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Articles by Linjiang Chen
OMC-bench and AtomBit-OMC: task-aligned benchmarks and robust, interpretable machine-learned interatomic potentials for organic molecular crystals
Abstract Organic molecular crystals (OMCs) underpin key applications in pharmaceuticals and functional materials, but accurate atomistic simulation remains difficult because OMC stability depends on subtle noncovalent interactions, conformational flexibility, and polymorphism.
Self-driving laboratories need an autonomy safety harness
Industrial self-driving laboratories need more than safe robots and instruments. They need an autonomy safety harness that defines how AI-generated intent becomes executable experiments, monitored actions and trustworthy evidence for downstream research and development (R&D).
Synthesis of covalent organic frameworks for photocatalytic hydrogen peroxide production guided by large language models - Nature Communications
Abstract The photosynthetic production of hydrogen peroxide (H2O2) from water and oxygen presents a sustainable alternative to the energy-intensive anthraquinone process. Covalent organic frameworks (COFs) have emerged as promising photocatalysts for H2O2 generation. However, most existing COF photocatalysts yield H2O2 at concentrations too low for practical applications, largely due to ongoing challenges in simultaneously optimizing photocatalytic activity and structural stability.
Dynamic guanidinium sulfate salt for selective carbon dioxide adsorption with negative pressure inflexion - Nature Communications
Abstract Hydrogen bonds’ flexible distances and moderate strength entitle compounds to dynamic properties under external stimuli. Here we report multiple phase transitions and counter-intuitive CO2 adsorption behavior of dynamic guanidinium sulfate (GS) salt assembled via hydrogen-bonds.
A practical inverse design approach for high-entropy catalysts using generative AI
Now An unexpected winner is emerging in the war on higher education. In the waning heat of last summer, freshly back in my office at a major research university, I found myself considering the higher-education hellscape that had lately descended upon the nation. I’d spent months reporting on the Trump …
Bottom-up computational design of shape-selective organic macrocycles for humid CO2 capture - Nature Chemistry
Abstract The capture of CO2 emissions using porous solids is challenging because polar water molecules bind more strongly in most materials than non-polar CO2 molecules. This is a challenge for both flue gas capture and for direct air capture alike. Here we develop a bottom-up computational screening workflow to calculate the binding energy of 27,446 diverse molecular fragments with both CO2 and water.
Selective CO2 Adsorption in Ultrahydrophobic Molecular Pyrene Frameworks by Computational Design
1. Introduction Click to copy section linkSection link copied! Anthropogenic climate change is a major challenge for society. (1) To tackle it, we need alternative energy sources, such as renewables, nuclear, and hydrogen power, but these have their own technical problems that must first be overcome before they can satisfy global energy demand. (2−4) In the meantime, interim technologies such as carbon capture and storage (CCS) are needed to reduce CO2 emissions.
Design of circularly polarized phosphorescence materials guided by transfer learning - Nature Communications
Abstract It is highly desirable that artificial circularly polarized phosphorescent materials with high luminescence asymmetry factor (glum), narrowband emission and tunable chiral phosphorescent performance can be constructed. Especially, precise control and simultaneous independent switching of circularly polarized fluorescent and phosphorescent performance for the same molecules remain a formidable challenge.
Quantifying interactions in the active encounter complex of frustrated Lewis pairs - Nature Communications
Abstract Sustainable catalysts based on main-group elements, such as frustrated Lewis pairs (FLPs), have emerged as alternatives to precious metal systems. The initial reaction of the Lewis acid, Lewis base and small molecule (e.g. H2) is formally termolecular, but the reaction is rationalised by the pre-association of the acid and base in an encounter complex.
A Machine Learned Potential for Investigating Single Crystal to Single Crystal Transformations in Complex Organic Molecular Systems
A Machine Learned Potential for Investigating Single Crystal to Single Crystal Transformations in Complex Organic Molecular Systems The packing of organic molecular crystals is often dominated by weak non-covalent interactions, making their in-situ rearrangement under external stimuli challenging to understand. We investigate a pressure-induced single-crystal-to-single-crystal (SCSC) transformation between two polymorphs of 2,4,5-triiodo-1H-imidazole using machine learning potentials.
Sequential closed-loop Bayesian optimization as a guide for organic molecular metallophotocatalyst formulation discovery - Nature Chemistry
Abstract Conjugated organic photoredox catalysts (OPCs) can promote a wide range of chemical transformations. It is challenging to predict the catalytic activities of OPCs from first principles, either by expert knowledge or by using a priori calculations, as catalyst activity depends on a complex range of interrelated properties. Organic photocatalysts and other catalyst systems have often been discovered by a mixture of design and trial and error.
Screening potential dye sensitizers for water splitting photocatalysts using a Genetic Algorithm
Screening potential dye sensitizers for water splitting photocatalysts using a Genetic Algorithm Addressing the global fossil energy crisis necessitates the efficient utilization of sustainable energy sources. Hydrogen, a green fuel, can be generated by using sunlight, water, and a photocatalyst. Employing sensitizers holds promise for enhancing photocatalyst performance, enabling high rates of hydrogen evolution through increased visible light absorption.
Fine-tuning GPT-3 for machine learning electronic and functional properties of organic molecules
Fine-tuning GPT-3 for machine learning electronic and functional properties of organic molecules We evaluate the effectiveness of fine-tuning GPT-3 for the prediction of electronic and functional properties of organic molecules. Our findings show that fine-tuned GPT-3 can successfully identify and distinguish between chemically meaningful patterns, and discern subtle differences among them, exhibiting robust predictive performance for the prediction of molecular properties.
Intuitive and Efficient Approach to Determine the Band Structure of Covalent Organic Frameworks from Their Chemical Constituents
Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Chem. Theory Comput. 2024, XXXX, XXX RETURN TO ARTICLES ASAPQuantum Electronic S...Quantum Electronic StructureNEXT * , , Linjiang Chen School of Chemistry and School of Computer Science, University of Birmingham, Birmingham B15 2TT, U.K. , and * Cite this: J. Chem. Theory Comput. 2024, XXXX, XXX .
Mechanism of APAF1 alleviating DR
Back to Journals » Diabetes, Metabolic Syndrome and Obesity » Volume 17 Authors Ding Y, Chen L, Xu J, Feng Y, Liu Q Received 22 November 2023 Accepted for publication 22 March 2024 Published 10 April 2024 Volume 2024:17 Pages 1635—1649 DOI https://doi.org/10.2147/DMSO.S449049 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 3 Editor who approved publication: Dr Konstantinos Tziomalos Yuanyuan Ding,* Linjiang Chen,* Jing Xu, Yuhan Feng, Qiong Liu...
Machine Learning Accelerated Exploration of Ternary Organic Heterojunction Photocatalysts for Sacrificial Hydrogen Evolution
Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Am. Chem. Soc. 2023, XXXX, XXX RETURN TO ARTICLES ASAPPREVArticleNEXT Haofan Yang Leverhulme Research Centre for Functional Materials Design, Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L7 3NY, U.K. , Yu Che Leverhulme Research Centre for Functional Materials Design, Materials Innovation Factory and Department of Chemistry, University of Liverpool, Liverpool L7 3NY, U.K. , * Andrew I.
Machine Learning Accelerated Exploration of Ternary Organic Heterojunction Photocatalysts for Sacrificial Hydrogen Evolution
Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Am. Chem. Soc. 2023, XXXX, XXX Terms & Conditions Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses).
Exploring cooperative porosity in organic cage crystals using in situ diffraction and molecular simulations
Exploring cooperative porosity in organic cage crystals using in situ diffraction and molecular simulations† A porous organic cage crystal, α-CC2, shows unexpected adsorption of sulphur hexafluoride (SF6) in its cage cavities: analysis of the static crystal structure indicates that SF6 is occluded, as even the smallest diatomic gas, H2, is larger than the window of the cage pore.
Geometric landscapes for material discovery within energy-structure-function maps
Geometric landscapes for material discovery within energy–structure–function maps†‡ Seyed Mohamad Moosavi, §a Henglu Xu,§a Linjiang Chen,b Andrew I.
Exploring cooperative porosity in organic cage crystals using in situ diffraction and molecular simulations
Exploring cooperative porosity in organic cage crystals using in situ diffraction and molecular simulations A porous organic cage crystal, α-CC2, shows unexpected adsorption of sulphur hexafluoride (SF6) in its cage cavities, which are formally occluded even to the smallest diatomic gas, H2, according to a pore analysis of the static crystal structure.
Efficient separation of propane and propene by a hypercrosslinked polymer doped with Ag(I)
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Sulfone-containing covalent organic frameworks for photocatalytic hydrogen evolution from water
The authors acknowledge funding from the Engineering and Physical Sciences Research Council (EPSRC) (EP/N004884/1), the European Union’s Seventh Framework Programme through grant agreement nos. 321156 (ERC-AG-PE5-ROBOT) and 692685, and the Leverhulme Trust via the Leverhulme Research Centre for Functional Materials Design. X.W. thanks the China Scholarship Council for a PhD studentship.
Inside Information on Xenon Adsorption in Porous Organic Cages by NMR
A solid porous molecular crystal formed from an organic cage, CC3, has unprecedented performance for the separation of rare gases. Here, xenon was used as an internal reporter providing extraordinarily versatile information about the gas adsorption phenomena in the cage and window cavities of the material.
Functional materials discovery using energy-structure-function maps
CSP was performed using a quasi-random sampling procedure, as implemented in the Global Lattice Energy Explorer software27. Molecules were first sketched in ChemDraw, followed by an initial molecular-geometry optimization with the COMPASS force field, as implemented in the Materials Studio software package34.
Three-dimensional protonic conductivity in porous organic cage solids
The neutral, crystalline cage solid CC3 can reversibly adsorb up to 20.1 wt% water, which equates to approximately 12 H O molecules per cage34. These H O molecules can be located by single-crystal X-ray diffraction (SC-XRD; Fig. 1c), but their displacement parameters indicate that they are mobile in the 3D interconnected pore network, and hence could introduce proton conductivity, as for Nafion11 and water-mediated proton-conducting MOFs8,9.
Understanding static, dynamic and cooperative porosity in molecular materials
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