BITS Faculty Publications
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Item Development of machine learning based model for low-temperature PEM fuel cells(Elsevier, 2024-09) Pandey, JayLow-Temperature Proton Exchange Membrane Fuel Cells (LT-PEMFC) are favored as an alternative power source due to their high efficiency, rapid initialization, shut-down cycles, and zero emissions. Developing an effective model for LT-PEMFC is essential. In this study, machine learning models are created for LT-PEMFC, utilizing techniques such as Gradient Boosting Regression (GBR), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) to predict cell voltage based on operating parameters. The dataset is generated using an in-house physics-based MATLAB model, complemented by experimental data from elsewhere. GBR exhibits superiority over XGBoost, LightGBM, and RF. These data-based models for LT-PEMFC, developed on generated datasets, achieve R 0.99 and MAPE 0.06 during testing. These models are further validated on experimental data with R 0.90 and MAPE 0.1. This underscores the ability to construct accurate data-based models and thus reducing reliance on extensive experimentation.Item Electrocatalyst for the oxygen reduction reaction (ORR): towards an active and stable electrocatalyst for low-temperature PEM fuel cell(Springer, 2024-08) Pandey, JayGreen hydrogen–fueled low-temperature proton exchange membrane (PEM) fuel cells have emerged as one of the most attractive technologies for electric-vehicle (EV) applications due to their high efficiency, zero emissions, and potential for renewable energy integration. The performance of the PEM fuel cells is significantly affected by the electrochemical activity of the oxygen reduction reaction (ORR) catalyst. This review comprehensively examines the role of ORR electrocatalysts in PEM fuel cell efficiency for portable, transport, and stationary applications. In this direction, we discuss the fundamentals of PEM fuel cell operation, the critical role of electrocatalysts, and advanced characterization techniques. A detailed overview of ORR electrocatalyst types, including platinum-based, non-noble metal-based, and carbon-supported as well as noncarbon supported, is presented, emphasizing recent advancements in design and synthesis. The review concludes with discussing current challenges and future directions for ORR electrocatalyst development. Understanding the characteristics and recent developments of ORR catalysts is essential for researchers and engineers to optimize the performance and durability of PEM fuel cells, thereby promoting the wider adoption of clean and efficient energy technologies. By providing insights into electrocatalyst characteristics and emerging trends, this work aims to accelerate the adoption of clean and efficient PEM fuel cell technology.Item Synthesis of manganese-doped N-C bifunctional electrocatalyst for low-temperature PEM fuel cell(Springer, 2025-01) Pandey, JayPEM fuel cell plays a vital role in ensuring a sustainable future in the energy domain. Electrochemical activities of oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) electrocatalysts induce a strong impact on the performance of PEM fuel cells. Bifunctional catalysts capable of facilitating both ORR and OER are crucial for enhancing the overall efficiency and durability of these electrochemical devices. Commercially, Pt/C and RuO2/C are the available options for PEM fuel cells, which makes the device very costly. Herein, we have prepared a Mn-doped N-C electrocatalyst that shows comparable bifunctional performance as commercial catalysts. The use of naturally occurring sources such as picolinic acid for the synthesis of catalysts over the expensive raw material helps in bringing down the cost. Synthesized electrocatalyst contains mixed oxidation states of Mn (Mn, Mn2+, Mn3+, Mn4+), follows 4e− path during the ORR, and for OER, the measured Tafel slope was 19.8 mv/dec with Eoer-10 of 1.617 V and ΔE of 1.004 V, showing promising potential for use in PEM fuel cells.