Prabhakaran Sampath

Led the development of ML-driven virtual engineering and reverse-engineering frameworks to predict area-specific resistance (ASR) in solid oxide fuel cells (SOFCs), integrating composition, structure, and performance data under physics-informed constraints.
Designed integrated DFT–ML workflows for high-entropy oxide (HEO) surfaces, identifying composition–structure descriptors governing catalytic activity, stability, and reversibility in RSOFC electrodes.
Performed first-principles simulations on hybrid quantum dots for energy storage and conversion, analyzing electronic structure, charge redistribution, and structure–function relationships.
Conducted DFT-based investigations of K-montmorillonite ceramic catalysts, correlating defect chemistry and charge-density redistribution with experimentally observed catalytic behavior.
Executed mechanistic DFT analysis of CuS@Cu heterostructures to support experimental CO₂ reduction studies toward C₂ products (C₂H₄), focusing on CO₂/CO adsorption, early C–C coupling pathways, vacancy-induced electronic effects, and interfacial charge transfer.

Conducted DFT-based mechanistic modeling of catalytic materials for HER, OER, ORR, and CO₂RR, supporting interdisciplinary experimental efforts through electronic-structure, adsorption, and reaction-energetics analyses.
Modeled Zn–Ni–N–doped carbon catalysts (pyrrolic, pyridinic, and pyrazolic configurations) to identify active-site motifs and reaction energetics governing bifunctional OER/ORR performance.
Analyzed Ni–N₃–doped carbon surfaces for CO₂RR, evaluating adsorption behavior, charge transfer, and electronic descriptors linked to catalytic selectivity.
Applied surface crystallography modeling to demonstrate how transitions from low-index (111) to high-index (220) facets enhance Au electrocatalyst activity toward CO₂ reduction.
Translated first-principles insights into synthesis-relevant design guidelines, aligning atomistic predictions with practical materials development for electrochemical energy-conversion systems.

Performed DFT-based mechanistic studies on electrocatalysts for water splitting and electrochemical energy conversion, integrating electronic-structure analysis with experimental validation.
Elucidated structure–activity relationships in Fe- and P-doped WS₂ monolayers, identifying bifunctional HER/OER active sites and doping-induced electronic effects.
Modeled surface-modified CoMoSe₂ systems, demonstrating that partial oxygenation enhances trifunctional HER/OER/ORR activity through charge redistribution and optimized adsorption energetics.
Designed oxygen-incorporated NiSe₂ surfaces using first-principles methods, identifying catalytically active sites and reaction energetics relevant to water-splitting performance.
Linked atomistic predictions with experimental synthesis and characterization of hierarchical 3D oxygenated Co₁₋ₓMoₓSe₂ nanosheets, supporting performance optimization in water splitting and Zn–air batteries.
Provided theoretical interpretation of HER, OER, and ORR mechanisms in close collaboration with interdisciplinary teams, guiding catalyst optimization and electrochemical performance assessment.

Synthesized and electrochemically evaluated electrocatalysts for hydrogen evolution and water electrolysis using standard electrochemical testing protocols.
Analyzed activity, stability, and durability trends through electrochemical measurements, providing performance benchmarks to guide materials optimization.
Developed and optimized catalyst materials for Zn–air batteries, linking electrochemical behavior to energy-storage performance improvements.