jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Annick De Backer | Sandra Van Aert | Christel Faes | Ece Arslan Irmak | Peter D. Nellist | Lewys Jones
Source: npj Computational Materials (article, 2022-10-12)
Field: Materials Science — Materials Chemistry

Experimental reconstructions of 3D atomic structures from electron microscopy images using a Bayesian genetic algorithm Abstract We introduce a Bayesian genetic algorithm for reconstructing atomic models of monotype crystalline nanoparticles from a single projection using Z-contrast imaging. The number of atoms in a projected atomic column obtained from annular dark field scanning transmission electron microscopy images serves as an input for the initial three-dimensional model. The algorithm minimizes the energy of the structure while utilizing a priori information about the finite precision of the atom-counting results and neighbor-mass relations. The results show promising prospects for obtaining reliable reconstructions of beam-sensitive nanoparticles during dynamical processes from images acquired with sufficiently low incident electron doses. Algorithm ; Dark field microscopy ; Projection (relational algebra) ; Bayesian probability ; Scanning transmission electron microscopy ; Electron ; Bayesian optimization ; Genetic algorithm ; A priori and a posteriori ; Transmission electron microscopy ; Atom (system on chip) ; Energy (signal processing) ; Physics ; Optics ; Computer science ; Computational physics ; Microscopy ; Materials science ; Artificial intelligence ; Machine learning ; Quantum mechanics Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications ; Electron and X-Ray Spectroscopy Techniques
Authors: R. Ramesh
Source: Journal of the Indian Institute of Science (review, 2022-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Materials for a Sustainable Microelectronics Future: Electric Field Control of Magnetism with Multiferroics Engineering ethics ; Multiferroics ; Field (mathematics) ; Perspective (graphical) ; Nanotechnology ; Sustainability ; Engineering physics ; Control (management) ; Engineering ; Sociology ; Computer science ; Electrical engineering ; Materials science ; Artificial intelligence ; Ferroelectricity Multiferroics and related materials ; Magnetic and transport properties of perovskites and related materials ; Ferroelectric and Piezoelectric Materials
Authors: Furkan Uzcan | Muhammad Saqaf Jagirani | Mustafa Soylak
Source: TURKISH JOURNAL OF CHEMISTRY (review, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Assessment of environmental pollutants at trace levels using ionic liquids-based liquid-phase microextraction Sample preparation is the crucial and most challenging part of analytical chemistry for the speciation of environmental pollutants' traces. Along with the development of the sample preparation methods, the ionic liquid-based microextraction technique plays an important role. Due to the unequivocally unique "green" characteristic of ionic liquids (ILs), they owe their tunable properties, such as highly selective and high reaction efficiency, reusability, and good thermal stability, to present advancements in the sample preparation process. The ionic liquid-based microextraction techniques miniaturize the sample preparation process. Liquid phase microextraction intermediate solvents, desorption solvent extractants, and mediators have been used. They are quoting the benefits and limitations of each method. A few essential sample preparation methods covered the microextraction technique. In this context, miniaturized microextraction methods have been developed. They are generally used for their unlimited positive features, including easy, simple, and environmentally friendly; they also extract inorganic and organic species with low-cost instrumentation. This review advances the sample preparation process using ILs-based liquid phase microextraction as an intermediate solvent, extractant desorption, and mediator solvents. Ionic liquid ; Chemistry ; Solid-phase microextraction ; Sample preparation ; Context (archaeology) ; Solvent ; Thermal desorption ; Chromatography ; Environmentally friendly ; Desorption ; Reusability ; Mass spectrometry ; Organic chemistry ; Adsorption ; Gas chromatography–mass spectrometry ; Computer science Analytical chemistry methods development ; Electrochemical Analysis and Applications ; Mercury impact and mitigation studies
Authors: Bienfait Kabuyaya Isamura | Kevin A. Lobb
Source: Journal of Cheminformatics (article, 2022-06-15)
Field: Chemistry — Spectroscopy

AMADAR: a python-based package for large scale prediction of Diels–Alder transition state geometries and IRC path analysis Predicting transition state geometries is one of the most challenging tasks in computational chemistry, which often requires expert-based knowledge and permanent human intervention. This short communication reports technical details and preliminary results of a python-based tool (AMADAR) designed to generate any Diels-Alder (DA) transition state geometry (TS) and analyze determined IRC paths in a (quasi-)automated fashion, given the product SMILES. Two modules of the package are devoted to performing, from IRC paths, reaction force analyses (RFA) and atomic (fragment) decompositions of the reaction force F and reaction force constant [Formula: see text]. The performance of the protocol has been assessed using a dataset of 2000 DA cycloadducts retrieved from the ZINC database. The sequential location of the corresponding TSs was achieved with a success rate of 95%. RFA plots confirmed the reaction force constant [Formula: see text] to be a good indicator of the (non)synchronicity of the associated DA reactions. Moreover, the atomic decomposition of [Formula: see text] allows for the rationalization of the (a)synchronicity of each DA reaction in terms of contributions stemming from pairs of interacting atoms. The source code of the AMADAR tool is available on GitHub [ CMCDD/AMADAR(github.com) ] and can be used directly with minor customizations, mostly regarding the local working environment of the user. Python (programming language) ; Computer science ; Path (computing) ; Scale (ratio) ; State (computer science) ; Data mining ; Computational science ; Programming language ; Cartography ; Geography Analytical Chemistry and Chromatography ; Catalysis and Oxidation Reactions ; Advanced Chemical Physics Studies
Authors: Н. В. Каманина | А. S. Toikka | Ya. V. Barnash | P. V. Kuzhakov | Dmitry G. Kvashnin
Source: Materials (article, 2022-07-07)
Field: Chemistry — Inorganic Chemistry

Advanced and Functional Structured Ceramics: MgF2 and ZnS Due to difficulties in obtaining monomaterials, intensive research into the properties of ceramic compositions has been undertaken, along with developments to the properties of the compositions. These are not inferior to monomeric structures for a number of basic parameters. Among the different types of ceramics, magnesium fluoride and zinc sulfide occupy a special place due to their unique properties and specific applications. In this paper, we studied functional optoelectronics and modulating technique elements based on the advanced ceramics MgF<sub>2</sub> and ZnS. The results of the transmittance spectral parameters and the contact angle estimation as well as an AFM analysis of the studied ceramics, both pure and structured with carbon nanotubes, are presented. We observed that the main characteristics of the studied materials with a surface modified by carbon nanotubes could be significantly changed when an innovative laser-oriented deposition method was applied. This method permitted the CNTs to be deposited in a vertical position on the material surface. The main features of the carbon nanotubes-such as the smaller value of the refractive index, the greater strength between the carbon atoms, and the effective surface-were taken into consideration. The analytical, quantum chemical, and experimental results of the studies of the changes in the basic physical parameters of the selected model of the inorganic matrices of the ceramics are given. Materials science ; Ceramic ; Composite material Inorganic Fluorides and Related Compounds ; Microwave Dielectric Ceramics Synthesis ; Magnesium Oxide Properties and Applications
Authors: Н. В. Каманина | А. S. Toikka | Dmitry G. Kvashnin
Source: Journal of Composites Science (article, 2022-06-20)
Field: Materials Science — Materials Chemistry

Nanostructuration Impact on the Basic Properties of the Materials: Novel Composite Carbon Nanotubes on a Copper Surface Copper is important material that is widely applicable in the electric and electronic industries. Nevertheless, in some circumstances, it is highly desirable to improve its properties. Therefore, combination of materials of various composition and properties attracts scientific and industrial society. Here, the composite based on carbon nanotubes (CNTs) on a Cu surface was fabricated using laser-oriented deposition (LOD) technique and studied. Examination of the novel composite showed that its reflectance was decreased, the microhardness was increased, and wetting of the surface exhibited higher hydrophobicity. A molecular dynamic simulation showed that the penetration depth increases with nanotube diameter decrease and growth of the acceleration rate. Topography observations made via AFM images revealed a dense thin film with an almost-homogeneous distribution of CNTs, with several locations with irregular thickness addressing the different lengths of CNTs. Carbon nanotube ; Wetting ; Materials science ; Composite number ; Copper ; Composite material ; Indentation hardness ; Nanotechnology ; Homogeneous ; Penetration (warfare) ; Microstructure ; Metallurgy Diamond and Carbon-based Materials Research ; Electrohydrodynamics and Fluid Dynamics ; Carbon Nanotubes in Composites
Authors: Weidong Li | jianping Qiu | Leila Baharinikoo | T. CH. Anil Kumar | Basim Al-Qargholi | Shafik S. Shafik | Reathab Abbass | Shelesh krishna Saraswat
Source: Scientific Reports (article, 2022-07-27)
Field: Chemistry — Analytical Chemistry

Dispersive solid phase microextraction based on magnesium oxide nanoparticles for preconcentration of auramine O and methylene blue from water samples In this study, we investigated the process of preconcentrate and determine trace amounts of Auramine O (AO) and methylene blue (MB) dyes in environmental water samples. For this purpose, the ultrasound-assisted dispersive-magnetic nanocomposites-solid-phase microextraction (UA-DMNSPME) method was performed to extract AO and MB from aqueous samples by applying magnesium oxide nanoparticles (MgO-NPs). The proposed technique is low-cost, facile, fast, and compatible with many existing instrumental methods. Parameters affecting the extraction of AO and MB were optimized using response surface methodology (RSM). Short extraction time, low experimental tests, low consumption of organic solvent, low limits of detection (LOD), and high preconcentration factor (PF) was the advantages of method. The PF was 44.5, and LOD for AO and MB was 0.33 ng mL<sup>-1</sup> and 1.66 ng mL<sup>-1</sup>, respectively. The linear range of this method for AO and MB were 1-1000 ng mL<sup>-1</sup> and 5-2000 ng mL<sup>-1</sup>, respectively. In addition, the relative standard deviation (RSD; n = 5) of the mentioned analytes was between 2.9% and 3.1%. The adsorption-desorption studies showed that the efficiency of adsorbent extraction had not declined significantly up to 6 recycling runs, and the adsorbent could be used several times. The interference studies revealed that the presence of different ions did not interfere substantially with the extraction and determination of AO and MB. Therefore, UA-DMNSPME-UV/Vis method can be proposed as an efficient method for preconcentration and extraction of AO and MB from water and wastewater samples. Detection limit ; Extraction (chemistry) ; Adsorption ; Methylene blue ; Chromatography ; Solid phase extraction ; Desorption ; Magnesium ; Enrichment factor ; Chemistry ; Solvent ; Aqueous solution ; Solid-phase microextraction ; Mass spectrometry ; Gas chromatography–mass spectrometry Analytical chemistry methods development ; Dye analysis and toxicity ; Electrochemical sensors and biosensors
Authors: Nobuyuki Yoshioka | Takeshi Sato | Yuya O. Nakagawa | Yu-ya Ohnishi | Wataru Mizukami
Source: Physical Review Research (preprint, 2022-01-26)
Field: Materials Science — Materials Chemistry

Variational quantum simulation for periodic materials We present a quantum-classical hybrid algorithm that simulates electronic structures of periodic systems such as ground states and quasiparticle band structures. By extending the unitary coupled cluster (UCC) theory to describe crystals in arbitrary dimensions, for a hydrogen chain, we numerically demonstrate that the UCC ansatz implemented on a quantum circuit can be successfully optimized with a small deviation from the exact diagonalization over the entire range of the potential energy curves. Furthermore, by using the quantum subspace expansion method, in which we truncate the Hilbert space within the linear response regime from the ground state, the quasiparticle band structure is computed as charged excited states. Our work establishes a powerful interface between the rapidly developing quantum technology and modern material science. Ansatz ; Quasiparticle ; Physics ; Hilbert space ; Subspace topology ; Excited state ; Quantum simulator ; Quantum mechanics ; Quantum ; Unitary state ; Quantum computer ; Mathematics ; Mathematical analysis Chemical and Physical Properties of Materials ; Advanced Chemical Physics Studies ; Quantum and electron transport phenomena
Authors: Tom A. Young | Tristan Johnston-Wood | Hanwen Zhang | Fernanda Duarte
Source: ChemRxiv (preprint, 2022-06-23)
Field: Materials Science — Materials Chemistry

Reaction dynamics of Diels-Alder reactions from machine learned potentials Recent advances in the development of reactive machine-learned potentials (MLPs) promise to transform reaction modelling. However, such methods have remained computationally expensive and limited to experts. Here, we employ different MLP methods (ACE, NequIP, GAP), combined with automated fitting and active learning, to study the reaction dynamics of representative Diels-Alder reactions. We demonstrate that the ACE and NequIP MLPs can consistently achieve chemical accuracy (± 1 kcal mol−1) to the ground-truth surface with only a few hundred reference calculations. These strategies are shown to enable routine ab initio-quality classical and quantum dynamics and obtain dynamical quantities such as product ratios and free energies from non-static methods. For ambimodal reactions, product distributions were found to be strongly dependent on the QM method and less so on the type of dynamics propagated. Ab initio ; Product (mathematics) ; Quantum ; Computer science ; Reaction dynamics ; Dynamics (music) ; Computational chemistry ; Diels–Alder reaction ; Chemistry ; Physics ; Mathematics ; Organic chemistry ; Quantum mechanics ; Molecule Machine Learning in Materials Science ; Topic Modeling ; Advanced Chemical Physics Studies
Authors: Renata Rezende Miranda | Anutthaman Parthasarathy | André O. Hudson
Source: Frontiers in Tropical Diseases (article, 2022-03-03)
Field: Chemistry — Organic Chemistry

Exploration of Chemical Biology Approaches to Facilitate the Discovery and Development of Novel Antibiotics Approximately 2.8 million people worldwide are infected with bacteria that are deemed resistant to clinically relevant antibiotics. This accounts for 700,000 deaths every year and represents a major public health threat that has been on the rise for the past two decades. In contrast, the pace of antibiotic discovery to treat these resistant pathogens has significantly decreased. Most antibiotics are complex natural products that were isolated from soil microorganisms during the golden era of antibiotic discovery (1940s to 1960s) employing the “Waksman platform”. After the collapse of this discovery platform, other strategies and approaches emerged, including phenotype- or target-based screenings of large synthetic compound libraries. However, these methods have not resulted in the discovery and/or development of new drugs for clinical use in over 30 years. A better understanding of the structure and function of the molecular components that constitute the bacterial system is of paramount importance to design new strategies to tackle drug-resistant pathogens. Herein, we review the traditional approaches as well as novel strategies to facilitate antibiotic discovery that are chemical biology-focused. These include the design and application of chemical probes that can undergo bioorthogonal reactions, such as copper (I)-catalyzed azide-alkyne cycloadditions (CuAAC). By specifically interacting with bacterial proteins or being incorporated in the microorganism’s metabolism, chemical probes are powerful tools in drug discovery that can help uncover new drug targets and investigate the mechanisms of action and resistance of new antibacterial leads. Drug discovery ; Bioorthogonal chemistry ; Chemical biology ; Antibiotics ; Phenotypic screening ; Computational biology ; Biology ; Drug development ; Chemical space ; Nanotechnology ; Chemistry ; Drug ; Microbiology ; Bioinformatics ; Combinatorial chemistry ; Click chemistry ; Genetics ; Phenotype ; Pharmacology Click Chemistry and Applications ; Microbial Natural Products and Biosynthesis ; Synthesis and Catalytic Reactions
Authors: Igor V. Kosarev | Sergey V. Dmitriev | А С Семенов | Elena A. Korznikova
Source: Materials (article, 2022-08-26)
Field: Materials Science — Materials Chemistry

Stability of Strained Stanene Compared to That of Graphene Stanene, composed of tin atoms, is a member of 2D-Xenes, two-dimensional single element materials. The properties of the stanene can be changed and improved by applying deformation, and it is important to know the range of in-plane deformation that the stanene can withstand. Using the Tersoff interatomic potential for calculation of phonon frequencies, the range of stability of planar stanene under uniform in-plane deformation is analyzed and compared with the known data for graphene. Unlike atomically flat graphene, stanene has a certain thickness (buckling height). It is shown that as the tensile strain increases, the thickness of the buckled stanene decreases, and when a certain tensile strain is reached, the stanene becomes absolutely flat, like graphene. Postcritical behaviour of stanene depends on the type of applied strain: critical tensile strain leads to breaking of interatomic bonds and critical in-plane compressive strain leads to rippling of stanene. It is demonstrated that application of shear strain reduces the range of stability of stanene. The existence of two energetically equivalent states of stanene is shown, and consequently, the possibility of the formation of domains separated by domain walls in the stanene is predicted. Graphene ; Materials science ; Ultimate tensile strength ; Deformation (meteorology) ; Condensed matter physics ; Composite material ; Nanotechnology ; Physics Graphene research and applications ; 2D Materials and Applications ; Boron and Carbon Nanomaterials Research
Authors: Kirill Shmilovich | Sayak Subhra Panda | Anna Stouffer | John D. Tovar | Andrew L. Ferguson
Source: Digital Discovery (article, 2022-01-01)
Field: Materials Science — Biomaterials

Hybrid computational–experimental data-driven design of self-assembling π-conjugated peptides A hybrid computational–experimental active learning workflow efficiently discovers π-conjugated peptides with superior capabilities for programmed self-assembly into pseudo-1D nanofibers. Conjugated system ; Workflow ; Computer science ; Self-assembly ; Nanofiber ; Nanotechnology ; Materials science ; Artificial intelligence ; Chemistry ; Organic chemistry Supramolecular Self-Assembly in Materials ; Chemical Synthesis and Analysis ; Advanced biosensing and bioanalysis techniques
Authors: Jhon Buendía Garcia | Marion Lacoue-Nègre | Julien Gornay | Sílvia Mas Garcia | Ryad Bendoula | Jean‐Michel Roger
Source: Fuel (article, 2022-05-25)
Field: Chemistry — Analytical Chemistry

Diesel cetane number estimation from NIR spectra of hydrocracking total effluent Cetane number ; Diesel fuel ; Calibration ; Distillation ; Effluent ; Partial least squares regression ; Environmental science ; Mathematics ; Process engineering ; Chemistry ; Statistics ; Biodiesel ; Chromatography ; Environmental engineering ; Engineering Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Amin Alibakhshi | Lars V. Schäfer
Source: Scientific Reports (article, 2022-04-06)
Field: Chemistry — Organic Chemistry

Accurate evaluation of combustion enthalpy by ab-initio computations Accurate evaluation of combustion enthalpy is of high scientific and industrial importance. Although ab-initio computation of the heat of reactions is one of the promising and well-established approaches in computational chemistry, reliable and precise computation of heat of combustion reactions by ab-initio methods is surprisingly scarce in the literature. A handful of works carried out for this purpose report significant inconsistencies between the computed and experimentally determined combustion enthalpies and suggest empirical corrections to improve the accuracy of the ab-initio predicted data. The main aim of the present study is to investigate the reasons behind those reported inconsistencies and propose guidelines for a high-accuracy estimation of heat of reactions via ab-initio computations. We show comparably accurate prediction of combustion enthalpy of 40 organic molecules based on a DSD-PBEP86 double-hybrid density functional theory approach and CCSD(T)-F12 coupled-cluster computations, with mean unsigned errors with respect to experimental data being below 0.5% for both methods. Computation ; Enthalpy ; Combustion ; Ab initio ; Ab initio quantum chemistry methods ; Standard enthalpy change of formation ; Computational chemistry ; Computer science ; Thermodynamics ; Chemistry ; Physical chemistry ; Physics ; Algorithm ; Organic chemistry ; Molecule Chemical Thermodynamics and Molecular Structure ; Computational Drug Discovery Methods ; Machine Learning in Materials Science