jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zongfa Li | Lijuan Huang | Xiaosong Zhou | Xiaoyu Huang | Zhiwei Chen | Shaoran Ren
Source: Physics of Fluids (article, 2024-03-01)
Field: Chemistry — Analytical Chemistry

Scaling up in situ combustion process for enhanced oil recovery in water-flooded light oil reservoirs from laboratory to field implementation Aiming at low permeability, high water content light reservoir with a recovery rate higher than 20%, an improved air injection enhanced heat flooding technology is applied by combining the combustion reaction flow and flue gas flooding mechanism. The method involves the injection of air into the reservoir, which reacts with the crude oil at temperatures ranging from 220 to 300 °C. This reaction consumes part of the oil, enabling effective evaporation and flow of the remaining oil. This process combines combustion reaction flow with flue gas flooding, using high-temperature oxidation reactions to mobilize residual oil. Experimental results from combustion tube tests demonstrate stable reaction fronts, peak temperatures reaching up to 550 °C, and a significant increase in recovery rates, reaching 73.8% in some cases. Field applications of this technology require maintaining high air flux and burning rates in low-permeability zones to ensure effective heat-driven evaporation. The geological model of the well group shows that the recovery factor of the target block can be increased by more than 20% by air injection based on the water drive recovery factor of 28%–30%. The oil exchange ratio can be less than 4000 sm3/m3 by optimizing the air injection rate and oxygen content. The research results provide technical feasibility for heat flooding to significantly improve oil flow and recovery in low-permeability light oil reservoirs. Enhanced oil recovery ; Flue gas ; Secondary air injection ; Petroleum engineering ; Combustion ; Light crude oil ; Residual oil ; Water injection (oil production) ; Environmental science ; Oil field ; Permeability (electromagnetism) ; Steam injection ; Environmental engineering ; Waste management ; Geology ; Chemistry Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: Minwoo Choi | Hye-Jin Kim | Azfar Ismail | Hyun‐Jun Kim | Heesang Hong | Ghiseok Kim | Cheorun Jo
Source: Animal Bioscience (article, 2024-08-26)
Field: Chemistry — Analytical Chemistry

Combination model for freshness prediction of pork using VIS/NIR hyperspectral imaging with chemometrics Combining HSI spectral data with metabolites correlated to the meat freshness may elucidate why certain HSI spectra indicate meat freshness and prove to be more effective in predicting the freshness state of pork loin compared to using only HSI spectral data. Hyperspectral imaging ; Chemometrics ; Chemical imaging ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Chemistry ; Chromatography Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Carina Meyenberg | Vincent Braun | C. Friedrich H. Longin | Patrick Thorwarth
Source: Theoretical and Applied Genetics (article, 2024-07-22)
Field: Chemistry — Analytical Chemistry

Feature engineering and parameter tuning: improving phenomic prediction ability in multi-environmental durum wheat breeding trials Optimized phenomic selection in durum wheat uses near-infrared spectra, feature engineering and parameter tuning. Our study reports improvements in predictive ability and emphasizes customized preprocessing for different traits and models. The success of plant breeding programs depends on efficient selection decisions. Phenomic selection has been proposed as a tool to predict phenotype performance based on near-infrared spectra (NIRS) to support selection decisions. In this study, we test the performance of phenomic selection in multi-environmental trials from our durum wheat breeding program for three breeding scenarios and use feature engineering as well as parameter tuning to improve the phenomic prediction ability. In addition, we investigate the influence of genotype and environment on the phenomic prediction ability for agronomic and quality traits. Preprocessing, based on a grid search over the Savitzky-Golay filter parameters based on 756,000 genotype best linear unbiased estimate (BLUE) computations, improved the phenomic prediction ability by up to 1500% (0.02-0.3). Furthermore, we show that preprocessing should be optimized depending on the dataset, trait, and model used for prediction. The phenomic prediction scenarios in our durum breeding program resulted in low-to-moderate prediction abilities with the highest and most stable prediction results when predicting new genotypes in the same environment as used for model training. This is consistent with the finding that NIRS capture both the genotype and genotype-by-environment <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>(</mml:mo> <mml:mi>G</mml:mi> <mml:mo>×</mml:mo> <mml:mi>E</mml:mi> <mml:mo>)</mml:mo></mml:mrow> </mml:math> interaction variance. Selection (genetic algorithm) ; Predictive modelling ; Feature selection ; Best linear unbiased prediction ; Biology ; Biotechnology ; Trait ; Computer science ; Machine learning Spectroscopy and Chemometric Analyses ; Genetic and phenotypic traits in livestock ; Genetics and Plant Breeding
Authors: Yuqi Gu | Jianhua Wu | Yijun Guo | Sheng Hu | Kaixuan Li | Yuqian Shang | Liwei Bao | Muhammad Hassan | Chao Zhao
Source: Foods (article, 2024-10-20)
Field: Chemistry — Analytical Chemistry

Grade Classification of Camellia Seed Oil Based on Hyperspectral Imaging Technology To achieve the rapid grade classification of camellia seed oil, hyperspectral imaging technology was used to acquire hyperspectral images of three distinct grades of camellia seed oil. The spectral and image information collected by the hyperspectral imaging technology was preprocessed by different methods. The characteristic wavelength selection in this study included the continuous projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS), and the gray-level co-occurrence matrix (GLCM) algorithm was used to extract the texture features of camellia seed oil at the characteristic wavelength. Combined with genetic algorithm (GA) and support vector machine algorithm (SVM), different grade classification models for camellia seed oil were developed using full wavelengths (GA-SVM), characteristic wavelengths (CARS-GA-SVM), and fusing spectral and image features (CARS-GLCM-GA-SVM). The results show that the CARS-GLCM-GA-SVM model, which combined spectral and image information, had the best classification effect, and the accuracy of the calibration set and prediction set of the CARS-GLCM-GA-SVM model were 98.30% and 96.61%, respectively. Compared with the CARS-GA-SVM model, the accuracy of the calibration set and prediction set were improved by 10.75% and 12.04%, respectively. Compared with the GA-SVM model, the accuracy of the calibration set and prediction set were improved by 18.28% and 18.15%, respectively. The research showed that hyperspectral imaging technology can rapidly classify camellia seed oil grades. Hyperspectral imaging ; Support vector machine ; Artificial intelligence ; Pattern recognition (psychology) ; Calibration ; Camellia ; Computer science ; Set (abstract data type) ; Mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Nicole Ollinger | Bernhard Blank‐Landeshammer | Lisa Schütz-Kapl | Angeline Rochard | Iris Pfeifenberger | Jens Michael Carstensen | Manfred Müller | Julian Weghuber
Source: Foods (article, 2024-05-28)
Field: Chemistry — Analytical Chemistry

High-Oleic Sunflower Oil as a Potential Substitute for Palm Oil in Sugar Coatings—A Comparative Quality Determination Using Multispectral Imaging and an Electronic Nose Palm oil has a bad reputation due to the exploitation of farmers and the destruction of endangered animal habitats. Therefore, many consumers wish to avoid the use of palm oil. Decorative sugar contains a small amount of palm oil to prevent the sugar from melting on hot bakery products. High-oleic sunflower oil used as a substitute for palm oil was analyzed in this study via multispectral imaging and an electronic nose, two methods suitable for potential large-batch analysis of sugar/oil coatings. Multispectral imaging is a nondestructive method for comparing the wavelength reflections of the surface of a sample. Reference samples enabled the estimation of the quality of unknown samples, which were confirmed via acid value measurements. Additionally, for quality determination, volatile compounds from decorative sugars were measured with an electronic nose. Both applications provide comparable data that provide information about the quality of decorative sugars. Sunflower oil ; Electronic nose ; Sugar ; Palm oil ; Multispectral image ; Pulp and paper industry ; Environmental science ; Oleic acid ; Food science ; Materials science ; Computer science ; Botany ; Chemistry ; Biology ; Artificial intelligence ; Nanotechnology ; Engineering Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Edible Oils Quality and Analysis
Authors: Frédéric A. Perras
Source: Chemical Communications (article, 2024-01-01)
Field: Chemistry — Spectroscopy

Elimination of homogeneous broadening in <sup>1</sup>H solid-state NMR <sup>1</sup>H solid-state NMR spectra are plagued by low resolution, necessitating the use of complex pulse sequences or specialized equipment. We introduce a new resolution enhancement method, inspired by super-resolution microscopy, that uses a 2D Hahn-echo experiment to constrain deconvolution. The result is an effective doubling of the MAS frequency. Homogeneous ; Deconvolution ; Equating ; Spectral line ; Homogeneous broadening ; Resolution (logic) ; Chemistry ; Nuclear magnetic resonance spectroscopy ; NMR spectra database ; Solid-state nuclear magnetic resonance ; Spinning ; Proton NMR ; Nuclear magnetic resonance ; Analytical Chemistry (journal) ; Physics ; Stereochemistry ; Optics ; Doppler broadening ; Mathematics ; Thermodynamics ; Chromatography ; Computer science Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; NMR spectroscopy and applications
Authors: Kei G. I. Webber | Siqi Huang | Hsien‐Jung L. Lin | Tony Hunter | Jeremy Tsang | Dasun Jayatunge | Joshua L. Andersen | Ryan Kelly
Source: Molecular & Cellular Proteomics (article, 2024-11-12)
Field: Chemistry — Spectroscopy

Gradient-Elution Nanoflow Liquid Chromatography Without a Binary Pump: Smoothed Step Gradients Enable Reproducible, Sensitive, and Low-Cost Separations for Single-Cell Proteomics Mass spectrometry-based proteome profiling of trace analytes including single cells benefits from liquid chromatography separations operated at low flow rates (e.g., <50 nl/min). However, high-pressure binary pumps needed to achieve such flow rates are not commercially available, and instead require splitting of the gradient flow to achieve low-nanoliter-per-minute flow rates. Gradient flow splitting can waste solvent and lead to flow inconsistencies. To address this, we have developed a method for creating gradients by combining segments of mobile phase having increasing solvent strength together in an open capillary, and then relying on Taylor dispersion to form the desired smooth gradient profile. Our method dramatically reduces costs, as only a single isocratic high-pressure pump is required. Following development of gradient profiles for both 10- and 20-min active gradients, we measured 200 pg injections of HeLa digest using a timsTOF mass spectrometer. Finally, we investigated differences in protein expression between single cells originating from two different colonies of ATG-KO HeLa cells. Thousands of proteins were quantified, and a potential mechanism explaining differential immune responses of these two colonies upon exposure to viral DNA treatment was determined. Chromatography ; Gradient elution ; Elution ; Chemistry ; Binary number ; Proteomics ; High-performance liquid chromatography ; Mathematics ; Biochemistry Analytical Chemistry and Chromatography ; Glycosylation and Glycoproteins Research ; Microfluidic and Capillary Electrophoresis Applications
Authors: M. Guermazi | Ahmed Yahia Kallel | Olfa Kanoun
Source: Sensors (article, 2024-08-12)
Field: Chemistry — Analytical Chemistry

Explainable Feature Engineering for Multi-Modal Tissue State Monitoring Based on Impedance Spectroscopy One of the most promising approaches to food quality assessments is the use of impedance spectroscopy combined with machine learning. Thereby, feature selection is decisive for a high classification accuracy. Physically based features have particularly significant advantages because they are able to consider prior knowledge and to concentrate the data into pertinent understandable information, building a solid basis for classification. In this study, we aim to identify physically based measurable features for muscle type and freshness classifications of bovine meat based on impedance spectroscopy measurements. We carry out a combined study where features are ranked based on their F1-score, cumulative feature selection, and t-distributed Stochastic Neighbor Embedding (t-SNE). In terms of features, we analyze the characteristic points (CPs) of the impedance spectrum and the model parameters (MPs) obtained by fitting a physical model to the measurements. The results show that either MPs or CPs alone are sufficient for detecting muscle type. Combining capacitance (C) and extracellular resistance (Rex) or the modulus of the characteristic point Z1 and the phase at the characteristic frequency of the beta dispersion (Phi2) leads to accurate separation. In contrast, the detection of freshness is more challenging. It requires more distinct features. We achieved a 90% freshness separation using the MPs describing intracellular resistance (Rin) and capacitance (C). A 95.5% freshness separation was achieved by considering the phase at the end of the beta dispersion (Phi3) and Rin. Including additional features related to muscle type improves the separability of samples; ultimately, a 99.6% separation can be achieved by selecting the appropriate features. Feature selection ; Capacitance ; Electrical impedance ; Dielectric spectroscopy ; Feature (linguistics) ; Artificial intelligence ; Noise (video) ; Computer science ; Dispersion (optics) ; Pattern recognition (psychology) ; Biological system ; Mathematics ; Engineering ; Chemistry ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Electrical and Bioimpedance Tomography
Authors: Ianis Ammam | Amaury Guillermin | Lucas Ouillon | R. Vargiolu | Jean Perrot | H. Zahouani
Source: Royal Society Open Science (article, 2024-06-01)
Field: Materials Science — Polymers and Plastics

Coupling tensile test with LC-OCT and ultrasound imaging: investigation of the skin sublayers mechanical behaviour The skin is an envelope that covers the entire body. Nowadays, understanding and studying the mechanical, biological and sensory properties of the skin is essential, especially in dermatology and cosmetology. The in-depth study of the skin's mechanical behaviour is a highly intriguing challenge, enabling the differentiation of the behaviour of each layer. An extension device was developed to perform relaxation and extension tests to characterize the skin. The device has also been coupled with imaging tools (LC-OCT and ultrasound), allowing us to observe layer-by-layer deformations during the tests. Relaxation tests revealed significant skin anisotropy, as well as an influence of age and gender on skin viscoelastic parameters calculated from relaxation curves and a skin viscoelastic model. These tests also unveiled their ability to distinguish certain characteristic pathologies that alter the mechanical properties of the skin, such as scleroderma or heliodermatitis. Furthermore, the optical-mechanical coupling and deformation calculation through image analysis demonstrated that the skin layers exhibit distinct mechanical behaviours owing to their different structures. Finally, Poisson's ratio of the skin was obtained by calculating the deformation in two directions for each layer. Viscoelasticity ; Materials science ; Relaxation (psychology) ; Deformation (meteorology) ; Anisotropy ; Coupling (piping) ; Tensile testing ; Cosmetology ; Ultimate tensile strength ; Biomedical engineering ; Composite material ; Optics ; Physics ; Medicine Textile materials and evaluations ; Cellular Mechanics and Interactions ; Optical Coherence Tomography Applications
Authors: Fabio Frassetto | Lorenzo Cocola | Paola Zuppella | Vania Da Deppo | Luca Poletto
Source: Scientific Reports (article, 2024-01-12)
Field: Chemistry — Spectroscopy

Static, refractive and monolithic Fourier transform spectrometer: development and prototyping Static Fourier transform spectrometers are devices that can be realized as monolithic and compact assemblies. In the "grating-based" monolithic version, they are usually realized gluing together a beam-splitter with two reflective diffraction gratings using spacers as connecting elements. In this work we present the development and test of an alternative form of this kind of instrument in which the dispersive elements are Littrow's prisms and are glued to the splitting element, forming in this way a robust and filled structure with no air gaps. The device can work in the visible/near infrared spectral region with a resolution power that varies across the spectral range due to the dispersion of the used glasses. The absence of hollow regions inside the monolithic block makes the device extremely robust and protects the optical surfaces inside the interferometer from possible contaminations. The device can be easily miniaturized, as it does not require spacers or structural elements other than just the optical parts. The tested instrument works in the 470-850 nm wavelength range with a variable resolution between 3000 and 300. Optics ; Spectrometer ; Beam splitter ; Materials science ; Interferometry ; Diffraction grating ; Grating ; Astronomical interferometer ; Fourier transform ; Free spectral range ; Prism ; Spectral resolution ; Diffraction ; Fourier transform infrared spectroscopy ; Optoelectronics ; Wavelength ; Physics ; Laser ; Spectral line Spectroscopy and Laser Applications ; Photonic and Optical Devices ; Optical and Acousto-Optic Technologies
Authors: Feng Hong | Yalei Pang | Weiming Ji | Lu Liang | Fang Fang | Junhong Hao | Jizhen Liu
Source: CSEE Journal of Power and Energy Systems (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Assessment and Enhancement of FRC of Power Systems Considering Thermal Power Dynamic Conditions Frequency stability and security have been a vital challenge as large-scale renewable energy is integrated into power systems.In contrast, the proportion of traditional thermal power units decreases during the decarbonization transformation process, resulting in poor frequency support.This paper aims to explore the potential of frequency regulation support, dynamic assessment, and capacity promotion of thermal power plants in the transition period.Considering the dynamic characteristics of the main steam working fluid under different working conditions, a nonlinear observer is constructed by extracting the main steam pressure and valve opening degree parameters.The realtime frequency modulation capacity of thermal power units can provide a dynamic state for the power grid.A dynamic adaptive modification for primary frequency control (PFC) of power systems, including wind power and thermal power, is proposed and improved.The power dynamic allocation factor is adaptively optimized by predicting the speed droop ratio, and the frequency modulation capability of the system is improved by more than 11% under extreme conditions.Finally, through the Monte Carlo simulation of unit states of the system under various working conditions, the promotion of the frequency regulation capacity with high wind power penetration (WPP) is verified. Power (physics) ; Thermal ; Materials science ; Electric power system ; Dynamic demand ; Thermodynamics ; Physics Magnetic Properties and Applications ; Power Quality and Harmonics ; Power Transformer Diagnostics and Insulation
Authors: Heejin Kim | Raed Al Kontar | Chinedum E. Okwudire
Source: IEEE Access (article, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Intelligent Feedrate Optimization Using an Uncertainty-Aware Digital Twin Within a Model Predictive Control Framework The future of intelligent manufacturing machines involves autonomous selection of process parameters to maximize productivity while maintaining quality within specified constraints. To effectively optimize process parameters, these machines need to adapt to existing uncertainties in the physical system. This paper proposes a novel framework and methodology for feedrate optimization that is based on a physics-informed data-driven digital twin with quantified uncertainty. The servo dynamics are modeled using a digital twin, which incorporates the known uncertainty in the physics-based models and predicts the distribution of contour error using a data-driven model that learns the unknown uncertainty on-the-fly by sensor measurements. Using the quantified uncertainty, the proposed feedrate optimization maximizes productivity while maintaining quality under desired servo error constraints and stringency (i.e., the tolerance for constraint violation under uncertainty) using a model predictive control framework. Experimental results obtained using a 3-axis desktop CNC machine tool and a desktop 3D printer demonstrate significant cycle time reductions of up to 38% and 17% respectively, while staying close to the error tolerances compared to the existing methods. Model predictive control ; Computer science ; Control (management) ; Control theory (sociology) ; Artificial intelligence Pigment Synthesis and Properties ; Minerals Flotation and Separation Techniques ; Manufacturing Process and Optimization
Authors: Zhien Gu | Shi Hua He | Xiangdong Li | Peng Sun | Jiehua Wu | Haoyang Hu | Qiang Zhang | Jun Jiang
Source: Energies (article, 2024-01-30)
Field: Materials Science — Materials Chemistry

Hundred-Watt Implantable TEG Module for Large-Scale Exhaust Gas Waste Heat Recovery In this study, we have designed and developed an implantable thermoelectric generator (TEG) module tailored for large-scale flue gas waste heat recovery. We also have established a test stand to simulate diverse operational conditions, and systematically examined the influence of different operating conditions, including flue gas temperature, flue gas velocity, and cooling water temperature, on the electrical performance of the TEG module. When the flue gas temperature is 139 °C, the flue gas flow rate is 3.4 m/s, and the cooling water temperature is 20 °C, the TEG module operates at its peak performance. It achieves an open-circuit voltage of 856.3 V and an output power of 150.58 W. Furthermore, the TEG module demonstrates a notable power generation capacity of 3.86 kW/m3 and a waste heat recovery capacity of 135.85 kW/m3. The results prove the TEG module as an effective solution for large-scale flue gas waste heat recovery in industrial settings, contributing to sustainable energy practices. This study supports the application of thermoelectric power generation in the industrial sector, offering significant potential for advancements in energy efficiency. Flue gas ; Waste heat recovery unit ; Thermoelectric generator ; Waste heat ; Heat recovery ventilation ; Environmental science ; Waste management ; Exhaust gas ; Nuclear engineering ; Recuperator ; Thermoelectric effect ; Materials science ; Process engineering ; Heat exchanger ; Engineering ; Mechanical engineering ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies ; Thermal properties of materials