ArticleNanophotonics (Berlin, Germany)2025
Nanophotonic device design based on large language models: multilayer and metasurface examples.
Article in Nanophotonics (Berlin, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Metasurface Vision Transformer: A Generic AI Model for Metasurface Inverse Design.Nanophotonics (Berlin, Germany) · 2026Article
- A data-driven design for sound absorption of acoustic metamaterials based on large language models.Scientific reports · 2025Article
- MCP-enabled LLM for meta-optics inverse design: leveraging differentiable solver without LLM expertise.Nanophotonics (Berlin, Germany) · 2025Article
- Chat to chip: large language model based design of arbitrarily shaped metasurfaces.Nanophotonics (Berlin, Germany) · 2025Article
- A multi-agentic framework for real-time, autonomous freeform metasurface design.Science advances · 2025Article
- Special issue: "Metamaterials and Plasmonics in Asia".Nanophotonics (Berlin, Germany) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large language models (LLMs) have gained significant prominence in language processing, demonstrating remarkable performance across a wide range of tasks. Recently, LLMs have been explored in various scientific fields beyond language-based tasks. However, their application in the design of nanophotonic devices remains less explored. Here, we investigate the capabilities of LLMs to address nanophotonic design problems without requiring domain-specific expertise of the user. Our findings show that an LLM with in-context learning enables nonexpert users to calculate optical responses of multilayer films via numerical simulations. Through conversational interaction and feedback between the LLM and the user, an optimal design of the multilayer films can be also produced for the user-provided target optical properties. Furthermore, we fine-tune the LLM using text-based representations of the structure and properties of optical metasurfaces. We demonstrate that the fine-tuned LLM can generate metasurface designs with target properties by reversing the input and output text. This research highlights the potential of LLMs to expedite the nanophotonic design process and to make it more accessible to a wider audience.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.