jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Manu Suvarna | Alain C. Vaucher | Sharon Mitchell | Teodoro Laino | Javier Pérez‐Ramírez
Source: Nature Communications (article, 2023-12-02)
Field: Materials Science — Materials Chemistry

Language models and protocol standardization guidelines for accelerating synthesis planning in heterogeneous catalysis Synthesis protocol exploration is paramount in catalyst discovery, yet keeping pace with rapid literature advances is increasingly time intensive. Automated synthesis protocol analysis is attractive for swiftly identifying opportunities and informing predictive models, however such applications in heterogeneous catalysis remain limited. In this proof-of-concept, we introduce a transformer model for this task, exemplified using single-atom heterogeneous catalysts (SACs), a rapidly expanding catalyst family. Our model adeptly converts SAC protocols into action sequences, and we use this output to facilitate statistical inference of their synthesis trends and applications, potentially expediting literature review and analysis. We demonstrate the model's adaptability across distinct heterogeneous catalyst families, underscoring its versatility. Finally, our study highlights a critical issue: the lack of standardization in reporting protocols hampers machine-reading capabilities. Embracing digital advances in catalysis demands a shift in data reporting norms, and to this end, we offer guidelines for writing protocols, significantly improving machine-readability. We release our model as an open-source web application, inviting a fresh approach to accelerate heterogeneous catalysis synthesis planning. Computer science ; Protocol (science) ; Standardization ; Task (project management) ; Data science ; Process management ; Systems engineering ; Engineering Machine Learning in Materials Science ; Software Engineering Research ; Topic Modeling
Authors: Ioan-Bogdan Magdău | Daniel J. Arismendi‐Arrieta | Holly E. Smith | Clare P. Grey | Kersti Hermansson | Gábor Cśanyi
Source: npj Computational Materials (article, 2023-08-17)
Field: Materials Science — Materials Chemistry

Machine learning force fields for molecular liquids: Ethylene Carbonate/Ethyl Methyl Carbonate binary solvent Abstract Highly accurate ab initio molecular dynamics (MD) methods are the gold standard for studying molecular mechanisms in the condensed phase, however, they are too expensive to capture many key properties that converge slowly with respect to simulation length and time scales. Machine learning (ML) approaches which reach the accuracy of ab initio simulation, and which are, at the same time, sufficiently affordable hold the key to bridging this gap. In this work we present a robust ML potential for the EC:EMC binary solvent, a key component of liquid electrolytes in rechargeable Li-ion batteries. We identify the necessary ingredients needed to successfully model this liquid mixture of organic molecules. In particular, we address the challenge posed by the separation of scale between intra- and inter-molecular interactions, which is a general issue in all condensed phase molecular systems. Ethylene carbonate ; Molecular dynamics ; Molecule ; Dimethyl carbonate ; Solvent ; Electrolyte ; Component (thermodynamics) ; Ab initio ; Chemical physics ; Materials science ; Chemistry ; Computational chemistry ; Physics ; Organic chemistry ; Thermodynamics ; Physical chemistry ; Electrode Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Crystallography and molecular interactions
Authors: Keisuke Takahashi | Junya Ohyama | Shun Nishimura | Jun Fujima | Lauren Takahashi | Takeaki Uno | Toshiaki Taniike
Source: Chemical Communications (review, 2023-01-01)
Field: Materials Science — Materials Chemistry

Catalysts informatics: paradigm shift towards data-driven catalyst design Designing catalysts is a challenging matter as catalysts are involved with various factors that impact synthesis, catalysts, reactor and reaction. In order to overcome these difficulties, catalysts informatics is proposed as an alternative way to design and understand catalysts. The underlying concept of catalysts informatics is to design the catalysts from trends and patterns found in catalysts data. Here, three key concepts are introduced: experimental catalysts database, knowledge extraction from catalyst data <i>via</i> data science, and a catalysts informatics platform. Methane oxidation is chosen as a prototype reaction for demonstrating various aspects of catalysts informatics. This work summarizes how catalysts informatics plays a role in catalyst design. The work covers big data generation <i>via</i> high throughput experiments, machine learning, catalysts network method, catalyst design from small data, catalysts informatics platform, and the future of catalysts informatics <i>via</i> ontology. Thus, the proposed catalysts informatics would help innovate how catalysts can be designed and understood. Catalysis ; Informatics ; Work (physics) ; Health informatics ; Materials informatics ; Computer science ; Nanotechnology ; Chemistry ; Materials science ; Engineering ; Engineering informatics ; Organic chemistry ; Medicine ; Nursing ; Public health Machine Learning in Materials Science ; Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions
Authors: Tiago F. T. Cerqueira | Antonio Sanna | Miguel A. L. Marques
Source: Advanced Materials (article, 2023-11-21)
Field: Chemistry — Inorganic Chemistry

Sampling the Materials Space for Conventional Superconducting Compounds A large scale study of conventional superconducting materials using a machine-learning accelerated high-throughput workflow is performed, starting by creating a comprehensive dataset of around 7000 electron-phonon calculations performed with reasonable convergence parameters. This dataset is then used to train a robust machine learning model capable of predicting the electron-phonon and superconducting properties based on structural, compositional, and electronic ground-state properties. Using this machine, the transition temperatures (T<sub>c</sub> ) of approximately 200 000 metallic compounds are evaluated, all of which are on the convex hull of thermodynamic stability (or close to it) to maximize the probability of synthesizability. Compounds predicted to have T<sub>c</sub> values exceeding 5 K are further validated using density-functional perturbation theory. As a result, 541 compounds with T<sub>c</sub> values surpassing 10 K, encompassing a variety of crystal structures and chemical compositions, are identified. This work is complemented with a detailed examination of several interesting materials, including nitrides, hydrides, and intermetallic compounds. Particularly noteworthy is LiMoN<sub>2</sub> , which is predicted to be superconducting in the stoichiometric trigonal phase, with a T<sub>c</sub> exceeding 38 K. LiMoN<sub>2</sub> has previously been synthesized in this phase, further heightening its potential for practical applications. Materials science ; Superconductivity ; Sampling (signal processing) ; Space (punctuation) ; Nanotechnology ; Engineering physics ; Condensed matter physics ; Optics ; Computer science ; Physics Inorganic Chemistry and Materials ; Machine Learning in Materials Science ; Superconductivity in MgB2 and Alloys
Authors: Selvaraj Sengottiyan | Alicja Mikołajczyk | Karolina Jagiełło | Marta Swirog | Tomasz Puzyn
Source: ACS Nano (article, 2023-01-18)
Field: Chemistry — Physical and Theoretical Chemistry

Core, Coating, or Corona? The Importance of Considering Protein Coronas in nano-QSPR Modeling of Zeta Potential To control stability in a biological medium, several factors affecting the zeta potential (ζ) of nanoparticles (NPs) must be considered, including complex interactions between the nanostructure and the composition of the protein corona (PC). Effective <i>in silico</i> methods (based on machine learning and quantitative structure-property relationship (QSPR) models) could help predict and characterize the relationship between the physicochemical properties of NP and the formation of PC and biological outcomes in the medium at an early stage of the experiment. However, the models currently developed are limited to simple descriptors that do not represent the complex interactions between the core, the coating, and their PC fingerprints. To be useful, the models developed should be described as a function of both the structural properties determined by the core and coating of the NPs and the biological medium determined by the formation of the protein corona. We have developed a set of complex descriptors that describe the quantitative relationship between the value of the zeta potential (ζ), core, the coating of NPs, and their PC fingerprints (the so-called nano-QSPR model). The nano-QSPR model was developed based on a genetic algorithm using a partial least-squares regression method (GA-PLS), which is characterized by high external predictive power (<i>Q</i><sup>2</sup><sub>EXT</sub> = 0.89). The GA-PLS model was developed using descriptors that describe (i) the core structure (determined by 7 different types of polymer-based NMs in the range of 20 different sizes), (ii) the coating structure with 7 different functional groups, and (iii) 80 different types of protein compositions adsorbed on the surface of the NPs. The presented study answers the question of how complex interactions between the corona and NP determine the zeta potential (ζ) of NP in a given medium. Moreover, our current study is a proof-of-concept that the zeta potential of NPs modeled on the original structure depends not only on the NPs themselves but also on the structure and properties determined by the NP core and coating, as well as the biological medium determined by the formation of the protein corona. On the basis of these results, our studies will be useful in determining the stability and mechanism of cell uptake, toxicity, and ability to predict the zeta potential of compounds not yet tested. Zeta potential ; Corona (planetary geology) ; Nanostructure ; Materials science ; Coating ; Nanotechnology ; Nanoparticle ; Nano- ; Quantitative structure–activity relationship ; Chemical physics ; Chemical engineering ; Chemistry ; Physics ; Stereochemistry ; Composite material ; Astrobiology thermodynamics and calorimetric analyses ; Computational Drug Discovery Methods ; Force Microscopy Techniques and Applications
Authors: Xiaoqian Wang | Yang Huang | Xiaoyu Xie | Yan Liu | Ziyu Huo | Maverick Lin | Hongliang Xin | Rong Tong
Source: Nature Communications (article, 2023-06-20)
Field: Materials Science — Biomaterials

Bayesian-optimization-assisted discovery of stereoselective aluminum complexes for ring-opening polymerization of racemic lactide Stereoselective ring-opening polymerization catalysts are used to produce degradable stereoregular poly(lactic acids) with thermal and mechanical properties that are superior to those of atactic polymers. However, the process of discovering highly stereoselective catalysts is still largely empirical. We aim to develop an integrated computational and experimental framework for efficient, predictive catalyst selection and optimization. As a proof of principle, we have developed a Bayesian optimization workflow on a subset of literature results for stereoselective lactide ring-opening polymerization, and using the algorithm, we identify multiple new Al complexes that catalyze either isoselective or heteroselective polymerization. In addition, feature attribution analysis uncovers mechanistically meaningful ligand descriptors, such as percent buried volume (%V<sub>bur</sub>) and the highest occupied molecular orbital energy (E<sub>HOMO</sub>), that can access quantitative and predictive models for catalyst development. Stereoselectivity ; Polymerization ; Lactide ; Combinatorial chemistry ; Catalysis ; Ring (chemistry) ; Chemistry ; Polymer ; Ring-opening polymerization ; Ligand (biochemistry) ; Monomer ; Computer science ; Materials science ; Organic chemistry ; Biochemistry biodegradable polymer synthesis and properties ; Carbon dioxide utilization in catalysis ; Organometallic Complex Synthesis and Catalysis
Authors: Md Sumon Reza | Shammya Afroze | К. А. Кутербеков | Asset Kabyshev | Кенжебатыр Бекмырза | Md. Naimul Haque | Shafi Noor Islam | Md Aslam Hossain | Mahbub Hassan | Hridoy Roy | Md. Shahinoor Islam | Md. Nahid Pervez | Абул Калам Азад
Source: Sustainability (review, 2023-05-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advanced Applications of Carbonaceous Materials in Sustainable Water Treatment, Energy Storage, and CO2 Capture: A Comprehensive Review The demand for energy has increased tremendously around the whole world due to rapid urbanization and booming industrialization. Energy is the major key to achieving an improved social life, but energy production and utilization processes are the main contributors to environmental pollution and greenhouse gas emissions. Mitigation of the energy crisis and reduction in pollution (water and air) difficulties are the leading research topics nowadays. Carbonaceous materials offer some of the best solutions to minimize these problems in an easy and effective way. It is also advantageous that the sources of carbon-based materials are economical, the synthesis processes are comfortable, and the applications are environmentally friendly. Among carbonaceous materials, activated carbons, graphene, and carbon nanotubes have shown outstanding performance in mitigating the energy crisis and environmental pollution. These three carbonaceous materials exhibit unique adsorption properties for energy storage, water purification, and gas cleansing due to their outstanding electrical conductivity, large specific surface areas, and strong mechanical strength. This paper reviews the synthesis methods for activated carbons, carbon nanotubes, and graphene and their significant applications in energy storage, water treatment, and carbon dioxide gas capture to improve environmental sustainability. Greenhouse gas ; Energy storage ; Environmental pollution ; Environmentally friendly ; Environmental science ; Pollution ; Sustainability ; Graphene ; Activated carbon ; Carbon sequestration ; Carbon fibers ; Waste management ; Materials science ; Adsorption ; Nanotechnology ; Carbon dioxide ; Process engineering ; Environmental protection ; Engineering ; Chemistry Supercapacitor Materials and Fabrication ; Membrane Separation Technologies ; Hydrogen Storage and Materials
Authors: Patricia Gómez de Santos | Ivan Mateljak | Manh Dat Hoang | Sarel J. Fleishman | Frank Hollmann | Miguel Alcalde
Source: Journal of the American Chemical Society (article, 2023-01-23)
Field: Chemistry — Organic Chemistry

Repertoire of Computationally Designed Peroxygenases for Enantiodivergent C–H Oxyfunctionalization Reactions The generation of enantiodivergent biocatalysts for C-H oxyfunctionalizations is ever more important in modern synthetic chemistry. Here, we have applied the FuncLib algorithm based on phylogenetic and Rosetta calculations to design a diverse repertoire of active, stable, and enantiodivergent fungal peroxygenases. 24 designs, each carrying 4-5 mutations in the catalytic core, were expressed functionally in yeast and benchmarked against characteristic model compounds. Several designs were active and stable in a range of temperature and pH, displaying unprecedented enantiodivergence, changing regioselectivity from alkyl to aromatic hydroxylation, and increasing catalytic efficiencies up to 10-fold, with 15-fold improvements in total turnover numbers over the parental enzyme. We find that this dramatic functional divergence stems from beneficial epistasis among the mutations and an extensive reorganization of the heme channel. Our work demonstrates that FuncLib can rapidly design highly functional libraries enriched in enantioselective peroxygenases not seen in nature for a range of biotechnological applications. Chemistry ; Repertoire ; Stereochemistry Synthesis and Catalytic Reactions ; Oxidative Organic Chemistry Reactions ; Catalytic C–H Functionalization Methods
Authors: Joseph Ekhebume Ogbezode | Ucheckukwu Stella Ezealigo | Abdulhakeem Bello | Vitalis C. Anye | Azikiwe Peter Onwualu
Source: Discover Nano (review, 2023-10-10)
Field: Materials Science — Materials Chemistry

A narrative review of the synthesis, characterization, and applications of iron oxide nanoparticles The significance of green synthesized nanomaterials with a uniform shape, reduced sizes, superior mechanical capabilities, phase microstructure, magnetic behavior, and superior performance cannot be overemphasized. Iron oxide nanoparticles (IONPs) are found within the size range of 1-100 nm in nanomaterials and have a diverse range of applications in fields such as biomedicine, wastewater purification, and environmental remediation. Nevertheless, the understanding of their fundamental material composition, chemical reactions, toxicological properties, and research methodologies is constrained and extensively elucidated during their practical implementation. The importance of producing IONPs using advanced nanofabrication techniques that exhibit strong potential for disease therapy, microbial pathogen control, and elimination of cancer cells is underscored by the adoption of the green synthesis approach. These IONPs can serve as viable alternatives for soil remediation and the elimination of environmental contaminants. Therefore, this paper presents a comprehensive analysis of the research conducted on different types of IONPs and IONP composite-based materials. It examines the synthesis methods and characterization techniques employed in these studies and also addresses the obstacles encountered in prior investigations with comparable objectives. A green engineering strategy was proposed for the synthesis, characterization, and application of IONPs and their composites with reduced environmental impact. Additionally, the influence of their phase structure, magnetic properties, biocompatibility, toxicity, milling time, nanoparticle size, and shape was also discussed. The study proposes the use of biological and physicochemical methods as a more viable alternative nanofabrication strategy that can mitigate the limitations imposed by the conventional methods of IONP synthesis. Nanotechnology ; Nanomaterials ; Environmental remediation ; Characterization (materials science) ; Iron oxide nanoparticles ; Materials science ; Biocompatibility ; Nanoparticle ; Biochemical engineering ; Engineering ; Metallurgy ; Contamination Nanoparticles: synthesis and applications ; Nanoparticle-Based Drug Delivery ; Nanomaterials for catalytic reactions
Authors: Michele Bianchi | Francesca Risplendi | Michele Re Fiorentin | Giancarlo Cicero
Source: Advanced Science (review, 2023-11-27)
Field: Materials Science — Materials Chemistry

Engineering the Electrical and Optical Properties of WS<sub>2</sub> Monolayers via Defect Control Two-dimensional (2D) materials as tungsten disulphide (WS<sub>2</sub> ) are rising as the ideal platform for the next generation of nanoscale devices due to the excellent electric-transport and optical properties. However, the presence of defects in the as grown samples represents one of the main limiting factors for commercial applications. At the same time, WS<sub>2</sub> properties are frequently tailored by introducing impurities at specific sites. Aim of this review paper is to present a complete description and discussion of the effects of both intentional and unintentional defects in WS<sub>2</sub> , by an in depth analysis of the recent experimental and theoretical investigations reported in the literature. First, the most frequent intrinsic defects in WS<sub>2</sub> are presented and their effects in the readily synthetized material are discussed. Possible solutions to remove and heal unintentional defects are also analyzed. Following, different doping schemes are reported, including the traditional substitution approach and innovative techniques based on the surface charge transfer with adsorbed atoms or molecules. The plethora of WS<sub>2</sub> monolayer modifications presented in this review and the systematic analysis of the corresponding optical and electronic properties, represent strategic degrees of freedom the researchers may exploit to tailor WS<sub>2</sub> optical and electronic properties for specific device applications. Monolayer ; Materials science ; Limiting ; Nanotechnology ; Doping ; Nanoscopic scale ; Electronics ; Optoelectronics ; Computer science ; Chemistry ; Physical chemistry 2D Materials and Applications ; MXene and MAX Phase Materials ; Graphene research and applications
Authors: Gregory S. Rohrer | Ian Chesser | Amanda R. Krause | S. Kiana Naghibzadeh | Zipeng Xu | Kaushik Dayal | Elizabeth A. Holm
Source: Annual Review of Materials Research (article, 2023-02-28)
Field: Materials Science — Materials Chemistry

Grain Boundary Migration in Polycrystals Grain boundaries in polycrystalline materials migrate to reduce the total excess energy. It has recently been found that the factors governing migration rates of boundaries in bicrystals are insufficient to explain boundary migration in polycrystals. We first review our current understanding of the atomistic mechanisms of grain boundary migration based on simulations and high-resolution transmission electron microscopy observations. We then review our current understanding at the continuum scale based on simulations and observations using high-energy diffraction microscopy. We conclude that detailed comparisons of experimental observations with atomistic simulations of migration in polycrystals (rather than bicrystals) are required to better understand the mechanisms of grain boundary migration, that the driving force for grain boundary migration in polycrystals must include factors other than curvature, and that current simulations of grain growth are insufficient for reproducing experimental observations, possibly because of an inadequate representation of the driving force. Grain boundary ; Materials science ; Crystallite ; Curvature ; Grain boundary strengthening ; Transmission electron microscopy ; Diffraction ; Condensed matter physics ; Grain boundary diffusion coefficient ; Microstructure ; Metallurgy ; Nanotechnology ; Geometry ; Physics ; Optics Microstructure and mechanical properties ; Force Microscopy Techniques and Applications ; Microstructure and Mechanical Properties of Steels