Quantum computing and quantum artificial intelligence for renewable and sustainable energy: A emerging prospect towards climate neutrality

A Ajagekar, F You - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Transitioning from fossil fuels to renewable sources and developing sustainable energy
materials for energy production and storage are critical factors in achieving climate …

A rising 2D star: novel MBenes with excellent performance in energy conversion and storage

T Xu, Y Wang, Z Xiong, Y Wang, Y Zhou, X Li - Nano-Micro Letters, 2023 - Springer
As a flourishing member of the two-dimensional (2D) nanomaterial family, MXenes have
shown great potential in various research areas. In recent years, the continued growth of …

Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective

MMF Hasan, MS Zantye, MK Kazi - Computers & Chemical Engineering, 2022 - Elsevier
Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize
fossil-based power and industrial sectors and is a bridging technology for a sustainable …

A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing

B Winter, C Winter, J Schilling, A Bardow - Digital Discovery, 2022 - pubs.rsc.org
The knowledge of mixtures' phase equilibria is crucial in nature and technical chemistry.
Phase equilibria calculations of mixtures require activity coefficients. However, experimental …

Perspectives of quantum computing for chemical engineering

DE Bernal, A Ajagekar, SM Harwood, ST Stober… - AIChE …, 2022 - Wiley Online Library
Quantum computing has been attracting public attention recently. This interest is driven by
the advancements in hardware, software, and algorithms required for its successful usage …

Generative ai and process systems engineering: The next frontier

B Decardi-Nelson, AS Alshehri, A Ajagekar… - Computers & Chemical …, 2024 - Elsevier
This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …

Deep learning to catalyze inverse molecular design

AS Alshehri, F You - Chemical Engineering Journal, 2022 - Elsevier
The discovery of superior molecular solutions through computational methods is critical for
innovative technologies and their role in addressing pressing resources, health, and …

Leveraging 2D molecular graph pretraining for improved 3D conformer generation with graph neural networks

K Alhamoud, Y Ghunaim, AS Alshehri, G Li… - Computers & Chemical …, 2024 - Elsevier
Predicting stable 3D molecular conformations from 2D molecular graphs is a challenging
and resource-intensive task, yet it is critical for various applications, particularly drug design …

[HTML][HTML] Synthesis and design methods for energy-efficient distillation processes

M Skiborowski - Current Opinion in Chemical Engineering, 2023 - Elsevier
In order to achieve net-zero emissions until 2050, it is of utmost importance to improve the
energy efficiency and thereby reduce the greenhouse gas emissions in the chemical …

A scalable and integrated machine learning framework for molecular properties prediction

G Chen, Z Song, Z Qi, K Sundmacher - AIChE Journal, 2023 - Wiley Online Library
This work introduced a scalable and integrated machine learning (ML) framework to
facilitate important steps of building quantitative structure–property relationship (QSPR) …