Sayan Banerjee

Sayan BanerjeeSayan BanerjeeSayan BanerjeeSayan Banerjee
  • About Me
  • Research Experience
  • Publications

Sayan Banerjee

Sayan BanerjeeSayan BanerjeeSayan Banerjee
  • About Me
  • Research Experience
  • Publications

Overview of research publications from my PhD at the University of Pennsylvania and my Masters at IIT Bombay.

Google Scholar

Two-Legged Molecular Walker and Curvature

This study enables a new way to tune the electronic structure of two-dimensional materials for a range of applications

S Banerjee, N Hawthorne, J Batteas, AM Rappe

J. Am. Chem. Soc. 2023, 145, 49, 26765–26773

Hydrogen Evolution on Nickel Phosphide

Relationship between the Surface Reconstruction of Nickel Phosphides and Their Activity toward the Hydrogen Evolution Reaction.

S Banerjee, A Kakekhani, RB Wexler, AM Rappe

ACS Catalysis 2023, 13, 7, 4611–4621

Bio-inspired CO2 Activation on Surfaces

We propose that dual atom alloys (DAAs), homo- and heterodimer islands in a Cu matrix, can offer stronger covalent CO2 binding than pristine Cu. 

D Behrendt*, S Banerjee*, C Clark, AM Rappe

J. Am. Chem. Soc. 2023, 145, 8, 4730–4735

Mechanochemical Molecular Migration on Graphene

We predict that the curvature of graphene can be exploited to perform directional molecular motion

S Banerjee, AM Rappe

J. Am. Chem. Soc. 2022, 144, 16, 7181–7188

Molecular Motion via Noncovalent Interactions

Mechanochemical Molecular Motion Using Noncovalent Interactions on Graphene and Its Application to Tailoring the Adsorption Energetics

S Banerjee, AM Rappe

ACS Materials Letters 2023, 5, 2, 574–579

CO2 Electroreduction toward Multicarbon Products

In order to understand the roots of high selectivity and low activity and to direct the design of more active CO2RR catalysts, we investigate the mechanism on Ni2P using density functional theory.

S Banerjee, A Kakekhani, RB Wexler, AM Rappe

ACS Catalysis 2021, 11, 18, 11706–11715

Photomechanochemical Control over Stereoselectivity

We validate photomechanochemistry as a viable new direction for the preparation of complex organic scaffolds.

S Biswas*, S Banerjee*, MA Shlain, AA Bardin, RV Ulijn, BL Nannenga, ...

Faraday Discussions, 2023,241, 266-277

Machine Learning for Predicting Product Distributions

We use machine learning tools, such as the neural network, decision tree, logistic regression, and Random forest algorithms, to analyze the outcome of an important catalytic regio-selective difluorination reaction of alkenes.

2018 PCCP HOT Articles

S Banerjee, A Sreenithya, RB Sunoj

Phys. Chem. Chem. Phys., 2018,20, 18311-18318

A Unified Machine Learning Protocol for Asymmetric Catalysis

The proposed approach provides a sustainable model that trains on known catalysts and helps to predict the efficacy of additional catalysts for asymmetric synthesis.

Editors' Choice in Science

S Singh, M Pareek, A Changotra, S Banerjee, B Bhaskararao, ...

PNAS, 117(3), 1339-1345.

Reactivity of Graphene Driven by Mechanical Distortions

Here, using Raman micro-spectroscopy and first-principles calculations, we have investigated the reaction of graphene, under varying degrees of strain.

N Hawthorne, S Banerjee, Q Moore, AM Rappe, JD Batteas

J. Phys. Chem. C 2022, 126, 41, 17569–17578

Reversible Atomization and Nano-Clustering of Pt

We report a way to drastically reduce precious metal loading of catalysts by judiciously choosing an active metal/support pair and using the reversible atomization–nanoparticulate formation of transition metal on a high-surface area support.

D Chakraborty, TEL Smitshuysen, A Kakekhani, SPF Jespersen, S Banerjee,...

J. Phys. Chem. C 2022, 126, 38, 16194–16203

Elastic Properties of (Quasi)Two-Dimensional Perovskite

We combine ab initio density functional theory modeling with a diverse set of experiments to study the elastic properties of (quasi)2D perovskites

MA Reyes-Martinez, P Tan, A Kakekhani, S Banerjee, AA Zhumekenov, ...

ACS Appl. Mater. Interfaces 2020, 12, 15, 17881–17892

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