jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ece Kalaycı | Ozan Avinç
Source: Fibers and Polymers (article, 2024-07-24)
Field: Materials Science — Polymers and Plastics

The Disperse Dyeing of Polyetherimide Fibers Using Orthogonal Array (Taguchi) Design Abstract Polyetherimide (PEI) fibers are classified as high-performance fibers due to their notable characteristics, including chemical resistance, heat resistance, and flame resistance. However, the amorphous structure and intrinsic dyeability of polyetherimide (PEI) fibers set them apart from other high-performance fibers. The fibers possess considerable potential due to their remarkable performance features and are utilized in a wide range of industries, containing fashion and technical textiles, for varied purposes. The present work utilized the Orthogonal Array Taguchi method to systematically improve the dyeing process parameters for fabric samples made of polyetherimide (PEI). The use of a systematic methodology enabled effective experimentation and enabled the determination of the most favorable values of factors, while simultaneously reducing the utilization of resources. The study involved conducting rigorous experiments to evaluate the influence of several parameters on the color strength, tensile qualities, and washing fastness properties of the fabric samples. Furthermore, the utilization of the Taguchi approach facilitated the anticipation of these pivotal fabric properties by considering certain parameters. The objectives of this research encompass not only the progression of textile industry, but also the provision of beneficial perspectives for augmenting the caliber and efficacy of PEI fabrics in various applications. Polyetherimide ; Materials science ; Taguchi methods ; Orthogonal array ; Dyeing ; Composite material ; Textile ; Ultimate tensile strength ; Polymer Textile materials and evaluations ; Dyeing and Modifying Textile Fibers ; Silk-based biomaterials and applications
Authors: Dennis F. Dinu | Milan Ončák | Sven Thorwirth | Klaus R. Liedl | Sandra Brünken | Stephan Śchlemmer | Pavol Jusko
Source: Journal of the American Chemical Society (article, 2024-07-25)
Field: Chemistry — Spectroscopy

Zero-Point-Energy Driven Isotopic Exchange of the [H<sub>3</sub>O]<sup>−</sup> anion Probed by Mid-Infrared Action Spectroscopy We present the first observation of vibrational transitions in the [H<sub>3</sub>O]<sup>-</sup> anion, an intermediate in the anion-molecule reaction of water, H<sub>2</sub>O, and hydride, H<sup>-</sup>, using a laser-induced isotopic H/D exchange reaction action spectroscopy scheme applied to anions. The observed bands are assigned as the fundamental and first overtone of the H<sub>2</sub>O-H<sup>-</sup> vibrational stretching mode, based on anharmonic calculations within the vibrational perturbation theory and vibrational configuration interaction. Although the D<sub>2</sub>O·D<sup>-</sup> species has the lowest energy, our experiments confirm the D<sub>2</sub>O·H<sup>-</sup> isotope to be a sink of the H/D exchange reaction. <i>Ab initio</i> calculations corroborate that the formation of D<sub>2</sub>O·H<sup>-</sup> is favored, as the zero-point-energy difference is larger between D<sub>2</sub> and H<sub>2</sub> than between D<sub>2</sub>O·H<sup>-</sup> and D<sub>2</sub>O·D<sup>-</sup>. Chemistry ; Zero-point energy ; Infrared ; Ion ; Infrared spectroscopy ; Spectroscopy ; Zero (linguistics) ; Vibrational energy ; Analytical Chemistry (journal) ; Physical chemistry ; Atomic physics ; Molecule ; Physics ; Organic chemistry Molecular Spectroscopy and Structure ; Advanced Chemical Physics Studies ; Quantum, superfluid, helium dynamics
Authors: Bowen Gong | Shilei Mao | Xinkai Li | Bo Chen
Source: Analytical Methods (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Mineral oil emulsion species and concentration prediction using multi-output neural network based on fluorescence spectra in the solar-blind UV band The accurate monitoring of oil spills is crucial for effective oil spill recovery, volume determination, and cleanup. Oil slicks become emulsified under the effects of wind and waves, which increases the consistency of the oil spills. This phenomenon makes oil spills more challenging to handle and exacerbates environmental pollution. In this study, the variation of the solar-blind ultraviolet (UV) fluorescence spectra obtained from simulated oil spills with different oil types and oil-water ratios was investigated. By designing and constructing a multi-angle excitation and detection system, an apparent fluorescence peak of the oil emulsions was observed at around 290 nm under 220 nm excitation. By utilizing competitive adaptive reweighted sampling (CARS) and multi-output neural network algorithms, both the types and concentrations of the emulsified oils were obtained simultaneously. The classification accuracy for identifying the oil type exceeds 98%, and the mean absolute percentage error (MAPE) for concentration regression is around 2%. The results indicate that active solar-blind UV fluorescence could become a supplementary method for on-site oil spill detection to achieve comprehensive monitoring of oil spills. This study provides potential applications for UV-induced fluorescence spectrometry in oil spill on-site monitoring during the daytime. Mineral oil ; Emulsion ; Fluorescence ; Spectral line ; Artificial neural network ; Analytical Chemistry (journal) ; Environmental science ; Chemistry ; Environmental chemistry ; Computer science ; Physics ; Optics ; Artificial intelligence ; Organic chemistry Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Ka Yang | Joao A. Paulo | Steven P. Gygi | Qing Yu
Source: Journal of the American Society for Mass Spectrometry (article, 2024-09-10)
Field: Chemistry — Spectroscopy

Enhanced Sample Multiplexing-Based Targeted Proteomics with Intelligent Data Acquisition Targeted proteomics has been playing an increasingly important role in hypothesis-driven protein research and clinical biomarker discovery. We previously created a workflow, Tomahto, to enable real-time targeted pathway proteomics assays using two-dimensional multiplexing technology. Coupled with the TMT 11-plex reagent, hundreds of proteins of interest from up to 11 samples can be targeted and accurately quantified in a single-shot experiment with remarkable sensitivity. However, room remains to further improve the sensitivity, accuracy, and throughput, especially for targeted studies demanding a high peptide-level success rate. Here, bearing in mind the goal to improve peptide-level targeting, we introduce several new functionalities in Tomahto, featuring the integration of gas-phase fractionation using the FAIMS device, an accompanying software program (TomahtoPrimer) to customize fragmentation for each peptide target, and support for higher multiplexing capacity with the latest TMTpro reagent. We demonstrate that adding these features to the Tomahto platform significantly improves overall success rate from 89% to 98% in a single 60 min targeted assay of 290 peptides across human cell lines, while boosting quantitative accuracy via reducing TMT reporter ion interference. Chemistry ; Proteomics ; Sample (material) ; Multiplexing ; Mass spectrometry ; Computational biology ; Chromatography ; Nanotechnology ; Biochemistry ; Computer science ; Telecommunications ; Gene Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Machine Learning in Bioinformatics
Authors: Dong Ye | Zhangyou Yang | Siqi Zhang | Rongrong Zhu | Bin Zheng | Huan Lu
Source: Progress In Electromagnetics Research M (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Flexible Foldable Broadband Metamaterial Absorber Fabricated by Intaglio Printing Technology Absorbing materials can absorb incident electromagnetic waves effectively and have important research value in radar fields. However, the current absorbing materials are mostly affected by the thickness and flexibility of the dielectric substrate, and they have shortcomings such as being not thin, not flexible, not folding, and not conformal with the protection target, which is not conducive to practical application. In this paper, we propose a flexible absorbing material that can be folded freely for wearable and practical engineering applications, which is composed of a conductive carbon paste ink resistance film layer, a flexible fabric dielectric substrate, and a metal backplane. When the incidence angle is less than 30 , more than 90% absorption performance can be achieved at the operating frequency of 9.5-11.5 GHz with polarization insensitive characteristics. Simulated and experimental results prove the effectiveness of the structure. Our work provides the groundwork for the commercialization of future meta-devices such as wearable invisibility cloaks, sensors, optical filters/switchers, photodetectors, and energy converters. Broadband ; Metamaterial ; Materials science ; Optoelectronics ; Metamaterial absorber ; Inkwell ; Computer science ; Tunable metamaterials ; Telecommunications ; Composite material Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Advanced Materials and Mechanics
Authors: Ke Li | Xin Zhang | Jıng Zhang | Biao Du | Xiaoping Song | Guixuan Wang | Qi Li | Yinglan Zhang | Fan Liu | Zhengdong Zhang
Source: ACS Omega (article, 2024-03-28)
Field: Chemistry — Analytical Chemistry

Simultaneous Rapid Detection of Multiple Physicochemical Properties of Jet Fuel Using Near-Infrared Spectroscopy Jet fuel is the primary fuel used in the aviation industry, and its quality has a direct impact on the safety and operational efficiency of aircraft. The accurate quantitative detection and analysis of various physicochemical property indicators are important for improving and ensuring the quality of jet fuel in the domestic market. This study used near-infrared (NIR) spectroscopy to establish a suitable model for the simultaneous and rapid detection of multiple physicochemical properties in jet fuel. Using more than 40 different sources of jet fuel, a rapid detection model was established by optimizing the spectral processing methods. The measurement models were separately built using the partial least-squares (PLS) and orthogonal PLS algorithms, and the model parameters were optimized. The results show that after the Savitzky-Golay second derivative preprocessing, the PLS model built using the feature spectra selected by the uninformative variable elimination wavelength algorithm achieved the best measurement performance. Compared with the PLS model without preprocessing, the range of the resulting accuracy improvement was at least 15.01%. Under the optimal model parameters, the calibration set regression coefficient (<i>R</i><sub>c</sub><sup>2</sup>) of the 11 jet fuel property index models ranged from 0.9102 to 0.9763, with the root-mean-square error of calibration values up to 0.8468 °C (for flash points). The regression coefficient (<i>R</i><sub>p</sub><sup>2</sup>) of the validation set ranged from 0.8239 to 0.9557, with the root-mean-square error of prediction values up to 1.1354 °C (for flash points). The ratios of prediction to deviation (RPD) values were all in the range of 1.9-3.0, indicating high accuracy and reliability of the model. The rapid NIR analysis method established in this study enables the simultaneous and rapid detection of multiple physicochemical properties of jet fuel, thereby providing effective technical support for ensuring the quality of jet fuel in the market. Partial least squares regression ; Calibration ; Jet fuel ; Mean squared error ; Root mean square ; Flash point ; Linear regression ; Regression analysis ; Coefficient of determination ; Mathematics ; Biological system ; Computer science ; Statistics ; Chemistry ; Engineering Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Dongyong Zhu | Xiao-Na Fu | Jia Liu | Xiaoming Liu | Lan Cheng | Xinli Zhang | Jue Lu | Qian Qin | Peng Sun | Zhenyu Zhou | Yiming Feng | Jing Wang
Source: Neurochemical Research (article, 2024-12-08)
Field: Materials Science — Materials Chemistry

Multiparametric Chemical Exchange Saturation Transfer MRI Detects Metabolic Changes in Mild Cognitive Impairment Cases at 3.0 Tesla Magnetic resonance imaging ; Magnetization transfer ; Amide ; Chemistry ; Nuclear magnetic resonance ; Hippocampus ; Nuclear medicine ; Cognitive impairment ; Internal medicine ; Medicine ; Radiology ; Biochemistry Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies
Authors: Maxwell Scale Uwadia Osagie | Faith Cyril-Musa
Source: Anchor University Journal of Science and Technology (article, 2024-09-28)
Field: Chemistry — Analytical Chemistry

Classification of Poultry Birds Based on Health State Using Convolutional Neural Network Monitoring the health of poultry birds is essential for ensuring the productivity and safety of poultry products. The conventional methods are often time-consuming, prone to errors, and ineffective at early disease detection. The drawbacks associated with the conventional methods often results to significant financial loss and increases disease spread within flocks, thereby impacting food productivity and safety. Addressing these challenges requires innovative solutions that improve the efficiency and accuracy of poultry health management. This study is part of a research work aimed at addressing the challenges of digitalized method of poultry bird’s disease classification. To solved this, a classification of poultry birds based on health state using convolutional neural network model was developed, technique such as deep learning was used to analyzes diverse dataset of annotated images of birds with health conditions, for proper datasets classification, a convolutional neural network (CNN) was employed, the model as designed can accurately classify the health system of poultry birds from images, evaluate the performance of the developed model in terms of accuracy, precision, recall and F1 score. The model is embedded with a user-friendly interface and this was achieved through computer vision-based techniques, the interface enable users to upload images and result of different diseases as analyzed displayed Convolutional neural network ; Computer science ; State (computer science) ; Artificial intelligence ; Algorithm Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Livestock and Poultry Management
Authors: F.M. Tangorra | Alessio Tugnolo | Ze’ev Schmilovitch | Aldo Calcante
Source: Computers and Electronics in Agriculture (article, 2024-05-15)
Field: Chemistry — Analytical Chemistry

On-Site assessment of corn silage biochemical methane potential using a cost-effective NIR device Corn silage, widely used as a feedstock in anaerobic digestion systems, plays a significant role in renewable energy production. The measurement of the biochemical methane potential (BMP) of ensiled corn at the farm level is of utmost importance for characterizing its methane production potential and optimizing biogas generation. Thus, understanding the BMP of corn silage from individual farms is crucial for efficient biogas plant management and proper utilization of this valuable resource. The study aimed to assess the BMP of corn silage using a cost-effective miniaturized handheld NIR spectrometer with minimal sample preparation. Twenty-nine corn silage wet samples from as many dairy farms located in Lombardy (Northern Italy) were used. NIR calibrations were developed by means of partial least-square (PLS) regression obtaining models with a fairly good coefficient of determination (R2C = 0.92 and R2CV = 0.80 for DM and R2C = 0.90 and R2CV = 0.75 for BMP) and a reasonable prediction error (RMSECV = 1.38 and 4.76 for DM and BMP, respectively). Based on these results, the handheld spectrometer would be useful for providing a fast screening of dry matter (DM) and biochemical methane potential (BMP) in corn silage wet samples at farm level, enabling proper management of biogas plants and rapid turnaround in farm advisory systems. Silage ; Methane ; Environmental science ; Agricultural engineering ; Agronomy ; Waste management ; Biotechnology ; Engineering ; Biology ; Ecology Spectroscopy and Chemometric Analyses ; Mineral Processing and Grinding ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Chao‐Hui Feng
Source: Sustainability (article, 2024-10-08)
Field: Chemistry — Analytical Chemistry

Colour Analysis of Sausages Stuffed with Modified Casings Added with Citrus Peel Extracts Using Hyperspectral Imaging Combined with Multivariate Analysis Recycling citrus peel waste offers several significant contributions to sustainability, transforming what would otherwise be discarded into valuable resources. In this study, the colour of sausages stored for 16 days, with varying amounts of orange extract added to the modified casing solution, was evaluated using response surface methodology (RSM) and a hyperspectral imaging system within the spectral range of 350–1100 nm for the first time. To enhance model performance, spectral pre-treatments such as normalisation, first derivative, standard normal variate (SNV), second derivative, and multiplicative scatter correction (MSC) were applied. Both raw and pre-treated spectral data, along with colour attributes, were fitted to a partial least squares regression model. The RSM results indicated that the highest R2 value, 80.61%, was achieved for the b* (yellowness) parameter using a second-order polynomial model. The interactive effects of soy oil and orange extracts on b* were found to be significant (p &lt; 0.05), and the square effects of soy oil on b* were significant at the 1% level. The identified key wavelengths for colour parameters can simplify the model, making it more suitable for practical industrial applications. Hyperspectral imaging ; Mathematics ; Response surface methodology ; Partial least squares regression ; Orange (colour) ; Biological system ; Second derivative ; Food science ; Chemistry ; Artificial intelligence ; Computer science ; Statistics ; Biology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Phytochemicals and Antioxidant Activities
Authors: Xiaoyu Wang | Warren E. Pickett | Michael Hutcheon | Rohit P. Prasankumar | Eva Zurek
Source: Angewandte Chemie (article, 2024-10-11)
Field: Materials Science — Materials Chemistry

Why Mg<sub>2</sub>IrH<sub>6</sub> Is Predicted to Be a High‐Temperature Superconductor, But Ca<sub>2</sub>IrH<sub>6</sub> Is Not Abstract The X 2 MH 6 family, consisting of an electropositive cation X n+ and a main group metal M octahedrally coordinated by hydrogen, have been identified as promising templates for high‐temperature conventional superconductivity. Herein, we analyze the electronic structure of two members of this family, Mg 2 IrH 6 and Ca 2 IrH 6 , showing why the former may possess superconducting properties rivaling those of the cuprates, whereas the latter does not. Within Mg 2 IrH 6 the vibrations of the anions IrH 6 4− anions are key for the superconducting mechanism, and they induce coupling in the set of orbitals, which are antibonding between the H 1 s and the Ir or orbitals. Because calcium possesses low‐lying d ‐orbitals, →Ca d back‐donation is preferred, quenching the superconductivity. Our analysis explains why high critical temperatures were only predicted for second or third row X metal atoms, and may provide rules for identifying likely high‐temperature superconductors in other systems where the antibonding anionic states are filled. Superconductivity ; Materials science ; Condensed matter physics ; Chemistry ; Physics Hydrogen Storage and Materials ; Nuclear Materials and Properties ; Thermodynamic and Structural Properties of Metals and Alloys
Authors: Yao Liu | Fu Qiao | Zhen Xu
Source: Journal of Food Science (article, 2024-11-04)
Field: Chemistry — Analytical Chemistry

Detection of mussels contaminated with cadmium by near‐infrared reflectance spectroscopy based on RELS‐TSVM Eating mussels contaminated with cadmium (Cd) can seriously harm health. In this study, a non-destructive and rapid detection method for Cd-contaminated mussels based on near-infrared reflectance spectroscopy was studied. The spectral data of Cd-contaminated and non-contaminated mussels were collected in the range of 950-1700 nm. The model based on a robust energy-based least squares twin support vector machine (RELS-TSVM) was established to detect Cd-contaminated mussels. The influence of parameters on the RELS-TSVM model was analyzed, and the most suitable parameters were determined. The average accuracy of the proposed RELS-TSVM model in detecting Cd-contaminated mussels reached 99.92%, which was better than other twin support vector machine-derived models. For test datasets with different kinds of spectral noises (Gaussian noise, baseline shift, stray light, and wavelength shift), the RELS-TSVM model had a high robustness for noise disturbance. The results show that near-infrared spectroscopy combined with the RELS-TSVM model can realize the detection of Cd-contaminated mussels, which can provide technical support for the monitoring of heavy metals in shellfish. PRACTICAL APPLICATION: The method of detecting Cd-contaminated mussels by the NIRS has important practical significance for ensuring the safety of consumers. It provides a new way for the quality assessment and safety detection of shellfish and provides a technical basis for the marine environment assessment and management. Environmental science ; Contamination ; Computer science ; Biology ; Ecology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Yifan Cui | C.C. Li | Li Y
Source: Applied Ecology and Environmental Research (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

ESTIMATION OF WHEAT BIOMASS USING HYPERSPECTRAL DATA, WAVELET TRANSFORM, AND FRACTIONAL-ORDER DERIVATIVE Hyperspectral imaging ; Biomass (ecology) ; Wavelet ; Mathematics ; Derivative (finance) ; Order (exchange) ; Estimation ; Wavelet transform ; Pattern recognition (psychology) ; Statistics ; Artificial intelligence ; Computer science ; Geology ; Engineering ; Economics Spectroscopy and Chemometric Analyses