jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Arcel Mutombo Mulowayi | Zhen Hui Shen | Witness Joseph Nyimbo | Zhi Feng Di | Nyumah Fallah | Shu He Zheng
Source: Scientific Reports (article, 2024-04-12)
Field: Chemistry — Analytical Chemistry

Quantitative measurement of internal quality of carrots using hyperspectral imaging and multivariate analysis The study aimed to measure the carotenoid (Car) and pH contents of carrots using hyperspectral imaging. A total of 300 images were collected using a hyperspectral imaging system, covering 472 wavebands from 400 to 1000 nm. Regions of interest (ROIs) were defined to extract average spectra from the hyperspectral images (HIS). We developed two models: least squares support vector machine (LS-SVM) and partial least squares regression (PLSR) to establish a quantitative analysis between the pigment amounts and spectra. The spectra and pigment contents were predicted and correlated using these models. The selection of EWs for modeling was done using the Successive Projections Algorithm (SPA), regression coefficients (RC) from PLSR models, and LS-SVM. The results demonstrated that hyperspectral imaging could effectively evaluate the internal attributes of carrot cortex and xylem. Moreover, these models accurately predicted the Car and pH contents of the carrot parts. This study provides a valuable approach for variable selection and modeling in hyperspectral imaging studies of carrots. Hyperspectral imaging ; Partial least squares regression ; Multivariate statistics ; Support vector machine ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Least squares support vector machine ; Mathematics ; Biological system ; Remote sensing ; Statistics ; Biology ; Geology Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Animal Nutrition and Physiology
Authors: Huan‐Teng Su | Lu-Yun Wang | Chih‐Yao Hsu | Yun-Chien Wu | Chang-Yi Lin | Shu-Ming Chang | Yao‐Wei Huang
Source: Nano Letters (article, 2024-07-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Topology Optimization Enables High-<i>Q</i> Metasurface for Color Selectivity Nonlocal metasurfaces, exemplified by resonant waveguide gratings (RWGs), spatially and angularly configure optical wavefronts through narrow-band resonant modes, unlike the broad-band and broad-angle responses of local metasurfaces. However, forward design techniques for RWGs remain constrained at lower efficiency. Here, we present a topology-optimized metasurface resonant waveguide grating (MRWG) composed of titanium dioxide on a glass substrate capable of operating simultaneously at red, yellow, green, and blue wavelengths. Through adjoint-based topology optimization, while considering nonlocal effects, we significantly enhance its diffraction efficiency, achieving numerical efficiencies up to 78% and <i>Q</i>-factors as high as 1362. Experimentally, we demonstrated efficiencies of up to 59% with a <i>Q</i>-factor of 93. Additionally, we applied our topology-optimized metasurface to color selectivity, producing vivid colors at 4 narrow-band wavelengths. Our investigation represents a significant advancement in metasurface technology, with potential applications in see-through optical combiners and augmented reality platforms. Grating ; Wavelength ; Topology (electrical circuits) ; Diffraction ; Materials science ; Wavefront ; Topology optimization ; Optoelectronics ; Optics ; Waveguide ; Diffraction efficiency ; Diffraction grating ; Selectivity ; Substrate (aquarium) ; Physics ; Chemistry ; Finite element method ; Mathematics Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Advanced Antenna and Metasurface Technologies
Authors: Carlos Rojas-Herrera | Aner Martínez-Soto | Constanza Avendaño-Vera | Juan Pablo Cárdenas-Ramírez
Source: Journal of Building Engineering (article, 2024-04-05)
Field: Materials Science — Polymers and Plastics

Characterization and utilization of sawdust waste generated from advanced manufacture for its application as a thermal insulation in sustainable buildings using the blowing technique The construction industry is vital for economic development, but it accounts for 40% of energy consumption and 45% of global greenhouse gas emissions. In this context, research has focused on reducing energy demand in homes, particularly through the development of insulation materials. Sawdust is a byproduct available annually in Chile in quantities exceeding 4.5 million tons. Therefore, the objective of this study was to characterize the physical and thermal properties of this waste to evaluate its use as a thermal insulation material. Stability and thermal conductivity tests, as well as density and moisture content measurements, were conducted on the sawdust. Additionally, to assess the functionality of this thermal insulator, the material was applied using the blowing technique in partitions, followed by physical tests. The results indicate that the proposed insulation material has thermal stability up to 270 °C. The thermal conductivity was comparable to conventional mineral wool and fiberglass (0.042–0.048 [W/mK]). The density ranged from 123.77 to 198.15 [kg/m³] depending on the filling time of the specimens but remained low compared to other organic materials. The moisture content was 11.31%, suitable for maintaining good thermal conductivity. This study concludes that sawdust is a viable alternative for thermal insulation, especially when applied through blowing. Its stability and thermal conductivity are comparable to conventional materials, while its thermal inertia is 200% higher than that of glass wool. Furthermore, the low moisture content suggests that there would be no proliferation of pathogens, making it a promising thermal insulator for sustainable construction development. Finally, it is mentioned that the material carbonizes within a limited time, leading to self-extinguishment of the flame. Sawdust ; Waste management ; Thermal insulation ; Characterization (materials science) ; Sustainability ; Waste material ; Environmental science ; Blowing agent ; Materials science ; Engineering ; Pulp and paper industry ; Composite material ; Polyurethane ; Layer (electronics) Natural Fiber Reinforced Composites ; Recycling and utilization of industrial and municipal waste in materials production ; Innovations in Concrete and Construction Materials
Authors: Weilin Ye | Linfeng He | Weihao Liu | Zhile Yuan | Kaiyuan Zheng | Guolin Li
Source: Photoacoustics (article, 2024-12-09)
Field: Chemistry — Spectroscopy

Optomechanical energy enhanced BF-QEPAS for fast and sensitive gas sensing Traditional beat frequency quartz-enhanced photoacoustic spectroscopy (BF-QEPAS) are limited by short energy accumulation times and the necessity of a decay period, leading to weaker signals and longer measurement cycles. Herein, we present a novel optomechanical energy-enhanced (OEE-) BF-QEPAS technique for fast and sensitive gas sensing. Our approach employs periodic pulse-width modulation (PWM) of the laser signal with an optimized duty cycle, maintaining the quartz tuning fork's (QTF) output at a stable steady-state level by applying stimulus signals at each half-period and allowing free vibration in alternate half-periods to minimize energy dissipation. This method enhances optomechanical energy accumulation in the QTF, resulting in an approximate 33-fold increase in response speed and a threefold increase in signal intensity compared to conventional BF-QEPAS. We introduce an energy efficiency coefficient <i>K</i> to quantify the relationship between transient signal amplitude and measurement duration, exploring its dependence on the modulation signal's period and duty cycle. Theoretical analyses and numerical simulations demonstrate that the maximum <i>K</i> occurs at a duty cycle of 50 % and an optimized beat frequency Δ<i>f</i> of 30 Hz. Experimental results using methane reveal a detection limit of 2.17 ppm with a rapid response time of 33 ms. The OEE-BF-QEPAS technique exhibits a wide dynamic range with exceptional linearity over five orders of magnitude and a record noise-equivalent normalized absorption (NNEA) coefficient of 9.46 × 10<sup>-10</sup> W cm<sup>-1</sup> Hz<sup>-1/2</sup>. Additionally, a self-calibration method is proposed for correcting resonant frequency shifts. The proposed method holds immense potential for applications requiring fast and precise gas detection. Energy (signal processing) ; Materials science ; Optoelectronics ; Environmental science ; Physics Spectroscopy and Laser Applications ; Atmospheric Ozone and Climate ; Gas Sensing Nanomaterials and Sensors
Authors: Javier Robles | Ananth Prakash | Juan Antonio Vizcaíno | J. Ignacio Casal
Source: PLoS Computational Biology (article, 2024-01-22)
Field: Chemistry — Spectroscopy

Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation The cancer biomarker field has been an object of thorough investigation in the last decades. Despite this, colorectal cancer (CRC) heterogeneity makes it challenging to identify and validate effective prognostic biomarkers for patient classification according to outcome and treatment response. Although a massive amount of proteomics data has been deposited in public data repositories, this rich source of information is vastly underused. Here, we attempted to reuse public proteomics datasets with two main objectives: i) to generate hypotheses (detection of biomarkers) for their posterior/downstream validation, and (ii) to validate, using an orthogonal approach, a previously described biomarker panel. Twelve CRC public proteomics datasets (mostly from the PRIDE database) were re-analysed and integrated to create a landscape of protein expression. Samples from both solid and liquid biopsies were included in the reanalysis. Integrating this data with survival annotation data, we have validated in silico a six-gene signature for CRC classification at the protein level, and identified five new blood-detectable biomarkers (CD14, PPIA, MRC2, PRDX1, and TXNDC5) associated with CRC prognosis. The prognostic value of these blood-derived proteins was confirmed using additional public datasets, supporting their potential clinical value. As a conclusion, this proof-of-the-concept study demonstrates the value of re-using public proteomics datasets as the basis to create a useful resource for biomarker discovery and validation. The protein expression data has been made available in the public resource Expression Atlas. Proteomics ; Biomarker ; Biomarker discovery ; Colorectal cancer ; Computational biology ; Bioinformatics ; Medicine ; Computer science ; Cancer ; Biology ; Internal medicine ; Gene Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Ferroptosis and cancer prognosis
Authors: Aldo F. P. Cantatore | Giansergio Menduni | Andrea Zifarelli | Pietro Patimisco | Marilena Giglio | Miguel González | Hüseyin R. Seren | Pan Luo | Vincenzo Spagnolo | Angelo Sampaolo
Source: Energy & Fuels (article, 2024-12-19)
Field: Chemistry — Spectroscopy

Methane, Ethane, and Propane Detection Using a Quartz-Enhanced Photoacoustic Sensor for Natural Gas Composition Analysis A compact and portable gas sensor based on quartz-enhanced photoacoustic spectroscopy (QEPAS) for the detection of methane (C1), ethane (C2), and propane (C3) in natural gas (NG)-like mixtures is reported. An interband cascade laser (ICL) emitting at 3367 nm is employed to target absorption features of the three alkanes, and partial least-squares regression analysis is employed to filter out spectral interferences and matrix effects characterizing the examined gas mixtures. Spectra of methane, ethane, and propane mixtures diluted in nitrogen are employed to train and test the regression algorithm, achieving a prediction accuracy of ∼98%, ∼96%, and ∼93% on C1, C2, and C3, respectively. With respect to previously reported QEPAS sensors for natural gas analysis, the high prediction accuracy as well as the capability to discriminate and detect C3 within natural gas-like complex mixtures provided by the employment of partial least-squares regression mark significant improvements. Furthermore, these results enable an improved performance of the sensor for in situ, real-time, and online natural gas composition analysis. Propane ; Methane ; Quartz ; Natural gas ; Photoacoustic imaging in biomedicine ; Gas analysis ; Composition (language) ; Gas chromatography ; Gas composition ; Analytical Chemistry (journal) ; Chemical engineering ; Materials science ; Environmental chemistry ; Chemistry ; Environmental science ; Mineralogy ; Chromatography ; Organic chemistry ; Optics ; Thermodynamics ; Composite material Spectroscopy and Laser Applications ; Advanced Chemical Sensor Technologies ; Atmospheric and Environmental Gas Dynamics
Authors: O. Zinovieva | Aleksandr Zinoviev | Mitesh Patel | Andrey Molotnikov | Mark Easton
Source: Materials & Design (article, 2024-08-18)
Field: Materials Science — Materials Chemistry

Modelling grain refinement under additive manufacturing solidification conditions using high performance cellular automata Despite increasing applications of additively manufactured parts, they still suffer from anisotropic mechanical properties and can experience cracking due to coarse columnar grain structures induced by metal 3D printing. Microstructural control is promising avenue to overcome these challenges, but requires deeper understanding of factors controlling solidification, particularly regarding grain refinement. Addressing this gap, this study explores grain refinement in Al-Cu alloys with a process-microstructure linking cellular automata-finite difference (CAFD) approach supported by single-track laser surface remelting (LSR) experiments. To enhance the understanding of nucleation behaviour in alloys under additive manufacturing solidification conditions, this research analyses the influence of nucleation parameters on the post-LSR microstructures. Additionally, this study explores the computational dimensions of microstructure modelling, testing CA mesh sensitivity effects and benchmarking our CAFD models on two high-performance computing platforms. The CAFD model captures well the key microstructural features observed in LSR Al-Cu alloys with and without grain refiner addition. It is shown that the maximum nucleation density has a significant effect on the final microstructure, resulting in different proportions of coarse columnar grains resulting from epitaxial solidification, newly nucleated thin columnar grains, and equiaxed grains. Materials science ; Cellular automaton ; Process engineering ; Metallurgy ; Computer science ; Algorithm Solidification and crystal growth phenomena ; Additive Manufacturing Materials and Processes ; Metallurgy and Material Forming
Authors: Yan Feng | Chenyang Liu | Weiping Cui | Liuqing Yang | Di Wu | Hua Zhang | Xueqing Wang | Yuqian Sun | Bing He | Wenbing Dai | Qiang Zhang
Source: Science Advances (article, 2024-10-23)
Field: Materials Science — Biomaterials

Engineering supramolecular peptide nanofibers for in vivo platelet-hitchhiking beyond ligand-receptor recognition Ex vivo or in vivo cell-hitchhiking has emerged as a potential means for efficient drug delivery and various disease therapies. However, many challenges remain, such as the complicated engineering process and dependence on ligand-receptor interaction. Here, we present a simple in vivo platelet-hitchhiking strategy based on self-assembling peptides without ligand modification. The engineered peptide nanofibers can hitchhike ultrafast (<5 s) and efficiently on both resting and activated platelets in a receptor-independent and species-independent manner. Mechanistic studies showed that unique secondary structure of nanofibers, which lead to surface exposure of hydrophobic and hydrogen bond-forming groups, might primarily contribute to the selective and efficient platelet-hitchhiking behavior. After intravenous injection, these peptide nanofibers hitchhiked in situ on circulating platelets and achieved almost 20-fold lung accumulation. Our study provides not only a different paradigm of in vivo platelet-hitchhiking beyond ligand-receptor recognition but also a potential strategy for lung-targeted drug delivery and pulmonary disease therapy. In vivo ; Nanofiber ; Ligand (biochemistry) ; Ex vivo ; Platelet ; Biophysics ; Receptor ; Peptide ; Chemistry ; Cell biology ; Drug delivery ; Nanotechnology ; Pharmacology ; Biology ; Materials science ; Biochemistry ; Immunology ; Biotechnology Supramolecular Self-Assembly in Materials ; RNA Interference and Gene Delivery ; Dendrimers and Hyperbranched Polymers
Authors: Pabitra Mohan Mahapatra | Dipransu Pradhan | Sachin Kumar | Achyut Kumar Panda
Source: Circular Economy (article, 2024-08-28)
Field: Materials Science — Materials Chemistry

Isothermal pyrolysis of discarded bakelite: Kinetics analysis and batch pyrolysis studies Plastic is widely used, leading to an increase in plastic waste in the environment and resulting in pollution. Plastic waste can currently be managed differently and reduced by converting it into useful products via different methods. The extensive use of thermosetting polymers such as bakelite, which are nonrecyclable, has led to an increase in bakelite scrap and pollution. Therefore, minimizing pollution due to such waste requires sustainable, modern, eco-friendly, and economical recycling technology and the upgrading of existing recycling technology. This work reports the recycling of discarded bakelite through pyrolysis and a kinetic study of the isothermal pyrolysis of bakelite via model fitting methods as well as product analyses. Therefore, isothermal degradation experiments for discarded bakelite were carried out at different temperatures (300, 350, 400, 450, and 500 °C) for 2 h. The isothermal degradation of bakelite follows the D 1 -diffusion model fitting method, with an activation energy ( E a ) of 17.178 kJ/mol and an Arrhenius constant ( A ) of 0.095 min −1 . The kinetic information provided throughout the research will aid in the development of an appropriate reactor for the valorization of discarded bakelite. Batch pyrolysis of bakelite gives the highest yield of 39.12% pyrolytic waxy oil at 450 °C. The presence of components such as alkanes, cycloalkenes, alkenes, alcohols, ethers, and aromatic compounds in the pyrolytic waxy oil and residue was confirmed by FTIR and GC‒MS analysis. Pyrolysis ; Isothermal process ; Kinetics ; Chemical engineering ; Materials science ; Thermodynamics ; Chemistry ; Organic chemistry ; Engineering ; Physics Thermal and Kinetic Analysis ; Thermochemical Biomass Conversion Processes ; Iron and Steelmaking Processes
Authors: Marta Perxés Perich | C. R. O'Connor | Koen M. Draijer | Nienke L. Visser | Nongnuch Artrith | C. Reece | Petra E. de Jongh | Jessi E. S. van der Hoeven
Source: Journal of Materials Chemistry A (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

<i>In situ</i> analysis of gas dependent redistribution kinetics in bimetallic Au-Pd nanoparticles The catalytic and plasmonic properties of bimetallic gold-palladium (Au-Pd) nanoparticles (NPs) critically depend on the distribution of the Au and Pd atoms inside the nanoparticle bulk and at the surface. Under operating conditions, the atomic distribution is highly dynamic. Analyzing gas induced redistribution kinetics at operating temperatures is therefore key in designing and understanding the behavior of Au-Pd nanoparticles for applications in thermal and light-driven catalysis, but requires advanced <i>in situ</i> characterization strategies. In this work, we achieve the <i>in situ</i> analysis of the gas dependent alloying kinetics in bimetallic Au-Pd nanoparticles at elevated temperatures through a combination of CO-DRIFTS and gas-phase <i>in situ</i> transmission electron microscopy (TEM), providing direct insight in both the surface- and nanoparticle bulk redistribution dynamics. Specifically, we employ a well-defined model system consisting of colloidal Au-core Pd-shell NPs, monodisperse in size and uniform in composition, and quantify the alloying dynamics of these NPs in H<sub>2</sub> and O<sub>2</sub> under isothermal conditions. By extracting the alloying kinetics from <i>in situ</i> TEM measurements, we show that the alloying behavior in Au-Pd NPs can be described by a numerical diffusion model based on Fick's second law. Overall, our results indicate that exposure to reactive gasses strongly affects the surface composition and surface alloying kinetics, but has a smaller effect on the alloying dynamics of the nanoparticle bulk. Both our <i>in situ</i> methodology as well as the quantitative insights on restructuring phenomena can be extended to a wider range of bimetallic nanoparticle systems and are relevant in understanding the behavior of nanoparticle catalysts under operating conditions. Bimetallic strip ; Redistribution (election) ; Kinetics ; In situ ; Nanoparticle ; Materials science ; Chemistry ; Chemical engineering ; Nanotechnology ; Catalysis ; Physics ; Engineering ; Political science ; Organic chemistry Catalytic Processes in Materials Science ; nanoparticles nucleation surface interactions ; Advanced Chemical Physics Studies
Authors: Ashes Rakshit | Dipankar Biswas | Rittwick Mondal | Soumyajyoti Kabi | Debasish Roy
Source: Physica B Condensed Matter (article, 2024-10-05)
Field: Materials Science — Ceramics and Composites

Electrical conduction and optical characteristics of Li2O and Bi2O3 Co-doped zinc-phosphate glassy nanocomposites: A critical observation of mixed ionic electronic effect Materials science ; Nanocomposite ; Ionic bonding ; Doping ; Zinc ; Ionic conductivity ; Zinc phosphate ; Phosphate ; Thermal conduction ; Phosphate glass ; Ionic liquid ; Nanotechnology ; Condensed matter physics ; Optoelectronics ; Composite material ; Physical chemistry ; Ion ; Electrode ; Organic chemistry ; Chemistry ; Electrolyte Glass properties and applications ; Luminescence Properties of Advanced Materials ; Crystal Structures and Properties