23 citations · 62 across the 13 of their papers we have counts for
13 papers
MatSKRAFT: A framework for large-scale materials knowledge extraction from scientific tables
Kausik Hira, Mohd Zaki, Mausam +1
Scientific progress increasingly depends on synthesizing knowledge across vast literature, yet most experimental data remains trapped in semi-structured formats that resist systema…
Foundational Large Language Models for Materials Research
Vaibhav Mishra, Somaditya Singh, Dhruv Ahlawat +7
Materials discovery and development are critical for addressing global challenges. Yet, the exponential growth in materials science literature comprising vast amounts of textual da…
Autonomous Microscopy Experiments through Large Language Model Agents
Indrajeet Mandal, Jitendra Soni, Mohd Zaki +5
Large language models (LLMs) are revolutionizing self driving laboratories (SDLs) for materials research, promising unprecedented acceleration of scientific discovery. However, cur…
Reconstructing Materials Tetrahedron: Challenges in Materials Information Extraction
Kausik Hira, Mohd Zaki, Dhruvil Sheth +2
The discovery of new materials has a documented history of propelling human progress for centuries and more. The behaviour of a material is a function of its composition, structure…
MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models
Mohd Zaki, Jayadeva, Mausam +1
Information extraction and textual comprehension from materials literature are vital for developing an exhaustive knowledge base that enables accelerated materials discovery. Langu…
Glass Hardness: Predicting Composition and Load Effects via Symbolic Reasoning-Informed Machine Learning
Sajid Mannan, Mohd Zaki, Suresh Bishnoi +8
Glass hardness varies in a non-linear fashion with the chemical composition and applied load, a phenomenon known as the indentation size effect (ISE), which is challenging to predi…
Cementron: Machine Learning the Constituent Phases in Cement Clinker from Optical Images
Mohd Zaki, Siddhant Sharma, Sunil Kumar Gurjar +3
Cement is the most used construction material. The performance of cement hydrate depends on the constituent phases, viz. alite, belite, aluminate, and ferrites present in the cemen…
Accelerated Design of Chalcogenide Glasses through Interpretable Machine Learning for Composition Property Relationships
Sayam Singla, Sajid Mannan, Mohd Zaki +1
Chalcogenide glasses possess several outstanding properties that enable several ground breaking applications, such as optical discs, infrared cameras, and thermal imaging systems.…
DiSCoMaT: Distantly Supervised Composition Extraction from Tables in Materials Science Articles
Tanishq Gupta, Mohd Zaki, Devanshi Khatsuriya +3
A crucial component in the curation of KB for a scientific domain (e.g., materials science, foods & nutrition, fuels) is information extraction from tables in the domain's publishe…
MatSciBERT: A Materials Domain Language Model for Text Mining and Information Extraction
Tanishq Gupta, Mohd Zaki, N. M. Anoop Krishnan +1
An overwhelmingly large amount of knowledge in the materials domain is generated and stored as text published in peer-reviewed scientific literature. Recent developments in natural…
Revealing the Compositional Control of Electrical, Mechanical, Optical, and Physical Properties of Inorganic Glasses
R. Ravinder, Suresh Bishnoi, Mohd Zaki +1
Inorganic glasses, produced by the melt-quenching of a concoction of minerals, compounds, and elements, can possess unique optical and elastic properties along with excellent chemi…
Unveiling the Glass Veil: Elucidating the Optical Properties in Glasses with Interpretable Machine Learning
Mohd Zaki, Vineeth Venugopal, R. Ravinder +5
Due to their excellent optical properties, glasses are used for various applications ranging from smartphone screens to telescopes. Developing compositions with tailored Abbe numbe…
Looking Through Glass: Knowledge Discovery from Materials Science Literature using Natural Language Processing
Vineeth Venugopal, Sourav Sahoo, Mohd Zaki +3
Most of the knowledge in materials science literature is in the form of unstructured data such as text and images. Here, we present a framework employing natural language processin…