jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Théo Jaffrelot Inizan | Thomas Plé | Olivier Adjoua | Pengyu Ren | Hatice Gökcan | Olexandr Isayev | Louis Lagardère | Jean‐Philip Piquemal
Source: Chemical Science (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Scalable hybrid deep neural networks/polarizable potentials biomolecular simulations including long-range effects Deep-HP is a scalable extension of the Tinker-HP multi-GPU molecular dynamics (MD) package enabling the use of Pytorch/TensorFlow Deep Neural Network (DNN) models. Deep-HP increases DNNs' MD capabilities by orders of magnitude offering access to ns simulations for 100k-atom biosystems while offering the possibility of coupling DNNs to any classical (FFs) and many-body polarizable (PFFs) force fields. It allows therefore the introduction of the ANI-2X/AMOEBA hybrid polarizable potential designed for ligand binding studies where solvent-solvent and solvent-solute interactions are computed with the AMOEBA PFF while solute-solute ones are computed by the ANI-2X DNN. ANI-2X/AMOEBA explicitly includes AMOEBA's physical long-range interactions <i>via</i> an efficient Particle Mesh Ewald implementation while preserving ANI-2X's solute short-range quantum mechanical accuracy. The DNN/PFF partition can be user-defined allowing for hybrid simulations to include key ingredients of biosimulation such as polarizable solvents, polarizable counter ions, <i>etc.</i>… ANI-2X/AMOEBA is accelerated using a multiple-timestep strategy focusing on the model's contributions to low-frequency modes of nuclear forces. It primarily evaluates AMOEBA forces while including ANI-2X ones only <i>via</i> correction-steps resulting in an order of magnitude acceleration over standard Velocity Verlet integration. Simulating more than 10 μs, we compute charged/uncharged ligand solvation free energies in 4 solvents, and absolute binding free energies of host-guest complexes from SAMPL challenges. ANI-2X/AMOEBA average errors are discussed in terms of statistical uncertainty and appear in the range of chemical accuracy compared to experiment. The availability of the Deep-HP computational platform opens the path towards large-scale hybrid DNN simulations, at force-field cost, in biophysics and drug discovery. Scalability ; Range (aeronautics) ; Polarizability ; Artificial neural network ; Computer science ; Deep neural networks ; Artificial intelligence ; Statistical physics ; Materials science ; Physics ; Quantum mechanics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Marvin Poul | Liam Huber | Erik Bitzek | Jörg Neugebauer
Source: Physical review. B./Physical review. B (article, 2023-03-13)
Field: Materials Science — Materials Chemistry

Systematic atomic structure datasets for machine learning potentials: Application to defects in magnesium We present a physically motivated strategy for the construction of training sets for transferable machine learning interatomic potentials. It is based on a systematic exploration of all possible space groups in random crystal structures, together with deformations of cell shape, size, and atomic positions. The resulting potentials turn out to be unbiased and generically applicable to studies of bulk defects without including any defect structures in the training set or employing any additional active learning. Using this approach we construct transferable potentials for pure magnesium that reproduce the properties of hexagonal closed packed (hcp) and body centered cubic (bcc) polymorphs very well. In the process we investigate how different types of training structures impact the properties and the predictive power of the resulting potential. Magnesium ; Hexagonal crystal system ; Construct (python library) ; Crystal structure ; Materials science ; Interatomic potential ; Set (abstract data type) ; Chemical physics ; Process (computing) ; Computer science ; Statistical physics ; Physics ; Crystallography ; Molecular dynamics ; Chemistry ; Quantum mechanics Machine Learning in Materials Science ; Microstructure and mechanical properties ; X-ray Diffraction in Crystallography
Authors: Shambhawi Shambhawi | Ojus Mohan | Tej S. Choksi | Alexei A. Lapkin
Source: Catalysis Science & Technology (article, 2023-12-01)
Field: Materials Science — Materials Chemistry

The design and optimization of heterogeneous catalysts using computational methods Computational design of catalytic materials is a high dimensional structure optimization problem that is limited by the bottleneck of expensive quantum computation tools. An illustration of interaction of different factors involved in the design and optimization of a catalyst. Bottleneck ; Catalysis ; Computation ; Computer science ; Mathematical optimization ; Biochemical engineering ; Chemistry ; Engineering ; Algorithm ; Mathematics ; Organic chemistry Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Catalysis and Oxidation Reactions
Authors: Piotr Koczoń | Jakub T. Hołaj-Krzak | Bharani Kumar Palani | Tymoteusz Bolewski | Jarosław Dąbrowski | Bartłomiej J. Bartyzel | Eliza Gruczyńska–Sękowska
Source: International Journal of Molecular Sciences (review, 2023-01-05)
Field: Chemistry — Spectroscopy

The Analytical Possibilities of FT-IR Spectroscopy Powered by Vibrating Molecules This paper discusses the state of advancement in the development of spectroscopic methods based on the use of mid (proper) infrared radiation in the context of applications in various fields of science and technology. The authors drew attention to the most important solutions specific to both spectroscopy itself (ATR technique) and chemometric data processing tools (PCA and PLS models). The objective of the current paper is to collect and consistently present information on various aspects of FT-IR spectroscopy, which is not only a well-known and well-established method but is also continuously developing. The innovative aspect of the current review is to show FT-IR's great versatility that allows its applications to solve and explain issues from both the scientific domain (e.g., hydrogen bonds) and practical ones (e.g., technological processes, medicine, environmental protection, and food analysis). Particular attention was paid to the issue of hydrogen bonds as key non-covalent interactions, conditioning the existence of living matter and determining the number of physicochemical properties of various materials. Since the role of FT-IR spectroscopy in the field of hydrogen bond research has great significance, a historical outline of the most important qualitative and quantitative hydrogen bond theories is provided. In addition, research on selected unconventional spectral effects resulting from the substitution of protons with deuterons in hydrogen bridges is presented. The state-of-the-art and originality of the current review are that it presents a combination of uses of FT-IR spectroscopy to explain the way molecules vibrate and the effects of those vibrations on macroscopic properties, hence practical applications of given substances. Spectroscopy ; Molecule ; Molecular spectroscopy ; Analytical Chemistry (journal) ; Infrared spectroscopy ; Materials science ; Chemistry ; Nanotechnology ; Physics ; Organic chemistry ; Quantum mechanics Spectroscopy and Laser Applications ; Spectroscopy and Quantum Chemical Studies ; Photochemistry and Electron Transfer Studies
Authors: Wenmiao Chen | Peiyu Cai | Hong‐Cai Zhou | Sherzod T. Madrahimov
Source: Angewandte Chemie International Edition (article, 2023-12-23)
Field: Chemistry — Inorganic Chemistry

Bridging Homogeneous and Heterogeneous Catalysis: Phosphine‐Functionalized Metal‐Organic Frameworks Phosphine-functionalized metal-organic frameworks (P-MOFs) as an emerging class of coordination polymers, have provided novel opportunities for the development of heterogeneous catalysts. Yet, compared with the ubiquitous phosphine systems in homogeneous catalysis, heterogenization of phosphines in MOFs is still at its early stage. In this Minireview, we summarize the synthetic strategies, characterization and catalytic reactions based on the P-MOFs reported in literature. In particular, various catalytic reactions are discussed in detail in terms of phosphine ligand structure-function relationship, including the potential obstacles for future development. Finally, we discuss the possible solutions, including new types of reactions and techniques as the perspectives for the development of P-MOF catalysts, highlighting the opportunities and challenges. Phosphine ; Homogeneous ; Metal-organic framework ; Catalysis ; Bridging (networking) ; Homogeneous catalysis ; Characterization (materials science) ; Nanotechnology ; Materials science ; Chemistry ; Combinatorial chemistry ; Computer science ; Organic chemistry ; Physics Metal-Organic Frameworks: Synthesis and Applications ; Chemical Synthesis and Reactions ; Asymmetric Hydrogenation and Catalysis
Authors: Karina J. Lagos | David García | Coralía Fabiola Cuadrado | Larissa Marila de Souza | Natasha Ferreira Mezzacappo | Ana Paula da Silva | Natália Mayumi Inada | Vanderlei Salvador Bagnato | María Paulina Romero
Source: Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology (review, 2023-04-26)
Field: Materials Science — Materials Chemistry

Carbon dots: Types, preparation, and their boosted antibacterial activity by photoactivation. Current status and future perspectives Carbon dots (CDs) correspond to carbon-based materials (CBM) with sizes usually below 10 nm. These nanomaterials exhibit attractive properties such us low toxicity, good stability, and high conductivity, which have promoted their thorough study over the past two decades. The current review describes four types of CDs: carbon quantum dots (CQDs), graphene quantum dots (GQDs), carbon nanodots (CNDs), and carbonized polymers dots (CPDs), together with the state of the art of the main routes for their preparation, either by "top-down" or "bottom-up" approaches. Moreover, among the various usages of CDs within biomedicine, we have focused on their application as a novel class of broad-spectrum antibacterial agents, concretely, owing their photoactivation capability that triggers an enhanced antibacterial property. Our work presents the recent advances in this field addressing CDs, their composites and hybrids, applied as photosensitizers (PS), and photothermal agents (PA) within antibacterial strategies such as photodynamic therapy (PDT), photothermal therapy (PTT), and synchronic PDT/PTT. Furthermore, we discuss the prospects for the possible future development of large-scale preparation of CDs, and the potential for these nanomaterials to be employed in applications to combat other pathogens harmful to human health. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease. Nanotechnology ; Current (fluid) ; Carbon fibers ; Materials science ; Engineering ethics ; Engineering ; Composite material Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Quantum Dots Synthesis And Properties
Authors: Danny Broberg | Kyle Bystrom | Shivani Srivastava | Diana Dahliah | Benjamin A. D. Williamson | Leigh Weston | David O. Scanlon | Gian‐Marco Rignanese | Shyam Dwaraknath | Joel B. Varley | Kristin A. Persson | Mark Asta | Geoffroy Hautier
Source: npj Computational Materials (article, 2023-05-04)
Field: Materials Science — Materials Chemistry

High-throughput calculations of charged point defect properties with semi-local density functional theory—performance benchmarks for materials screening applications Abstract Calculations of point defect energetics with Density Functional Theory (DFT) can provide valuable insight into several optoelectronic, thermodynamic, and kinetic properties. These calculations commonly use methods ranging from semi-local functionals with a-posteriori corrections to more computationally intensive hybrid functional approaches. For applications of DFT-based high-throughput computation for data-driven materials discovery, point defect properties are of interest, yet are currently excluded from available materials databases. This work presents a benchmark analysis of automated, semi-local point defect calculations with a-posteriori corrections, compared to 245 “gold standard” hybrid calculations previously published. We consider three different a-posteriori correction sets implemented in an automated workflow, and evaluate the qualitative and quantitative differences among four different categories of defect information: thermodynamic transition levels, formation energies, Fermi levels, and dopability limits. We highlight qualitative information that can be extracted from high-throughput calculations based on semi-local DFT methods, while also demonstrating the limits of quantitative accuracy. Density functional theory ; Benchmark (surveying) ; A priori and a posteriori ; Computer science ; Throughput ; Statistical physics ; Point (geometry) ; Computation ; Hybrid functional ; Algorithm ; Physics ; Mathematics ; Chemistry ; Computational chemistry Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Catalysis and Oxidation Reactions
Authors: Michael G. Taylor | Daniel J. Burrill | Jan Janßen | Enrique R. Batista | Danny Pérez | Ping Yang
Source: Nature Communications (article, 2023-05-15)
Field: Materials Science — Materials Chemistry

Architector for high-throughput cross-periodic table 3D complex building Rare-earth and actinide complexes are critical for a wealth of clean-energy applications. Three-dimensional (3D) structural generation and prediction for these organometallic systems remains a challenge, limiting opportunities for computational chemical discovery. Here, we introduce Architector, a high-throughput in-silico synthesis code for s-, p-, d-, and f-block mononuclear organometallic complexes capable of capturing nearly the full diversity of the known experimental chemical space. Beyond known chemical space, Architector performs in-silico design of new complexes including any chemically accessible metal-ligand combinations. Architector leverages metal-center symmetry, interatomic force fields, and tight binding methods to build many possible 3D conformers from minimal 2D inputs including metal oxidation and spin state. Over a set of more than 6,000 x-ray diffraction (XRD)-determined complexes spanning the periodic table, we demonstrate quantitative agreement between Architector-predicted and experimentally observed structures. Further, we demonstrate out-of-the box conformer generation and energetic rankings of non-minimum energy conformers produced from Architector, which are critical for exploring potential energy surfaces and training force fields. Overall, Architector represents a transformative step towards cross-periodic table computational design of metal complex chemistry. Chemical space ; Periodic table ; Conformational isomerism ; Computational science ; Table (database) ; Chemical physics ; In silico ; Chemistry ; Materials science ; Computational chemistry ; Molecule ; Computer science ; Nanotechnology ; Crystallography ; Physics ; Drug discovery ; Quantum mechanics ; Data mining Machine Learning in Materials Science ; Organometallic Complex Synthesis and Catalysis ; Inorganic Chemistry and Materials
Authors: Seung‐Jae Shin | Jamie W. Gittins | Chloe J. Balhatchet | Aron Walsh | Alexander C. Forse
Source: ChemRxiv (preprint, 2023-07-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metal-Organic Framework Supercapacitors: Challenges and Opportunities Supercapacitors offer superior energy storage capabilities than traditional capacitors, making them useful for applications such as electric vehicles and rapid large-scale energy storage. The energy storage performance of these devices relies on electrical double-layer capacitance and/or pseudo-capacitance from rapid reversible redox reactions. Metal-organic frameworks (MOFs) have recently emerged as a new class of electrode materials with promising supercapacitor performances and capacitances that exceed those of traditional materials. However, our comparison of the supercapacitor performance of a porous carbon and a state-of-the-art MOF highlights a number of challenges for MOF supercapacitors, including low potential windows, limited cycle lifetimes, and poor rate performances. We propose that the well-defined and tuneable chemical structures of MOFs present a number of avenues for improving supercapacitor performance. We also discuss recent experimental and theoretical work on charging mechanisms in MOF-based supercapacitors, and find a need for more studies that elucidate the charge storage and degradation mechanisms. Ultimately, a deeper understanding will lead to design principles for realising improved supercapacitor energy storage devices. Supercapacitor ; Capacitance ; Energy storage ; Capacitor ; Materials science ; Nanotechnology ; Metal-organic framework ; Electrode ; Electrical engineering ; Power (physics) ; Voltage ; Engineering ; Chemistry ; Physics Supercapacitor Materials and Fabrication ; Metal-Organic Frameworks: Synthesis and Applications ; Electrocatalysts for Energy Conversion
Authors: Yifan Bao | Marc Pignitter
Source: Comprehensive Reviews in Food Science and Food Safety (review, 2023-04-25)
Field: Chemistry — Organic Chemistry

Mechanisms of lipid oxidation in water‐in‐oil emulsions and oxidomics‐guided discovery of targeted protective approaches Lipid oxidation is an inevitable event during the processing, storage, and even consumption of lipid-containing food, which may cause adverse effects on both food quality and human health. Water-in-oil (W/O) food emulsions contain a high content of lipids and small water droplets, which renders them vulnerable to lipid oxidation. The present review provides comprehensive insights into the lipid oxidation of W/O food emulsions. The key influential factors of lipid oxidation in W/O food emulsions are presented systematically. To better interpret the specific mechanisms of lipid oxidation in W/O food emulsions, a comprehensive detection method, oxidative lipidomics (oxidomics), is proposed to identify novel markers, which not only tracks the chemical molecules but also considers the changes in supramolecular properties, sensory properties, and nutritional value. The microstructure of emulsions, components from both phases, emulsifiers, pH, temperature, and light should be taken into account to identify specific oxidation markers. A correlation of these novel oxidation markers with the shelf life, the organoleptic properties, and the nutritional value of W/O food emulsions should be applied to develop targeted protective approaches for limiting lipid oxidation. Accordingly, the processing parameters, the application of antioxidants and emulsifiers, as well as packing and storage conditions can be optimized to develop W/O emulsions with improved oxidative stability. This review may help in emphasizing the future research priorities of investigating the mechanisms of lipid oxidation in W/O emulsion by oxidomics, leading to practical solutions for the food industry to prevent oxidative rancidity in W/O food emulsions. Lipid oxidation ; Food science ; Emulsion ; Chemistry ; Shelf life ; Oxidative phosphorylation ; Food industry ; Organoleptic ; Food additive ; Biochemistry ; Antioxidant Edible Oils Quality and Analysis ; Dye analysis and toxicity ; Advanced Chemical Sensor Technologies
Authors: Husam M. Younes | Hana Kadavil | Hesham Ismail | Sandi Saad Ali Adib | Somayeh Zamani | Raid G. Alany | Ali A. Al-Kinani
Source: Pharmaceutics (review, 2023-12-26)
Field: Materials Science — Biomaterials

Overview of Tissue Engineering and Drug Delivery Applications of Reactive Electrospinning and Crosslinking Techniques of Polymeric Nanofibers with Highlights on Their Biocompatibility Testing and Regulatory Aspects Traditional electrospinning is a promising technique for fabricating nanofibers for tissue engineering and drug delivery applications. The method is highly efficient in producing nanofibers with morphology and porosity similar to the extracellular matrix. Nonetheless, and in many instances, the process has faced several limitations, including weak mechanical strength, large diameter distributions, and scaling-up difficulties of its fabricated electrospun nanofibers. The constraints of the polymer solution's intrinsic properties are primarily responsible for these limitations. Reactive electrospinning constitutes a novel and modified electrospinning techniques developed to overcome those challenges and improve the properties of the fabricated fibers intended for various biomedical applications. This review mainly addresses reactive electrospinning techniques, a relatively new approach for making in situ or post-crosslinked nanofibers. It provides an overview of and discusses the recent literature about chemical and photoreactive electrospinning, their various techniques, their biomedical applications, and FDA regulatory aspects related to their approval and marketing. Another aspect highlighted in this review is the use of crosslinking and reactive electrospinning techniques to enhance the fabricated nanofibers' physicochemical and mechanical properties and make them more biocompatible and tailored for advanced intelligent drug delivery and tissue engineering applications. Electrospinning ; Nanofiber ; Drug delivery ; Materials science ; Nanotechnology ; Tissue engineering ; Biocompatibility ; Polymer ; Biomedical engineering ; Composite material ; Engineering Electrospun Nanofibers in Biomedical Applications ; Tissue Engineering and Regenerative Medicine ; Advanced Sensor and Energy Harvesting Materials
Authors: Jin Soo Lee | Jeong-Wook Kim | Jae Hee Lee | Yong Koo Son | Young Bin Kim | Kyoohee Woo | Chanhee Lee | Il‐Doo Kim | Jae Young Seok | Jong Won Yu | Jung Hwan Park | Keon Jae Lee
Source: Nano-Micro Letters (article, 2023-08-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Flash-Induced High-Throughput Porous Graphene via Synergistic Photo-Effects for Electromagnetic Interference Shielding Porous 2D materials with high conductivity and large surface area have been proposed for potential electromagnetic interference (EMI) shielding materials in future mobility and wearable applications to prevent signal noise, transmission inaccuracy, system malfunction, and health hazards. Here, we report on the synthesis of lightweight and flexible flash-induced porous graphene (FPG) with excellent EMI shielding performance. The broad spectrum of pulsed flashlight induces photo-chemical and photo-thermal reactions in polyimide films, forming 5 × 10 cm<sup>2</sup>-size porous graphene with a hollow pillar structure in a few milliseconds. The resulting material demonstrated low density (0.0354 g cm<sup>-3</sup>) and outstanding absolute EMI shielding effectiveness of 1.12 × 10<sup>5</sup> dB cm<sup>2</sup> g<sup>-1</sup>. The FPG was characterized via thorough material analyses, and its mechanical durability and flexibility were confirmed by a bending cycle test. Finally, the FPG was utilized in drone and wearable applications, showing effective EMI shielding performance for internal/external EMI in a drone radar system and reducing the specific absorption rate in the human body. Materials science ; Electromagnetic interference ; EMI ; Electromagnetic shielding ; Graphene ; Optoelectronics ; Flash (photography) ; Nanotechnology ; Composite material ; Electronic engineering ; Optics ; Engineering Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis