jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Raymart B. Balakit | Acer Jay G. Castillo | Christian Julius R. Garcia | Ma. Caira Gail M. Libang | Joshua S. Mallapre | Anthony D. Navarro | Rosemarie L. Pangyarihan | Krisha Mae N. Pariño | Erecha B. Wenceslao | Rose Anne L. Reaño
Source: PUP Journal of Science and Technology (article, 2024-02-16)
Field: Chemistry — Analytical Chemistry

SB21: DEVELOPMENT OF PORTABLE WATERMELON RIPENESS DETECTOR USING NEAR-INFRARED SPECTROSCOPY (NIRS)AND ACOUSTICS ANALYSIS Watermelon is one of the toughest fruits to distinguish if it is ripe, unripe, or overripe. Its quality must be monitored to improve its commercial viability and profitability. Manual procedures deploy tapping, color examination, and approximate the number of days to determine its maturity stage. These are useful, but their accuracy and precision are constrained since they rely on assumptions. This research aims to develop a non- destructive method of identifying watermelon maturity in the Sugar Baby variety through Acoustics Analysis and Spectral Identification using Fast Fourier Transform and Near-Infrared Spectroscopy (NIRS). A portable and automated device is built, which includes operations such as detecting sound and internal content quality using a NIRS sensor and microphone, analyzing the wavelength and frequencies collected, and interpreting the results per the standard values provided. The K-Nearest Neighbor approach is applied in which altered signals are computed, compared, and voted on. Three hundred (300) watermelon samples were assessed, wherein two hundred ten (210) were used for standardization, seventy-five (75) for testing and assessment, and fifteen (15) for repeatability. In addition, thirty (30) cohorts were polled to rate the device's efficacy. Based on the findings, combining NIRS and Fast Fourier Transform showed that the ripeness condition of watermelon can be readily identified with high accuracy. Additionally, the data indicated that the device is reproducible and that the human and automated approaches differed significantly. With an overall accuracy of 90.7%, the automated watermelon ripeness detector outperformed the manual detection method. Ripeness ; Detector ; Acoustics ; Infrared ; Near-infrared spectroscopy ; Spectroscopy ; Materials science ; Optics ; Physics ; Chemistry ; Food science Spectroscopy and Chemometric Analyses
Authors: Nabiha R. Syed | Nafisa B. Masud | Colin A. Smith
Source: Magnetic Resonance (article, 2024-08-19)
Field: Chemistry — Spectroscopy

Analysis of chi angle distributions in free amino acids via multiplet fitting of proton scalar couplings Scalar couplings are a fundamental aspect of nuclear magnetic resonance (NMR) experiments and provide rich information about electron-mediated interactions between nuclei. <sup>3</sup> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>J</mml:mi></mml:mrow> </mml:math> couplings are particularly useful for determining molecular structure through the Karplus relationship, a mathematical formula used for calculating <sup>3</sup> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>J</mml:mi></mml:mrow> </mml:math> coupling constants from dihedral angles. In small molecules, scalar couplings are often determined through analysis of one-dimensional proton spectra. Larger proteins have typically required specialized multidimensional pulse programs designed to overcome spectral crowding and multiplet complexity. Here, we present a generalized framework for fitting scalar couplings with arbitrarily complex multiplet patterns using a weak-coupling model. The method is implemented in FitNMR and applicable to one-dimensional, two-dimensional, and three-dimensional NMR spectra. To gain insight into the proton-proton coupling patterns present in protein side chains, we analyze a set of free amino acid one-dimensional spectra. We show that the weak-coupling assumption is largely sufficient for fitting the majority of resonances, although there are notable exceptions. To enable structural interpretation of all couplings, we extend generalized and self-consistent Karplus equation parameterizations to all <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>χ</mml:mi></mml:math> angles. An enhanced model of side-chain motion incorporating rotamer statistics from the Protein Data Bank (PDB) is developed. Even without stereospecific assignments of the beta hydrogens, we find that two couplings are sufficient to exclude a single-rotamer model for all amino acids except proline. While most free amino acids show rotameric populations consistent with crystal structure statistics, beta-branched valine and isoleucine deviate substantially. Multiplet ; Dihedral angle ; Conformational isomerism ; Scalar (mathematics) ; Coupling constant ; Proton ; Spectral line ; Physics ; J-coupling ; Chemistry ; Computational chemistry ; Molecule ; Molecular physics ; Quantum mechanics ; Mathematics ; Hydrogen bond ; Geometry Molecular spectroscopy and chirality ; Advanced NMR Techniques and Applications ; Protein Structure and Dynamics
Authors: Bahman Zohuri | Farhang Mossavar-Rahmani
Source:  (article, 2024-07-16)
Field: Materials Science — Materials Chemistry

Navigating the Nuclear Renaissance Economic Viability, Zero Emissions, and the Future of Nuclear Energy with Generation IV Reactors and SMRs with Artificial Intelligence Integration As global efforts intensify to combat climate change and achieve sustainable energy goals, nuclear power is re-emerging as a vital component of the energy mix. This article explores modern nuclear technologies' economic and environmental potential, focusing on the nuclear fuel cycle, Generation IV reactors, Small Modular Reactors (SMRs), and the transformative role of Artificial Intelligence (AI). The nuclear fuel cycle, encompassing fuel production, utilization, and disposal, is evolving to become more efficient and sustainable, reducing costs and environmental impacts. Generation IV reactors and SMRs represent significant advancements, offering enhanced safety, efficiency, and flexibility, making nuclear power more accessible and adaptable. AI integration revolutionizes nuclear operations by optimizing performance, predictive maintenance, and safety monitoring. These technologies collectively enhance nuclear power's economic viability and environmental benefits, positioning it as a cornerstone of global zero-emission strategies. The return on involvement in nuclear energy is substantial, driven by economic growth, energy security, and technological advancements. Continued investment and innovation in these areas are essential for realizing the full potential of nuclear energy in a sustainable and carbon-neutral future. This article underscores the importance of nuclear power in achieving global climate objectives and fostering a sustainable energy landscape. The Renaissance ; Zero emission ; Zero (linguistics) ; Nuclear engineering ; Nuclear transmutation ; Engineering ; Political science ; Environmental science ; Nuclear physics ; Waste management ; Art ; Art history ; Physics ; Philosophy Graphite, nuclear technology, radiation studies ; Economic and Technological Developments in Russia ; Global Energy and Sustainability Research
Authors: Baljit Singh Bhathal Singh
Source: Journal of Mechanical Engineering (article, 2024-11-15)
Field: Materials Science — Materials Chemistry

AI-Enhanced Generative Design for Efficient Heat Exchangers in Thermoelectric Generators: Revolutionizing Waste Heat Recovery in Thermoelectricity Thermoelectric generators (TEGs) offer the potential for converting waste heat into electricity, but their efficiency, particularly at low temperatures, remains inadequate. Plate-Fin Heat Exchangers (PFHEs) in TEG systems are not fully optimized, resulting in limited efficiency and applicability. The low conversion efficiency of TEGs means only a small fraction of waste heat is utilized, posing challenges to their long-term viability. While Genetic Algorithms (GAs) have shown promise in optimizing heat exchanger designs, advanced methods like Non-dominated Sorting Genetic Algorithm II (NSGAII) have yet to be fully applied for PFHE TEG design. This study addresses these challenges by using NSGA-II, combined with a semi-empirical model, to optimize PFHE design in TEG systems. The optimization focuses on refining fin design parameters such as number, width, and height while adhering toconstraints on fin area and pressure drop. The optimized design achieved a 3.94% increase in output power and a 1.72% increase in efficiency at 373.15 K, with conversion efficiency rising by 154.74% and maximum output power by 549.64% at 428.15 K. In conclusion, this research bridges the gap by applying NSGA-II to enhance PFHE design in TEGs, significantly improving performance and sustainability. Future work will explore alternative models and further optimization to achieve even higher efficiencies. Thermoelectric generator ; Heat exchanger ; Sorting ; Process engineering ; Waste heat recovery unit ; Computer science ; Materials science ; Waste heat ; Pressure drop ; Automotive engineering ; Optimal design ; Electricity generation ; Thermoelectric effect ; Power (physics) ; Environmental science ; Mechanical engineering ; Engineering ; Thermodynamics ; Algorithm Advanced Thermoelectric Materials and Devices ; Heat Transfer and Optimization ; Advanced Multi-Objective Optimization Algorithms
Authors: Pratyay Ghosh
Source: Israel Journal of Chemistry (article, 2024-01-30)
Field: Materials Science — Materials Chemistry

Ising Spins on Frustrated Bronze‐Mean Hexagonal Quasicrystal Abstract We investigate the Ising model on the Bronze‐mean hexagonal quasicrystal (BMH QC), an aperiodic tiling with geometric frustration. Our extensive Monte Carlo simulations explore the model's rich phase diagram, revealing six distinct phases with diverse magnetic properties and degrees of frustration. We uncover exotic spin glass phases, signaled by the replica symmetry breaking and slow relaxation dynamics. We shed light on the intriguing magnetic properties of frustrated quasicrystals and open new avenues for studying exotic phases in condensed matter physics. Frustration ; Quasicrystal ; Phase diagram ; Spin glass ; Condensed matter physics ; Spins ; Ising model ; Geometrical frustration ; Hexagonal crystal system ; Aperiodic graph ; Relaxation (psychology) ; Symmetry breaking ; Symmetry (geometry) ; Monte Carlo method ; Chemistry ; Physics ; Phase (matter) ; Quantum mechanics ; Crystallography ; Geometry ; Combinatorics ; Psychology Quasicrystal Structures and Properties ; Theoretical and Computational Physics ; Archaeology and Rock Art Studies
Authors: Débora P. Schmitz | Beatriz S. Cunha | Bluma G. Soares
Source: Journal of Vinyl and Additive Technology (article, 2024-08-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Effect of melt‐processing conditions on the electrical conductivity and microwave absorbing properties of composites based on clean scrap poly(vinylidene fluoride/ethylene vinyl acetate copolymer and graphene nanoplatelets Abstract Clean scrap polyvinylidene fluoride (rPVDF) from industrial reject was compounded with ethylene vinyl acetate (EVA) copolymer and graphene nanoplatelets (GNP) to produce low cost and scalable conductive composites. The effect of the melt processing conditions (temperature, time, and rotor speed) on the electrical conductivity and microwave absorbing (MWA) properties was investigated. All systems presented co‐continuous morphology indicated by scanning electron microscopy (SEM) and selective extraction experiments. The preferential localization of GNP in the EVA phase was evidenced by selective extraction and thermogravimetric analysis (TGA). Higher conductivity value was observed for the composite processed at 210°C for 3 min at a rotor speed of 200 rpm. The MWA performance of monolayer and bilayer composite structures with 2 mm thickness was investigated in terms of minimum reflection loss (RL) and effective absorption bandwidth (EAB). The bilayer system provided the best MWA response with RL = − 43.1 dB (&gt;99.99% of EM attenuation) when prepared at 190°C for 3 min at a rotor speed of 200 rpm. The ecological and environmental importance of finding new applications for plastic waste, and the low cost of the materials and processing make this composite an interesting candidate for MWA purpose. Highlights Promising application of clean scrap polyvinylidene fluoride (PVDF) in microwave absorbing materials; Conductivity and absorbing performance are affected by processing conditions; Co‐continuous structure of rPVDF/EVA blend influenced by graphene nanoplatelets (GNP); Selective localization of GNP in EVA phase; Outstanding microwave absorption properties achieved with bi‐layer structure. Materials science ; Polyvinylidene fluoride ; Composite material ; Ethylene-vinyl acetate ; Composite number ; Reflection loss ; Vinyl acetate ; Thermogravimetric analysis ; Copolymer ; Chemical engineering ; Polymer Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Dielectric materials and actuators
Authors: Adrian Wee Wen Ong | Steve Yueran Cao | Lai Wah Chan | Jiaqing Lim | L. C. Kwek
Source: Journal of Chemical Theory and Computation (article, 2024-12-18)
Field: Chemistry — Spectroscopy

Geometry-Corrected Quadratic Optimization Algorithm for NDDO-Descendant Semiempirical Models The long-held assumption that the optimization of parameters for NDDO-descendant semiempirical methods may be performed without precise geometry optimization is assessed in detail; the relevant equations for the analytical evaluation of the geometry-corrected derivatives of molecular properties that account for changes in the optimum geometry are then presented. The first and second derivatives calculated from our implementation of MNDO are used for a limited reparameterization of 1,113 CHNO molecules taken from the PM7 training set, demonstrating an improvement over the PARAM program used in the optimization of parameters for the PMx methods. MNDO ; Descendant ; Computer science ; Set (abstract data type) ; Quadratic equation ; Algorithm ; Energy minimization ; Geometry ; Optimization algorithm ; Mathematical optimization ; Mathematics ; Molecule ; Computational chemistry ; Physics ; Chemistry ; Programming language Analytical Chemistry and Chromatography ; Mass Spectrometry Techniques and Applications ; Machine Learning in Materials Science
Authors: Yumi Kwon | Jongmin Jacob Woo | Fengchao Yu | Sarah Williams | Lye Meng Markillie | Ronald Moore | Ernesto Nakayasu | Jing Chen | Martha Campbell‐Thompson | Clayton E. Mathews | Alexey I. Nesvizhskii | Weijun Qian | Ying Zhu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-03-04)
Field: Chemistry — Spectroscopy

Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis. Proteome ; Computational biology ; Label-free quantification ; Proteomics ; Mass spectrometry imaging ; Mass spectrometry ; Workflow ; Identification (biology) ; Computer science ; Quantitative proteomics ; Biology ; Chemistry ; Bioinformatics ; Biochemistry ; Chromatography Advanced Proteomics Techniques and Applications ; Single-cell and spatial transcriptomics ; Cell Image Analysis Techniques
Authors: Tomasz N. Kołtunowicz
Source: Energies (article, 2024-06-03)
Field: Materials Science — Materials Chemistry

Dielectric Insulation in Medium- and High-Voltage Power Equipment—Degradation and Failure Mechanism, Diagnostics, and Electrical Parameters Improvement The proper operation of medium- and high-voltage power equipment is greatly affected by the degradation of its insulation [...] Degradation (telecommunications) ; Dielectric ; Materials science ; Mechanism (biology) ; Electrical engineering ; Failure mechanism ; High voltage ; Power (physics) ; Voltage ; Engineering physics ; Optoelectronics ; Composite material ; Engineering ; Physics High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Power Transformer Diagnostics and Insulation
Authors: Wahyuaji Narottama Putra | Myrna Ariati | Bambang Suharno | Sri Harjanto | Ghiska Ramahdita
Source: Evergreen (article, 2024-06-01)
Field: Materials Science — Materials Chemistry

The Effect of Sodium Dodecyl Benzene Sulphonate Addition in Carbon Nanotube-Based Nanofluid Quenchant for Carbon Steel Heat Treatment Nanofluid is widely researched as it has a superior thermal characteristics. It is synthesized by adding a nano-sized particle with high thermal conductivity in the base fluid. The particle addition would increase the overall thermal conductivity of the fluid. Because of its thermally enhanced characteristics, nanofluid is commonly utilized for thermal transfer applications. However, agglomeration could hinder the dispersion of the particle in the fluid. To improve the nanoparticle dispersion, surfactant is commonly added. In heat treatment, nanofluid can be used as a quench medium. This research used a Multiwalled Carbon nanotube (MWCNT) as the nanoparticle, ranging from 0.1, 0.3, and 0.5% w/v. Sodium Dodecyl Benzene Sulphonate (SDBS) was added as the surfactant with a 0 – 30% w/v concentration. Higher concentrations of SDBS create better stability, as shown in Zeta Potential at -71.2 mV. The thermal conductivity was increased to 0.68 W/mK by adding 0.5% MWCNT and 3% SDBS. S45C medium carbon steel was quenched in the nanofluid and achieved a maximum hardness of 40 HRC at the addition of 0.3% MWCNT and 5% SBDS. Excessive addition of SDBS surfactant could decrease the thermal conductivity and steel hardness, even though the stability was better. Nanofluid ; Carbon nanotube ; Benzene ; Sodium ; Materials science ; Carbon fibers ; Chemical engineering ; Chemistry ; Nanotechnology ; Composite material ; Organic chemistry ; Metallurgy ; Nanoparticle ; Composite number Diamond and Carbon-based Materials Research ; Petroleum Processing and Analysis ; Advanced materials and composites
Authors: C. W. Song | Yan Zhang
Source: General Physiology and Biophysics (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Down-regulated miR-10a protects against spinal cord injury by up-regulating SIRT1 MicroRNAs (miRNAs) are essential modulators of gene expression and are associated with various pathological processes, including spinal cord injury (SCI). This investigation aimed to elucidate miR-10a activity in SCI and its potential interaction with sirtuin 1 (SIRT1). The SCI rat model was established to assess hind limb movement, measure levels of miR-10a, SIRT1, neuronal survival, and inflammatory factors. An in-vitro SCI cell model was also developed to evaluate cell viability and inflammatory factor levels. The interaction between miR10a and SIRT1 was verified. Upregulated miR-10a and downregulated SIRT1 expression were found in the tissues of SCI rats. miR-10a knockdown in SCI rats enhanced the recovery of motor function, increased neuronal survival, and reduced the levels of inflammatory cytokines. Luciferase reporter assays confirmed that miR-10a targeted SIRT1 directly. In PC12 cells, downregulation of miR-10a increased SIRT1 expression, enhanced cell viability, and reduced inflammatory factor levels after LPS stimulation. Conversely, SIRT1 knockdown inhibited the protective effects of downregulated miR-10a on cell viability and inflammatory responses. The results suggest that miR-10a downregulation protects against SCI by upregulating SIRT1 expression, improving functional recovery, and reducing inflammation. Targeting the miR-10a/SIRT1 axis is a promising strategy for SCI treatment. Downregulation and upregulation ; Gene knockdown ; Sirtuin 1 ; Viability assay ; Spinal cord injury ; Cell biology ; microRNA ; Chemistry ; Cell ; Spinal cord ; Biology ; Cancer research ; Neuroscience ; Apoptosis ; Biochemistry ; Gene Conducting polymers and applications ; Spinal Cord Injury Research ; Nerve injury and regeneration
Authors: Ina Heckelmann | Mathieu Bertrand | Andres Forrer | Mehran Shahmohammadi | Mattias Beck | Jérôme Faist
Source: Applied Physics Letters (article, 2024-05-06)
Field: Chemistry — Spectroscopy

Measurement of sub-Poissonian shot noise in a quantum cascade detector In a Quantum Cascade Detector, photocurrent is generated by the absorption of infrared and terahertz radiation in the quantum-well-based modules arranged in series. Consequently, the current responsivity is by construction inversely proportional to the number of cascading modules. Upon absorption of a photon, the electron travels through only a single period of the detector, with a mean free path corresponding to the period length. Therefore, the shot noise power density is expected to decrease by the same factor under sufficiently high illumination, reflecting the same inverse relationship with the number of cascading modules. This phenomenon leads to sub-Poissonian noise characteristics. We experimentally observe this effect in a 90-period Quantum Cascade Detector operating at 4.5 μm, confirming a reduction in the shot noise contribution by the anticipated Fano factor of 1/90. This measurement underscores the suitability of these detectors for coherent detection scenarios, particularly where shot noise dominates. Cascade ; Detector ; Shot noise ; Physics ; Noise (video) ; Quantum ; Quantum noise ; Shot (pellet) ; Single shot ; Optoelectronics ; Optics ; Materials science ; Quantum mechanics ; Computer science ; Chemistry Spectroscopy and Laser Applications ; Advanced Fiber Laser Technologies ; Atmospheric Ozone and Climate