jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Brenda Andrade | Ashley Chen | Michael K. Gilson
Source: ChemRxiv (preprint, 2023-11-07)
Field: Chemistry — Spectroscopy

Binding of Phenothiazine Drugs to Heptakis-Methylated β-Cyclodextrin Derivatives: Thermodynamics and Structure Model systems are widely used in biology and chemistry to gain insight into more complex systems. In the field of computational chemistry, researchers use host-guest systems, relatively simple exemplars of noncovalent binding, to train and test the computational methods used in drug discovery. Indeed, host-guest systems have been developed to support the community-wide blinded SAMPL prediction challenges for over a decade. While seeking new host-guest systems for the recent SAMPL9 binding prediction challenge, which is the focus of the present PCCP Themed Collection, we identified phenothiazine as a privileged scaffold for guests of β cyclodextrin (βCD) and its derivatives. Building on this observation, we used calorimetry and NMR spectroscopy to characterize the noncovalent association of native βCD and three methylated derivatives of βCD with five phenothiazine drugs. The strongest association observed, that of thioridazine and one of the methyl derivatives, exceeds the well-known high affinity of rimantidine with βCD. Intriguingly, however, methylation of βCD at the 3 position abolished detectible binding for all of the drugs studied. The dataset has a clear pattern of entropy-enthalpy compensation. The NMR data show that all of the drugs position at least one aromatic proton at the secondary face of the CD, and most also show evidence of deep penetration of the binding site. The results of this study were used in the SAMPL9 blinded binding affinity-prediction challenge, which are detailed in accompanying papers of the present Themed Collection. These data also open the phenothiazines and, potentially, chemically similar drugs, such as the tricyclic antidepressants, as relatively potent binders of βCD, setting the stage for future SAMPL challenge datasets and for possible applications as drug reversal agents. Chemistry ; Phenothiazine ; Non-covalent interactions ; Isothermal titration calorimetry ; Computational chemistry ; Stereochemistry ; Combinatorial chemistry ; Computational biology ; Hydrogen bond ; Molecule ; Pharmacology ; Biochemistry ; Organic chemistry ; Biology Analytical Chemistry and Chromatography ; Drug Solubulity and Delivery Systems ; Crystallization and Solubility Studies
Authors: Irina Piyanzina | Kirill V. Evseev | А. А. Kаmаshev | Р. Ф. Мамин
Source: Magnetism (article, 2023-07-31)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ab Initio Characterization of Magnetoelectric Coupling in Fe/BaTiO3, Fe/SrTiO3, Co/BaTiO3 and Co/SrTiO3 Heterostructures Magneto-electric coupling is a desirable property for a material used in modern electronic devices to possess due to the favorable possibilities of tuning the electronic properties using a magnetic field and vice versa. However, such materials are rare in nature. That is why the so-called superlattice approach to creating such materials is receiving so much attention. In the superlattice approach, the functionality of a combined heterostructure depends on the interacting components and can be adjusted depending on the desired property. In the present paper, we present supercells of ferromagnetic thin films of Fe and Co deposited on ferroelectric and piezoelectric substrates of BaTiO3 and SrTiO3 that exhibit magnetism, ferroelectric polarization and piezoelectric effects. Within the structures under investigation, magnetic moments can be tuned by an external electric field via the ferroelectric dipoles. We investigate the effect of magnetoelectric coupling by means of ab initio spin-polarized and spin–orbit calculations. We study the structural, electronic and magnetic properties of heterostructures, and show that electrostriction can reduce the magnitude of the magnetization vector of a ferromagnet. This approach can become the basis for controlling the properties of one of the ferromagnetic layers of a superconducting spin valve, and thus the superconducting properties of the valve. Condensed matter physics ; Materials science ; Ferroelectricity ; Ferromagnetism ; Superlattice ; Magnetism ; Magnetic moment ; Magnetization ; Heterojunction ; Ab initio ; Spintronics ; Magnetic field ; Dielectric ; Optoelectronics ; Physics Multiferroics and related materials ; Advanced Condensed Matter Physics ; Magnetic and transport properties of perovskites and related materials
Authors: Peng Wang | Yi Wu | Xuefeng Wang | Mengmeng Shi | Xingjing Chen | Ying Yuan
Source: Forests (article, 2023-06-01)
Field: Chemistry — Organic Chemistry

Multispectral Image Determination of Water Content in Aquilaria sinensis Based on Machine Learning The real-time nondestructive monitoring of plant water content can enable operators to understand the water demands of crops in a timely manner and provide a reliable basis for precise irrigation. In this study, a method for rapid estimation of water content in Aquilaria sinensis using multispectral imaging was proposed. First, image registration and segmentation were performed using the Fourier–Mellin transform (FFT) and the fuzzy local information c-means clustering algorithm (FLICM). Second, the spectral features (SFs), texture features (TFs), and comprehensive features (CFs) of the image were extracted. Third, using the eigenvectors of the SFs, TFs, and CFs as input, a random forest regression model for estimating the water content of A. sinensis was constructed, respectively. Finally, the monarch butterfly optimization (MBO), Harris hawks optimization (HHO), and sparrow search algorithm (SSA) were used to optimize all models to determine the best estimation model. The results showed that: (1) 60%–80% soil water content is the most suitable for A. sinensis growth. Compared with waterlogging, drought inhibited A. sinensis growth more significantly. (2) FMT + FLICM could achieve rapid segmentation of discrete A. sinensis multispectral images on the basis of guaranteed accuracy. (3) The prediction effect of TFs was basically the same as that of SFs, and the prediction effect of CFs was higher than that of SFs and TFs, but this difference would decrease with the optimization of the RFR model. (4) Among all models, SSA-RFR_CFs had the highest accuracy, with an R2 of 0.8282. These results confirmed the feasibility and accuracy of applying multispectral imaging technology to estimate the water content of A. sinensis and provide a reference for the protection and cultivation of endangered precious tree species. Multispectral image ; Artificial intelligence ; Computer science ; Pattern recognition (psychology) ; Cluster analysis ; Segmentation ; Mathematics Wood and Agarwood Research ; Remote Sensing in Agriculture ; Remote-Sensing Image Classification
Authors: Mikhail Finko | Batikan Köroğlu | Kate E. Rodriguez | Timothy P. Rose | Jonathan C. Crowhurst | Davide Curreli | Harry B. Radousky | Kim B. Knight
Source: Scientific Reports (article, 2023-06-07)
Field: Materials Science — Materials Chemistry

Stochastic optimization of a uranium oxide reaction mechanism using plasma flow reactor measurements In this work, a coupled Monte Carlo Genetic Algorithm (MCGA) approach is used to optimize a gas phase uranium oxide reaction mechanism based on plasma flow reactor (PFR) measurements. The PFR produces a steady Ar plasma containing U, O, H, and N species with high temperature regions (3000-5000 K) relevant to observing UO formation via optical emission spectroscopy. A global kinetic treatment is used to model the chemical evolution in the PFR and to produce synthetic emission signals for direct comparison with experiments. The parameter space of a uranium oxide reaction mechanism is then explored via Monte Carlo sampling using objective functions to quantify the model-experiment agreement. The Monte Carlo results are subsequently refined using a genetic algorithm to obtain an experimentally corroborated set of reaction pathways and rate coefficients. Out of 12 reaction channels targeted for optimization, four channels are found to be well constrained across all optimization runs while another three channels are constrained in select cases. The optimized channels highlight the importance of the OH radical in oxidizing uranium in the PFR. This study comprises a first step toward producing a comprehensive experimentally validated reaction mechanism for gas phase uranium molecular species formation. Uranium ; Mechanism (biology) ; Plasma ; Uranium oxide ; Oxide ; Flow (mathematics) ; Reaction mechanism ; Chemistry ; Chemical engineering ; Computer science ; Materials science ; Biochemistry ; Mechanics ; Physics ; Metallurgy ; Organic chemistry ; Nuclear physics ; Engineering Catalytic Processes in Materials Science ; Laser-induced spectroscopy and plasma ; Nuclear Materials and Properties
Authors: Tomislav Medić
Source: The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences (article, 2023-12-14)
Field: Chemistry — Analytical Chemistry

ESTIMATING DRY MATTER AND TOTAL SOLUBLE CONTENT IN APPLES USING A COMMERCIAL PORTABLE HYPERSPECTRAL IMAGING SYSTEM Abstract. The quest for rapid, non-destructive, and precise technologies for fruit quality estimation is motivated by the needs across the whole food production chain. One of the emerging technologies fulfilling these requirements is spectral imaging. However, despite documented successes, the technology is yet to become established in commercial applications. The best results reported in the literature rely on fixed, non-portable dedicated setups, and controlled light conditions, which limits the potential use cases along the food production chain. In our study, we investigate the possibility of estimating dry matter content (DMC) and total soluble content (TSC) of store-bought apples in non-regulated indoor conditions using a commercial, portable, hand-held imaging system featuring a hyperspectral camera. The acquired images are transformed into per-fruit representative spectral profiles, pre-processed, and analyzed using partial least squares (PLS), the established method in the chemometrics community. We achieved the R2 of 0.93 for TSC and 0.91 for DMC on the test dataset, with a mean absolute error of 0.71 °Brix for TSC and 0.7% for DMC, which is comparable to the state-of-the-art results presented in the literature. These results indicate that recent instrumental developments enable the deployment of spectral imaging systems in a wider range of tasks in food production, requiring portability and allowing for less stringent control of environmental conditions. Hyperspectral imaging ; Software portability ; Computer science ; Partial least squares regression ; Chemometrics ; Environmental science ; Process engineering ; Remote sensing ; Artificial intelligence ; Machine learning ; Geography ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: Fakhrony Sholahudin Rohman | Dinie Muhammad | Iylia Idris | Muhamad Nazri Murat | Khairul Azly Zahan | Ashraf Azmi‬‬‬‬‬
Source: Optimal Control Applications and Methods (article, 2023-11-17)
Field: Materials Science — Polymers and Plastics

Orthogonal collocation based‐optimization of fouling resistance for industrial low‐density polyethylene production in a tubular reactor Abstract In tubular reactors, fouling issues are caused due to two reasons. One is the heating–cooling prerequisite, and the other is the exothermic nature of the low‐density polyethylene (LDPE) polymerization process. These issues must be considered while optimizing LDPE production to provide maximum productivity and a safe operation. However, it is not a simple process because the conversion of the monomer ( X M ) is generally related to significant profits. This conversion might be performed at high reaction temperatures, resulting in fouling formation. Therefore, in this research, a study of dynamic optimization to find the most efficient production of LDPE in the presence of fouling resistance ( R f ) restrictions is conducted. An R f is employed as a measure of fouling. To establish the highest reactor R f , this study employs variations in the heat transfer coefficient ( U ) calculated from industry data. This dynamic optimization study addresses the optimization challenges using dynopt coded programming based on orthogonal collocation (OC) and sequential quadratic programming methodologies. Beforehand, the LDPE model is validated with industrial data. This study evaluates three possibilities to determine the most optimum reactor performance. The most optimum reactor output is determined from the constrained maximum conversion, which gave 32.15% conversion, while the was effectively met at 47.37cm 2 s K/cal. Low-density polyethylene ; Fouling ; Exothermic reaction ; Process engineering ; Sequential quadratic programming ; Materials science ; Production (economics) ; Process (computing) ; Collocation (remote sensing) ; Polyethylene ; Mathematics ; Mathematical optimization ; Computer science ; Quadratic programming ; Composite material ; Engineering ; Chemistry ; Organic chemistry Polymer crystallization and properties ; Rheology and Fluid Dynamics Studies ; Probabilistic and Robust Engineering Design
Authors: Y Zhang | Xiaosong LI | Hui Li | Liang Huang | Jiacheng Huang | Qian Tang
Source: Food Science and Technology (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Rapid and non-destructive determination of tea polyphenols content in Chongzhou new loquat tea lines based on near infrared spectroscopy Near infrared spectroscopy (NIRS) combined with multiple algorithms was used to determinate the tea polyphenols content in Chongzhou new loquat tea lines quickly and nondestructively. Samples of 26 Chongzhou new loquat tea lines were collected, then scanning NIRS, pretreating spectral noise information, screening characteristic spectral intervals by backward interval partial least squares, proceeding principal component analysis. Finally, the artificial neural network (BP-ANN) method with three kinds of transfer functions was applied to establish models. The best pretreated method was the combination of standard normal variation (SNV) and first derivative, and the characteristic spectral regions selected were 4381.5-4755.6 cm–1, 4759.5-5133.6 cm–1, 6266.6-6637.8 cm–1 and 7389.9-7760.2 cm–1, respectively. The cumulative contribution rate of the first three principal components of the selected characteristic spectra was 95.24%. When the BP-ANN calibration set model was established with the logistic function, NIRS model had the best results, whose root mean square error and determination coefficient of the cross validation were 0.975 and 0.372%, respectively. The root mean square error and the determination coefficient of the prediction set model were 0.962 and 0.400%, respectively. The results showed NIRS can predict the tea polyphenols content in Chongzhou new loquat tea lines quickly and accurately. Principal component analysis ; Polyphenol ; Near-infrared spectroscopy ; Calibration ; Partial least squares regression ; Mathematics ; Coefficient of determination ; Biological system ; Standard error ; Mean squared error ; Content (measure theory) ; Green tea ; Analytical Chemistry (journal) ; Chemistry ; Statistics ; Food science ; Chromatography ; Optics ; Physics ; Mathematical analysis ; Biology Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Meat and Animal Product Quality
Authors: G. L. van de Stolpe | Dominic Kwiatkowski | C. E. Bradley | J. Randall | Abobeih, M. H. | S. Alexander Breitweiser | Lee C. Bassett | Matthew Markham | D. J. Twitchen | T. H. Taminiau
Source: arXiv (Cornell University) (preprint, 2023-07-13)
Field: Materials Science — Materials Chemistry

Mapping a 50-spin-qubit network through correlated sensing Spins associated to optically accessible solid-state defects have emerged as a versatile platform for exploring quantum simulation, quantum sensing and quantum communication. Pioneering experiments have shown the sensing, imaging, and control of multiple nuclear spins surrounding a single electron-spin defect. However, the accessible size of these spin networks has been constrained by the spectral resolution of current methods. Here, we map a network of 50 coupled spins through high-resolution correlated sensing schemes, using a single nitrogen-vacancy center in diamond. We develop concatenated double-resonance sequences that identify spin-chains through the network. These chains reveal the characteristic spin frequencies and their interconnections with high spectral resolution, and can be fused together to map out the network. Our results provide new opportunities for quantum simulations by increasing the number of available spin qubits. Additionally, our methods might find applications in nano-scale imaging of complex spin systems external to the host crystal. Spins ; Qubit ; Spin (aerodynamics) ; Diamond ; Quantum network ; Spin engineering ; Physics ; Nitrogen-vacancy center ; Quantum sensor ; Quantum ; Vacancy defect ; Quantum computer ; Condensed matter physics ; Quantum mechanics ; Materials science ; Spin polarization ; Electron Diamond and Carbon-based Materials Research ; Electronic and Structural Properties of Oxides ; Ion-surface interactions and analysis
Authors: Lingfei Wei | Jinguo Lin | Cen Chen | Li Yu | Canhui Lu | Feng Liu
Source: Advanced Materials Interfaces (article, 2023-02-25)
Field: Materials Science — Materials Chemistry

Structural Spectrum of 2D Materials in Solution: Toward Establishing 2D Assemblies’ Digital Factory Abstract The numerous hierarchical architectures of 2D assemblies endow them with a new dimension to realize novel properties. From theoretical perspective, freedoms stem from in‐plane and out‐plane mechanical properties of 2D materials separately, which makes 2D materials embrace more than one “persistence length” giving rise to the diverse morphologies. However, the understanding of 3D architecture formation in 2D assemblies is still in its infancy. In fact, there is even no theoretical classification or reference to help clarify structural difference among numerous experimental obtained 2D assemblies. Based on the theoretical model composed by 2D sheets and Lennard‐Jones liquids, solution concentration dependence of 2D materials conformation is systematically studied, and a ln K behavior is uncovered that can realize the theoretical conformation prediction of 2D materials. More importantly, the digital production line (solution processing procedure) is set up toward establishing the 2D assemblies’ digital factory. The obtained structures may provide a reference to 2D assemblies, which benefits the understanding of the structural difference among different experiments and even help to guide the experimental design of 2D assemblies with targeted architectures and properties. Materials science ; Factory (object-oriented programming) ; Perspective (graphical) ; Dimension (graph theory) ; Nanotechnology ; Set (abstract data type) ; Computer science ; Artificial intelligence ; Mathematics Graphene research and applications ; Advanced Sensor and Energy Harvesting Materials ; Thermal properties of materials
Authors: Yanira Méndez | Aldrin V. Vasco | Galway Ivey | Ana Laura Dias | Peter Gierth | Bárbara B. Sousa | Claudio D. Navo | Ángel Torres-Mozas | Tiago Rodrigues | Gonzalo Jiménez‐Osés | Gonçalo J. L. Bernardes
Source: Angewandte Chemie (article, 2023-09-08)
Field: Chemistry — Organic Chemistry

Merging the Isonitrile‐Tetrazine (4+1) Cycloaddition and the Ugi Four‐Component Reaction into a Single Multicomponent Process Abstract Multicomponent reactions are of utmost importance at generating a unique, wide, and complex chemical space. Herein we describe a novel multicomponent approach based on the combination of the isonitrile‐tetrazine (4+1) cycloaddition and the Ugi four‐component reaction to generate pyrazole amide derivatives. The scope of the reaction as well as mechanistic insights governing the 4 H ‐pyrazol‐4‐imine tautomerization are provided. This multicomponent process provides access to a new chemical space of pyrazole amide derivatives and offers a tool for peptide modification and stapling. Cycloaddition ; Tetrazine ; Chemistry ; Tautomer ; Combinatorial chemistry ; Chemical space ; Amide ; Pyrazole ; Ugi reaction ; Component (thermodynamics) ; Imine ; Computational chemistry ; Drug discovery ; Organic chemistry ; Isocyanide ; Catalysis ; Thermodynamics Multicomponent Synthesis of Heterocycles ; Click Chemistry and Applications ; Synthesis and biological activity
Authors: Tomas Rosén | Hongrui He | Ruifu Wang | Korneliya Gordeyeva | Ahmad Reza Motezakker | Andrei Fluerasu | Daniel Söderberg | Benjamin S. Hsiao
Source: Physical review. E (article, 2023-07-27)
Field: Materials Science — Biomaterials

Exploring nanofibrous networks with x-ray photon correlation spectroscopy through a digital twin We demonstrate a framework of interpreting data from x-ray photon correlation spectroscopy experiments with the aid of numerical simulations to describe nanoscale dynamics in soft matter. This is exemplified with the transport of passive tracer gold nanoparticles in networks of charge-stabilized cellulose nanofibers. The main structure of dynamic modes in reciprocal space could be replicated with a simulated system of confined Brownian motion, a digital twin, allowing for a direct measurement of important effective material properties describing the local environment of the tracers. Photon ; Spectroscopy ; Nanoscopic scale ; Chemical physics ; Brownian motion ; Reciprocal lattice ; Digital image correlation ; Materials science ; Physics ; Molecular physics ; Statistical physics ; Nanotechnology ; Optics ; Computational physics ; Quantum mechanics ; Diffraction Advanced Cellulose Research Studies ; Material Dynamics and Properties ; Theoretical and Computational Physics
Authors: Fernando Henrique Gruber Colaço | Almir Turazi | Joel Stryhalski | Gil Magno Portal Chagas | Alexandre Galiotto | Giuseppe Pintaúde
Source: Materials Performance and Characterization (article, 2023-09-13)
Field: Materials Science — Materials Chemistry

Wear Resistance of Fe–Cr–C Hardfacing Deposited by Flux-Core-Double-Wire GTAW in Rubber Wheel Abrasion Test ABSTRACT The wear resistance of metals can be improved by using the hardfacing technique. Different processes can produce it with the desirable microstructures and mechanical properties. This study presents an original method, flux-core-double-wire of gas-shielded tungsten arc welding, in which wires of different compositions are used simultaneously to obtain different microstructures. The deposition was controlled through the following parameters: welding speed, deposition current, standoff distance, torch angle, and pulse frequency of wire feed. Four coatings were deposited on AISI 1020 steel substrate by combining the cored wires: Fe–Cr–C, Fe–Cr–C–Nb, Fe–Cr–C–Mo–Nb, and Fe–Cr–C–Mo–Ti. The combination of these wires resulted in a hypoeutectic microstructure with niobium and titanium carbides, with an average hardness of 650 HV0.3. The hypereutectic microstructures were formed by different niobium contents, with a microhardness range from 820 to 1,020 HV0.3. The performance of the hardfacing was evaluated in the rubber wheel abrasion test described by ASTM G65, Standard Test Method for Measuring Abrasion Using the Dry Sand/Rubber Wheel Apparatus (Superseded), procedure B. The results revealed that the carbide cracking distinguished the wear resistance, and the hardness was not enough to separate the wear behavior. Still, the volume fraction of carbides was a decisive microstructural parameter. Hardfacing ; Materials science ; Microstructure ; Metallurgy ; Indentation hardness ; Abrasion (mechanical) ; Gas tungsten arc welding ; Niobium ; Composite material ; Carbide ; Abrasive ; Welding ; Arc welding Metal Alloys Wear and Properties ; Advanced materials and composites ; High Entropy Alloys Studies