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Journal of Computational and Data-Driven Materials Engineering
ISSN: 3149-9368
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Articles

Experimental Data Integration into ML Workflows for Real Alloys: A Review of Noisy, Sparse, and Heterogeneous Fusion
Hassan Rahman, Tariq Mahmood & Ali Raza
Review | Open access | 18 January 2026 | Article: 75
Why GNNs Fail for Metastable Phase Formation Energies: A Failure Mode Analysis
Kevin O’Brien, Liam Murphy & Sean Doyle
Original Research | Open access | 18 January 2026 | Article: 74
A Conceptual Framework for Uncertainty-Aware Active Learning in Compositional Design Spaces with Multiple Objectives
Isabella Garcia & Diego Herrera
Original Research | Open access | 18 January 2026 | Article: 73
A Decade of Data-Driven Materials Engineering: Progress, Remaining Gaps, and Unlearned Lessons
Mohamed Salah, Youssef Karim, Ahmed Nabil, Mahmoud Adel & Karim Hassan
Review | Open access | 18 January 2026 | Article: 72
Perspective: Why Materials AI Needs More Failure Reporting — A Position on Negative Results as Community Infrastructure
Anna Novak & Tomas Hruby
Original Research | Open access | 18 January 2026 | Article: 71
Critique of De-Facto Standard Loss Functions for Force-Field Training: Why Energy–Force Balance Fails on Anharmonic Systems
Luca Bianchi, Marco Rossi & Giulia Romano
Original Research | Open access | 18 January 2026 | Article: 70
Theory of Equivariant Error Cancellation in Multi-Property Materials GNNs: When Shared Representations Harm Specialization
Elif Yilmaz, Mehmet Demir, Ayse Kaya & Hasan Aydin
Original Research | Open access | 18 January 2026 | Article: 69
Defining “Chemical Space Coverage” for Generative Materials Models: A Boundary Problem for Diversity Metrics
Victor Hugo, Daniel Cruz & Javier Salazar
Original Research | Open access | 18 January 2026 | Article: 68
Why Invariant GNNs Predict Zero Piezoelectricity: Failure Modes under Tensor Property Prediction
Ahmed Al-Sayed & Omar Khalifa
Original Research | Open access | 18 January 2026 | Article: 67
A Framework for Validating ML Potentials against Experimental Phonon Dispersion and Elastic Constants
Sophie Laurent, Pierre Dubois, Marc Lefevre & Claire Moreau
Original Research | Open access | 18 January 2026 | Article: 66
Foundation Models and LLMs for Materials Science: A Review of Prompting, Fine-Tuning, and What Does Not Transfer
Gabriel Costa, Rafael Mendes, Bruno Teixeira & Lucas Ribeiro
Review | Open access | 18 January 2026 | Article: 65
Perspective: Autonomous Laboratories and Real-Time ML Feedback Loops — A Position for Closed-Loop Discovery
Minh Tran & Duc Pham
Original Research | Open access | 18 January 2026 | Article: 64
The Illusion of Generalizability in Foundation Models for Materials Science: A Critique of Zero-Shot Property Prediction
Ethan Wright, Chloe Bennett & Jack Turner
Original Research | Open access | 18 January 2026 | Article: 63
Neural Scaling Laws for Materials Property Databases: Theoretical Analysis of Power-Law Exponents from Data Redundancy
Diego Morales, Andres Gutierrez, Lucia Navarro & Pablo Rios
Original Research | Open access | 18 January 2026 | Article: 62
Redefining "Reproducibility" in Data-Driven Materials Synthesis: Between Algorithmic and Experimental Replication
Fatima Al-Zahra & Amina El Idrissi
Original Research | Open access | 18 January 2026 | Article: 61
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