Large language models for inorganic synthesis predictions
We evaluate the effectiveness of pretrained and fine-tuned large language models (LLMs)
for predicting the synthesizability of inorganic compounds and the selection of precursors …
for predicting the synthesizability of inorganic compounds and the selection of precursors …
A survey on potentials, pathways and challenges of large language models in new-generation intelligent manufacturing
C Zhang, Q Xu, Y Yu, G Zhou, K Zeng, F Chang… - Robotics and Computer …, 2025 - Elsevier
Abstract Nowadays, Industry 5.0 starts to gain attention, which advocates that intelligent
manufacturing should adequately consider the roles and needs of humans. In this context …
manufacturing should adequately consider the roles and needs of humans. In this context …
Strongly-confined colloidal lead-halide perovskite quantum dots: from synthesis to applications
Colloidal semiconductor nanocrystals enable the realization and exploitation of quantum
phenomena in a controlled manner, and can be scaled up for commercial uses. These …
phenomena in a controlled manner, and can be scaled up for commercial uses. These …
A survey on the memory mechanism of large language model based agents
Large language model (LLM) based agents have recently attracted much attention from the
research and industry communities. Compared with original LLMs, LLM-based agents are …
research and industry communities. Compared with original LLMs, LLM-based agents are …
CataLM: Empowering Catalyst Design Through Large Language Models
The field of catalysis holds paramount importance in shaping the trajectory of sustainable
development, prompting intensive research efforts to leverage artificial intelligence (AI) in …
development, prompting intensive research efforts to leverage artificial intelligence (AI) in …
Literature classification and its applications in condensed matter physics and materials science by natural language processing
The exponential growth of literature is constraining researchers' access to comprehensive
information in related fields. While natural language processing (NLP) may offer an effective …
information in related fields. While natural language processing (NLP) may offer an effective …
Exploring the Expertise of Large Language Models in Materials Science and Metallurgical Engineering
C Bajan, G Lambard - arXiv preprint arXiv:2501.04277, 2025 - arxiv.org
The integration of artificial intelligence into various domains is rapidly increasing, with Large
Language Models (LLMs) becoming more prevalent in numerous applications. This work is …
Language Models (LLMs) becoming more prevalent in numerous applications. This work is …
From Deep Learning to ChatGPT for Materials Design
M Mudabbiruddin, A Mosavi… - 2024 IEEE 11th …, 2024 - ieeexplore.ieee.org
Large language models (LLMs) provide competitive advantages to various fields of
research. This survey explores the journey from using deep learning to adopting ChatGPT in …
research. This survey explores the journey from using deep learning to adopting ChatGPT in …
基于机器学习的材料设计
赵纪军 - 物理, 2024 - cpsjournals.cn
近年来, 计算机算力的飞速提升推动了科学计算和人工智能领域的突破性进展.
这两个领域深度融合, 共同催生了数据驱动的变革性科学研究范式. 作为人工智能技术的代表 …
这两个领域深度融合, 共同催生了数据驱动的变革性科学研究范式. 作为人工智能技术的代表 …
Crystal Structure Generation Based On Material Properties
C Huang, JH Chen, HR Liang, CY Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
The discovery of new materials is very important to the field of materials science. When
researchers explore new materials, they often have expected performance requirements for …
researchers explore new materials, they often have expected performance requirements for …