jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nicholas M. Pearce | R. Skyner | T. Krojer
Source: Frontiers in Molecular Biosciences (article, 2022-04-11)
Field: Materials Science — Materials Chemistry

Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies The throughput of macromolecular X-ray crystallography experiments has surged over the last decade. This remarkable gain in efficiency has been facilitated by increases in the availability of high-intensity X-ray beams, (ultra)fast detectors and high degrees of automation. These developments have in turn spurred the development of several dedicated centers for crystal-based fragment screening which enable the preparation and collection of hundreds of single-crystal diffraction datasets per day. Crystal structures of target proteins in complex with small-molecule ligands are of immense importance for structure-based drug design (SBDD) and their rapid turnover is a prerequisite for accelerated development cycles. While the experimental part of the process is well defined and has by now been established at several synchrotron sites, it is noticeable that software and algorithmic aspects have received far less attention, as well as the implications of new methodologies on established paradigms for structure determination, analysis, and visualization. We will review three key areas of development of large-scale protein-ligand studies. First, we will look into new software developments for batch data processing, followed by a discussion of the methodological changes in the analysis, modeling, refinement and deposition of structures for SBDD, and the changes in mindset that these new methods require, both on the side of depositors and users of macromolecular models. Finally, we will highlight key new developments for the presentation and analysis of the collections of structures that these experiments produce, and provide an outlook for future developments. Computer science ; Software ; Automation ; Nanotechnology ; Materials science ; Engineering Enzyme Structure and Function ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Şükran Katmer | Çetin Karataş
Source: Materiale Plastice (article, 2022-01-04)
Field: Materials Science — Polymers and Plastics

Shrinkage and Warpage in the Permanent Shape of Sape-Memory Polyurethane Parts The shape memory effect, as the most important ability of shape memory polymers, is a working property and provides the design ability to shape memory polymer features. Shrinkage and warpage are important parameters to control the dimensional accuracy of permanent and temporary shapes of an injection moulded shape memory polyurethane (SMPU) part. In this study, the effects of injection moulding parameters on the shrinkage and warpage of the permanent shape of moulded SMPU parts were experimentally investigated. The parameters of injection pressure, melt temperature, mould temperature, packing pressure, packing time, and cooling time, were chosen as the injection moulding control factors. Taguchi�s L27 orthogonal array design table was used with six injection moulding parameters and their three levels. The results showed that the part has different shrinkage ratios in three main directions, namely, the flow direction, perpendicular to the flow direction, and the direction through the thickness. The results of the analysis of variance showed that the cooling time is the most influential parameter on both the shrinkage (except in thickness) and warpage. The shrinkage in the flow direction as well as in perpendicular to the flow direction decreased with increasing the cooling time. Warpage also decreased with increasing the cooling time. Injection pressure and melt temperature were found to be effective on shrinkage in thickness. Effects of mould temperature, packing pressure, and packing time were found to be limited. A statistically significant relationship has been noticed among shrinkage, warpage, and residual stresses during the study. Shrinkage ; Materials science ; Composite material ; Perpendicular ; Injection moulding ; Polyurethane ; Taguchi methods ; Shape-memory polymer ; Flow (mathematics) ; Shape-memory alloy ; Geometry ; Mathematics Polymer composites and self-healing
Authors: Martin Amezcua | Jeffry Setiadi | Ge Yunhui | David L. Mobley
Source: ChemRxiv (preprint, 2022-04-11)
Field: Chemistry — Spectroscopy

An Overview of the SAMPL8 Host-Guest BindingChallenge The SAMPL series of challenges aim to focus the community on specific modeling challenges, while testing and hopefully driving progress of computational methods to help guide pharmaceutical drug discovery. In this study, we report on the results of the SAMPL8 host-guest blind challenge for predicting absolute binding affinities. SAMPL8 focused on two host-guest datasets, one involving the cucurbituril CB8 (with a series of common drugs of abuse) and another involving two different Gibb deep-cavity cavitands. The latter dataset involved a previously featured deep cavity cavitand (TEMOA) as well as a new variant (TEETOA), both binding to a series of relatively rigid fragment-like guests. Challenge participants employed a reasonably wide variety of methods, though many of these were based on molecular simulations, and predictive accuracy was mixed. As in some previous SAMPL iterations (SAMPL6 and SAMPL7), we found that one approach to achieve greater accuracy was to apply empirical corrections to the binding free energy predictions, taking advantage of prior data on binding to these hosts. Another approach which performed well was a hybrid MD-based approach with reweighting to a force matched QM potential. In the cavitand challenge, an alchemical method using the AMOEBA-polarizable force field achieved the best success with RMSE less than 1 kcal/mol, while another alchemical approach (ATM/GAFF2-AM1BCC/TIP3P/HREM) had RMSE less than 1.75 kcal/mol. The work discussed here also highlights several important lessons; for example, retrospective studies of reference calculations demonstrate the sensitivity of predicted binding free energies to ethyl group sampling and/or guest starting pose, providing guidance to help improve future studies on these systems. Cavitand ; Binding affinities ; Computational chemistry ; Chemistry ; Force field (fiction) ; Computer science ; Binding potential ; Cucurbituril ; Machine learning ; Artificial intelligence ; Molecule ; Supramolecular chemistry Mass Spectrometry Techniques and Applications ; Crystallography and molecular interactions ; Chemical Synthesis and Analysis
Authors: Çağrı Köksal | Emrah Dokur | Aysel Ersoy
Source: Mathematical Problems in Engineering (article, 2022-05-17)
Field: Materials Science — Materials Chemistry

Stress Cone Effect Analysis and Optimum Design of Extra High-Voltage Cable Joint Using Neural Networks The major problem in high-voltage cable accessories is the electric field stress caused by the high-voltage level at the cable junction. In this paper, a neural network and simulation-based optimal design for extra high-voltage (EHV) cable accessory is proposed to ensure the optimum electrical design. The different kinds of geometries of the EHV underground cable accessory are realized in the Comsol Multiphysics software program, and the electric field analyses are conducted based on the finite element method. The design of high-voltage underground cable accessories is examined both within and without the optimal stress cone geometry. A neural network-based model is developed according to the analysis results obtained in the simulation. Thanks to this model, the geometry of the stress cone is determined. In the simulation-based analysis, the electric field stress caused by the high-voltage level at critical points is controlled with an optimum joint design using neural networks. The proposed model will contribute to EHV cable joint design at different stress levels. Multiphysics ; Finite element method ; High voltage ; Stress (linguistics) ; Voltage ; Joint (building) ; Structural engineering ; Artificial neural network ; Engineering ; Electric field ; Optimal design ; High-voltage cable ; Electrical engineering ; Computer science ; Physics High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Thermal Analysis in Power Transmission
Authors: Mao‐Mao Zhang | Juan Guo | Yang Lu | Lichao Jiao | Tuo He | Yafang Yin
Source: Journal of Wood Science (article, 2022-06-21)
Field: Chemistry — Organic Chemistry

Similarity network fusion for aggregating headspace GC–MS and direct analysis in real time–mass spectrometry data from solid samples to enhance species identification efficiency of high–temperature heated wood Abstract Pterocarpus santalinus and Pterocarpus tinctorius are commonly used species of the genus Pterocarpus in the wood trade. Although both of them have been listed in Appendix II of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) since 2019, it is still critical to identify them in terms of plant taxonomy. Currently, high-temperature heating is an accepted treatment method for high-density wood species such as Pterocarpus to improve dimensional stability and restore previous drying defects partially. It has proved challenging to identify the high-temperature (e.g., 120 °C) heated wood from these two species. Thus, this study approaches species identification of two Pterocarpus of high-temperature (e.g., 120 °C) heated solid wood samples using headspace–gas chromatography–mass spectrometry (HS–GC–MS). Besides, a computational analytical method named similarity network fusion (SNF) was proposed to aggregate data in two different types, respectively, derived from the HS–GC–MS and direct analysis in real time–mass spectrometry (DART–MS) to explore the feasibility of improving the efficiency and accuracy of wood species discrimination. The SNF exhibits more significant differences and higher predictive accuracy (100%) between P. santalinus and P. tinctorius than that based on the HS–GC–MS data (77.78%) or DART–MS (66.67%) alone. These results demonstrated the capability of the HS–GC–MS technique in the analysis of high-temperature heated solid wood and the potential of multidimensional or comprehensive data sets based on the SNF algorithm in the field of wood species identification. Hardwood ; Mass spectrometry ; Gas chromatography–mass spectrometry ; Solid wood ; Species identification ; Biology ; Botany ; Chemistry ; Chromatography Wood and Agarwood Research ; Cultural Heritage Materials Analysis ; Plant Pathogens and Fungal Diseases
Authors: Wangfang Li | Wei Huang | Desheng Fan | Xuhui Gao | Xian Zhang | Yaoyong Meng | Timon Cheng-yi Cheng
Source: Research Square (preprint, 2022-07-18)
Field: Chemistry — Analytical Chemistry

Rapid quantification of goat milk adulteration with cow milk using Raman spectroscopy and chemometrics <title>Abstract</title> As goat milk has a higher economic value compared to cow milk, the phenomenon of adulterating goat milk with cow milk appears in the market. In this article, the potential of Raman spectroscopy along with chemometrics was investigated for authentication and quantitation liquid goat milk adulterated with cow milk. First, the Raman spectra of goat milk and cow milk were examined by principal component analysis (PCA), the results showed that there were differences between the Raman spectra of cow and goat milk, which made quantitative experiments possible. For quantification, three different brands of cow milk and goat milk were selected randomly and adulterated goat milk with cow milk at the proportion of 5%-95%. 342 samples were used for the construction of the partial least square regression (PLSR) model, with 80% for the training set and 20% for the test set. The PLSR model showed the excellent performance for quantifying the level of adulteration, for the prediction set, with a coefficient of determination (R<sup>2</sup>) of 0.9781, root mean square error (RMSE) of 3.82%, ratio of prediction to deviation (RPD) of 6.8. The results demonstrated the potential of Raman spectroscopy as a rapid, low cost and nondestructive analytical tool for adulteration detection in goat milk. Chemometrics ; Cow milk ; Raman spectroscopy ; Partial least squares regression ; Food science ; Principal component analysis ; Coefficient of determination ; Mathematics ; Chemistry ; Animal science ; Chromatography ; Biology ; Statistics ; Physics Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Chunli Fu | Jiemei Chen | Lifang Fang | Tao Pan
Source: American Journal of Analytical Chemistry (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Identification of Soy Sauce Adulteration The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C5H10NNaO5) and caramel color (C6H8O3). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively; in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RARV) was 99.6%; while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RARV = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions. Linear discriminant analysis ; Near-infrared spectroscopy ; Partial least squares regression ; Chromatography ; Chemistry ; Mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Naciye ÜNVER | Şerafettin Çelik
Source: Hacettepe Journal of Biology and Chemistry (article, 2022-02-10)
Field: Chemistry — Organic Chemistry

OPTIMIZATION OF ULTRASOUND-ASSISTED EXTRACTION OF OLIVE LEAF (var. HALHALI) EXTRACTS In this study, the effects of three different independent variables (extraction temperature, extraction time, ultrasonic power) on the total phenolic content, extraction yield and antioxidant capacity (IC50) value of olive leaf extracts of Halhalı variety which is originated from South-eastern Anatolia Region were investigated. As a result of the evaluation made with Box-Behnken Design Model, the optimum conditions were determined as 62.94°C, 50.67 min, and 64.65% ultrasonic power for the optimization of ultrasonic-assisted extraction. In order to visualize the effect of extraction method on TPC, extraction yield and IC50 value of olive leaf extracts, results of three extraction methods were compared. The differences among the mean values of the investigated parameters in terms of extraction method were found significantly different (P&amp;lt;0.05). In addition, it can be inferenced that ultrasound assisted extraction accelerated the transition of phenolic substances to solvent in terms of SEM images and investigated other parameters. Extraction (chemistry) ; Yield (engineering) ; Chromatography ; Ultrasonic sensor ; Solvent ; Olive leaf ; Box–Behnken design ; Response surface methodology ; Chemistry ; Botany ; Materials science ; Food science ; Biology ; Biochemistry ; Medicine Edible Oils Quality and Analysis ; Essential Oils and Antimicrobial Activity ; Phytochemicals and Antioxidant Activities
Authors: Bin Yang | Zhanran Xia | Xinyun Gao | Jing Tu | Hao Zhou | Jun Wu | Mingzhen Li
Source: Energies (article, 2022-11-11)
Field: Materials Science — Materials Chemistry

Research on the Application of Uncertainty Quantification (UQ) Method in High-Voltage (HV) Cable Fault Location In HV cable fault location technology, line parameter uncertainty has an impact on the location criterion and affects the fault location result. Therefore, it is of great significance to study the uncertainty quantification of line parameters. In this paper, an impedance-based fault location criterion was used for an uncertainty study. Three kinds of uncertainty factors, namely the sheath resistivity per unit length, the equivalent grounding resistance on both sides, and the length of the cable section, were taken as random input variables without interaction. They were subject to random uniform distribution within a 50% amplitude variation. The relevant statistical information, such as the mean value, standard deviation and probability distribution, of the normal operation and fault state were calculated using the Monte Carlo simulation (MCS) method, the polynomial chaos expansion (PCE) method, and the univariate dimension reduction method (UDRM), respectively. Thus, the influence of uncertain factors on fault location was analyzed, and the calculation results of the three uncertainty quantification methods compared. The results indicate that: (1) UQ methods are effective for simulation analysis of fault locations, and UDRM has certain application prospects for HV fault location in practice; (2) the quantification results of the MCS, PCE, and UDRM were very close, while the mean convergence rate was significantly higher for the UDRM; (3) compared with the MCS, PCE, and UDRM, the PCE and UDRM had higher accuracy, and MCS and UDRM required less running time. Monte Carlo method ; Polynomial chaos ; Fault (geology) ; Standard deviation ; Random variable ; Voltage ; Univariate ; Convergence (economics) ; Probability distribution ; Uncertainty quantification ; Algorithm ; Mathematics ; Statistics ; Computer science ; Engineering ; Electrical engineering ; Geology High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Power Systems Fault Detection
Authors: Daniel Hickox-Young | Geneva Laurita | Quintin N. Meier | Daniel Olds | Nicola A. Spaldin | M. R. Norman | James M. Rondinelli
Source: Physical Review Research (article, 2022-09-06)
Field: Materials Science — Materials Chemistry

Local structure and its implications for the relaxor ferroelectric <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:msub><mml:mi>Cd</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi>Nb</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>7</mml:mn></mml:msub></mml:mrow></mml:math> The relaxor ferroelectric transition in ${\mathrm{Cd}}_{2}{\mathrm{Nb}}_{2}{\mathrm{O}}_{7}$ is thought to be described by the unusual condensation of two $\mathrm{\ensuremath{\Gamma}}$-centered phonon modes, ${\mathrm{\ensuremath{\Gamma}}}_{4}^{\ensuremath{-}}$ and ${\mathrm{\ensuremath{\Gamma}}}_{5}^{\ensuremath{-}}$. However, their respective roles have proven to be ambiguous, with disagreement between ab initio studies, which favor ${\mathrm{\ensuremath{\Gamma}}}_{4}^{\ensuremath{-}}$ as the primary mode, and global crystal refinements, which point to ${\mathrm{\ensuremath{\Gamma}}}_{5}^{\ensuremath{-}}$ instead. Here, we resolve this issue by demonstrating from x-ray pair distribution function measurements that locally, ${\mathrm{\ensuremath{\Gamma}}}_{4}^{\ensuremath{-}}$ dominates, but globally, ${\mathrm{\ensuremath{\Gamma}}}_{5}^{\ensuremath{-}}$ dominates. This behavior is consistent with the near degeneracy of the energy surfaces associated with these two distortion modes found in our own ab initio simulations. Our first-principles calculations also show that these energy surfaces are almost isotropic, providing an explanation for the numerous structural transitions found in ${\mathrm{Cd}}_{2}{\mathrm{Nb}}_{2}{\mathrm{O}}_{7}$, as well as its relaxor behavior. Our results point to several candidate descriptions of the local structure, some of which demonstrate two-in/two-out behavior for Nb displacements within a given Nb tetrahedron. Although this suggests the possibility of a charge analog of spin ice in ${\mathrm{Cd}}_{2}{\mathrm{Nb}}_{2}{\mathrm{O}}_{7}$, our results are more consistent with a Heisenberg-like description for dipolar fluctuations rather than an Ising one. We hope this encourages future experimental investigations of the Nb and Cd dipolar fluctuations, along with their associated mode dynamics. Physics ; Energy (signal processing) ; Ab initio ; Condensed matter physics ; Ising model ; Ferroelectricity ; Crystallography ; Quantum mechanics ; Dielectric ; Chemistry Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Microwave Dielectric Ceramics Synthesis
Authors: Paolo Crippa | Giorgio Biagetti | Lorenzo Minelli | Claudio Turchetti | Martino Aldrigo | Mircea Dragoman | Davide Mencarelli | Luca Pierantoni
Source: Electronics (article, 2022-11-12)
Field: Materials Science — Materials Chemistry

Next-Generation Hybrid RF Front-End with MoS2-FET Supply Management Circuit, CNT-FET Amplifiers, and Graphene Thin-Film Antennas One-dimensional (1D) and two-dimensional (2D) materials represent the emerging technologies for transistor electronics in view of their attractive electrical (high power gain, high cut-off frequency, low power dissipation) and mechanical properties. This work investigates the integration of carbon-nanotube-based field-effect transistors (CNT-FETs) and molybdenum disulphide (MoS2)-based FETs with standard CMOS technology for designing a simple analog system integrating a power switching circuit for the supply management of a 10 GHz transmitting/receiving (T/R) module that embeds a low-noise amplifier (LNA) and a high-power amplifier (HPA), both of which loaded by nanocrystalline graphene (NCG)-based patch antennas. Verilog-A models, tuned to the technology that will be used to manufacture the FETs, were implemented to perform electrical simulations of the MoS2 and CNT devices using a commercial integrated circuit software simulator. The obtained simulation results prove the potential of hybrid CNT-MoS2-FET circuits as building blocks for next-generation integrated circuits for radio frequency (RF) applications, such as radars or IoT systems. Transistor ; Amplifier ; Electrical engineering ; CMOS ; Radio frequency ; Materials science ; Electronic circuit ; Transistor model ; Electronic engineering ; Low-noise amplifier ; Integrated circuit ; Electronic circuit simulation ; Engineering Graphene research and applications ; 2D Materials and Applications ; Advancements in Semiconductor Devices and Circuit Design