jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Bowen Deng | Peichen Zhong | KyuJung Jun | Janosh Riebesell | Kevin Han | Christopher J. Bartel | Gerbrand Ceder
Source: Nature Machine Intelligence (article, 2023-09-14)
Field: Materials Science — Materials Chemistry

CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling Abstract Large-scale simulations with complex electron interactions remain one of the greatest challenges for atomistic modelling. Although classical force fields often fail to describe the coupling between electronic states and ionic rearrangements, the more accurate ab initio molecular dynamics suffers from computational complexity that prevents long-time and large-scale simulations, which are essential to study technologically relevant phenomena. Here we present the Crystal Hamiltonian Graph Neural Network (CHGNet), a graph neural network-based machine-learning interatomic potential (MLIP) that models the universal potential energy surface. CHGNet is pretrained on the energies, forces, stresses and magnetic moments from the Materials Project Trajectory Dataset, which consists of over 10 years of density functional theory calculations of more than 1.5 million inorganic structures. The explicit inclusion of magnetic moments enables CHGNet to learn and accurately represent the orbital occupancy of electrons, enhancing its capability to describe both atomic and electronic degrees of freedom. We demonstrate several applications of CHGNet in solid-state materials, including charge-informed molecular dynamics in Li x MnO 2 , the finite temperature phase diagram for Li x FePO 4 and Li diffusion in garnet conductors. We highlight the significance of charge information for capturing appropriate chemistry and provide insights into ionic systems with additional electronic degrees of freedom that cannot be observed by previous MLIPs. Degrees of freedom (physics and chemistry) ; Hamiltonian (control theory) ; Statistical physics ; Ionic bonding ; Electron ; Ab initio ; Molecular dynamics ; Computer science ; Artificial neural network ; Atomic units ; Electronic structure ; Phase diagram ; Physics ; Chemical physics ; Condensed matter physics ; Quantum mechanics ; Ion ; Machine learning ; Phase (matter) ; Mathematics Machine Learning in Materials Science ; Fuel Cells and Related Materials ; X-ray Diffraction in Crystallography
Authors: Yali Zhang | Kunpeng Ruan | Kun Zhou | Junwei Gu
Source: Advanced Materials (article, 2023-01-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Controlled Distributed Ti<sub>3</sub>C<sub>2</sub>T<i><sub>x</sub></i> Hollow Microspheres on Thermally Conductive Polyimide Composite Films for Excellent Electromagnetic Interference Shielding Flexible multifunctional polymer-based electromagnetic interference (EMI) shielding composite films have important applications in the fields of 5G communication technology, wearable electronic devices, and artificial intelligence. Based on the design of a porous/multilayered structure and using polyimide (PI) as the matrix and polymethyl methacrylate (PMMA) microspheres as the template, flexible (Fe<sub>3</sub> O<sub>4</sub> /PI)-Ti<sub>3</sub> C<sub>2</sub> T<sub>x</sub> -(Fe<sub>3</sub> O<sub>4</sub> /PI) composite films with controllable pore sizes and distribution of Ti<sub>3</sub> C<sub>2</sub> T<sub>x</sub> hollow microspheres are successfully prepared by sacrificial template method. Owing to the porous/multilayered structure, when the pore size of the Ti<sub>3</sub> C<sub>2</sub> T<sub>x</sub> hollow microspheres is 10 µm and the mass ratio of PMMA/Ti<sub>3</sub> C<sub>2</sub> T<sub>x</sub> is 2:1, the (Fe<sub>3</sub> O<sub>4</sub> /PI)-Ti<sub>3</sub> C<sub>2</sub> T<sub>x</sub> -(Fe<sub>3</sub> O<sub>4</sub> /PI) composite film has the most excellent EMI shielding performance, with EMI shielding effectiveness (EMI SE) of 85 dB. It is further verified by finite element simulation that the composite film has an excellent shielding effect on electromagnetic waves. In addition, the composite film has good thermal conductivity (thermal conductivity coefficient of 3.49 W (m·K)<sup>-1</sup> ) and mechanical properties (tensile strength of 65.3 MPa). This flexible (Fe<sub>3</sub> O<sub>4</sub> /PI)-Ti<sub>3</sub> C<sub>2</sub> T<sub>x</sub> -(Fe<sub>3</sub> O<sub>4</sub> /PI) composite film with excellent EMI shielding performance, thermal conductivity, and mechanical properties has demonstrated great potential for applications in EMI shielding protection for high-power, portable, and wearable flexible electronic devices. Materials science ; Polyimide ; Electromagnetic shielding ; Composite number ; Microsphere ; Electrical conductor ; Electromagnetic interference ; Composite material ; Electromagnetic radiation ; Optoelectronics ; Optics ; Chemical engineering ; Electronic engineering ; Layer (electronics) Electromagnetic wave absorption materials ; MXene and MAX Phase Materials ; Advanced Antenna and Metasurface Technologies
Authors: Jared L. Johnson | Tomer M. Yaron | Emily M. Huntsman | Alexander Kerelsky | Junho Song | Amit Regev | Ting-Yu Lin | Katarina Liberatore | Daniel M. Cizin | Benjamin M. Cohen | Neil Vasan | Yilun Ma | Konstantin Krismer | Jaylissa Torres Robles | Bert van de Kooij | Anne E. van Vlimmeren | Nicole Andrée-Busch | Norbert F. Käufer | Maxim V. Dorovkov | Alexey G. Ryazanov | Yuichiro Takagi | Edward R. Kastenhuber | Marcus D. Goncalves | Benjamin D. Hopkins | Olivier Elemento | Dylan J. Taatjes | Alexandre Maucuer | Akio Yamashita | Alexei Degterev | Mohamed Uduman | Jingyi Lu | Sean D. Landry | Bin Zhang | Ian Cossentino | Rune Linding | John Blenis | Peter Hornbeck | Benjamin E. Turk | Michael B. Yaffe | Lewis C. Cantley
Source: Nature (article, 2023-01-11)
Field: Chemistry — Spectroscopy

An atlas of substrate specificities for the human serine/threonine kinome Protein phosphorylation is one of the most widespread post-translational modifications in biology<sup>1,2</sup>. With advances in mass-spectrometry-based phosphoproteomics, 90,000 sites of serine and threonine phosphorylation have so far been identified, and several thousand have been associated with human diseases and biological processes<sup>3,4</sup>. For the vast majority of phosphorylation events, it is not yet known which of the more than 300 protein serine/threonine (Ser/Thr) kinases encoded in the human genome are responsible<sup>3</sup>. Here we used synthetic peptide libraries to profile the substrate sequence specificity of 303 Ser/Thr kinases, comprising more than 84% of those predicted to be active in humans. Viewed in its entirety, the substrate specificity of the kinome was substantially more diverse than expected and was driven extensively by negative selectivity. We used our kinome-wide dataset to computationally annotate and identify the kinases capable of phosphorylating every reported phosphorylation site in the human Ser/Thr phosphoproteome. For the small minority of phosphosites for which the putative protein kinases involved have been previously reported, our predictions were in excellent agreement. When this approach was applied to examine the signalling response of tissues and cell lines to hormones, growth factors, targeted inhibitors and environmental or genetic perturbations, it revealed unexpected insights into pathway complexity and compensation. Overall, these studies reveal the intrinsic substrate specificity of the human Ser/Thr kinome, illuminate cellular signalling responses and provide a resource to link phosphorylation events to biological pathways. Kinome ; Phosphorylation ; Serine ; Kinase ; Phosphoproteomics ; Threonine ; Biology ; Protein phosphorylation ; Protein-Serine-Threonine Kinases ; Biochemistry ; Computational biology ; Protein kinase A ; Cell biology Advanced Proteomics Techniques and Applications ; Protein Kinase Regulation and GTPase Signaling ; Enzyme Structure and Function
Authors: Pengcheng Xu | Xiaobo Ji | Minjie Li | Wencong Lu
Source: npj Computational Materials (article, 2023-03-25)
Field: Materials Science — Materials Chemistry

Small data machine learning in materials science Abstract This review discussed the dilemma of small data faced by materials machine learning. First, we analyzed the limitations brought by small data. Then, the workflow of materials machine learning has been introduced. Next, the methods of dealing with small data were introduced, including data extraction from publications, materials database construction, high-throughput computations and experiments from the data source level; modeling algorithms for small data and imbalanced learning from the algorithm level; active learning and transfer learning from the machine learning strategy level. Finally, the future directions for small data machine learning in materials science were proposed. Computer science ; Machine learning ; Workflow ; Artificial intelligence ; Small data ; Active learning (machine learning) ; Computational learning theory ; Database Machine Learning in Materials Science ; Advanced X-ray and CT Imaging ; Computational Drug Discovery Methods
Authors: Lihui Xuan | Zhao Ju | Magdalena Skonieczna | Ping‐Kun Zhou | Ruixue Huang
Source: MedComm (review, 2023-07-14)
Field: Materials Science — Materials Chemistry

Nanoparticles‐induced potential toxicity on human health: Applications, toxicity mechanisms, and evaluation models Nanoparticles (NPs) have become one of the most popular objects of scientific study during the past decades. However, despite wealth of study reports, still there is a gap, particularly in health toxicology studies, underlying mechanisms, and related evaluation models to deeply understanding the NPs risk effects. In this review, we first present a comprehensive landscape of the applications of NPs on health, especially addressing the role of NPs in medical diagnosis, therapy. Then, the toxicity of NPs on health systems is introduced. We describe in detail the effects of NPs on various systems, including respiratory, nervous, endocrine, immune, and reproductive systems, and the carcinogenicity of NPs. Furthermore, we unravels the underlying mechanisms of NPs including ROS accumulation, mitochondrial damage, inflammatory reaction, apoptosis, DNA damage, cell cycle, and epigenetic regulation. In addition, the classical study models such as cell lines and mice and the emerging models such as 3D organoids used for evaluating the toxicity or scientific study are both introduced. Overall, this review presents a critical summary and evaluation of the state of understanding of NPs, giving readers more better understanding of the NPs toxicology to remedy key gaps in knowledge and techniques. Toxicity ; Human health ; Mechanism (biology) ; Nanotoxicology ; Nanomedicine ; Nanotechnology ; DNA damage ; Computational biology ; Chemistry ; Computer science ; Bioinformatics ; Biology ; Medicine ; Nanoparticle ; DNA ; Materials science ; Physics ; Biochemistry Nanoparticles: synthesis and applications ; Nanoparticle-Based Drug Delivery ; Air Quality and Health Impacts
Authors: Albert Musaelian | Simon Batzner | Anders Johansson | Lixin Sun | Cameron J. Owen | Mordechai Kornbluth | Boris Kozinsky
Source: Nature Communications (article, 2023-02-03)
Field: Materials Science — Materials Chemistry

Learning local equivariant representations for large-scale atomistic dynamics A simultaneously accurate and computationally efficient parametrization of the potential energy surface of molecules and materials is a long-standing goal in the natural sciences. While atom-centered message passing neural networks (MPNNs) have shown remarkable accuracy, their information propagation has limited the accessible length-scales. Local methods, conversely, scale to large simulations but have suffered from inferior accuracy. This work introduces Allegro, a strictly local equivariant deep neural network interatomic potential architecture that simultaneously exhibits excellent accuracy and scalability. Allegro represents a many-body potential using iterated tensor products of learned equivariant representations without atom-centered message passing. Allegro obtains improvements over state-of-the-art methods on QM9 and revMD17. A single tensor product layer outperforms existing deep MPNNs and transformers on QM9. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular simulations using Allegro recover structural and kinetic properties of an amorphous electrolyte in excellent agreement with ab-initio simulations. Finally, we demonstrate parallelization with a simulation of 100 million atoms. Computer science ; Scalability ; Iterated function ; Parametrization (atmospheric modeling) ; Equivariant map ; Molecular dynamics ; Statistical physics ; Physics ; Computational chemistry ; Mathematics ; Chemistry ; Quantum mechanics Machine Learning in Materials Science ; Topic Modeling ; Protein Structure and Dynamics
Authors: Angelo Frei | Anthony D. Verderosa | Alysha G. Elliott | Johannes Zuegg | Mark A. T. Blaskovich
Source: Nature Reviews Chemistry (review, 2023-02-08)
Field: Chemistry — Inorganic Chemistry

Metals to combat antimicrobial resistance Bacteria, similar to most organisms, have a love-hate relationship with metals: a specific metal may be essential for survival yet toxic in certain forms and concentrations. Metal ions have a long history of antimicrobial activity and have received increasing attention in recent years owing to the rise of antimicrobial resistance. The search for antibacterial agents now encompasses metal ions, nanoparticles and metal complexes with antimicrobial activity ('metalloantibiotics'). Although yet to be advanced to the clinic, metalloantibiotics are a vast and underexplored group of compounds that could lead to a much-needed new class of antibiotics. This Review summarizes recent developments in this growing field, focusing on advances in the development of metalloantibiotics, in particular, those for which the mechanism of action has been investigated. We also provide an overview of alternative uses of metal complexes to combat bacterial infections, including antimicrobial photodynamic therapy and radionuclide diagnosis of bacterial infections. Antimicrobial ; Antibiotics ; Antibiotic resistance ; Nanotechnology ; Chemistry ; Medicine ; Intensive care medicine ; Microbiology ; Biology ; Materials science Radioactive element chemistry and processing ; Bacterial biofilms and quorum sensing ; Antibiotic Resistance in Bacteria
Authors: Lichen Liu | Avelino Corma
Source: Chemical Reviews (review, 2023-03-27)
Field: Chemistry — Organic Chemistry

Bimetallic Sites for Catalysis: From Binuclear Metal Sites to Bimetallic Nanoclusters and Nanoparticles Heterogeneous bimetallic catalysts have broad applications in industrial processes, but achieving a fundamental understanding on the nature of the active sites in bimetallic catalysts at the atomic and molecular level is very challenging due to the structural complexity of the bimetallic catalysts. Comparing the structural features and the catalytic performances of different bimetallic entities will favor the formation of a unified understanding of the structure-reactivity relationships in heterogeneous bimetallic catalysts and thereby facilitate the upgrading of the current bimetallic catalysts. In this review, we will discuss the geometric and electronic structures of three representative types of bimetallic catalysts (bimetallic binuclear sites, bimetallic nanoclusters, and nanoparticles) and then summarize the synthesis methodologies and characterization techniques for different bimetallic entities, with emphasis on the recent progress made in the past decade. The catalytic applications of supported bimetallic binuclear sites, bimetallic nanoclusters, and nanoparticles for a series of important reactions are discussed. Finally, we will discuss the future research directions of catalysis based on supported bimetallic catalysts and, more generally, the prospective developments of heterogeneous catalysis in both fundamental research and practical applications. Bimetallic strip ; Nanoclusters ; Catalysis ; Nanoparticle ; Nanotechnology ; Chemistry ; Heterogeneous catalysis ; Materials science ; Organic chemistry Nanomaterials for catalytic reactions ; Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion
Authors: Mohamad Zandieh | Juewen Liu
Source: Advanced Materials (article, 2023-02-17)
Field: Materials Science — Materials Chemistry

Nanozymes: Definition, Activity, and Mechanisms "Nanozyme" is used to describe various catalysts from immobilized inorganic metal complexes, immobilized enzymes to inorganic nanoparticles. Here, the history of nanozymes is dvescribed in detail, and they can be largely separated into two types. Type 1 nanozymes refer to immobilized catalysts or enzymes on nanomaterials, which were dominant in the first decade since 2004. Type 2 nanozymes, which rely on the surface catalytic properties of inorganic nanomaterials, are the dominating type in the past decade. The definition of nanozymes is evolving, and a definition based on the same substrates and products as enzymes are able to cover most currently claimed nanozymes, although they may have different mechanisms compared to their enzyme counterparts. A broader definition can inspire application-based research to replace enzymes with nanomaterials for analytical, environmental, and biomedical applications. Comparison with enzymes also requires a clear definition of a nanozyme unit. Four ways of defining a nanozyme unit are described, with iron oxide and horseradish peroxidase activity comparison as examples in each definition. Growing work is devoted to understanding the catalytic mechanism of nanozymes, which provides a basis for further rational engineering of active sites. Finally, future perspective of the nanozyme field is discussed. Nanomaterials ; Nanotechnology ; Catalysis ; Biochemical engineering ; Materials science ; Chemistry ; Computer science ; Combinatorial chemistry ; Engineering ; Organic chemistry Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Nanoparticles: synthesis and applications
Authors: Jiayang Wu | Han Lin | David Moss | Kian Ping Loh | Baohua Jia
Source: Nature Reviews Chemistry (review, 2023-01-17)
Field: Materials Science — Materials Chemistry

Graphene oxide for photonics, electronics and optoelectronics Graphene ; Nanotechnology ; Photonics ; Electronics ; Materials science ; Fabrication ; Engineering physics ; Computer science ; Optoelectronics ; Engineering ; Electrical engineering Graphene research and applications ; 2D Materials and Applications ; Nanowire Synthesis and Applications
Authors: Morteza Mahmoudi | Markita P. Landry | Anna Moore | Roxana Coreas
Source: Nature Reviews Materials (review, 2023-03-24)
Field: Materials Science — Biomaterials

The protein corona from nanomedicine to environmental science Nanomedicine ; Nanobiotechnology ; Nanotechnology ; Corona (planetary geology) ; Nanotoxicology ; Data science ; Computer science ; Materials science ; Nanoparticle ; Physics ; Astrobiology Nanoparticle-Based Drug Delivery ; Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications
Authors: Vincent Tournier | Sophie Duquesne | Frédérique Guillamot | Henri Cramail | Daniel Taton | Alain Marty | Isabelle André
Source: Chemical Reviews (review, 2023-03-14)
Field: Materials Science — Biomaterials

Enzymes’ Power for Plastics Degradation Plastics are everywhere in our modern way of living, and their production keeps increasing every year, causing major environmental concerns. Nowadays, the end-of-life management involves accumulation in landfills, incineration, and recycling to a lower extent. This ecological threat to the environment is inspiring alternative bio-based solutions for plastic waste treatment and recycling toward a circular economy. Over the past decade, considerable efforts have been made to degrade commodity plastics using biocatalytic approaches. Here, we provide a comprehensive review on the recent advances in enzyme-based biocatalysis and in the design of related biocatalytic processes to recycle or upcycle commodity plastics, including polyesters, polyamides, polyurethanes, and polyolefins. We also discuss scope and limitations, challenges, and opportunities of this field of research. An important message from this review is that polymer-assimilating enzymes are very likely part of the solution to reaching a circular plastic economy. Circular economy ; Commodity chemicals ; Commodity ; Incineration ; Scope (computer science) ; Biochemical engineering ; Plastic waste ; Chemistry ; Waste management ; Business ; Engineering ; Catalysis ; Computer science ; Organic chemistry ; Ecology biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Enzyme Catalysis and Immobilization
Authors: Shameran Jamal Salih | Wali M. Mahmood
Source: Heliyon (review, 2023-05-25)
Field: Materials Science — Materials Chemistry

Review on magnetic spinel ferrite (MFe2O4) nanoparticles: From synthesis to application Magnetic spinel ferrite materials offer various applications in biomedical, water treatment, and industrial electronic devices, which has sparked a lot of attention. This review focuses on the synthesis, characterization, and applications of spinel ferrites in a variety of fields, particularly spinel ferrites with doping. Spinel ferrites nanoparticles doped with the elements have remarkable electrical and magnetic properties, allowing them to be used in a wide range of applications such as magnetic fields, microwave absorbers, and biomedicine. Furthermore, the physical properties of spinel ferrites can be modified by substituting metallic atoms, resulting in improved performance. The most recent and noteworthy applications of magnetic ferrite nanoparticles are reviewed and discussed in this review. This review goes over the synthesis, doping and applications of different types of metal ferrite nanoparticles, as well as views on how to choose the appropriate magnetic ferrites based on the intended application. Spinel ; Ferrite (magnet) ; Materials science ; Nanoparticle ; Doping ; Magnetic nanoparticles ; Nanotechnology ; Microwave ; Characterization (materials science) ; Optoelectronics ; Metallurgy ; Computer science ; Composite material ; Telecommunications Magnetic Properties and Synthesis of Ferrites ; Electromagnetic wave absorption materials ; Advancements in Battery Materials