Energy and Advanced Computing in the Age of Machine Learning: From Quantum to Grid

A special issue of Computation (ISSN 2079-3197).

Deadline for manuscript submissions: 15 December 2026 | Viewed by 1642

Special Issue Editor


E-Mail Website
Guest Editor
Chemical Engineering Department, Texas A & M University, College Station, TX 77840, USA
Interests: machine learning; multiscale modeling; Li-ion battery; computational electrochemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The lack of understanding at various length and time scales has brought to focus the powerful need for more research in high-performance energy storage systems. This Special Issue, “Energy and Advanced Computing in the Age of Machine Learning: From Quantum to Grid” invokes advanced contributions using focused multiscale simulation methods in fundamental and applied battery research.

Our goal is to showcase advances from electronic structure calculations and molecular simulations down to continuum-level modeling while describing how these approaches provide a holistic understanding of the system. Of particular interest will be simulations explaining but not limited to:

  • Capacity Fading;
  • Ion transport;
  • Interfacial stability and dynamics;
  • Phase change mechanisms;
  • Mechanical degradation;
  • Thermal processes;
  • Li dendrite formation/growth;
  • Manufacturing parameters;
  • Battery performance.

Focused on lithium-ion, sodium-ion, solid-state, redox-flow batteries and other emerging battery chemistries.

We encourage submission of formulating new scale-bridging methodologies like Quantum Mechanics /Molecular Mechanics coupling or hierarchical modeling. Also welcome is the use of machine learning to accelerate simulation pace, guide material discovery simulations or experimental measurements linked with simulation outputs.

Dr. Diego E. Galvez-Aranda
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computation is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multiscale modeling
  • machine learning
  • computational simulation
  • multiphysics simulation
  • energy storage devices
  • electrode/electrolyte interfaces

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

20 pages, 4442 KB  
Article
Modeling a High-Efficiency BMS for Light Electromobility and Energy Storage in Critical Environments
by Manuel J. Pasion-Fuentes, Mauricio P. Galvez-Legua and Diego E. Galvez-Aranda
Computation 2026, 14(3), 61; https://doi.org/10.3390/computation14030061 - 2 Mar 2026
Viewed by 673
Abstract
Recent advances in energy storage systems and in increasingly efficient, safe, and energy-dense cell chemistries have driven the need for commercial Battery Management System (BMS) architectures with greater control, data acquisition, and communication capabilities, primarily oriented towards customization. This demand introduces a significant [...] Read more.
Recent advances in energy storage systems and in increasingly efficient, safe, and energy-dense cell chemistries have driven the need for commercial Battery Management System (BMS) architectures with greater control, data acquisition, and communication capabilities, primarily oriented towards customization. This demand introduces a significant change in how electrical systems are modeled and simulated when they integrate active electrochemical elements such as lithium-ion cells. This work presents the development and modeling of a BMS for critical and high-efficiency applications, based on active balancing techniques and incorporating an additional safety stage to respond to failures when charging LiFePO4 cells. The electrochemical model was built using an equivalent RLC circuit and RC pairs to represent the Thevenin response of the cell. For the simulation of active balancers, LTspice was employed, while charging and discharging processes and their effects on state of charge (SOC) and state of health (SOH) were complemented through analysis in MATLAB R2024a.The proposed approach offers an efficient tool for evaluating cell dynamics and validating battery management strategies in demanding scenarios. While the current approach prioritizes the individual modeling of electrical conversion systems, our framework presents an innovative multisystem macromodel, where not only is the electrical behavior simulated but also the control, efficiency, and safety of the system are determined, prioritizing reproducibility through SPICE tools. Full article
Show Figures

Figure 1

Back to TopTop