jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Francesco Enrichi | Gabriella G. Mastantuoni | Michele Cassetta | Alessia Sambugaro | N. Daldosso | Alessandro Martucci | Alberto Vomiero | E. Cattaruzza | Giancarlo C. Righini
Source: The European Physical Journal Plus (article, 2024-04-24)
Field: Materials Science — Materials Chemistry

Structural and optical properties of Eu3+-doped sol–gel silica–soda glasses Abstract Rare earths (REs) incorporated in glasses, mostly in the form of RE 3+ ions, have several applications such as lasers and optical amplifiers, spectral conversion layers for solar cells, light emitters and sensors. In this context, both the composition and the structural properties of the glass, as well as the dopant concentration play an important role in determining the optical properties and the efficiency of the system. Usually, the concentration of REs is small, below 1 at%, to avoid clustering and optical quenching. In this paper, we report the case of sol–gel Eu-doped silica–soda glass films. The addition of soda to silica can reduce RE clustering and precipitation, according to molecular dynamic simulations, but brings structural instabilities to the network. Here, sodium was varied from 10 to 30 at% and Eu from 0 to 8 at%. It was shown that Eu plays a significant role in the stabilization of the matrix, improving the transparency, the refractive index and the thickness of the films. The increase of Eu concentration provides a decrease of site symmetry and an increase of quantum efficiency (QY), reaching 71% for the highest 8 at% Eu doping, with remarkable absence of concentration quenching. Dopant ; Materials science ; Doping ; Context (archaeology) ; Refractive index ; Ion ; Quenching (fluorescence) ; Spectral hole burning ; Sol-gel ; Chemical engineering ; Analytical Chemistry (journal) ; Optics ; Optoelectronics ; Laser ; Fluorescence ; Nanotechnology ; Chemistry Lanthanide and Transition Metal Complexes ; Glass properties and applications ; Luminescence Properties of Advanced Materials
Authors: Zheyao Hu | Jordi Martı́
Source: Computational and Structural Biotechnology Journal (article, 2024-05-24)
Field: Materials Science — Materials Chemistry

Isomer-sourced structure iteration methods for in silico development of inhibitors: Inducing GTP-bound NRAS-Q61 oncogenic mutations to an “off-like” state The NRAS-mutant subset of melanoma represent some of the most aggressive and deadliest types associated with poor overall survival. Unfortunately, for more than 40 years, no therapeutic agent directly targeting NRAS mutations has been clinically approved. In this work, based on microsecond scale molecular dynamics simulations, the effect of Q61 mutations on NRAS conformational characteristics is revealed at the atomic level. The GTP-bound NRAS-Q61R and Q61K mutations show a specific targetable pocket between Switch-II and <i>α</i>-helix 3 whereas the NRAS-Q61L non-polar mutation category shows a different targetable pocket. Moreover, a new isomer-sourced structure iteration method has been developed for the <i>in silico</i> design of potential inhibitor prototypes for oncogenes. We show the possibility of a designed prototype HM-387 to target activated NRAS-Q61R and that it can gradually induce the transition from the activated NRAS-Q61R to an "off-like" state. In silico ; Neuroblastoma RAS viral oncogene homolog ; GTP' ; Computational biology ; Chemistry ; Biology ; Cancer research ; Mutation ; Gene ; Genetics ; Biochemistry ; Enzyme ; KRAS Enzyme Structure and Function ; ATP Synthase and ATPases Research ; Protein Structure and Dynamics
Authors: Agus Arip Munawar | Kusumiyati Kusumiyati | Andasuryani | Yusmanizar Yusmanizar | Adrizal
Source: Acta Technologica Agriculturae (article, 2024-02-24)
Field: Chemistry — Analytical Chemistry

Near Infrared Technology Coupled with Different Spectra Correction Approaches for Fast and Non-Destructive Prediction of Chlorogenic Acid on Intact Coffee Beans Abstract The primary objective of this research was to utilise near-infrared reflectance spectroscopy as a swift, non-destructive method for identifying chlorogenic acid in whole coffee beans. Additionally, this investigation explored the efficacy of different spectral improvement techniques alongside partial least square regression to construct predictive models. NIR spectral data was gleaned from whole coffee beans spanning a wavelength range of 1000–2500 nm, while the chlorogenic acid content was ascertained via high-performance liquid chromatography procedures. Our findings revealed that the highest coefficient of determination reached for chlorogenic acid was 0.97, and the root mean square error for calibration was 0.31% when using the multiplicative scatter correction method. Furthermore, upon testing the model using an external validation dataset, a determination coefficient of 0.91 and a ratio error to range index of 11.56 with a root mean square prediction error at 0.51% was attained. From these results, it can be inferred that the near-infrared technology, coupled with an effective spectral enhancement process, can facilitate quick, non-invasive determination of chlorogenic acid in whole coffee beans. Chlorogenic acid ; Infrared ; Biological system ; Chemistry ; Analytical Chemistry (journal) ; Materials science ; Food science ; Organic chemistry ; Physics ; Optics ; Biology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Evrim Buyukaslan Oosterom | Fatma Baytar | Deniz Akdemir | Fatma Kalaoğlu
Source: Autex Research Journal (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Predicting consumers’ garment fit satisfactions by using machine learning Abstract The objectives of this study were to apply alternative machine learning (ML) algorithms to predict consumers’ garment fit satisfactions (real fit satisfaction [RFS]) and compare the efficiencies of these algorithms to predict RFS. Skirts made from different fabrics were used as test garments. Mechanical properties of the skirts’ fabrics were assigned as predictor variables to estimate RFS. Study participants’ virtual body models were created by using 3D body scanner and used for virtual fitting. Each participant physically tried on the skirts and evaluated the fit. Participants also viewed the skirt simulations on their avatars and evaluated the virtual fit, which represented participants’ virtual fit satisfactions (VFS). Random Forest (RF), support vector machine (SVM), and conditional tree (CT) algorithms were used to learn from the data to predict participants’ RFSs. The mean correlations between the predicted and observed RFS values in the validation sets were 0.74 (RF), 0.70 (SVM-linear kernel), 0.72 (SVM-radial kernel), and 0.55 (CT). According to the variable importance analysis, VFS had the highest importance among 35 predictor variables. ML is used mostly for sales forecasting and manufacturing purposes in the fashion industry. However, garment fit, which restrains consumers from shopping online, did not get enough attention in ML studies. Besides, the ML algorithms used in fashion and apparel studies are often genetic algorithms and neural networks; therefore, there is a need to test other algorithm types. In this study, we offered alternative ML algorithms (i.e., RF, SVM, and CT) to predict consumers’ garment fit satisfactions. Support vector machine ; Clothing ; Machine learning ; Artificial intelligence ; Random forest ; Kernel (algebra) ; Computer science ; Artificial neural network ; Algorithm ; Engineering ; Mathematics Textile materials and evaluations ; Color perception and design ; 3D Shape Modeling and Analysis
Authors: Tian Hong Zhou | Baochao Zhang | Xing Zheng | Youngwoon Song | Ping-Zhan Si | Chul-Jin Choi | Young‐Rae Cho | Jihoon Park
Source: Nanomaterials (article, 2024-08-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Anisotropic SmFe10V2 Bulk Magnets with Enhanced Coercivity via Ball Milling Process Anisotropic bulk magnets of ThMn<sub>12</sub>-type SmFe<sub>10</sub>V<sub>2</sub> with a high coercivity (<i>H<sub>c</sub></i>) were successfully fabricated. Powders with varying particle sizes were prepared using the ball milling process, where the particle size was controlled with milling time. A decrease in <i>H<sub>c</sub></i> occurred in the heat-treated bulk pressed from large-sized powders, while heavy oxidation excessively occurred in small powders, leading to the decomposition of the SmFe<sub>10</sub>V<sub>2</sub> (1-12) phase. The highest <i>H<sub>c</sub></i> of 8.9 kOe was achieved with powders ball-milled for 5 h due to the formation of the grain boundary phase. To improve the maximum energy product ((<i>BH</i>)<i><sub>max</sub></i>), which is only 2.15 MGOe in the isotropic bulk, anisotropic bulks were prepared using the same powders. The easy alignment direction, confirmed by XRD and EBSD measurements, was <002>. Significant enhancements were observed, with saturation magnetization (<i>M<sub>s</sub></i>) increasing from 59 to 79 emu/g and a remanence ratio (<i>M<sub>r</sub></i>/<i>M<sub>s</sub></i>) of 83.7%. (<i>BH</i>)<i><sub>max</sub></i> reaching 7.85 MGOe. For further improvement of magnetic properties, controlling oxidation is essential to form a uniform grain boundary phase and achieve perfect alignment with small grain size. Coercivity ; Materials science ; Remanence ; Ball mill ; Particle size ; Magnet ; Anisotropy ; Grain size ; Grain boundary ; Isotropy ; Metallurgy ; Composite material ; Analytical Chemistry (journal) ; Microstructure ; Nuclear magnetic resonance ; Magnetization ; Condensed matter physics ; Chemical engineering ; Magnetic field ; Optics ; Mechanical engineering Magnetic Properties of Alloys ; Magnetic properties of thin films ; Magnetic Properties and Applications
Authors: Yufeng Wang | Ripeng Luo | Jian Chen | Xuefeng Zhou | Shanmin Wang | Junqiao Wu | Feiyu Kang | Kuang Yu | Bo Sun
Source: Physical Review Letters (article, 2024-06-26)
Field: Materials Science — Materials Chemistry

Proton Collective Quantum Tunneling Induces Anomalous Thermal Conductivity of Ice under Pressure Proton tunneling is believed to be nonlocal in ice, but its range has been shown to be limited to only a few molecules. Here, we measured the thermal conductivity of ice under pressure up to 50 GPa and found it increases with pressure until 20 GPa but decreases at higher pressures. We attribute this nonmonotonic thermal conductivity to the collective tunneling of protons at high pressures, supported by large-scale quantum molecular dynamics simulations. The collective tunneling loops span several picoseconds in time and are as large as nanometers in space, which match the phonon periods and wavelengths, leading to strong phonon scattering at high pressures. Our results show direct evidence of global quantum motion existing in high-pressure ice and provide a new perspective to understanding the coupling between phonon propagation and atomic tunneling. Quantum tunnelling ; Phonon ; Thermal conductivity ; Condensed matter physics ; Picosecond ; Physics ; Quantum ; Materials science ; Thermal conduction ; Scattering ; Molecular dynamics ; Quantum mechanics Thermal properties of materials ; High-pressure geophysics and materials ; Quantum, superfluid, helium dynamics
Authors: Macaulay M. Owen | Leong Sing Wong | Emmanuel O. Achukwu | Ahmad Zafir Romli | Muhammad Firdaus Mohd Nazeri | Solehuddin Shuib
Source: Journal of Industrial Textiles (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Composites techniques optimization and finite element analysis of kenaf fiber reinforced epoxy nonwoven composite structures for renewable energy infrastructure In exploring the viability of kenaf fiber-reinforced epoxy nonwoven composites (KFRECs) for renewable energy infrastructure, the optimization of their manufacturing techniques for maximum performance remains a significant research gap. This study addresses this challenge by investigating the optimization of nonwoven composites’ fabrication techniques to enhance their mechanical, thermal, and microstructural robustness. Thus, an innovative vacuum double-bagging technique was compared with single-bagging and hand lay-up methods aimed at evaluating their impact on tensile and flexural strength, hardness, impact, and thermal resistance. The obtained results indicate that the vacuum single-bagging method significantly improved tensile and impact strength by 16% and 38.5%, respectively, while the vacuum double-bagging offered the greatest improvements in flexural strength and hardness, with increases of 112.6% and 15.3%, respectively, compared to the hand lay-up technique. SEM analysis confirmed the vacuum processing techniques produced well-consolidated composite structures with uniform fiber distribution, complete wettability, a good fiber-matrix interface, and a reduced void content, leading to improved material properties. Finite Element Analysis (FEA) simulations revealed a variation in tensile stress of approximately 22.4% and a close agreement with a minimal variation of 2.1% in flexural stress, further validating these optimized techniques. The results also correlate with enhanced thermal behavior and rigidity at elevated temperatures, with the vacuum double-bagging technique exhibiting the highest thermal stability for the demanding conditions of the energy infrastructure sector. The study concludes that the choice of fabrication technique is pivotal for advancing the design, properties and performance of KFRECs, for sustainable energy structures. Materials science ; Kenaf ; Composite material ; Epoxy ; Composite number ; Biocomposite ; Nonwoven fabric ; Fiber ; Renewable energy ; Finite element method ; Structural engineering ; Engineering Natural Fiber Reinforced Composites ; Mechanical Engineering and Vibrations Research ; Textile materials and evaluations
Authors: Leah Munyendo | K. Schuster | Wolfgang Armbruster | Majharulislam Babor | Daniel Njoroge | Yanyan Zhang | Almut von Wrochem | Alexander Schaum | Bernd Hitzmann
Source: Journal of Chemometrics (article, 2024-12-12)
Field: Chemistry — Analytical Chemistry

Monitoring a Coffee Roasting Process Based on Near‐Infrared and Raman Spectroscopy Coupled With Chemometrics ABSTRACT Roasting is a fundamental step in coffee processing, where complex reactions form chemical compounds related to the coffee flavor and its health‐beneficial effects. These reactions occur on various time scales depending on the roasting conditions. To monitor the process and ensure reproducibility, the study proposes simple and fast techniques based on spectroscopy. This work uses analytical tools based on near‐infrared (NIR) and Raman spectroscopy to monitor the coffee roasting process by predicting chemical changes in coffee beans during roasting. Green coffee beans of Robusta and Arabica species were roasted at 240°C for different roasting times. The spectra of the samples were taken using the spectrometers and modeled by the k‐nearest neighbor regression (KNR), partial least squares regression (PLSR), and multiple linear regression (MLR) to predict concentrations from the spectral data sets. For NIR spectra, all the models provided satisfactory results for the prediction of chlorogenic acid, trigonelline, and DPPH radical scavenging activity with low relative root mean square error of prediction (pRMSEP &lt; 9.649%) and high coefficient of determination ( R 2 &gt; 0.915). The predictions for ABTS radical scavenging activity were reasonably good. On the contrary, the models poorly predicted the caffeine and total phenolic content (TPC). Similarly, all the models based on the Raman spectra provided good prediction accuracies for monitoring the dynamics of chlorogenic acid, trigonelline, and DPPH radical scavenging activity (pRMSEP &lt; 7.849% and R 2 &gt; 0.944). The results for ABTS radical scavenging activity, caffeine, and TPC were similar to those of NIR spectra. These findings demonstrate the potential of Raman and NIR spectroscopy methods in tracking chemical changes in coffee during roasting. By doing so, it may be possible to control the quality of coffee in terms of its aroma, flavor, and roast level. Chemometrics ; Roasting ; Raman spectroscopy ; Process analytical technology ; Chemistry ; Analytical Chemistry (journal) ; Near-infrared spectroscopy ; Process (computing) ; Process engineering ; Chromatography ; Materials science ; Computer science ; Physical chemistry ; Optics ; Physics ; Chemical engineering ; Engineering Spectroscopy and Chemometric Analyses ; Coffee research and impacts ; Advanced Chemical Sensor Technologies
Authors: Semih Bal | Zoltán Ádám Tamus
Source: Electronics (article, 2024-03-15)
Field: Materials Science — Materials Chemistry

A Method for Assessing the Degradation of PVC-Insulated Low-Voltage Distribution Cables Exposed to Short-Term Cyclic Aging The distribution grid comprises cables with diverse constructions. The insulating material used in low-voltage (LV) distribution cables is predominantly PVC. Furthermore, the presence of cables with different structures in the grid poses challenges in detecting the aging of the cable network. Finding a universal and dependable condition-monitoring technique that can be applied to various types of cables is indeed a challenge. The diverse construction and materials used in different cables make it difficult to identify a single monitoring approach that can effectively assess the condition of all cables. To address this issue, this study aims to compare the thermal aging behavior of different LV distribution cables with various structures, i.e., one cable contains a PVC belting layer, while the other contains filler material. The growing adoption of distributed generation sources, electric vehicles, and new consumer appliances in low-voltage distribution grids can lead to short, repetitive overloads on the low-voltage cable network. Hence, these cable samples were exposed to short-term cyclic accelerated aging in the climate chamber at 110 °C. The cable’s overall behavior under thermal stress was evaluated through frequency and time domain electrical measurements (including tan δ and extended voltage response) and a mechanical measurement (Shore D). The tan δ was measured in the frequency range of 20 Hz–500 kHz by using the Wayne-Kerr impedance analyzer. The extended voltage response measurement was conducted using a C# application developed in-house specifically for laboratory measurements in the .NET environment. The study observed a strong correlation between the different measurement methods used, indicating that electrical methods have the potential to be adopted as a non-destructive condition-monitoring technique. Voltage ; Electrical impedance ; Low voltage ; Electrical engineering ; Thermal ; Materials science ; Accelerated aging ; Degradation (telecommunications) ; Engineering ; Electronic engineering ; Composite material High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Thermal Analysis in Power Transmission
Authors: Caroline J. Cushman | Andrew Ibrahim | Alexander D Smith | Evan Hernandez | Brendan J. MacKay | Mimi Zumwalt
Source: The Yale Journal of Biology and Medicine (review, 2024-09-30)
Field: Materials Science — Biomaterials

Local and Systemic Peptide Therapies for Soft Tissue Regeneration: ANarrative Review <b>Background</b>: The musculoskeletal system, due to inherent structure and function, lends itself to contributing toward joint pain, whether from inflammatory disorders such as rheumatoid arthritis, degenerative diseases such as osteoarthritis, or trauma causing soft tissue injury. Administration of peptides for treatment of joint pain or inflammation is an emerging line of therapy that seeks to offer therapeutic benefits while remaining safe and relatively non-invasive. <b>Purpose</b>: The purpose of this study is to review the current literature on existing oral peptide agents, intra-articular peptide agents, and new developments in human trials to assess route of administration (RoA) for drug delivery in terms of soft tissue regeneration. <b>Study Design</b>: Narrative Review. <b>Methods</b>: A comprehensive literature search was conducted using the PubMed database. The search included medical subject headings (MeSH) terms related to peptide therapy, soft tissue regeneration, and RoA. Inclusion criteria comprised articles focusing on the mechanisms of action of peptides, clinical or biochemical outcomes, and review articles. Exclusion criteria included insufficient literature or studies not meeting the set evidence level. <b>Conclusion</b>: The review identified various peptides demonstrating efficacy in soft tissue repair. Oral and intra-articular peptides showed distinct advantages in soft tissue regeneration, with intra-articular routes providing localized effects and oral routes offering systemic benefits. However, both routes have limitations in bioavailability and absorption. Still in their infancy, further inquiries/research into the properties and efficacy of emerging peptides will be necessary before widespread use. As a viable alternative prior to surgical intervention, peptide treatments present as promising candidates for positive outcomes in soft tissue regeneration. Regeneration (biology) ; Soft tissue ; Narrative ; Medicine ; Pathology ; Cell biology ; Biology ; Art ; Literature Silk-based biomaterials and applications ; Electrospun Nanofibers in Biomedical Applications ; Knee injuries and reconstruction techniques
Authors: Yu Xia | Wei Zhang | Tianci Che | Jinghao Hu | Shangqiao Cao | Wenbo Liu | Jie Kang | Wei Tang | Hongbo Li
Source: Applied Sciences (article, 2024-11-01)
Field: Chemistry — Analytical Chemistry

Comparison of Diffuse Reflectance and Diffuse Transmittance Vis/NIR Spectroscopy for Assessing Soluble Solids Content in Kiwifruit Coupled with Chemometrics Kiwifruit, as a climacteric fruit, undergoes rapid ripening and senescence after harvest, making it highly susceptible to softening, rotting, and spoilage. Therefore, monitoring the key quality parameters of kiwifruit, particularly the accurate detection of soluble solids content (SSC), is considered crucial. The performance of two spectral acquisition methods—diffuse reflectance and diffuse transmission—in detecting SSC in kiwifruit was compared. Various preprocessing methods and feature wavelength selection techniques were employed, and regression models were constructed using partial least squares (PLS) analysis. The stability and accuracy of the models were validated through an independent validation set. The results indicated that the spectral data acquired by the diffuse reflectance method, preprocessed using Savitzky–Golay smoothing and combined with competitive adaptive reweighted sampling (CARS), yielded a coefficient of determination (R2) of 0.98 for the prediction set, with a root-mean-square error (RMSE) of 0.66. In contrast, the spectral data obtained by the diffuse transmission method, preprocessed using multiplicative scatter correction and combined with CARS, achieved an R2 of 0.95 and an RMSE of 0.93 for the prediction set. This study demonstrated that both methods were effective for detecting SSC in kiwifruit, with the diffuse reflectance method showing the greater advantage. Chemometrics ; Diffuse reflectance infrared fourier transform ; Transmittance ; Diffuse reflection ; Content (measure theory) ; Materials science ; Chemistry ; Analytical Chemistry (journal) ; Optics ; Chromatography ; Optoelectronics ; Mathematics ; Physics ; Organic chemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality