2026 Guide to Choosing Journals for Physics-Informed Neural Networks (PINNs)

Overview

Twenty‑one journals commonly targeted for Physics‑Informed Neural Networks (PINN) research are grouped by regional ranking (A‑D) and TOP label. The grouping does not imply quality ordering; it is only for quick lookup.

Code repository: https://github.com/xgxgnpu/Physics-informed-vibe-coding

Category A – Region 1, TOP Journals

Computer Methods in Applied Mechanics and Engineering (CMAME) – ISSN 0045‑7825 – Region T1 – TOP – Sub‑disciplines: Engineering (Comprehensive T1), Mathematics (Interdisciplinary Applications T1), Mechanics (T1)

Engineering Applications of Artificial Intelligence – ISSN 0952‑1976 – Region T1 – TOP – Sub‑disciplines: Automation & Control Systems (T1), Engineering (Comprehensive T1), Computer (AI T2), Engineering (Electrical & Electronic T2)

Nature Machine Intelligence – ISSN 2522‑5839 – Region T1 – TOP – Sub‑disciplines: Computer (AI T1), Computer (Interdisciplinary Applications T1)

Nature Computational Science – ISSN 2662‑8457 – Region T1 – TOP – Sub‑disciplines: Computer (Interdisciplinary Applications T1), Computer (Theoretical Methods T1), General‑purpose (T1)

Category B – Region 2, TOP Journals

Journal of Computational Physics (JCP) – ISSN 0021‑9991 – Region T2 – TOP – Sub‑disciplines: Physics (Mathematical Physics T1), Computer (Interdisciplinary Applications T3)

Neural Networks – ISSN 0893‑6080 – Region T2 – TOP – Sub‑disciplines: Computer (AI T2), Neuroscience (T2)

IEEE Transactions on Neural Networks and Learning Systems (TNNLS) – ISSN 2162‑237X – Region T2 – TOP – Sub‑disciplines: Computer (Hardware T1), Computer (Theoretical Methods T1), Computer (AI T2), Engineering (Electrical & Electronic T2)

Journal of Fluid Mechanics – ISSN 0022‑1120 – Region T2 – TOP – Sub‑disciplines: Physics (Fluid & Plasma T1), Mechanics (T2)

Applied Mathematics and Computation – ISSN 0096‑3003 – Region T2 – TOP – Sub‑discipline: Applied Mathematics (T2)

SIAM Journal on Scientific Computing – ISSN 1064‑8275 – Region T2 – TOP – Sub‑discipline: Applied Mathematics (T2)

International Journal of Heat and Mass Transfer – ISSN 0017‑9310 – Region T2 – TOP – Sub‑disciplines: Thermodynamics (T2), Engineering (Mechanical T2), Mechanics (T2)

Category C – Region 2 (non‑TOP)

Physics of Fluids – ISSN 1070‑6631 – Region T2 – Sub‑disciplines: Physics (Fluid & Plasma T1), Mechanics (T2)

Engineering with Computers – ISSN 0177‑0667 – Region T2 – Sub‑disciplines: Engineering (Mechanical T2), Computer (Interdisciplinary Applications T3)

Computers & Mathematics with Applications – ISSN 0898‑1221 – Region T2 – Sub‑discipline: Applied Mathematics (T2)

Computational Mechanics – ISSN 0178‑7675 – Region T2 – Sub‑disciplines: Mathematics (Interdisciplinary Applications T2), Mechanics (T3)

Advances in Water Resources – ISSN 0309‑1708 – Region T2 – Sub‑discipline: Water Resources (T2)

Machine Learning: Science and Technology – ISSN 2632‑2153 – Region T2 – Sub‑disciplines: Computer (AI T3), Computer (Interdisciplinary Applications T3)

Category D – Region 3 (non‑TOP)

Computer Physics Communications – ISSN 0010‑4655 – Region T3 – Sub‑disciplines: Physics (Mathematical Physics T2), Computer (Interdisciplinary Applications T3)

International Journal for Numerical Methods in Engineering (IJNME) – ISSN 0029‑5981 – Region T3 – Sub‑disciplines: Engineering (Comprehensive T3), Mathematics (Interdisciplinary Applications T3)

Scientific Reports – ISSN 2045‑2322 – Region T3 – Sub‑discipline: General‑purpose (T3)

Journal of Machine Learning Research (JMLR) – ISSN 1532‑4435 – Region T3 – Sub‑disciplines: Automation & Control Systems (T3), Computer (AI T3)

Statistics by Discipline

Engineering Technology – 7 journals: CMAME (T1), J. Fluid Mechanics (T2), Physics of Fluids (T2), International Journal of Heat and Mass Transfer (T2), Engineering with Computers (T2), Computational Mechanics (T2), IJNME (T3)

Computer Science – 6 journals: Nature Machine Intelligence (T1), Nature Computational Science (T1), Engineering Applications of AI (T1), Neural Networks (T2), IEEE TNNLS (T2), JMLR (T3)

Mathematics – 3 journals: Applied Mathematics and Computation (T2), SIAM Journal on Scientific Computing (T2), Computers & Mathematics with Applications (T2)

Physics & Astronomy – 3 journals: Journal of Computational Physics (T2), Machine Learning: Science and Technology (T2), Computer Physics Communications (T3)

Environmental Science & Ecology – 1 journal: Advances in Water Resources (T2)

General‑purpose – 1 journal: Scientific Reports (T3)

Journal Selection by Research Direction

Methodology & Algorithm Innovation – Suitable venues: CMAME, JCP, Neural Networks, SIAM Journal on Scientific Computing.

Fluid Mechanics & Heat Science Applications – Suitable venues: Physics of Fluids, Journal of Fluid Mechanics, International Journal of Heat and Mass Transfer.

Solid Mechanics & Structural Engineering – Suitable venues: Computational Mechanics, IJNME, Engineering with Computers.

Mathematical Analysis & Theory – Suitable venues: Applied Mathematics and Computation, Computers & Mathematics with Applications, SIAM Journal on Scientific Computing.

AI & Machine Learning Perspective – Suitable venues: IEEE TNNLS, Engineering Applications of AI, JMLR, Machine Learning: Science and Technology; Nature Machine Intelligence and Nature Computational Science welcome breakthrough interdisciplinary work.

Earth Science & Hydrology Applications – Suitable venue: Advances in Water Resources.

Broad Interdisciplinary Dissemination – Suitable venue: Scientific Reports.

Rational View on Rankings

Rankings are statistical tools, not value judgments. They reflect overall citation performance and do not set an upper or lower bound on the quality of individual articles.

Match matters more than rank. Publishing a PINN paper on fluid mechanics in Physics of Fluids can have greater impact than placing it in a higher‑ranked journal with a mismatched readership.

Rankings change; good work endures. Journal rankings are updated annually, but research that solves real problems retains lasting academic value.

The ultimate goal of research is to push knowledge boundaries, not to chase ranking metrics. Choose a venue that reaches the intended audience and focus on meaningful contributions.