jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kirill Zinovjev
Source: Journal of Chemical Theory and Computation (article, 2023-02-23)
Field: Materials Science — Materials Chemistry

Electrostatic Embedding of Machine Learning Potentials This work presents a variant of an electrostatic embedding scheme that allows the embedding of arbitrary machine learned potentials trained on molecular systems <i>in vacuo</i>. The scheme is based on physically motivated models of electronic density and polarizability, resulting in a generic model without relying on an exhaustive training set. The scheme only requires <i>in vacuo</i> single point QM calculations to provide training densities and molecular dipolar polarizabilities. As an example, the scheme is applied to create an embedding model for the QM7 data set using Gaussian Process Regression with only 445 reference atomic environments. The model was tested on the SARS-CoV-2 protease complex with PF-00835231, resulting in a predicted embedding energy RMSE of 2 kcal/mol, compared to explicit DFT/MM calculations. Embedding ; Polarizability ; Scheme (mathematics) ; Computer science ; Set (abstract data type) ; Dipole ; Gaussian ; Statistical physics ; Theoretical computer science ; Artificial intelligence ; Machine learning ; Algorithm ; Computational chemistry ; Physics ; Molecule ; Chemistry ; Mathematics ; Quantum mechanics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Tanner Q. Kimberly | Kamil Ciesielski | Xiao Qi | Eric S. Toberer | Susan M. Kauzlarich
Source: ACS Applied Electronic Materials (article, 2023-06-05)
Field: Materials Science — Materials Chemistry

High Thermoelectric Performance in 2D Sb<sub>2</sub>Te<sub>3</sub> and Bi<sub>2</sub>Te<sub>3</sub> Nanoplate Composites Enabled by Energy Carrier Filtering and Low Thermal Conductivity Thermoelectrics are an important class of materials with great potential in alternative energy applications. In this study, two-dimensional (2D) nanoplates of the layered chalcogenides, Sb<sub>2</sub>Te<sub>3</sub> and Bi<sub>2</sub>Te<sub>3</sub>, are synthesized and composites of the two are investigated for their thermoelectric properties. The two materials, Sb<sub>2</sub>Te<sub>3</sub> and Bi<sub>2</sub>Te<sub>3</sub>, were synthesized as hexagonal, 2D nanoplates via a colloidal polyol route. The as-synthesized Sb<sub>2</sub>Te<sub>3</sub> and Bi<sub>2</sub>Te<sub>3</sub> vary drastically from one another in their lateral and vertical dimensions as revealed by scanning electron microscopy and atomic force microscopy. The single crystalline nanoplate nature is deduced by high-resolution transmission electron microscopy and selected area electron diffraction. Nanoplates have well-defined hexagonal facets as seen in the scanning and transmission electron microscopy images. The nanoplates were consolidated as an anisotropic nanostructured pellet via spark plasma sintering. Preferred orientation observed in the powder X-ray diffraction pattern and scanning electron microscopy images of the fractured pellets confirm the anisotropic structure of the nanoplates. Thermoelectric properties in the parallel and perpendicular directions were measured, revealing strong anisotropy with a significant reduction to thermal conductivity in the perpendicular direction due to increased phonon scattering at nanoplate interfaces. All compositions, except that of the 25% Bi<sub>2</sub>Te<sub>3</sub> nanoplate composite, behave as degenerate semiconductors with increasing electrical resistivity as the temperature increases. The Seebeck coefficient is also increased dramatically in the nanocomposites, the highest reaching 210 μV/K for 15% Bi<sub>2</sub>Te<sub>3</sub>. The increase in Seebeck is attributed to energy carrier filtering at the nanoplate interfaces. Overall, these enhanced thermoelectric properties lead to a drastic increase in the thermoelectric performance in the perpendicular direction, with <i>zT</i> ∼ 1.26, for the 15% Bi<sub>2</sub>Te<sub>3</sub> nanoplate composite at 450 K. Materials science ; Thermoelectric effect ; Seebeck coefficient ; Spark plasma sintering ; Scanning electron microscope ; Thermoelectric materials ; Transmission electron microscopy ; Composite material ; Thermal conductivity ; Nanotechnology ; Sintering Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies ; Thermal properties of materials
Authors: Monireh Alimohamadi | Alireza Khataee | Samira Arefi-Oskoui | Behrouz Vahid | Yasin Orooji | Yeojoon Yoon
Source: Ultrasonics Sonochemistry (article, 2023-01-07)
Field: Materials Science — Materials Chemistry

Catalytic activation of hydrogen peroxide by Cr2AlC MAX phase under ultrasound waves for a treatment of water contaminated with organic pollutants This study aims to investigate the sonocatalytic activation of hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) using Cr<sub>2</sub>AlC MAX phase prepared by the reactive sintering process. The hexagonal structure of the crystalline MAX phase was confirmed by X-ray diffraction. Moreover, the compacted layered structure of the MAX phase was observed via scanning electron microscopy and high-resolution transmission electron microscopy. Under the desired operating conditions, Cr<sub>2</sub>AlC MAX phase (0.75 g/L) showed suitable potential to activate H<sub>2</sub>O<sub>2</sub> (1 mmol/L) under sonication, thereby allowing a considerable removal efficiency for various organic pollutants, including dimethyl phthalate (69.1%), rifampin (94.5%), hydroxychloroquine (100%), and acid blue 7 (91.5%) with initial concentration of 15 mg/L within 120 min of treatment. Kinetic analysis proved that the degradation reaction followed pseudo-first-order kinetics. Scavenging tests demonstrated that hydroxyl radicals and singlet oxygen were effective species during degradation. Furthermore, a probable mechanism for dimethyl phthalate degradation was suggested according to gas chromatography-mass spectroscopy and nuclear magnetic resonance analyses. The obtained results confirmed the capability of the triple Cr<sub>2</sub>AlC/H<sub>2</sub>O<sub>2</sub>/US process as a promising method for treating contaminated water. Hydrogen peroxide ; Chemistry ; Radical ; Singlet oxygen ; Dimethyl phthalate ; Catalysis ; Nuclear chemistry ; Oxygen ; Phthalate ; Organic chemistry MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques ; Graphene and Nanomaterials Applications
Authors: Adam McSloy | Guozheng Fan | Wenbo Sun | Christian Hölzer | Marvin Friede | Sebastian Ehlert | Nils-Erik Schütte | Stefan Grimme | Thomas Frauenheim | Bálint Aradi
Source: The Journal of Chemical Physics (article, 2023-01-02)
Field: Materials Science — Materials Chemistry

TBMaLT, a flexible toolkit for combining tight-binding and machine learning Tight-binding approaches, especially the Density Functional Tight-Binding (DFTB) and the extended tight-binding schemes, allow for efficient quantum mechanical simulations of large systems and long-time scales. They are derived from ab initio density functional theory using pragmatic approximations and some empirical terms, ensuring a fine balance between speed and accuracy. Their accuracy can be improved by tuning the empirical parameters using machine learning techniques, especially when information about the local environment of the atoms is incorporated. As the significant quantum mechanical contributions are still provided by the tight-binding models, and only short-ranged corrections are fitted, the learning procedure is typically shorter and more transferable as it were with predicting the quantum mechanical properties directly with machine learning without an underlying physically motivated model. As a further advantage, derived quantum mechanical quantities can be calculated based on the tight-binding model without the need for additional learning. We have developed the open-source framework-Tight-Binding Machine Learning Toolkit-which allows the easy implementation of such combined approaches. The toolkit currently contains layers for the DFTB method and an interface to the GFN1-xTB Hamiltonian, but due to its modular structure and its well-defined interfaces, additional atom-based schemes can be implemented easily. We are discussing the general structure of the framework, some essential implementation details, and several proof-of-concept applications demonstrating the perspectives of the combined methods and the functionality of the toolkit. Tight binding ; Computer science ; Modular design ; Hamiltonian (control theory) ; Quantum ; Atom (system on chip) ; Ab initio ; Artificial intelligence ; Theoretical computer science ; Machine learning ; Electronic structure ; Mathematics ; Physics ; Quantum mechanics ; Mathematical optimization Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Electronic and Structural Properties of Oxides
Authors: Sunday J. Olakanmi | Digvir S. Jayas | Jitendra Paliwal
Source: Comprehensive Reviews in Food Science and Food Safety (review, 2023-03-13)
Field: Chemistry — Analytical Chemistry

Applications of imaging systems for the assessment of quality characteristics of bread and other baked goods: A review One of the most widely researched topics in the food industry is bread quality analysis. Different techniques have been developed to assess the quality characteristics of bakery products. However, in the last few decades, the advancement in sensor and computational technologies has increased the use of computer vision to analyze food quality (e.g., bakery products). Despite a large number of publications on the application of imaging methods in the bakery industry, comprehensive reviews detailing the use of conventional analytical techniques and imaging methods for the quality analysis of baked goods are limited. Therefore, this review aims to critically analyze the conventional methods and explore the potential of imaging techniques for the quality assessment of baked products. This review provides an in-depth assessment of the different conventional techniques used for the quality analysis of baked goods which include methods to record the physical characteristics of bread and analyze its quality, sensory-based methods, nutritional-based methods, and the use of dough rheological data for end-product quality prediction. Furthermore, an overview of the image processing stages is presented herein. We also discuss, comprehensively, the applications of imaging techniques for assessing the quality of bread and other baked goods. These applications include studying and predicting baked goods' quality characteristics (color, texture, size, and shape) and classifying them based on these features. The limitations of both conventional techniques (e.g., destructive, laborious, error-prone, and expensive) and imaging methods (e.g., illumination, humidity, and noise) and the future direction of the use of imaging methods for quality analysis of bakery products are discussed. Quality (philosophy) ; Computer science ; Food quality ; Product (mathematics) ; Food products ; Food science ; Mathematics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: Jiaojiao Zhou | Yuantao Liu | Xiaoping Du | Yue Gui | Jiangling He | Fang Xie | Jie Cai
Source: ACS Omega (article, 2023-11-28)
Field: Materials Science — Materials Chemistry

Recent Advances in Design and Application of Nanomaterials-Based Colorimetric Biosensors for Agri-food Safety Analysis A colorimetric sensor detects an analyte by utilizing the optical properties of the sensor unit, such as absorption or reflection, to generate a structural color that serves as the output signal to detect an analyte. Detecting the refractive index of an analyte by recording the color change of the sensor structure on its surface has several advantages, including simple operation, low cost, suitability for onsite analysis, and real-time detection. Colorimetric sensors have drawn much attention owing to their rapidity, simplicity, high sensitivity and selectivity. This Review discusses the use of colorimetric sensors in the food industry, including their applications for detecting food contaminants. The Review also provides insight into the scope of future research in this area. Analyte ; Colorimetry ; Computer science ; Scope (computer science) ; Reflection (computer programming) ; Nanotechnology ; Biochemical engineering ; Process engineering ; Materials science ; Engineering ; Chemistry Advanced Nanomaterials in Catalysis ; Advanced biosensing and bioanalysis techniques ; Biosensors and Analytical Detection
Authors: Stephanie Rankin‐Turner | Patrick Sears | Liam M. Heaney
Source: Analytical Science Advances (review, 2023-04-26)
Field: Chemistry — Spectroscopy

Applications of ambient ionization mass spectrometry in 2022: An annual review The development of ambient ionization mass spectrometry (AIMS) has transformed analytical science, providing the means of performing rapid analysis of samples in their native state, both in and out of the laboratory. The capacity to eliminate sample preparation and pre-MS separation techniques, leading to true real-time analysis, has led to AIMS naturally gaining a broad interest across the scientific community. Since the introduction of the first AIMS techniques in the mid-2000s, the field has exploded with dozens of novel ion sources, an array of intriguing applications, and an evident growing interest across diverse areas of study. As the field continues to surge forward each year, ambient ionization techniques are increasingly becoming commonplace in laboratories around the world. This annual review provides an overview of AIMS techniques and applications throughout 2022, with a specific focus on some of the major fields of research, including forensic science, disease diagnostics, pharmaceuticals and food sciences. New techniques and methods are introduced, demonstrating the unwavering drive of the analytical community to further advance this exciting field and push the boundaries of what analytical chemistry can achieve. Field (mathematics) ; Computer science ; Nanotechnology ; Environmental science ; Data science ; Engineering physics ; Engineering ; Materials science Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Jialu Zhang | Huinan Chen | Kaidi Xu | Dongmei Deng | Qixian Zhang | Liqiang Luo
Source: Biosensors (review, 2023-02-07)
Field: Materials Science — Materials Chemistry

Current Progress of Ratiometric Fluorescence Sensors Based on Carbon Dots in Foodborne Contaminant Detection Carbon dots (CDs) are widely used in the detection of foodborne contaminants because of their biocompatibility, photoluminescence stability, and ease of chemical modification. In order to solve the interference problem of complexity in food matrices, the development of ratiometric fluorescence sensors shows great prospects. In this review, the progress of ratiometric fluorescence sensors based on CDs in foodborne contaminant detection in recent years will be summarized, focusing on the functionalized modification of CDs, the fluorescence sensing mechanism, the types of ratiometric fluorescence sensors, and the application of portable devices. In addition, the outlook on the development of the field will be presented, with the development of smartphone applications and related software helping to better enable the on-site detection of foodborne contaminants to ensure food safety and human health. Nanotechnology ; Fluorescence ; Biocompatibility ; Human health ; Materials science ; Computer science ; Biochemical engineering ; Engineering Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Umuhoza Aline | Tanima Bhattacharya | Mohammad Akbar Faqeerzada | Moon S. Kim | Insuck Baek | Byoung–Kwan Cho
Source: Frontiers in Plant Science (review, 2023-08-16)
Field: Chemistry — Analytical Chemistry

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review The quality of tropical fruits and vegetables and the expanding global interest in eating healthy foods have resulted in the continual development of reliable, quick, and cost-effective quality assurance methods. The present review discusses the advancement of non-destructive spectral measurements for evaluating the quality of major tropical fruits and vegetables. Fourier transform infrared (FTIR), Near-infrared (NIR), Raman spectroscopy, and hyperspectral imaging (HSI) were used to monitor the external and internal parameters of papaya, pineapple, avocado, mango, and banana. The ability of HSI to detect both spectral and spatial dimensions proved its efficiency in measuring external qualities such as grading 516 bananas, and defects in 10 mangoes and 10 avocados with 98.45%, 97.95%, and 99.9%, respectively. All of the techniques effectively assessed internal characteristics such as total soluble solids (TSS), soluble solid content (SSC), and moisture content (MC), with the exception of NIR, which was found to have limited penetration depth for fruits and vegetables with thick rinds or skins, including avocado, pineapple, and banana. The appropriate selection of NIR optical geometry and wavelength range can help to improve the prediction accuracy of these crops. The advancement of spectral measurements combined with machine learning and deep learning technologies have increased the efficiency of estimating the six maturity stages of papaya fruit, from the unripe to the overripe stages, with F1 scores of up to 0.90 by feature concatenation of data developed by HSI and visible light. The presented findings in the technological advancements of non-destructive spectral measurements offer promising quality assurance for tropical fruits and vegetables. Hyperspectral imaging ; Near-infrared spectroscopy ; Environmental science ; Remote sensing ; Horticulture ; Mathematics ; Computer science ; Artificial intelligence ; Biology ; Optics ; Geography ; Physics Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Smart Agriculture and AI
Authors: Julius Seumer | Jonathan Kirschner Solberg Hansen | Mogens Brøndsted Nielsen | Jan H. Jensen
Source: Angewandte Chemie International Edition (article, 2023-02-14)
Field: Chemistry — Organic Chemistry

Computational Evolution Of New Catalysts For The Morita–Baylis–Hillman Reaction** We present a de novo discovery of an efficient catalyst of the Morita-Baylis-Hillman (MBH) reaction by searching chemical space for molecules that lower the estimated barrier of the rate-determining step using a genetic algorithm (GA) starting from randomly selected tertiary amines. We identify 435 candidates, virtually all of which contain an azetidine N as the catalytically active site, which is discovered by the GA. Two molecules are selected for further study based on their predicted synthetic accessibility and have predicted rate-determining barriers that are lower than that of a known catalyst. Azetidines have not been used as catalysts for the MBH reaction. One suggested azetidine is successfully synthesized and showed an eightfold increase in activity over a commonly used catalyst. We believe this is the first experimentally verified de novo discovery of an efficient catalyst using a generative model. Azetidine ; Catalysis ; Chemistry ; Chemical space ; Molecule ; Combinatorial chemistry ; Stereoisomerism ; Reaction rate ; Organic chemistry ; Drug discovery Synthesis and Catalytic Reactions ; Chemical Synthesis and Analysis ; Asymmetric Hydrogenation and Catalysis
Authors: Akun Liang | Robin Turnbull | Daniel Errandonea
Source: Progress in Materials Science (review, 2023-03-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A review on the advancements in the characterization of the high-pressure properties of iodates Lone pair ; Characterization (materials science) ; Raman spectroscopy ; Interpretation (philosophy) ; Nanotechnology ; Engineering physics ; Materials science ; Chemistry ; Computer science ; Physics ; Optics ; Molecule ; Organic chemistry Crystal Structures and Properties ; High-pressure geophysics and materials ; Crystallography and molecular interactions
Authors: Kévin Bernot
Source: European Journal of Inorganic Chemistry (article, 2023-07-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Get under the Umbrella: A Comprehensive Gateway for Researchers on Lanthanide‐Based Single‐Molecule Magnets Abstract The number of scientific articles that need to be considered to cover a research topic is ever‐increasing and quite difficult for a newcomer to assimilate. This is particularly true in dynamic discipline like Molecular Magnetism. In order to help young researchers in this field, this article proposes a “review of reviews” also known as an “umbrella review” on lanthanide‐based single‐molecule magnets ( 4 f ‐SMM). As a preamble, various bibliographic search techniques and AI‐based tools for bibliographic search, indexing, and summarization are proposed and commented. Then, the main milestones in 4 f ‐SMM are identified. In the core of the paper, books, book articles, and reviews dealing with 4 f ‐SMM are contextualized and classified by subtopics. This article is therefore proposed as a gateway to the 4 f ‐SMM field. Automatic summarization ; Gateway (web page) ; Lanthanide ; Field (mathematics) ; Chemistry ; Information retrieval ; Search engine indexing ; Web of science ; Citation ; World Wide Web ; Data science ; Library science ; Computer science ; MEDLINE Magnetism in coordination complexes ; Lanthanide and Transition Metal Complexes ; Porphyrin and Phthalocyanine Chemistry