Gaurav Deshmukh

110 posts

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Gaurav Deshmukh

Gaurav Deshmukh

@ChemAndCode

I'm a postdoc in the Broadbelt group at @NorthwesternU. PhD from @GroupGreeley in @PurdueChemE. B. Chem. Engg. from @ICTMumbai1933. 🇮🇳

Mumbai, India शामिल हुए Temmuz 2018
403 फ़ॉलोइंग311 फ़ॉलोवर्स
पिन किया गया ट्वीट
Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
Delighted to share a recent review, coauthored with @mepgg as part of my work in @GroupGreeley, on fundamentals and applications of deep learning models in computational heterogeneous catalysis published in the Journal of the Indian Institute of Science: link.springer.com/article/10.100…
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Tristan Maxson
Tristan Maxson@tgmaxson·
Happy to have the my nanoparticle simulation work out in the new Angewante Novit (@angew_chem) open access journal!
Tibor Szilvási@SzilvasiGroup

A potentially carrier defining paper is out in @angew_chem Novit! We show how to simulate supported nanoparticle catalysts with 1-5 nm in diameter under experimental conditions in quantitative agreement with benchmark microcalorimetric measurements onlinelibrary.wiley.com/doi/10.1002/an…

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Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
Presenting a talk on the application of deep learning towards the study and design of high-entropy alloy catalysts at @NAM29NACS in the "Using AI to Navigate Large Catalyst Design Spaces" session on June 10 (Tuesday) at 3:00 PM. Happy to chat and connect with those attending NAM!
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Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
We develop a computational framework to analyze key relationships between surface structure, composition, and thermodynamic stability of alloy catalysts and using this, we describe the origin and formation of "Pt skins" on Pt3Ni that are responsible for its exceptional activity.
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Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
Glad to share my latest manuscript published in J. Phys. Chem. C on an atomic scale study of the stability of bimetallic Pt alloys for electrochemical oxygen reduction using density functional theory, thermodynamics, and machine learning.
Greeley Group@GroupGreeley

Congratulations to Gaurav (@ChemAndCode ) and Pushkar (@mepgg) for publishing their work on first-principles analysis of binary alloy catalyst stability! This study has been published in @JPhysChem in a special issue in honor of Jens Norskov. pubs.acs.org/doi/10.1021/ac…

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Ranga Rohit Seemakurthi
Ranga Rohit Seemakurthi@rangarohit_7·
In this work, we go beyond Cu catalysts, and explore oxide-derived Co catalysts for producing long-chain hydrocarbons! The experiments from @catalysis_eth have been followed up with simulations at @TheorHetCatICIQ, pin-pointing the role of polarized sites at the interface.
Javier Perez-Ramirez@catalysis_eth

🔥Out in Advanced Energy Materials. Cobalt catalyzes CO2 electroreduction to long-chain hydrocarbons, with the highest chain growth probability reported for any electrocatalyst!👇 onlinelibrary.wiley.com/doi/10.1002/ae… @NCCR_Catalysis @ETH_DCHAB @ChemNUS @ICIQchem Stronger together! ✊

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Yinan Xu
Yinan Xu@YinanXu2·
A molecular view of methane activation on Ni(111) using machine learning and enhanced sampling! We developed MLIPs to predict DFT-level accuracy in catalytic processes, revealing insights into free energy landscapes and surface dynamics. 🧪 #Catalysis #MachineLearning #Chemistry
Machine Learning in Chemistry@ML_Chem

A Molecular View of Methane Activation on Ni(111) through Enhanced Sampling and Machine Learning #machinelearning #compchem pubs.acs.org/doi/abs/10.102…

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Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
Excited to share our work on developing an active learning workflow to extrapolate formation energies of binary alloys to ternary alloys using a dropout graph convolutional network (dGCN), that provides associated uncertainty estimates as well.
Greeley Group@GroupGreeley

Congrats to Gaurav (@ChemAndCode), Noah, and Nikolaos for their recent work on developing an active learning workflow to predict formation free energies of ternary alloys using a dropout graph neural network in NPJ computational materials (@Nature_NPJ). nature.com/articles/s4152…

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Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
We also utilize Diffusion Maps (courtesy of the Kevrekidis group), a non-linear dimensionality reduction technique, to provide more interpretability to the network's predictions and serve as a data-driven coordinate for optimization.
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Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
We perform Bayesian optimization with a novel acquisition function inspired by statistical mechanics and show how to improve predictions on ternary alloys by relying primarily on binary alloy data and a few carefully sampled ternary data points.
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Gaurav Deshmukh
Gaurav Deshmukh@ChemAndCode·
Thrilled to be part of this work! We show that DFT-based electronic structure predictions of Pt nanoparticles with varying sizes align well with expt. VtC-XES measurements. We also elucidate the influence of factors such as coordination and strain on the electronic structure.
Greeley Group@GroupGreeley

Congrats to David Dean and Gaurav Deshmukh (@ChemAndCode) for their recent article in @CatalysisSciTec on studying the size-dependence of the electronic structure of Pt nanoparticles using Valence-to-Core X-ray Emission Spectroscopy. pubs.rsc.org/en/content/art…

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Yash Laxman Kamble
Yash Laxman Kamble@YashLaxmanKamb1·
Check out our latest article in PNAS where we report on the fly control of structural color using bottlebrush block copolymers!! Shoutout to an awesome collaboration effort! pnas.org/doi/10.1073/pn…
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Greeley Group
Greeley Group@GroupGreeley·
We recently bid farewell to @Kaustubh_Savant over a hearty group dinner. We wish him luck in all future endeavors! This also provided us with an opportunity to welcome and introduce new members, Brady, Masa, and Dhruv, to the group.
Greeley Group tweet media
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