jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Stephan Thaler | Gregor Doehner | Julija Zavadlav
Source: Journal of Chemical Theory and Computation (article, 2023-04-04)
Field: Materials Science — Materials Chemistry

Scalable Bayesian Uncertainty Quantification for Neural Network Potentials: Promise and Pitfalls Neural network (NN) potentials promise highly accurate molecular dynamics (MD) simulations within the computational complexity of classical MD force fields. However, when applied outside their training domain, NN potential predictions can be inaccurate, increasing the need for Uncertainty Quantification (UQ). Bayesian modeling provides the mathematical framework for UQ, but classical Bayesian methods based on Markov chain Monte Carlo (MCMC) are computationally intractable for NN potentials. By training graph NN potentials for coarse-grained systems of liquid water and alanine dipeptide, we demonstrate here that scalable Bayesian UQ via stochastic gradient MCMC (SG-MCMC) yields reliable uncertainty estimates for MD observables. We show that cold posteriors can reduce the required training data size and that for reliable UQ, multiple Markov chains are needed. Additionally, we find that SG-MCMC and the Deep Ensemble method achieve comparable results, despite shorter training and less hyperparameter tuning of the latter. We show that both methods can capture aleatoric and epistemic uncertainty reliably, but not systematic uncertainty, which needs to be minimized by adequate modeling to obtain accurate credible intervals for MD observables. Our results represent a step toward accurate UQ that is of vital importance for trustworthy NN potential-based MD simulations required for decision-making in practice. Markov chain Monte Carlo ; Computer science ; Uncertainty quantification ; Scalability ; Bayesian probability ; Bayesian inference ; Machine learning ; Artificial intelligence ; Monte Carlo method ; Hyperparameter ; Mathematics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Gaussian Processes and Bayesian Inference
Authors: Chaofan Li | Siting Hou | Changjian Xie
Source: Journal of Chemical Theory and Computation (article, 2023-05-22)
Field: Materials Science — Materials Chemistry

Constructing Diabatic Potential Energy Matrices with Neural Networks Based on Adiabatic Energies and Physical Considerations: Toward Quantum Dynamic Accuracy A permutation invariant polynomial-neural network (PIP-NN) approach for constructing the global diabatic potential energy matrices (PEMs) of the coupled states of molecules is proposed. Specifically, the diabatization scheme is based merely on the adiabatic energy data of the system, which is ideally a most convenient way due to not requiring additional <i>ab initio</i> calculations for the data of the derivative coupling or any other physical properties of the molecule. Considering the permutation and coupling characteristics of the system, particularly in the presence of conical intersections, some vital treatments for the off-diagonal terms in diabatic PEM are essentially needed. Taking the photodissociation of H<sub>2</sub>O(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover><mml:mi>X</mml:mi><mml:mo>~</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:mover><mml:mi>B</mml:mi><mml:mo>~</mml:mo></mml:mover></mml:math>)/NH<sub>3</sub>(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover><mml:mi>X</mml:mi><mml:mo>~</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:mover><mml:mi>A</mml:mi><mml:mo>~</mml:mo></mml:mover></mml:math>) and nonadiabatic reaction Na(3<i>p</i>) + H<sub>2</sub> → NaH(Σ<sup>+</sup>) + H for example, this PIP-NN method is shown to build up the global diabatic PEMs effectively and accurately. The root-mean-square errors of the adiabatic potential energies in the fitting for three different systems are all small (<10 meV). Further quantum dynamic calculations show that the absorption spectra and product branching ratios in both H<sub>2</sub>O(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover><mml:mi>X</mml:mi><mml:mo>~</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:mover><mml:mi>B</mml:mi><mml:mo>~</mml:mo></mml:mover></mml:math>) and NH<sub>3</sub>(<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mover><mml:mi>X</mml:mi><mml:mo>~</mml:mo></mml:mover><mml:mo>/</mml:mo><mml:mover><mml:mi>A</mml:mi><mml:mo>~</mml:mo></mml:mover></mml:math>) nonadiabatic photodissociation are well reproduced on the new diabatic PEMs, and the nonadiabatic reaction probability of Na(3<i>p</i>) + H<sub>2</sub> → NaH(Σ<sup>+</sup>) + H obtained on the new diabatic PEMs of the 1<sup>2</sup>A<sub>1</sub> and 1<sup>2</sup>B<sub>2</sub> states is in reasonably good agreement with previous theoretical result as well, validating this new PIP-NN method. Diabatic ; Adiabatic process ; Potential energy ; Chemistry ; Vibronic coupling ; Physics ; Quantum mechanics ; Atomic physics ; Molecule Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Spectroscopy and Quantum Chemical Studies
Authors: Hasan Can Gülbalkan | Gokhan Onder Aksu | Goktug Ercakir | Seda Keskın
Source: Industrial & Engineering Chemistry Research (article, 2023-12-25)
Field: Chemistry — Inorganic Chemistry

Accelerated Discovery of Metal–Organic Frameworks for CO<sub>2</sub> Capture by Artificial Intelligence The existence of a very large number of porous materials is a great opportunity to develop innovative technologies for carbon dioxide (CO<sub>2</sub>) capture to address the climate change problem. On the other hand, identifying the most promising adsorbent and membrane candidates using iterative experimental testing and brute-force computer simulations is very challenging due to the enormous number and variety of porous materials. Artificial intelligence (AI) has recently been integrated into molecular modeling of porous materials, specifically metal-organic frameworks (MOFs), to accelerate the design and discovery of high-performing adsorbents and membranes for CO<sub>2</sub> adsorption and separation. In this perspective, we highlight the pioneering works in which AI, molecular simulations, and experiments have been combined to produce exceptional MOFs and MOF-based composites that outperform traditional porous materials in CO<sub>2</sub> capture. We outline the future directions by discussing the current opportunities and challenges in the field of harnessing experiments, theory, and AI for accelerated discovery of porous materials for CO<sub>2</sub> capture. Metal-organic framework ; Porous medium ; Porosity ; Adsorption ; Computer science ; Nanotechnology ; Variety (cybernetics) ; Process engineering ; Materials science ; Artificial intelligence ; Engineering ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Membrane Separation and Gas Transport
Authors: Anshul Sharma | Hyo‐Kyoung Choi | Hae‐Jeung Lee
Source: Oxidative Medicine and Cellular Longevity (review, 2023-05-25)
Field: Materials Science — Materials Chemistry

Carbon Dots for the Treatment of Inflammatory Diseases: An Appraisal of In Vitro and In Vivo Studies In recent decades, several studies demonstrating various applications of carbon dots (C-dots), including metal sensing, bioimaging, pH sensing, and antimicrobial activities, have been published. Recent developments have shifted this trend toward biomedical applications that target various biomarkers relevant to chronic diseases. However, relevant developments and research results regarding the anti-inflammatory properties of C-dots against inflammation-associated diseases have not been systematically reviewed. Hence, this review discusses the anti-inflammatory effects of C-dots in <i>in vivo</i> and <i>in vitro</i> models of LPS-induced inflammation, gout, cartilage tissue engineering, drug-induced inflammation, spinal cord injury, wound healing, liver diseases, stomach cancer, gastric ulcers, acute kidney and lung injury, psoriasis, fever or hypothermia, and bone tissue regeneration. The compiled studies demonstrate the promising potential of C-dots as anti-inflammatory agents for the development of new drugs. In vivo ; Inflammation ; Medicine ; Psoriasis ; Pharmacology ; Immunology ; Biology ; Biotechnology Carbon and Quantum Dots Applications ; Selenium in Biological Systems ; Curcumin's Biomedical Applications
Authors: Xuan Gao | Kejiang Liu | Chang Su | Wei Zhang | Yuhang Dai | Ivan P. Parkin | Claire J. Carmalt | Guanjie He
Source: SmartMat (article, 2023-03-15)
Field: Materials Science — Polymers and Plastics

From bibliometric analysis: 3D printing design strategies and battery applications with a focus on zinc‐ion batteries Abstract Three‐dimensional (3D) printing has the potential to revolutionize the way energy storage devices are designed and manufactured. In this paper, we explore the use of 3D printing in the design and production of energy storage devices, especially zinc‐ion batteries (ZIBs) and examine its potential advantages over traditional manufacturing methods. 3D printing could significantly improve the customization of ZIBs, making it a promising strategy for the future of energy storage. In particular, 3D printing allows for the creation of complex, customized geometries, and designs that can optimize the energy density, power density, and overall performance of batteries. Simultaneously, we discuss and compare the impact of 3D printing design strategies based on different configurations of film, interdigitation, and framework on energy storage devices with a focus on ZIBs. Additionally, 3D printing enables the rapid prototyping and production of batteries, reducing leading times and costs compared with traditional manufacturing methods. However, there are also challenges and limitations to consider, such as the need for further development of suitable 3D printing materials and processes for energy storage applications. 3D printing ; Energy storage ; Rapid prototyping ; Battery (electricity) ; Focus (optics) ; Process engineering ; Computer data storage ; Materials science ; Manufacturing engineering ; Engineering ; Nanotechnology ; Mechanical engineering ; Computer science ; Power (physics) ; Computer hardware Conducting polymers and applications ; Advanced battery technologies research ; Supercapacitor Materials and Fabrication
Authors: Xueqi Guo | Lili Wang | Linjie Wang | Q. Huang | Lijuan Bu | Qiang Wang
Source: Frontiers in Chemistry (review, 2023-01-18)
Field: Chemistry — Inorganic Chemistry

Metal-organic frameworks for food contaminant adsorption and detection Metal-organic framework materials (MOFs) have been widely used in food contamination adsorption and detection due to their large specific surface area, specific pore structure and flexible post-modification. MOFs with specific pore size can be targeted for selective adsorption of some contaminants and can be used as pretreatment and pre-concentration steps to purify samples and enrich target analytes for food contamination detection to improve the detection efficiency. In addition, MOFs, as a new functional material, play an important role in developing new rapid detection methods that are simple, portable, inexpensive and with high sensitivity and accuracy. The aim of this paper is to summarize the latest and insightful research results on MOFs for the adsorption and detection of food contaminants. By summarizing Zn-based, Cu-based and Zr-based MOFs with low cost, easily available raw materials and convenient synthesis conditions, we describe their principles and discuss their applications in chemical and biological contaminant adsorption and sensing detection in terms of stability, adsorption capacity and sensitivity. Finally, we present the limitations and challenges of MOFs in food detection, hoping to provide some ideas for future development. Adsorption ; Metal-organic framework ; Contamination ; Nanotechnology ; Analyte ; Biochemical engineering ; Process engineering ; Materials science ; Environmental science ; Chemistry ; Chromatography ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Molecular Sensors and Ion Detection ; Advanced Nanomaterials in Catalysis
Authors: Samuel H. Newman-Stonebraker | T. Judah Raab | Hootan Roshandel | Abigail G. Doyle
Source: Journal of the American Chemical Society (article, 2023-08-23)
Field: Chemistry — Organic Chemistry

Synthesis of Nickel(I)–Bromide Complexes via Oxidation and Ligand Displacement: Evaluation of Ligand Effects on Speciation and Reactivity Nickel's +1 oxidation state has received much interest due to its varied and often enigmatic behavior in increasingly popular catalytic methods. In part, the lack of understanding about Ni<sup>I</sup> results from common synthetic strategies limiting the breadth of complexes that are accessible for mechanistic study and catalyst design. We report an oxidative approach using tribromide salts that allows for the generation of a well-defined precursor, [Ni<sup>I</sup>(COD)Br]<sub>2</sub>, as well as several new Ni<sup>I</sup> complexes. Included among them are complexes bearing bulky monophosphines, for which structure-speciation relationships are established and catalytic reactivity in a Suzuki-Miyaura coupling (SMC) is investigated. Notably, these routes also allow for the synthesis of well-defined monomeric <sup><i>t</i>-Bu</sup>bpy-bound Ni<sup>I</sup> complexes, which has not previously been achieved. These complexes, which react with aryl halides, can enable previously challenging mechanistic investigations and present new opportunities for catalysis and synthesis. Chemistry ; Reactivity (psychology) ; Nickel ; Bromide ; Catalysis ; Ligand (biochemistry) ; Oxidative addition ; Halide ; Aryl ; Combinatorial chemistry ; Oxidation state ; Organic chemistry Catalytic C–H Functionalization Methods ; Catalytic Cross-Coupling Reactions ; Radical Photochemical Reactions
Authors: Peter A. Macdonald | Sumanta Banerjee | Alan R. Kennedy | Alexander van Teijlingen | Stuart D. Robertson | Tell Tuttle | Robert E. Mulvey
Source: Angewandte Chemie International Edition (article, 2023-05-03)
Field: Chemistry — Inorganic Chemistry

Alkali Metal Dihydropyridines in Transfer Hydrogenation Catalysis of Imines: Amide Basicity versus Hydride Surrogacy Catalytic reduction of a representative set of imines, both aldimines and ketimines, to amines has been studied using transfer hydrogenation from 1,4-dicyclohexadiene. Unusually, this has been achieved using s-block pre-catalysts, namely 1-metallo-2-tert-butyl-1,2-dihydropyridines, 2-tBuC<sub>5</sub> H<sub>5</sub> NM, M(tBuDHP), where M=Li-Cs. Reactions have been monitored in C<sub>6</sub> D<sub>6</sub> and tetrahydrofuran-d<sub>8</sub> (THF-d<sub>8</sub> ). A definite trend is observed in catalyst efficiency with the heavier alkali metal tBuDHPs outperforming the lighter congeners. In general, Cs(tBuDHP) is the optimal pre-catalyst with, in the best cases, reactions producing quantitative yields of amines in minutes at room temperature using 5 mol % catalyst. Supporting the experimental study, Density Functional Theory (DFT) calculations have also been carried out which reveal that Cs has a pathway with a significantly lower rate determining step than the Li congener. In the postulated initiation pathways DHP can act as either a base or as a surrogate hydride. Chemistry ; Catalysis ; Tetrahydrofuran ; Hydride ; Amide ; Alkali metal ; Aldimine ; Base (topology) ; Medicinal chemistry ; Inorganic chemistry ; Metal ; Organic chemistry Asymmetric Hydrogenation and Catalysis ; Chemical Synthesis and Analysis ; Nanomaterials for catalytic reactions
Authors: Suresh K. Verma | Aditya Nandi | Faizan Zarreen Simnani | Dibyangshee Singh | Adrija Sinha | Shaikh Sheeran Naser | Jyotirmayee Sahoo | Sudakshya S. Lenka | Pritam Kumar Panda | Ateet Dutt | Nagendra Kumar Kaushik | Deobrat Singh | Mrutyunjay Suar
Source: Materials & Design (article, 2023-11-01)
Field: Materials Science — Materials Chemistry

In silico nanotoxicology: The computational biology state of art for nanomaterial safety assessments In recent decade, nanotechnology has got an extensive advancement in terms of production and application of nanomaterials. With the advancement, concern has risen for their biomedical and ecological safety, provoking a detailed analysis of the safety assement. Numerous experimental and computational approach has been developed to accomplish the goal of safety assessment of nanomaterials leading to orgin of interdisciplinary fields like nanoinformatics. Nanoinformatics has accomplished significant strides with the development of several modeling frameworks, data platforms, knowledge infrastructures, and in silico tools for risk assessment forecasts of nanomaterials. This review is an attemption to decipher and establish the bridge between the two emerging scientific arenas that includes computational modeling and nanotoxicity. We have reviewed the recent informations to uncover the link between the computational toxicology and nanotoxicology in terms of biomedical and ecological applications. In addition to the details about nanomaterials interaction with the biological system, this article offers a concise evaluation of recent developments in the various nanoinformatics domains. In detail, the computational tools like molecular docking, QSAR, etc. for the prediction of nanotoxicity here have been described. Moreover, techniques like molecular dynamics simulations used for experimental data collection and their translation to standard computational formats are explored. Nanotoxicology ; Nanotechnology ; Computer science ; Computational model ; In silico ; Risk analysis (engineering) ; Biochemical engineering ; Data science ; Engineering ; Biology ; Artificial intelligence ; Materials science ; Nanoparticle Nanoparticles: synthesis and applications ; Computational Drug Discovery Methods
Authors: Yang Li | Zelong Zhou | Yongyong He
Source: Materials (review, 2023-12-22)
Field: Materials Science — Materials Chemistry

Tribocorrosion and Surface Protection Technology of Titanium Alloys: A Review Titanium alloy has the advantages of high specific strength, good corrosion resistance, and biocompatibility and is widely used in marine equipment, biomedicine, aerospace, and other fields. However, the application of titanium alloy in special working conditions shows some shortcomings, such as low hardness and poor wear resistance, which seriously affect the long life and safe and reliable service of the structural parts. Tribocorrosion has been one of the research hotspots in the field of tribology in recent years, and it is one of the essential factors affecting the application of passivated metal in corrosive environments. In this work, the characteristics of the marine and human environments and their critical tribological problems are analyzed, and the research connotation of tribocorrosion of titanium alloy is expounded. The research status of surface protection technology for titanium alloy in marine and biological environments is reviewed, and the development direction and trends in surface engineering of titanium alloy are prospected. Tribocorrosion ; Materials science ; Corrosion ; Titanium alloy ; Tribology ; Metallurgy ; Titanium ; Alloy Titanium Alloys Microstructure and Properties ; Orthopaedic implants and arthroplasty ; Advanced materials and composites
Authors: Bohayra Mortazavi
Source: Materials (article, 2023-10-11)
Field: Materials Science — Materials Chemistry

Electronic, Thermal and Mechanical Properties of Carbon and Boron Nitride Holey Graphyne Monolayers In a recent experimental accomplishment, a two-dimensional holey graphyne semiconducting nanosheet with unusual annulative π-extension has been fabricated. Motivated by the aforementioned advance, herein we theoretically explore the electronic, dynamical stability, thermal and mechanical properties of carbon (C) and boron nitride (BN) holey graphyne (HGY) monolayers. Density functional theory (DFT) results reveal that while the C-HGY monolayer shows an appealing direct gap of 1.00 (0.50) eV according to the HSE06(PBE) functional, the BNHGY monolayer is an indirect insulator with large band gaps of 5.58 (4.20) eV. Furthermore, the elastic modulus (ultimate tensile strength) values of the single-layer C- and BN-HGY are predicted to be 127(41) and 105(29) GPa, respectively. The phononic and thermal properties are further investigated using machine learning interatomic potentials (MLIPs). The predicted phonon spectra confirm the dynamical stability of these novel nanoporous lattices. The room temperature lattice thermal conductivity of the considered monolayers is estimated to be very close, around 14.0 ± 1.5 W/mK. At room temperature, the C-HGY and BN-HGY monolayers are predicted to yield an ultrahigh negative thermal expansion coefficient, by more than one order of magnitude larger than that of the graphene. The presented results reveal decent stability, anomalously low elastic modulus to tensile strength ratio, ultrahigh negative thermal expansion coefficients and moderate lattice thermal conductivity of the semiconducting C-HGY and insulating BN-HGY monolayers. Graphyne ; Materials science ; Monolayer ; Boron nitride ; Bulk modulus ; Nanosheet ; Phonon ; Thermal expansion ; Thermal conductivity ; Density functional theory ; Graphene ; Condensed matter physics ; Thermal stability ; Composite material ; Nanotechnology ; Computational chemistry ; Chemical engineering ; Chemistry Graphene research and applications ; Thermal properties of materials ; Boron and Carbon Nanomaterials Research
Authors: Rizwan Nabi | Jakob K. Staab | Andrea Mattioni | Jon G. C. Kragskow | Daniel Reta | Jonathan M. Skelton | Nicholas F. Chilton
Source: Journal of the American Chemical Society (article, 2023-11-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Accurate and Efficient Spin–Phonon Coupling and Spin Dynamics Calculations for Molecular Solids Molecular materials are poised to play a significant role in the development of future optoelectronic and quantum technologies. A crucial aspect of these areas is the role of spin-phonon coupling and how it facilitates energy transfer processes such as intersystem crossing, quantum decoherence, and magnetic relaxation. Thus, it is of significant interest to be able to accurately calculate the molecular spin-phonon coupling and spin dynamics in the condensed phase. Here, we demonstrate the maturity of <i>ab initio</i> methods for calculating spin-phonon coupling by performing a case study on a single-molecule magnet and showing quantitative agreement with the experiment, allowing us to explore the underlying origins of its spin dynamics. This feat is achieved by leveraging our recent developments in analytic spin-phonon coupling calculations in conjunction with a new method for including the infinite electrostatic potential in the calculations. Furthermore, we make the first <i>ab initio</i> determination of phonon lifetimes and line widths for a molecular magnet to prove that the commonplace Born-Markov assumption for the spin dynamics is valid, but such "exact" phonon line widths are not essential to obtain accurate magnetic relaxation rates. Calculations using this approach are facilitated by the open-source packages we have developed, enabling cost-effective and accurate spin-phonon coupling calculations on molecular solids. Phonon ; Quantum decoherence ; Coupling (piping) ; Relaxation (psychology) ; Spin (aerodynamics) ; Condensed matter physics ; Chemistry ; Spin engineering ; Ab initio ; Molecular dynamics ; Ab initio quantum chemistry methods ; Quantum ; Physics ; Spin polarization ; Quantum mechanics ; Molecule ; Computational chemistry ; Materials science ; Electron ; Thermodynamics Magnetism in coordination complexes ; Organic and Molecular Conductors Research ; Lanthanide and Transition Metal Complexes