jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anwardi Jamil | Amirul Ridzuan Abu Bakar | Nurul Husna Khairuddin
Source: Journal of Advanced Research in Applied Sciences and Engineering Technology (article, 2023-03-08)
Field: Materials Science — Biomaterials

Structural Elucidation of the Masp1 and Masp2 Protein from Nephila Pilipes Web Via Bioinformatics Approaches Major ampullate spidroin (MaSps) from orb-weaver spp spider has recently gained interest due to its exceptional characteristics. The biomechanical and biochemical properties from MaSps offer potential in harvesting and exploiting MaSps as a promising bio-based product. However, the current research on the structural elucidation focused more onto the Nephila clavipes spider web rather than the Nephila pilipes which are more common in this region. Herein, this study integrates the used of computational power and algorithm to elucidate the 3D protein morphology of MaSp1 and MaSp2 of Nephila pilipes dragline silk protein using nearly complete amino acid sequences obtained from the protein database. In silico homology modelling via Phyre2, SWISS-MODEL and RaptorX was adopted to predict the protein structure of MaSP-1 and 2 using proteins threading, automated comparative modelling of three-dimensional (3D) protein structures and deep learning approaches. Consequently, we described a thorough 3D protein models of MaSp1 and MaSp2 with a higher percentage of coils, α-helix and a low percentage of β-sheet on repetitive regions of MaSp1 and MaSp2. The results of this current work provide insights into Bioinformatics potentials in engineering spider silk-based biomaterial and bridging the most apparent gaps in the knowledge of MaSp1 and MaSp2. In silico ; MASP1 ; Structural bioinformatics ; Computational biology ; Biology ; Bioinformatics ; Protein structure ; Biochemistry ; Serine protease Silk-based biomaterials and applications ; Biochemical and Structural Characterization ; Neurobiology and Insect Physiology Research
Authors: Na Xu | Xinmiao Yao | Shuwen Lu
Source: Emirates Journal of Food and Agriculture (article, 2023-05-24)
Field: Chemistry — Organic Chemistry

The manufacturing of puffed corn flakes: Optimization, characterization and sensory attributes Corn snacks are growing worldwide in food market. Puffing is an alternative processing technology to improve the characteristics of food products with the benefit of low oil. However, the puffing process of corn flakes is rarely studied in recent research. Thus, the objective of this study is to optimize the conditions of puffing with the raw material of corn grit and compare with extrusion, frying and baking process in the aspect of microstructure and sensory evaluation of corn flakes. The results showed that the optimized conditions of puffing flakes were 6 min of pretreated time, 226 °C of puffing temperature, 9 s of puffing time. And the experimental responses of crispy, hardness and browning index at the optimized conditions are 0.73±0.05 nm, 1317.52±23.14 g, 56.91±0.87, respectively. To compared with other traditional process that manufacture the corn flakes, the microstructure and sensory evaluation are applied. The microstructure of puffing method presented porous and spongy structure with numerous cavities in small sizes. For the sensory evaluation, the score of taste, texture, color and overall acceptability applied for puffing is the highest. In conclusion, the puffing would be a novel technology to manufacture tasty corn flakes in the snack food industry. Keywords: Corn flakes; Optimization; Puffing; Response surface methodology; Sensory attributes Food science ; Microstructure ; Raw material ; Response surface methodology ; Extrusion ; Materials science ; Texture (cosmology) ; Browning ; Taste ; Mathematics ; Chemistry ; Composite material ; Computer science Edible Oils Quality and Analysis ; Food composition and properties ; Food Chemistry and Fat Analysis
Authors: An Staes | Teresa Mendes Maia | Sara Dufour | Robbin Bouwmeester | Ralf Gabriels | Lennart Martens | Francis Impens | Simon Devos
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-06-06)
Field: Chemistry — Spectroscopy

Benchmarking DIA data analysis workflows Abstract Data independent acquisition (DIA) has become a well-established method in LC-MS driven proteomics. Nonetheless, there are still a lot of possibilities at the data analysis level. By benchmarking different DIA analysis workflows using a ground-truth sample, consisting of a differential spike-in of UPS2 in a constant yeast background, we provide a roadmap for DIA data analysis of shotgun samples based on whether sensitivity, precision or accuracy is of the essence. Three different commonly used DIA software tools (DIA-NN, EncyclopeDIA and Spectronaut TM ) were tested in both spectral library mode and spectral library-free mode. In spectral library mode we used the independent spectral library prediction tools PROSIT and MS2PIP together with DeepLC, next to the classical DDA-based spectral libraries. In total we benchmarked 12 DIA workflows. DIA-NN in library-free mode or using in silico predicted libraries, together with Spectronaut in library-free mode, shows the highest sensitivity maintaining a high reproducibility and accuracy. In general, DIA-NN shows the best reproducibility, while the accuracy is comparable for all DIA workflows. Benchmarking ; Reproducibility ; Workflow ; Computer science ; Ground truth ; Sensitivity (control systems) ; Software ; Data mining ; Mode (computer interface) ; Pattern recognition (psychology) ; Artificial intelligence ; Chemistry ; Database ; Engineering ; Human–computer interaction ; Chromatography ; Operating system Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Leonie Beek | Wilhelm Barthlott | Matthias Mail | Kai Klopp | Thomas Gries
Source: Separations (article, 2023-12-04)
Field: Materials Science — Surfaces, Coatings and Films

Self-Driven Sustainable Oil Separation from Water Surfaces by Biomimetic Adsorbing and Transporting Materials Oil films on water are an increasingly major contamination problem worldwide. In 2020, we published a novel adsorption and transportation technology for oil–water separation based on biological role models like the floating fern Salvinia. This application provides an unexpected ability for the fast and efficient removal of oil films, particularly in ecologically important freshwater biota. A single small Bionic Oil Adsorber (BOA) with 1 m2 functional textile can collect up to 4 L of oil per hour, which equals about 100 m2 of oil film from a water surface into a collecting vessel. This is a safe, fast, and sustainable solution for the ubiquitous contaminations of, e.g., fuel oil in freshwater environments. Here, we present updated, new experimental data, and a review of the literature published since. Environmental science ; Oil spill ; Adsorption ; Biota ; Waste management ; Environmental engineering ; Chemistry ; Ecology ; Engineering ; Biology Surface Modification and Superhydrophobicity ; Electrohydrodynamics and Fluid Dynamics ; Diatoms and Algae Research
Authors: Gourab Basu | Kshanaprava Dhalsamant | Punyadarshini Punam Tripathy | Sonu Sharma
Source: Computing and artificial intelligence. (article, 2023-12-30)
Field: Chemistry — Analytical Chemistry

Application of machine vision in drying process modeling of carrot slices In this current research, the drying characteristics of carrot slices dried in a convective hot-air dryer are analyzed employing image analysis to determine the most significant factor. From the acquired images, nine parameters viz. redness (R), greenness (G), blueness (B), lightness (L), redness (a), yellowness (b), energy, entropy, and upper surface area of carrot slices were calculated using the algorithm developed in MATLAB 2015a. Boruta feature selection algorithm in the R console showed lightness, redness, and energy were the most significant features among calculated parameters. Additionally, single-layer feed-forward artificial neural network (ANN) architecture with three inputs (hot air temperature, thickness of slices, drying time), and outputs namely lightness, redness, and energy with one hidden layer was used to model input variables to that of responses. Multiple regression models are employed to optimize the drying condition by further assessing the behavior of response variables with hot air temperature and thickness of slices as inputs and lightness, redness, and energy as outputs. The lightness and redness of samples are found to be decreasing with an increase in temperature and a decrease in thickness. Whereas, the effect of these input parameters on energy, the measure of homogeneity of the product surface, is found to be reversed to that of the effect on lightness and redness. Lightness and redness are set to be highest, whereas energy was kept to be lowest. Convective hot air temperature of 60 ℃ and 7 mm thickness sample was found to provide the best quality product within the experiment range. Process (computing) ; Computer science ; Artificial intelligence ; Computer vision ; Process engineering ; Machine vision ; Biological system ; Engineering ; Biology ; Programming language Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Remote-Sensing Image Classification
Authors: Rui Xu | Jan Meisner | Alexander M. Chang | Keiran C. Thompson | Todd J. Martı́nez
Source: ChemRxiv (preprint, 2023-03-02)
Field: Materials Science — Materials Chemistry

First Principles Reaction Discovery: From the Schrodinger Equation to Experimental Prediction for Methane Pyrolysis Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling. Nanoreactor ; Ab initio ; Transition state theory ; Elementary reaction ; Chemistry ; Kinetic Monte Carlo ; Computational chemistry ; Reaction rate ; Methane ; Kinetic energy ; Pyrolysis ; Statistical physics ; Monte Carlo method ; Reaction rate constant ; Physics ; Kinetics ; Organic chemistry ; Mathematics ; Catalysis ; Quantum mechanics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Electrocatalysts for Energy Conversion
Authors: Demet Demirci Gültekin | Arif Daştan | Yavuz Taşkesenligil | Cavit Kazaz | Yunus Zorlu | Metin Balcı
Source: Beilstein Journal of Organic Chemistry (article, 2023-06-02)
Field: Chemistry — Spectroscopy

Bromination of <i>endo-</i>7-norbornene derivatives revisited: failure of a computational NMR method in elucidating the configuration of an organic structure Previously we reported on the bromination of <i>endo-</i>7-bromonorbornene at different temperatures yielding mixtures of addition products. The structural elucidations of the formed compounds were achieved by NMR spectroscopy. Particularly, the γ-gauche effect and long-range couplings were instrumental in assigning the stereochemistry of the adducts. However, in a recent paper, Novitskiy and Kutateladze claimed that based on an applied machine learning-augmented DFT method for computational NMR that the structure of the product, (1<i>R</i>,2<i>R</i>,3<i>S</i>,4<i>S</i>,7<i>s</i>)-2,3,7-tribromobicyclo[2.2.1]heptane was wrong. With the aid of their computational method, they revised a number of published structures, including ours, and assigned our product the structure (1<i>R</i>,2<i>S</i>,3<i>R</i>,<i>4S</i>,7<i>r</i>)-2,3,7-tribromobicyclo[2.2.1]heptane. To fit their revised structure, they proposed an alternative mechanism featuring a skeletal rearrangement without the intermediacy of a carbocation. Herein, we are not only confirming the structure originally assigned by us through crucial NMR experiments, we also present the ultimate structural proof by means of X-ray crystallography. Moreover, we disprove the mechanism proposed by the aforementioned authors based on sound mechanistic reasoning and point to an oversight by the authors that led them to an erroneous mechanistic pathway. Chemistry ; Halogenation ; Carbocation ; Nuclear magnetic resonance spectroscopy ; Norbornene ; Computational chemistry ; Heptane ; Stereochemistry ; Organic chemistry ; Monomer Molecular spectroscopy and chirality ; Microbial Natural Products and Biosynthesis ; Asymmetric Synthesis and Catalysis
Authors: Jeppe C. Dyre
Source: PubMed (preprint, 2023-11-24)
Field: Materials Science — Materials Chemistry

Solid-that-flows picture of glass-forming liquids This perspective article reviews arguments that glass-forming liquids are different from those of standard liquid-state theory, which typically have a viscosity in the mPa·s range and relaxation times on the order of picoseconds. These numbers grow dramatically and become 10<sup>12</sup> - 10<sup>15</sup> times larger for liquids cooled toward the glass transition. This translates into a qualitative difference, and below the "solidity length" which is roughly one micron at the glass transition, a glass-forming liquid behaves much like a solid. Recent numerical evidence for the solidity of ultraviscous liquids is reviewed, and experimental consequences are discussed in relation to dynamic heterogeneity, frequency-dependent linear-response functions, and the temperature dependence of the average relaxation time. Solidity ; Glass transition ; Relaxation (psychology) ; Viscosity ; Materials science ; Thermodynamics ; Picosecond ; Short range order ; Perspective (graphical) ; Order (exchange) ; Condensed matter physics ; Optics ; Physics ; Mathematics ; Composite material ; Geometry ; Computer science Material Dynamics and Properties ; Glass properties and applications ; Theoretical and Computational Physics
Authors: Ibrahim Ahmed | Piero Baraldi | Enrico Zio | Horst Lewitschnig
Source:  (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Prediction of the Number of Defectives in a Production Batch of Semiconductor Devices The production of semiconductor devices requires to satisfy high reliability standards.For this reason, manufactured devices are subject to burn-in, i.e., extensive testing under accelerated stress conditions, which is costly and time-consuming.The present work develops a model for predicting the quality of the devices from data collected during the production process.The developed modelling approach is based on: a) a combination of Piecewise Aggregate Approximation (PAA) and Principal Component Analysis (PCA) for the extraction of features relevant for inferring the quality of the devices from signal measurements collected during the production; and b) a model based on Probabilistic Support Vector Regression (PSVR) for predicting the number of defective devices in the production batch.The model is validated on synthetic data, which emulate signal measurements collected during the production of semiconductor devices.The obtained results show that the proposed model is able of predicting the number of defective devices in a production batch with satisfactory accuracy. Computer science ; Reliability (semiconductor) ; Production (economics) ; Principal component analysis ; Reliability engineering ; Batch production ; Semiconductor device fabrication ; Probabilistic logic ; Semiconductor device ; Aggregate (composite) ; Process (computing) ; Quality (philosophy) ; Piecewise ; SIGNAL (programming language) ; Semiconductor device modeling ; Data mining ; Electronic engineering ; Artificial intelligence ; Engineering ; Mathematics ; CMOS ; Materials science ; Electrical engineering Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Advanced Statistical Process Monitoring
Authors: Shuang Gao | Angpeng Liu | Yuxin Jiang | Yi Liu
Source: ACS Omega (article, 2023-10-19)
Field: Chemistry — Analytical Chemistry

Online Estimation of Combustion Oxygen Content with an Image-Augmented Soft Sensor Using Imbalanced Flame Images High-accuracy oxygen content measurement and control is one key to improving combustion efficiency and economic efficiency. The soft measurement technique of the oxygen content based on flame images is promising. However, image feature acquisition at different oxygen contents and image generation under unbalanced conditions are still challenging. To relieve this dilemma, a new generative-based regression model is developed. It not only learns the potential vectors but also captures flame features well to generate virtually high-quality-labeled flame images. The training data sets can be augmented, thus saving a lot of data collection experiments. Subsequently, a convolutional-based regression model is constructed to estimate the oxygen content using the augmented flame images directly. The designed method generates informative flame images and obtains more accurate oxygen content estimation results than several common methods. Combustion ; Computer science ; Artificial intelligence ; Content (measure theory) ; Feature (linguistics) ; Image (mathematics) ; Computer vision ; Pattern recognition (psychology) ; Chemistry ; Mathematics Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Xu Wang | Jianbiao Wang | Haihui Ruan
Source: Physical review. B./Physical review. B (preprint, 2023-01-30)
Field: Materials Science — Materials Chemistry

Ergodicity breaking of an inorganic glass aging near <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>T</mml:mi><mml:mi>g</mml:mi></mml:msub></mml:math> probed by elasticity relaxation We performed a series of aging experiments with an inorganic glass (${\mathrm{As}}_{2}{\mathrm{Se}}_{3}$) at a temperature ${T}_{2}$ near the glass transition point ${T}_{g}$ by first relaxing it at ${T}_{1}$. The relaxations of Young's modulus were monitored, which were (almost if not ideally) exponential with ${T}_{1}$-dependent relaxation time \ensuremath{\tau}, corroborating the Kovacs' paradox in an inorganic glass. Associated with the divergence of \ensuremath{\tau}, the quasiequilibrated Young's modulus ${E}_{\ensuremath{\infty}}$ does not converge either. An elastic model of relaxation time and a Mori-Tanaka analysis of ${E}_{\ensuremath{\infty}}$ lead to a similar estimate of the persistent memory of the history, illuminating ergodicity breaking within the accessible experimental time, as described in the Gardner transition theory. Experiments with different ${T}_{2}$ exhibit a critical temperature ${T}_{p}\ensuremath{\sim}{T}_{g}$, i.e., when ${T}_{2}&gt;{T}_{p}$, both \ensuremath{\tau} and ${E}_{\ensuremath{\infty}}$ converge. The results unveil a long-expected phenomenon that structural glass transition could be a zero-to-nonzero transition, manifested by a nonvanishing structural memory in aging when the temperature is below ${T}_{p}$ in the glass transition range. This demonstrates the existence of the ergodicity breaking deep in the glass state and ${T}_{p}$ could be the Gardner transition point of the structural glass. Ergodicity ; Computer science ; Mathematics ; Statistics Material Dynamics and Properties ; Phase-change materials and chalcogenides ; Glass properties and applications
Authors: Rasha Sami
Source: Egyptian Dental Journal /Egyptian Dental Journal (article, 2023-04-01)
Field: Materials Science — Ceramics and Composites

Translucency, Microhardness and Fracture Toughness of Two Machinable Ceramics as Affected by Two Acidic Beverages Aim of the Study: To evaluate the translucency, microhardness, and fracture toughness of two CAD/CAM materials (IPS e.max CAD and Vita Enamic) after immersion in two acidic beverages (Coffee and Coca-Cola). Materials and methods: A total of 36 samples were equally divided into two groups each (n=18) as follows, Group I: IPS e.max CAD and Group II: Vita Enamic. Each group was further subdivided into two subgroups (n=9) according to the acidic beverage used, either Coffee, or Coca-Cola. Samples were immersed in acidic beverage solutions for three weeks, after which all samples were subjected to measure the translucency parameter using a Reflective Spectrophotometer and then using Vickers Micro-Hardness Tester to measure surface microhardness and fracture toughness. Statistical analysis was performed using one-way analysis of variance followed by Tukey’s post-hoc test if showed significance. Student t-test was done between main groups, while Two-way ANOVA compared the effect of each factor. Results: There was a statistically significant difference between IPS e.max CAD and Vita Enamic regarding translucency. Significant difference in surface microhardness, and fracture toughness after immersion in two acidic beverage solutions was revealed. Conclusions: Acidic beverages can adversely affect the translucency of glass-ceramic and hybrid ceramic materials. Microhardness and fracture toughness of different CAD/CAM esthetic materials was negatively affected secondary to exposure to beverages with low pH values. Indentation hardness ; Fracture toughness ; Materials science ; Ceramic ; Composite material ; Fracture (geology) ; Microstructure Advanced ceramic materials synthesis ; Dental materials and restorations ; Injection Molding Process and Properties
Authors: Lang Qin | Ang Zhang | Jinglian Du | Zhihua Dong | Feng Liu | Bin Jiang
Source: Materials (article, 2023-12-18)
Field: Materials Science — Materials Chemistry

Effect of Forced Convection on Magnesium Dendrite: Comparison between Constant and Altering Flow Fields Convection has a nonnegligible effect on the growth of the magnesium dendrite with six-primary-branch pattern. Most work, however, investigates the effect of the convection by simplifying the melt flow as a constant horizontal flow. In this work, four convection behaviors, including equally distributed convection, linearly distributed convection, sinusoidal-wave convection, and square-wave convection, are imposed and simulated through the phase-field lattice-Boltzmann schemes. The effects of constant (the former two) and altering (the latter two) flow fields are quantified by the length ratio of the upstream primary arm to the downstream one. The results show that the dendrite asymmetry increases under the constant forced convections but presents nonmonotonic change under the altering convections. A simple mathematical relation is fitted to summarize the dependence of the dendrite asymmetry on the input velocity, the undercooling, and the flow frequency. Deep understanding of the convection effects can guide the prediction and control of the magnesium dendrite under more complex situations. Convection ; Forced convection ; Mechanics ; Combined forced and natural convection ; Dendrite (mathematics) ; Materials science ; Convection cell ; Rayleigh–Bénard convection ; Natural convection ; Work (physics) ; Thermodynamics ; Physics ; Geometry ; Mathematics Solidification and crystal growth phenomena ; Fluid Dynamics and Thin Films ; Aluminum Alloy Microstructure Properties