29 citations · 46 across the 5 of their papers we have counts for
5 papers
Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework
Zihan Guan, Rituparna Datta, Mengxuan Hu +5
Large language models (LLMs) have shown promise in constructing mechanistic models from data. However, existing evaluations largely focus on simplified settings and fail to capture…
Expert-Grounded Automatic Prompt Engineering for Extracting Lattice Constants of High-Entropy Alloys from Scientific Publications using Large Language Models
Shunshun Liu, Talon R. Booth, Yangfeng Ji +2
Large language models (LLMs) have shown promise for scientific data extraction from publications, but rely on manual prompt refinement. We present an expert-grounded automatic prom…
Type-1.5 SNSPD: Interacting vortex theory of two bandgap superconducting single photon detectors
Leif Bauer, Daien He, Sathwik Bharadwaj +3
Photon detectors based on type-2 superconductors have found widespread applications from on-chip quantum computing to quantum remote sensing. Here, we develop the theory for a new…
Observation of helimagnetism in the candidate ferroelectric CrI
John A. Schneeloch, Shunshun Liu, Prasanna V. Balachandran +2
CrI is a quasi-one dimensional (1D) van der Waals (vdW) system that exhibits helimagnetism that propagates along the ribbons. This was determined from neutron time-of-flight…
Integrating Machine Learning with Mechanistic Models for Predicting the Yield Strength of High Entropy Alloys
Shunshun Liu, Kyungtae Lee, Prasanna V. Balachandran
Accelerating the design of materials with targeted properties is one of the key materials informatics tasks. The most common approach takes a data-driven motivation, where the unde…