Sustainable Energy & Fuels 2025 Outstanding Papers

We are proud to announce the launch of the Sustainable Energy & Fuels Outstanding Papers. This is an opportunity to recognise the excellent work published in the journal and celebrate the authors behind the work by selecting one Outstanding Article and one Outstanding Review each year.

These papers are chosen from a shortlist compiled by the Editorial Office using a range of metrics. The journal's Editorial and Advisory Boards review and vote on these papers based on the science presented and the potential impact. The Editor-in-Chief selects the final winning papers, taking the Board members' votes into account.

We are delighted to introduce the inaugural Outstanding Article and Outstanding Review. Please join us in congratulating the authors behind these excellent contributions.

Sustainable Energy & Fuels 2025 Outstanding Article

A photo/biocatalytic system for visible-light driven L-alanine production from ammonia and pyruvate

Kyosuke Yamada and Yutaka Amao

“This exciting communication exploits solar energy to drive molecular transformations and improve the energy efficiency of chemical syntheses.¹ Here the authors demonstrate a versatile visible-light driven photocatalytic route to regenerate cofactor NADH used for hydrogen transfer in enzymatic reactions, which should have broad impact for diverse biocatalytic processes.” – Karen Wilson, Editor-in-Chief, Sustainable Energy & Fuels.

We spoke to the authors Kyosuke Yamada and Yutaka Amao about their work.

Which part of this paper do you think will have the greatest impact?

By using light energy as the driving force and incorporating an enzymatic reaction, we were able to construct a photo/biocatalyst hybrid system and synthesize amino acids, which serve as precursors for biodegradable nylon, from biomass-derived compounds. We believe that this artificial photosynthesis system is significant in that it synthesizes sustainable materials, rather than simply producing compounds or fuels.

What was the most challenging part of completing this research?

The biggest challenge was to investigate the conditions for two simultaneously functioning catalysts with different properties, a photocatalyst and a biocatalyst, in the same system. Designing a reaction environment in which both catalysts can work efficiently was the most important challenge.

What are the next steps for this research?

In the future, we aim to expand the nitrogen source used in the reaction to renewable biomass-derived compounds, thereby building a more sustainable system. Furthermore, by replacing the currently used electron donor with inexhaustible water, we hope to develop an ideal artificial photosynthesis system that is closer to natural photosynthesis.

Sustainable Energy & Fuels 2025 Outstanding Review

An intelligent battery management system (BMS) with end-edge-cloud connectivity – a perspective

Sai Krishna Mulpuri, Bikash Sah and Praveen Kumar

“This impactful perspective presents a vision for how evolving cloud-based management technology coupled with AI-powered analytics could enable intelligent control and monitoring of large-scale battery management systems,² ensuring efficient harnessing of renewable energy, and reliable and safe operation of distributed battery units.” – Karen Wilson, Editor-in-Chief, Sustainable Energy & Fuels.

The authors Sai Krishna Mulpuri, Bikash Sah and Praveen Kumar were invited to answer a few questions about their perspective.

What do you see as the most significant insights or conclusions from your paper?

Our central conclusion is that the next leap in battery safety, lifetime, and reliability will come less from “one smarter estimator” and more from a systems-architecture shift: an intelligent battery management system (BMS) must be hierarchical (end-edge-cloud), so time-critical protection and control remain local, while computationally intensive diagnosis, prognostics, and learning scale in the cloud.

We show that this architecture is the natural enabler for three capabilities that conventional BMSs struggle to deliver at scale: (i) high-fidelity, continuously updated digital-twin representations using model, data, and fusion approaches; (ii) secure, auditable lifecycle traceability (e.g., via blockchain) to support second-life and recycling decisions; and (iii) control of reconfigurable packs to mitigate faults and manage heterogeneous ageing at different levels – cell, module and pack. This positioning is also consistent with the broader direction of “cloud-side-end” battery digital-twin concepts emerging in the literature.

What are the biggest challenges currently facing researchers in this area?

The hardest problems are not purely algorithmic; they are end-to-end and socio-technical. A major challenge is achieving reliable cell-level observability at scale through robust sensing, synchronisation, and quality control of high-rate, multi-modal data across large battery packs, especially when ageing is non-uniform; in parallel, researchers still need practical methods to localise and isolate degraded cells or modules in real operating conditions. Another key challenge is defining the right latency-aware partitioning of algorithms and responsibilities, i.e., deciding what must run at the end and/or edge assets for real-time protection and control versus what can run in the cloud, without compromising safety-critical response times.

Additionally, maintaining the validity of battery digital twins over time remains difficult because model fidelity must be preserved under drift, chemistry and format diversity, and continuously changing operating conditions, which requires updating the twin while retaining robustness and safety guarantees.

As BMS architectures become connected, they inherently expand the cyber-attack surface, and ensuring secure communication, strong access control, and privacy-preserving analytics becomes essential, yet is still under-addressed in many current implementations.

Finally, cloud-enabled BMS solutions must remain commercially viable, energy-justified, and globally accessible; otherwise, they risk widening a “digital divide” in electrification by making advanced safety and lifetime features available only to well-resourced users or regions.

What do you hope readers take away from your paper?

We hope readers take away a clear design principle: an intelligent BMS is a “battery lifecycle operating system”, not just a pack monitor. Practically, that means (i) architecting the compute stack (end-edge-cloud) around safety-critical latency constraints, (ii) combining physics-based understanding with data-driven adaptation (toward physics-informed machine learning (ML) and hybrid digital twins), and (iii) treating data governance and cybersecurity as first-class engineering requirements, not add-ons.

We also want to stimulate community work on standardised validation and benchmarking for cloud and edge BMS functions (diagnostics, remaining useful life prediction, early fault prediction), and on interoperable data pipelines that make second life and recycling decisions more transparent and accountable across stakeholders.

We extend our sincerest congratulations to the authors of our 2025 Outstanding Papers whose work will continue to advance and shape sustainable energy science. We look forward to celebrating more excellent work in the years to come.

Author Biographies

Sustainable Energy & Fuels 2025 Outstanding Article

A photo/biocatalytic system for visible-light driven L-alanine production from ammonia and pyruvate

Kyosuke Yamada is a master's student working in chemistry at Osaka Metropolitan University. His research focuses on constructing hybrid catalytic systems that combine photocatalysts and biocatalysts to convert biomass-derived compounds into value-added chemicals and environmentally friendly materials using visible light as an energy source. His recent work involves the development of a photo-bio catalytic system for carbon–nitrogen bond formation, enabling the synthesis of amino acids for biodegradable nylon precursors from renewable resources. Through this research, he aims to contribute to reducing greenhouse gas emissions and addressing environmental pollution by advancing bio-based and biodegradable polymer production.

Yutaka Amao received his doctorate in Engineering in 1997 from the Tokyo Institute of Technology, Japan. He worked as a researcher at the Kanagawa Academy of Science and Technology from 1997 to 1998, as a researcher at the National Aerospace Laboratory from 1998 to 2001, and as an Associate Professor in the Department of Applied Chemistry of Oita University from 2001 to 2013. He also worked as a Precursory Research for Embryonic Science and Technology (PRESTO) researcher at the Japan Science and Technology Agency from 2011 to 2016. From 2013 to 2020, he was a Full Professor at the Advanced Research Institutes of Natural Sciences, Osaka City University. In 2020, he was appointed Full Professor at the Research Centre for Artificial Photosynthesis, Osaka City University (becoming Osaka Metropolitan University after its merger with Osaka Prefecture University in 2022). He was appointed as a Fellow of the Royal Society of Chemistry in 2018. His current research interests include photocatalysts, molecular catalysts, biocatalysts, and the development of carbon dioxide conversion to organic molecules with hybrid catalysis systems.

Sustainable Energy & Fuels 2025 Outstanding Review

An intelligent battery management system (BMS) with end-edge-cloud connectivity – a perspective

Sai Krishna Mulpuri received his Bachelor of Technology (BTech) in Electrical and Electronics Engineering at the National Institute of Technology Warangal, India (2012 to 2016). From 2021 to 2024, he pursued his Doctor of Philosophy (PhD) at the Indian Institute of Technology Guwahati, India, as a Prime Minister's Research Fellow. His research focused on electric vehicle (EV) battery testing and end-of-life assessment, lithium-ion battery electrochemical modelling, cloud-based battery test bed development for life cycle and performance evaluation, and the design of an intelligent battery management system (IBMS) with edge-cloud connectivity. Prior to joining his PhD program, he worked as a General Manager at Trident Group in India from 2016 to 2017, leading energy conservation projects and conducting energy audits. Since February 2025, he has been working as a researcher at the University of Twente, Netherlands, on the “FreeTwinEV” project, focusing on the development of digital-twin technologies for EV batteries to improve performance and reliability. His research interests include electric mobility, EV charging, lithium-ion battery modelling, and lithium-ion battery ageing and degradation.

Bikash Sah received a Bachelor of Technology (BTech.) degree in Electrical and Electronics Engineering from the National Institute of Technology Arunachal Pradesh, India, in 2014, and a Doctor of Philosophy (PhD) degree from the Department of Electronics and Electrical Engineering, Indian Institute of Technology Guwahati, Guwahati, India, in 2022. His PhD research focused on the development of intelligent charging vehicle infrastructure, including advanced vehicle-to-grid controllers, hardware systems for electric mobility applications, physics-based battery modelling, Li-ion battery ageing and degradation studies, innovative online state and parameter estimation for batteries, cloud-based battery management systems, and frameworks to align the needs of multiple stakeholders across electric mobility ecosystems. Post-PhD (Jan 2022 to Feb 2024), he worked jointly with Bonn-Rhein-Sieg University of Applied Sciences, Germany, and the Fraunhofer Institute for Energy Economics and Energy System Technology IEE in multiple roles, including Scientific Staff and Group Leader (Power Electronics for Electrochemical Systems). Since March 2025, he has been a Senior Scientist and Deputy Head at the Chair of Interconnected Automation Systems at the University of Siegen, Germany. His research covers a wide range of topics in testing, characterisation, modelling, design, prototyping, ageing and degradation of energy systems, with a focus on power electronics and electrochemical systems such as batteries, electrolysers, and fuel cells.

Praveen Kumar received a BTech. degree in electrical engineering from the National Institute of Technology, Hamirpur, India, in 1998, an M. Tech. degree in energy systems from the Indian Institute of Technology Delhi, India, in 2000, and a PhD degree in electrical machines from Delft University of Technology, the Netherlands, in 2008. He is an accomplished researcher and engineer with nearly 30 years of experience in the field of electric motor design, electric vehicle (EV) drivetrains, battery systems, and the application of artificial intelligence (AI) and machine learning (ML) to enhance these systems. Dr Kumar's career began in academia, where he has held various positions at prestigious institutions, including a professorship at the Indian Institute of Technology Guwahati. There, he established the e-Mobility Lab, a centre of excellence dedicated to EV drivetrain research, and led numerous industry-sponsored projects focusing on the development of high-efficiency motors and smart charging systems. His professional journey also includes significant industry experience in Germany and the Netherlands, where he worked on the design and prototyping of high-temperature superconducting motors and hybrid drive systems. As a co-founder of elmoCAD GmbH, Dr Kumar developed advanced simulation algorithms for motor design, significantly reducing design cycle time. Dr Kumar's work is recognised globally through his numerous patents, publications, and successful project executions that have had a profound impact on the field of sustainable transportation. He is currently Senior R&D Staff at Oak Ridge National Laboratory (ORNL), where he leads cutting-edge research in AI-driven diagnostics and digital-twin technologies for electric motors and powertrain systems. His current focus at ORNL is on pioneering AI and ML applications to predict and prevent failures in electric vehicle systems, thereby extending their operational life and enhancing reliability.

References

1. K. Yamada and Y. Amao, A photo/biocatalytic system for visible-light driven L-alanine production from ammonia and pyruvate, Sustainable Energy Fuels, 2025, 9, 419–423.
2. S. M. Mulpuri, B. Sah and P. Kumar, An intelligent battery management system (BMS) with end-edge-cloud connectivity – a perspective, Sustainable Energy Fuels, 2025, 9, 1142–1159.

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