TY - JOUR
T1 - Failure Case Reporting in Materials Informatics — What Is Documented and What Is Silenced
AU - Ahmed Mansour
AU - Omar Saeed
AU - Lina Hassan
JF - Journal of Artificial Intelligence for Materials Science
JO - J. Artif. Intell. Mater. Sci.
SN - 3149-8957
Y1 - 2023
VL - 2
IS - 2
SP - 29
N2 - Materials informatics, the application of data science and machine learning to materials research, has revolutionized the discovery and design of new materials. However, the field faces significant challenges in reporting failure cases, negative results, and biases, which are often silenced in the literature. This review examines documented failures in materials informatics, such as data bias, model overoptimism, and reproducibility issues, and highlights the systemic factors that lead to their underreporting. Drawing on 30 recent peer-reviewed articles, we explore themes including data quality, algorithmic limitations, and publication bias. The objectives are to assess what is typically documented, identify silenced aspects, such as unsuccessful experiments, and propose strategies for more transparent reporting. By addressing these gaps, the review aims to foster a more robust and trustworthy materials informatics ecosystem, ultimately accelerating sustainable innovation in materials science.
UR - https://iamrp.net/b172201838
ER -