE) in alkaline electrolyte. At not-so-high elevated potentials (1.2 V vs. RHE), oxidative CC scission prevails, yielding shorter-chain carboxylates along with C6-acids. Reaction products are thoroughly characterized and quantitatively estimated by NMR spectral methods; NMR methods also provide CC cleavage and mechanistic pathways of glucose to various products. Complementary DFT calculations delineate the thermodynamic favorability of glucose adsorption on Pd-NC surfaces (-1.83 eV) and the exergonic oxidation pathway under applied bias, corroborating experimental product distributions. In a two-electrode electrolyzer, Pd-NC anode paired with Pt/C and Ni2P cathode demonstrates 100 mA/cm(2) at 0.99 V and 1.37 V, respectively, with 48 % reduction in energy input (26.6 kWh/kg H-2) compared to conventional alkaline electrolysis; critically, H-2 production energy is lower than the usable energy (33.3 kWh/kg H-2). Sustainable chronopotentiometric assays confirm sustainability (similar to 140 h) in alkaline as well as saline electrolytes, underscoring the system's resilience against chloride-mediated corrosion. Present work establishes a proof of concept for integrated biomass-component valorization and carbon-negative green hydrogen production, merging atomic-level mechanistic insights with scalable reactor design. Optimization of reaction parameters, including potential tuning, reaction temperature and electrolyte engineering, offers a compelling strategy to further enhance C6 and fragmented product selectivity and overall system efficiency.
Keywords: biomass valorization; electrocatalysis; energy conversion; Sustainability

What drives property prediction for solid-state hydrogen storage? data or smart features? - Verma, Ashwini; Joshi, Kavita (International Journal of Hydrogen Energy, 2026)
Metal hydrides play a pivotal role in a wide range of applications, including hydrogen storage, compression, heat management, and catalysis, making them a central focus of interdisciplinary research spanning chemistry, materials science, and engineering. The performance of the metal hydride-based systems is strongly governed by the thermodynamics of metal-hydrogen interactions. Among key thermodynamic properties, the equilibrium plateau pressure (P-eq) is particularly critical, as it defines operating conditions for hydrogen absorption and desorption. Traditionally, determining P-eq requires extensive experimental measurements, which limits the pace of materials discovery. On the other hand, predicting it through ML-based models is constrained by the availability of limited data. In this work, we demonstrate that smart features can be a way to overcome this limitation. EquiP, an ML model trained to predict ln(P-eq) as a function of temperature, generates Van't Hoff plots (P-eq vs. 1/T), enabling rapid determination of enthalpy and entropy of hydride formation. We demonstrate that incorporating structural descriptors derived from X-ray diffraction (XRD) data improves the performance of the model, particularly with sparse training datasets. A model trained using only compositional descriptors yields a validation mean absolute error (MAE) of 0.21 bar, whereas incorporating XRD features reduces the MAE substantially to 0.07 bar. This work demonstrates that with limited data, intelligent feature design grounded in domain knowledge is the key to improving predictions of complex material properties.
Keywords: Experimental data; Feature engineering; Hydrogen storage; machine learning; Metal hydrides; Property prediction

When facets meet impurities: Trace gas dominance over CO2 adsorption on ZnO - Bhati, Meema; Joshi, Kavita (Applied Surface Science, 2026)
The catalytic hydrogenation of CO2 to methanol using Cu-ZnO/Al2O3 (CZA) is a key route for sustainable chemical production, when coupled with CO2-rich industrial off-gases. However, trace secondary gases, though present only at ppm levels, can poison active sites and suppress catalytic performance. In this work, we employ periodic density functional theory (DFT) to investigate interactions of H2S, SO2, NO2, NO, CO and CH4 with ZnO surfaces:(10(-)10), (10(-)11), (11(-)20), (10(-)13), and (11(-)22), and compared their adsorption pattern with CO2, the principle component of methanol synthesis. H2S dissociates on all the surfaces, SO2, and NO2 are chemisorbed, CH4 remains physisorbed, and NO, CO, and CO2 exhibit facet-dependent adsorption. Electronic structure analysis reveal that chemisorption occurs when surface energy states near the Fermi level overlap with HOMO of adsorbate, enabling charge transfer, whereas physisorption lacks such overlap. The adsorption strength follows the order: H2S SO2 NO2 NO CO CO2 CH4, suggesting that sulfur and nitrogen containing species exhibit strong chemisorption and compete with CO2 for active sites, potentially impacting the efficiency of methanol synthesis. These insights provide an atomic scale understanding of impurity-surface interactions and highlight potential role of ZnO as an efficient feed stock purifier for CO2-rich gas streams.
Keywords: CZA catalyst; flue gases; Valorization of CO2; ZnO