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Towards Agentic Intelligence for Materials Science
Authors:
Huan Zhang,
Yizhan Li,
Wenhao Huang,
Ziyu Hou,
Yu Song,
Xuye Liu,
Farshid Effaty,
Jinya Jiang,
Sifan Wu,
Qianggang Ding,
Izumi Takahara,
Leonard R. MacGillivray,
Teruyasu Mizoguchi,
Tianshu Yu,
Lizi Liao,
Yuyu Luo,
Yu Rong,
Jia Li,
Ying Diao,
Heng Ji,
Bang Liu
Abstract:
The convergence of artificial intelligence and materials science presents a transformative opportunity, but achieving true acceleration in discovery requires moving beyond task-isolated, fine-tuned models toward agentic systems that plan, act, and learn across the full discovery loop. This survey advances a unique pipeline-centric view that spans from corpus curation and pretraining, through domai…
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The convergence of artificial intelligence and materials science presents a transformative opportunity, but achieving true acceleration in discovery requires moving beyond task-isolated, fine-tuned models toward agentic systems that plan, act, and learn across the full discovery loop. This survey advances a unique pipeline-centric view that spans from corpus curation and pretraining, through domain adaptation and instruction tuning, to goal-conditioned agents interfacing with simulation and experimental platforms. Unlike prior reviews, we treat the entire process as an end-to-end system to be optimized for tangible discovery outcomes rather than proxy benchmarks. This perspective allows us to trace how upstream design choices-such as data curation and training objectives-can be aligned with downstream experimental success through effective credit assignment.
To bridge communities and establish a shared frame of reference, we first present an integrated lens that aligns terminology, evaluation, and workflow stages across AI and materials science. We then analyze the field through two focused lenses: From the AI perspective, the survey details LLM strengths in pattern recognition, predictive analytics, and natural language processing for literature mining, materials characterization, and property prediction; from the materials science perspective, it highlights applications in materials design, process optimization, and the acceleration of computational workflows via integration with external tools (e.g., DFT, robotic labs). Finally, we contrast passive, reactive approaches with agentic design, cataloging current contributions while motivating systems that pursue long-horizon goals with autonomy, memory, and tool use. This survey charts a practical roadmap towards autonomous, safety-aware LLM agents aimed at discovering novel and useful materials.
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Submitted 6 February, 2026; v1 submitted 29 January, 2026;
originally announced February 2026.
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Chiral emergence in multistep hierarchical assembly of achiral conjugated polymers
Authors:
Kyung Sun Park,
Zhengyuan Xue,
Bijal B. Patel,
Hyosung An,
Justin J. Kwok,
Prapti Kafle,
Qian Chen,
Diwakar Shukla,
Ying Diao
Abstract:
Intimately connected to the rule of life, chirality remains a long-time fascination in biology, chemistry, physics and materials science. Chiral structures, e.g., nucleic acid and cholesteric phase developed from chiral molecules are common in nature and synthetic soft materials. While it was recently discovered that achiral but bent core mesogens can also form chiral helices, the assembly of chir…
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Intimately connected to the rule of life, chirality remains a long-time fascination in biology, chemistry, physics and materials science. Chiral structures, e.g., nucleic acid and cholesteric phase developed from chiral molecules are common in nature and synthetic soft materials. While it was recently discovered that achiral but bent core mesogens can also form chiral helices, the assembly of chiral microstructures from achiral polymers has rarely been explored. Here, we reveal chiral emergence from achiral conjugated polymers for the first time, in which hierarchical helical structures are developed through a multistep assembly pathway. Upon increasing concentration beyond a threshold volume fraction, pre-aggregated polymer nanofibers form lyotropic liquid crystalline (LC) mesophases with complex, chiral morphologies. Combining imaging, X-ray and spectroscopy techniques with molecular simulations, we demonstrate that this structural evolution arises from torsional polymer molecules which induce multiscale helical assembly, progressing from nano- to micron scale helical structures as the solution concentration increases. This study unveils a previously unknown complex state of matter for conjugated polymers that can pave way to a new field of chiral (opto)electronics. We anticipate that hierarchical chiral helical structures can profoundly impact how conjugated polymers interact with light, transport charges, and transduce signals from biomolecular interactions and even give rise to properties unimagined before.
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Submitted 13 July, 2021;
originally announced July 2021.
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A Reversible Structural Phase Transition by Electrochemical Ion Injection into a Conjugated Polymer
Authors:
Connor G. Bischak,
Lucas Q. Flagg,
Kangrong Yan,
Tahir Rehman,
Daniel W. Davies,
Ramsess J. Quezada,
Jonathan W. Onorato,
Christine K. Luscombe,
Ying Diao,
Chang-Zhi Li,
David S. Ginger
Abstract:
We find that conjugated polymers can undergo reversible structural phase transitions during electrochemical oxidation and ion injection. We study poly[2,5-bis(thiophenyl)-1,4-bis(2-(2-(2-methoxyethoxy)ethoxy)ethoxy)benzene] (PB2T-TEG), a conjugated polymer with glycolated side chains. Using grazing incidence wide angle X-ray scattering (GIWAXS), we show that, in contrast to previously known polyme…
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We find that conjugated polymers can undergo reversible structural phase transitions during electrochemical oxidation and ion injection. We study poly[2,5-bis(thiophenyl)-1,4-bis(2-(2-(2-methoxyethoxy)ethoxy)ethoxy)benzene] (PB2T-TEG), a conjugated polymer with glycolated side chains. Using grazing incidence wide angle X-ray scattering (GIWAXS), we show that, in contrast to previously known polymers, this polymer switches between two structurally distinct crystalline phases associated with electrochemical oxidation/reduction in an aqueous electrolyte. Importantly, we show that this unique phase change behavior has important physical consequences for ion transport. Notably, using moving front experiments visualized by both optical microscopy and super-resolution photoinduced force microscopy (PiFM), we show that a propagating ion front in PB2T-TEG exhibits non-Fickian transport, retaining a sharp step-edge profile, in stark contrast to the Fickian diffusion more commonly observed. This structural phase transition is reminiscent of those accompanying ion uptake in inorganic materials like LiFePO$_{4}$. We propose that engineering similar properties in future conjugated polymers may enable the realization of new materials with superior performance in electrochemical energy storage or neuromorphic memory applications.
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Submitted 14 October, 2019;
originally announced October 2019.