iScience, Journal Year: 2024, Volume and Issue: 27(4), P. 109451 - 109451
Published: March 7, 2024
This study explores the use of large language models (LLMs) in interpreting and predicting experimental outcomes based on given variables, leveraging human-like reasoning inference capabilities LLMs, using selective catalytic reduction NO
Language: Английский
Journal of the American Chemical Society, Journal Year: 2023, Volume and Issue: 145(51), P. 28284 - 28295
Published: Dec. 13, 2023
We construct a data set of metal-organic framework (MOF) linkers and employ fine-tuned GPT assistant to propose MOF linker designs by mutating modifying the existing structures. This strategy allows model learn intricate language chemistry in molecular representations, thereby achieving an enhanced accuracy generating structures compared with its base models. Aiming highlight significance design strategies advancing discovery water-harvesting MOFs, we conducted systematic variant expansion upon state-of-the-art MOF-303 utilizing multidimensional approach that integrates extension multivariate tuning strategies. synthesized series isoreticular aluminum termed Long-Arm MOFs (LAMOF-1 LAMOF-10), featuring bear various combinations heteroatoms their five-membered ring moiety, replacing pyrazole either thiophene, furan, or thiazole rings combination two. Beyond consistent robust architecture, as demonstrated permanent porosity thermal stability, LAMOF offers generalizable synthesis strategy. Importantly, these 10 LAMOFs establish new benchmarks for water uptake (up 0.64 g g-1) operational humidity ranges (between 13 53%), expanding diversity MOFs.
Language: Английский
Citations
54
Chemical Reviews, Journal Year: 2024, Volume and Issue: 124(16), P. 9633 - 9732
Published: Aug. 13, 2024
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through automation experimental workflows, along with autonomous planning, SDLs hold potential to greatly accelerate research in chemistry and materials discovery. This review provides in-depth analysis state-of-the-art SDL technology, its applications across various disciplines, implications for industry. additionally overview enabling technologies SDLs, including their hardware, software, integration laboratory infrastructure. Most importantly, this explores diverse range domains where have made significant contributions, from drug discovery science genomics chemistry. We provide a comprehensive existing real-world examples different levels automation, challenges limitations associated each domain.
Language: Английский
Citations
39
Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(19)
Published: Jan. 17, 2024
Abstract Photocatalytic CO 2 reduction into renewable hydrocarbon fuels is a green solution to address emission and energy issues simultaneously. However, the fast recombination of photogenerated charge carriers sluggish surface reaction kinetics restrict efficiency photocatalytic reduction. The emergence 2D MXenes has potential in improving reduction, owing their high electrical conductivity, flexible structural properties, abundant active sites. Hence, this review will concisely summarize highlight recent advances MXenes‐based photocatalysts used First, synthesis properties briefly introduced. Second, mechanism photoreduction along with roles are summarized, including promoting adsorption , enhancing separation photo‐induced carriers, acting as robust support, photothermal effect. Third, different kinds such MXenes/metal oxides, MXenes/nitrides, MXenes/LDH, MXenes/perovskite, MXene‐derived for classified via type semiconductors. Finally, challenges perspectives also presented, exploring suitable machine learning, uncovering structure‐activity relationship by situ, time‐ space‐resolved characterization techniques, anti‐oxidization ability, scale‐up applications.
Language: Английский
Citations
22
Digital Discovery, Journal Year: 2024, Volume and Issue: 3(3), P. 491 - 501
Published: Jan. 1, 2024
The integration of artificial intelligence into scientific research opens new avenues with the advent GPT-4V, a large language model equipped vision capabilities.
Language: Английский
Citations
18
ACS Nano, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 3, 2025
This perspective highlights the transformative potential of Metal-Organic Frameworks (MOFs) in environmental and healthcare sectors. It discusses work that has advanced beyond technology readiness levels >4 including applications capture, storage, conversion gases to value added products. showcases efforts most salient MOFs which have been performed at a great cadence, enabled by federal government, large companies, startups commercialize these technologies despite facing significant challenges. article also forecasts role nanoscale healthcare, strides toward personalized medicine, advocating for their use custom-tailored drug delivery systems. Finally we underscore acceleration MOF research development through integration machine learning AI, positioning as versatile tools poised address global sustainability health
Language: Английский
Citations
5
Nature Reviews Materials, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 31, 2025
Language: Английский
Citations
4
Advanced Electronic Materials, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 14, 2025
Abstract As hydrogel research progresses, hydrogels are becoming essential tools in bioelectronics and biotechnology. This review explores the diverse range of natural synthetic gel materials tailored for specific bioelectronic applications, with a focus on their integration electronic components to create responsive, multifunctional systems. The role Artificial Intelligence (AI) advancing design functionality from optimizing material properties enabling precise, predictive modeling is investigated. Furthermore, recent innovations that harness synergy between hydrogels, electronics, AI discussed, emphasizing potential these drive future advances biomedical technologies. AI‐driven approaches transforming development applications wound healing, biosensing, drug delivery, tissue engineering.
Language: Английский
Citations
2
Journal of Nanobiotechnology, Journal Year: 2025, Volume and Issue: 23(1)
Published: Feb. 28, 2025
Cancer treatment is currently one of the most critical healthcare issues globally. A well-designed drug delivery system can precisely target tumor tissues, improve efficacy, and reduce damage to normal tissues. Stimuli-responsive systems (SRDDSs) have shown promising application prospects. Intelligent nano responsive endogenous stimuli such as weak acidity, complex redox characteristics, hypoxia, active energy metabolism, well exogenous like high temperature, light, pressure, magnetic fields are increasingly being applied in chemotherapy, radiotherapy, photothermal therapy, photodynamic various other anticancer approaches. Metal–organic frameworks (MOFs) become candidate materials for constructing SRDDSs due their large surface area, tunable porosity structure, ease synthesis modification, good biocompatibility. This paper reviews MOF-based modes cancer therapy. It summarizes key aspects, including classification, synthesis, modifications, loading modes, stimuli-responsive mechanisms, roles different modalities. Furthermore, we address current challenges summarize potential applications artificial intelligence MOF synthesis. Finally, propose strategies enhance efficacy safety SRDDSs, ultimately aiming at facilitating clinical translation.
Language: Английский
Citations
2
Journal of Chemical Information and Modeling, Journal Year: 2024, Volume and Issue: 64(13), P. 4958 - 4965
Published: March 26, 2024
Along with the development of machine learning, deep and large language models (LLMs) such as GPT-4 (GPT: Generative Pre-Trained Transformer), artificial intelligence (AI) tools have been playing an increasingly important role in chemical material research to facilitate screening design. Despite exciting progress based AI assistance, open-source LLMs not gained much attention from scientific community. This work primarily focused on metal–organic frameworks (MOFs) a subdomain chemistry evaluated six top-rated comprehensive set tasks including MOFs knowledge, basic in-depth knowledge extraction, database reading, predicting property, experiment design, computational scripts generation, guiding experiment, data analysis, paper polishing, which covers units research. In general, these were capable most tasks. Especially, Llama2-7B ChatGLM2-6B found perform particularly well moderate resources. Additionally, performance different parameter versions same model was compared, revealed superior higher versions.
Language: Английский
Citations
14
Chemical Science, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 9, 2024
Large language models (LLMs) have emerged as powerful tools in chemistry, significantly impacting molecule design, property prediction, and synthesis optimization. This review highlights LLM capabilities these domains their potential to accelerate scientific discovery through automation. We also LLM-based autonomous agents: LLMs with a broader set of interact surrounding environment. These agents perform diverse tasks such paper scraping, interfacing automated laboratories, planning. As are an emerging topic, we extend the scope our beyond chemistry discuss across any domains. covers recent history, current capabilities, design agents, addressing specific challenges, opportunities, future directions chemistry. Key challenges include data quality integration, model interpretability, need for standard benchmarks, while point towards more sophisticated multi-modal enhanced collaboration between experimental methods. Due quick pace this field, repository has been built keep track latest studies: https://github.com/ur-whitelab/LLMs-in-science.
Language: Английский
Citations
13