jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: D. Castro‐Reigía | A. I. Martín-García | S. Sanllorente | M.C. Ortiz | L.A. Sarabia
Source: Applied Sciences (article, 2025-04-26)
Field: Chemistry — Analytical Chemistry

Detection of Nutrients and Contaminants in the Agri-Food Industry Evaluating the Probabilities of False Compliance and False Non-Compliance Through PLS Models and NIR Spectroscopy NIR spectroscopy has become one of the most prominent techniques in the food industry due to its easy and fast use. Coupled with PLS, it is a well-established method for determining nutrients, contaminants, or adulterants in foods. Nevertheless, it is not common when calculating the capability of detection or discrimination given a target/permitted value, providing probabilities of false non-compliance (α) or false compliance (β). That is exactly the main purpose of this work, where a single procedure using the accuracy line to evaluate these figures of merit by generalizing ISO 11843 when using NIR-PLS in real scenarios in agri-food industries is shown. Nevertheless, it is a completely general procedure and can be used in any analytical context in which a PLS calibration is applied. As an example of its versatility, several analytical determinations were performed using different common food matrices in the agri-food industry (butter, flour, milk, yogurt, oil, and olives) for the quantification of protein, fat, salt, and two agrochemicals. Some results were a detection capability of 5.2% of fat in milk, 1.20 mg kg−1 for diflufenican, and 2.34 mg kg−1 for piretrin in olives when maximum limits were established at 5%, 0.6 mg kg−1, and 0.5 mg kg−1 respectively. Also, 1.02% for salt in butter and 11.45%, 3.78%, and 2.65% for protein in flour, milk, and yogurt, respectively, were obtained when minimum limits were established at 1.2%, 12%, 4%, and 3% respectively. In all cases α = β = 0.05. Compliance (psychology) ; Environmental science ; Contamination ; Nutrient ; Business ; Chemistry ; Psychology ; Social psychology ; Ecology ; Biology Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Pesticide Residue Analysis and Safety
Authors: Daniel Marx | Ivan Gligonov | Oleksii Nevskyi | David Malsbenden | Dominik Wöll | Jörg Enderlein
Source: ArXiv.org (article, 2025-01-01)
Field: Chemistry — Spectroscopy

Mapping complex optical light field distributions with single fluorescent molecules Single fluorescent molecules, behaving as ideal electric dipole emitters, are powerful nanoscopic probes of complex optical fields. Here, this property is exploited to precisely map the polarization and vectorial structure of tightly focused laser beams, utilizing both linear and circular polarization states. The resulting three-dimensional fluorescence excitation maps strikingly reveal the intrinsic chiral and non-chiral structure of the light field, in perfect quantitative agreement with a full vectorial wave-optical model. This precise correspondence not only enables the reliable determination of absolute molecular orientations but also allows for the accurate characterization of the field's properties. These results fundamentally advance our understanding of light-matter interaction at the single-molecule level and open new avenues for characterizing complex light fields, with broad applications in super-resolution microscopy and nanophotonics. Excitation ; Polarization (electrochemistry) ; Nanoscopic scale ; Fluorescence ; Dipole ; Characterization (materials science) ; Microscopy ; Electric field Molecular spectroscopy and chirality ; Spectroscopy and Quantum Chemical Studies ; Photoreceptor and optogenetics research
Authors: Tian-Hui Ma | Yizu Zou | Zihao Chen | Iqra Afzal | Doudou Wang | Depeng Kong | Li Ma | ­Jun Li­
Source:  (preprint, 2025-04-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Resonant chiroptical effects in all-dielectric metasurface with monoclinic lattices for terahertz sensing applications Over recent years, chiral metasurfaces have emerged as pivotal platforms for ultrasensitive biosensing, particularly in detecting and identifying chiral biochemical samples. However, the excitation of chiroptical responses in conventional chiral metasurfaces predominantly rely on intricate asymmetric meta-atoms or elaborate geometric configurations, which complicate fabrication process and limit scalability. Here, we report an all-dielectric chiral metasurface consisting of an array of circular air-hole in monoclinic lattice. By breaking in-plane mirror symmetries through introducing side-length differences δ and changing lattice angle θ, the proposed metasurface achieves strong intrinsic chirality, yielding an enhanced circular dichroism (CD) signal with a simulated peak value of 0.89 at 0.254THz and a quality factor of ~50.4. Theoretical analyses of induced electromagnetic fields reveal that the observed chiroptical responses originate from spin-selective multipole excitations and localized field enhancements, where the left-handed circularly polarized (LCP) waves exhibit significantly stronger optical chirality (C_E=251) than that of the right-handed circularly polarized (RCP) waves. Experimental validations based on the fabricated sample and terahertz characterization confirm the excitation of resonant CD signals with peak value of ~0.52 around 0.25THz. Furthermore, we demonstrate practical biosensing capabilities of the proposed chiral metasurface by detecting bovine serum albumin (BSA) samples with different concentrations, which manifests good sensing performances including high sensitivity (0.023(mg/mL)^(-1)) and wide detection range (0.3-50 mg/mL). This work paves a new avenue for designing chiral metasurfaces with simple structures but high-performance, advancing practical applications in label-free biosensing and chiral nanophotonics. Terahertz radiation ; Monoclinic crystal system ; Dielectric ; Materials science ; Optoelectronics ; Dielectric response ; Nanotechnology ; Physics ; Quantum mechanics ; Molecule Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Quantum Mechanics and Non-Hermitian Physics
Authors: Dimitrios S. Kasampalis | Pavlos Tsouvaltzis | Anastasios S. Siomos
Source: Horticulturae (article, 2025-06-10)
Field: Chemistry — Analytical Chemistry

Assessment of Melon Fruit Nutritional Composition Using VIS/NIR/SWIR Spectroscopy Coupled with Chemometrics The objective of this study was to evaluate the feasibility of using visible, near-infrared, and short-wave infrared (VIS/NIR/SWIR) spectroscopy coupled with chemometrics for non-destructive prediction of nutritional components in Galia-type melon fruit. A total of 175 fully ripened melons were analyzed for soluble solids content (SSC), dry matter (DM), pH, and titratable acidity (TA) using partial least squares regression (PLSR), principal components regression (PCR), and multilinear regression (MLR) models. Reflectance spectra were captured at three fruit locations (pedicel, equatorial, and blossom end) in the 350–2500 nm range. The PLSR models yielded the highest accuracy, particularly for SSC (R = 0.80) and SSC/TA (R = 0.79), using equatorial zone data. Variable selection using the genetic algorithm (GA) successfully identified the spectral regions critical for each nutritional parameter at the pedicel, equatorial, and blossom end areas. Key wavelengths for SSC were found around 670–720 nm and 900–1100 nm, with important wavelengths for pH prediction located near 1450 nm, and, for dry matter, in the ranges 1900–1950 nm. Variable importance in projection (VIP) analysis confirmed that specific wavelengths between 680 and 720 nm, 900 and 1000 nm, 1400 and 1500 nm, and 1900 and 2000 nm were consistently critical in predicting the SSC, DM, and SSC/TA ratio. The highest VIP scores for SSC prediction were noted around 690 nm and 950 nm, while dry matter prediction was influenced most by wavelengths in the 1450 nm to 1950 nm range. This study demonstrates the potential of VIS/NIR/SWIR spectroscopy for rapid, non-destructive melon quality assessment, with implications for commercial postharvest management. Chemometrics ; Melon ; Chemistry ; Composition (language) ; Chemical composition ; Fruit juice ; Food science ; Spectroscopy ; Horticulture ; Chromatography ; Biology ; Organic chemistry Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: 崔家学 Cui Jiaxue | 李政涛 Li Zhengtao | 徐邦联 Xu Banglian | 张大伟 Zhang Dawei | 廖信清 Liao Xinqing | 金宇辉 Jin Yuhui | 薛一川 Xue Yichuan
Source: Laser & Optoelectronics Progress (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

基于红外光谱的燃油组分检测技术研究进展 本文对红外光谱技术在汽油、柴油和喷气燃料组分检测中的研究进展进行了详细的介绍。首先介绍两种常用红外光谱仪器的基本结构和检测原理，进而阐述了适用于燃油组分分析的数据建模和预测分析方法，探讨了红外光谱技术在汽油辛烷值、甲醇、乙醇含量以及柴油十六烷值、甲醇、乙醇含量等检测中的应用，同时对喷气燃料的闪点、馏程、密度、初馏点等关键物理性质的红外光谱测定方法进行了介绍，并评估了各种建模方法和优化算法的效果，展示了红外光谱在提升燃油质量和环保性能方面的潜力。利用红外光谱技术可以实现燃油多组分的快速检测，未来通过与人工智能技术的结合，有望不断提升模型的预测精度和扩展预测范围，显示出十分显著的发展前景。 Computer science Spectroscopy and Chemometric Analyses
Authors: Gustavo Santiago | Amanda de Freitas Wendt | Pietra Costa Putarov | Telmo Pereira | Ignacio A. Ciampitti
Source: ChemRxiv (preprint, 2025-06-11)
Field: Chemistry — Analytical Chemistry

Estimating Total Polyphenol Content of Ilex paraguariensis Water Extracts Using Colorimetric Methods and Machine Learning Ilex paraguariensis contains numerous bioactive compounds and is a form of social interaction in many countries. Yerba mate beverages generally contain higher total polyphenol content (TPC) compared to other plant-based drinks, with hot water-extracted mate offering a higher amount of polyphenol intake, highlighting its importance as a source of antioxidants. For TPC quantification, the colorimetric method using smartphones combined with the Folin-Ciocalteu (FC) assay has been employed for a low-cost and rapid evaluation in different products. However, this approach relies on the FC assay, limiting this method’s accessibility due to the reagent costs and equipment involved. Following this rationale, the objective of this study was to use machine learning models to correlate the color of hot water extracts of Ilex paraguariensis with total polyphenol content. The color must be obtained using a smartphone before starting the FC assay. Thirty samples of Ilex paraguariensis were subjected to three successive hot water extractions. Using a smartphone camera and a color box, the RGB and HSV color channels of the extracts were collected and used in various machine-learning models. While the Elastic Net achieved the best performance (a Relative Root Mean Square Error of 128.53 mg Gallic Acid Equivalent/L), the models' accuracy was constrained by the limited dataset. This approach offers a cost-effective and accessible alternative for TPC estimation, with potential applications in beverage quality control. Polyphenol ; Food science ; Chemistry ; Machine learning ; Mathematics ; Computer science ; Antioxidant ; Biochemistry Heavy Metals in Plants ; Metabolomics and Mass Spectrometry Studies ; Spectroscopy and Chemometric Analyses
Authors: David Debot | Giuseppe Marra
Source: ArXiv.org (preprint, 2025-10-07)
Field: Chemistry — Spectroscopy

Quantifying the Accuracy-Interpretability Trade-Off in Concept-Based Sidechannel Models Concept Bottleneck Models (CBNMs) are deep learning models that provide interpretability by enforcing a bottleneck layer where predictions are based exclusively on human-understandable concepts. However, this constraint also restricts information flow and often results in reduced predictive accuracy. Concept Sidechannel Models (CSMs) address this limitation by introducing a sidechannel that bypasses the bottleneck and carry additional task-relevant information. While this improves accuracy, it simultaneously compromises interpretability, as predictions may rely on uninterpretable representations transmitted through sidechannels. Currently, there exists no principled technique to control this fundamental trade-off. In this paper, we close this gap. First, we present a unified probabilistic concept sidechannel meta-model that subsumes existing CSMs as special cases. Building on this framework, we introduce the Sidechannel Independence Score (SIS), a metric that quantifies a CSM's reliance on its sidechannel by contrasting predictions made with and without sidechannel information. We propose SIS regularization, which explicitly penalizes sidechannel reliance to improve interpretability. Finally, we analyze how the expressivity of the predictor and the reliance of the sidechannel jointly shape interpretability, revealing inherent trade-offs across different CSM architectures. Empirical results show that state-of-the-art CSMs, when trained solely for accuracy, exhibit low representation interpretability, and that SIS regularization substantially improves their interpretability, intervenability, and the quality of learned interpretable task predictors. Our work provides both theoretical and practical tools for developing CSMs that balance accuracy and interpretability in a principled manner. Interpretability ; Bottleneck ; Probabilistic logic ; Flexibility (engineering) ; Task (project management) ; Metric (unit) ; Quality (philosophy) ; Representation (politics) Mass Spectrometry Techniques and Applications
Authors: Alsaid Ahmed Almetwally
Source: Scientific Reports (article, 2025-12-16)
Field: Materials Science — Polymers and Plastics

Multi-objective optimization of covering parameters for cotton/spandex core-spun yarn using grey relational analysis in conjunction with the Taguchi technique The growing need for high-performance stretchable fabrics led scientists to innovate a new spinning technique, especially for manufacturing cotton/spandex core-spun yarns. This type of yarn is spun by using spandex monofilament or multifilament as a core, which is surrounded by a sheath of staple cotton fibers. The key covering process parameters include spindle speed, delivery roller speed, spandex drafting ratio, spandex linear density, and tension level, which simultaneously influence the core-spun yarn characteristics such as tensile properties, hairiness index, imperfection index, and fabric aesthetic and performance properties. Fine-tuning these multiple covering parameters achieves optimal performance of these types of yarns. This paper aimed at employing multi-objective optimization for the covering parameters of cotton/spandex composite yarn to maximize the yarn tensile properties and minimize both hairiness and imperfection indices using the robust Taguchi technique in conjunction with the grey relational analysis. A full factorial design composed of three factors, namely spandex monofilament drafting ratio, linear density, and core-spun yarn twist multiplier, with five, four, and two levels, was conducted. Average values of the grey relational grades of all combinations were estimated, and its highest value refers to the optimal combinations of the controllable factors, which yield the best performance of cotton/spandex core-spun yarn. This study revealed that core-spun yarn with a 4.2 twist multiplier, a 44 dtex linear density of spandex monofilament, and a 4.4 drafting ratio of spandex yielded the optimal yarn performance characteristics. This study provides a methodological breakthrough with beneficial ramifications for the textile industry seeking a multi-objective optimization of core-spun yarn manufacturing parameters. Yarn ; Taguchi methods ; Grey relational analysis ; Spinning ; Ultimate tensile strength ; Linear density ; Tension (geology) ; Orthogonal array Textile materials and evaluations ; Dyeing and Modifying Textile Fibers ; Mechanical Behavior of Composites
Authors: Chuhang Li | Yang Wang | Yongbo Jiang | Shuiyuan Wang | Chunsen Liu | Peng Zhou
Source: National Science Open (article, 2025-11-01)
Field: Materials Science — Materials Chemistry

Ultrafast and stable flash memory with metal nanocrystals for logic-in-memory computing Flash memory, the dominant non-volatile memory technology, is essential for data-driven computing systems. With the growing demands of the information age, there is an urgent need to enhance both its operational speed and data retention capabilities. Consequently, developing highly reliable memory that combines ultrafast write/erase operations with long-term retention has become a critical research objective. Here, we demonstrate a floating-gate memory based on a discrete Pt nanocrystal/h-BN/MoS2 van der Waals heterostructure, which combines ultrafast operation with long-term reliability. The Pt nanocrystals formed via rapid thermal annealing (RTA) are spatially isolated and effectively suppress charge leakage through tunneling defects, enabling stable device operation. The device exhibits excellent performance metrics, including a high on-off ratio (>10<sup>6</sup>), ultrafast operational speed (20 ns), impressive retention time (>10<sup>5</sup> s), good endurance (>20000 cycles). Furthermore, configurable logic-in-memory circuits are constructed and logic function is achieved by tuning the conductance of the FG memory. Ultrashort pulse ; Data retention ; Flash memory ; Nanocrystal ; Non-volatile memory ; Quantum tunnelling ; Annealing (glass) ; Resistive random-access memory ; Computer data storage 2D Materials and Applications ; Ferroelectric and Negative Capacitance Devices ; Semiconductor materials and devices
Authors: Chanhyeong Kim | Jae-Young Her
Source: Food Science and Preservation (article, 2025-10-01)
Field: Materials Science — Biomaterials

Development and application of poly(butylene adipate-coterephthalate) composite film with copper oxide nanoparticles for prevention of greening in potatoes In this study, an eco-friendly packaging film was developed to inhibit light-induced greening in potatoes by incorporating various organic and inorganic fillers, such as copper oxide nanoparticles (CuONPs), zinc oxide nanoparticles, zinc basic salts, microcrystalline cellulose, nanocrystalline cellulose, and calcium–iron layered double hydroxides, into poly(butylene adipate-co-terephthalate) (PBAT) via solvent casting. Among these fillers, the PBAT film with CuONPs exhibited the lowest UV-visible light transmittance, especially at 450 nm, and was selected for further study. Three potato cultivars commonly distributed for processing in Korea (Superior, Duback, and Eunsun) were packaged with the CuONPs composite films. Neat PBAT film, commercial HDPE film, and unpackaged samples were used as controls. After 6 days of fluorescent light exposure, the CuONPs composite film significantly reduced color change (ΔE=7) in Duback and Eunsun, indicating effective greening inhibition. SEM and XRD analyses confirmed uniform CuONPs dispersion without altering PBAT crystallinity. FT-IR spectra revealed no chemical interaction, indicating physical incorporation. Mechanical testing showed no significant difference in tensile strength, elongation, or elastic modulus compared to neat PBAT, with tensile strength values comparable to those of commercial LDPE. The CuONPs composite film also exhibited favorable water vapor permeability (5.83×10−10 g · m/m2 · Pa · s), supporting its potential as a functional packaging material for light-sensitive produce like potatoes. Greening ; Composite number ; Zinc ; Ultimate tensile strength ; Nanoparticle ; Nanocrystalline material ; Copper ; Copper oxide Nanocomposite Films for Food Packaging ; Potato Plant Research ; Polymer-Based Agricultural Enhancements
Authors: Noor Asidah Mohamed
Source: Journal Of Agrobiotechnology (article, 2025-12-31)
Field: Chemistry — Inorganic Chemistry

Homology Modeling of Cu/Zn Superoxide Dismutase in Sweet Potato (Ipomoea batatas) Superoxide dismutase (SOD) is a ubiquitous antioxidant enzyme essential for protecting cells from damage caused by reactive oxygen species. While the role of SOD in plant stress tolerance, particularly in crops like Ipomoea batatas (Sweet Potato), is well-established but high-resolution experimental structure for its isoenzymes is still lacking. This study aimed to predict the three-dimensional structure of the Cu/Zn SOD in I. batatas using the homology modelling method. Here, we focus on Cu/Zn SOD because it is the dominant isoform in photosynthetically active tissues and provides the fastest catalytic efficiency, making it the primary defence against reactive oxygen species (ROS) in plant. The target sequence was retrieved from the NCBI database, and a suitable template was identified via sequence alignment with 88.16% sequence identity. The model was generated using SWISS-MODEL and subsequently validated using established tools, including Ramachandran analysis, MolProbity, global model evaluation and local model evaluation including GMQE (Global Model Quality Estimate) QMEANDisCo global score and QMEAN Z-score analysis. The structural models provided insights into key functional regions, including the metal-binding active sites. The Cu/Zn active site displayed a distorted tetrahedral geometry, which is essential for superoxide detoxification. Evaluation of the model generated confirmed that it exhibits high reliability, high stereochemical quality, correct folding and strong suitability. These findings provide valuable insights into the action and regulation Cu/Zn SOD of I. batatas and a foundation for guiding targeted enzyme engineering, enhancing our molecular understanding of stress resilience in sweet potato, and supporting future agrobiotechnology efforts. Understanding the structural features of Cu/Zn SOD enables identification of stability-enhancing or activity-boosting residues that can be targeted through gene editing or molecular breeding. Such insights support the development of sweet potato varieties with improved oxidative stress tolerance, higher resilience in changing climates, and better overall crop performance. Superoxide dismutase ; Homology modeling ; Isozyme ; Ramachandran plot ; Reactive oxygen species ; Enzyme ; Active site ; Gene isoform Metal-Catalyzed Oxygenation Mechanisms ; Photosynthetic Processes and Mechanisms ; Plant Gene Expression Analysis
Authors: A. Ousegui | Bernard Marcos
Source: Preprints.org (preprint, 2025-08-28)
Field: Chemistry — Inorganic Chemistry

Hydrogen Adsorption in Metal-Organic Framework: CFD Study and Parametric Optimization of the Process This study investigates hydrogen storage enhancement through adsorption in porous materials by coupling the Dubinin-Astakhov (D-A) adsorption model with H₂ conservation equations (mass, momentum, and energy). The resulting system of partial differential equations (PDEs) was solved numerically using the finite element method (FEM). Experimental work using activated carbon as an adsorbent was carried out to validate the model. The comparison showed good agreement in terms of temperature distribution, average pressure of the system, and the amount of adsorbed hydrogen (H₂). Further simulations with different adsorbents indicated that compact metal-organic framework (MOF-5) is the most effective material in terms of H₂ adsorption. Additionally, the pair (273 K, 800 s) remains the optimal combination of injection temperature and time. The findings underscore the prospective advantages of optimized MOF-5-based systems for enhanced hydrogen storage. These systems offer increased capacity and safety compared to traditional adsorbents. Subsequent research should investigate multi-objective optimization of material properties and system geometry, along with evaluating dynamic cycling performance in practical operating conditions. Additionally, experimental validation on MOF-5-based storage prototypes would further reinforce the model's predictive capabilities for industrial applications. Adsorption ; Parametric statistics ; Hydrogen ; Process (computing) ; Computational fluid dynamics ; Metal ; Metal-organic framework ; Process engineering ; Materials science ; Computer science ; Chemistry ; Thermodynamics ; Engineering ; Metallurgy ; Mathematics ; Organic chemistry ; Physics Metal-Organic Frameworks: Synthesis and Applications ; Catalytic Processes in Materials Science