jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Steve P. Meisburger | Nozomi Ando
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-01-16)
Field: Materials Science — Materials Chemistry

Scaling and merging macromolecular diffuse scattering with <i>mdx2</i> Diffuse scattering is a promising method to gain additional insight into protein dynamics from macromolecular crystallography (MX) experiments. Bragg intensities yield the average electron density, while the diffuse scattering can be processed to obtain a three-dimensional reciprocal space map, that is further analyzed to determine correlated motion. To make diffuse scattering techniques more accessible, we have created software for data processing called <i>mdx2</i> that is both convenient to use and simple to extend and modify. <i>Mdx2</i> is written in Python, and it interfaces with <i>DIALS</i> to implement self-contained data reduction workflows. Data are stored in NeXus format for software interchange and convenient visualization. <i>Mdx2</i> can be run on the command line or imported as a package, for instance to encapsulate a complete workflow in a Jupyter notebook for reproducible computing and education. Here, we describe <i>mdx2</i> version 1.0, a new release incorporating state-of-the-art techniques for data reduction. We describe the implementation of a complete multi-crystal scaling and merging workflow, and test the methods using a high-redundancy dataset from cubic insulin. We show that redundancy can be leveraged during scaling to correct systematic errors, and obtain accurate and reproducible measurements of weak diffuse signals. Computer science ; Workflow ; Python (programming language) ; Scaling ; Software ; Computational science ; Redundancy (engineering) ; Data reduction ; Algorithm ; Data mining ; Programming language Enzyme Structure and Function ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications
Authors: Yucheng Xu | Jia‐Qi Yang | Kebin Fan | Sheng Wang | Jingbo Wu | Caihong Zhang | De‐Chuan Zhan | Willie J. Padilla | Biaobing Jin | Jian Chen | Peiheng Wu
Source: arXiv (Cornell University) (preprint, 2024-05-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Physics-informed Inverse Design of Multi-bit Programmable Metasurfaces Emerging reconfigurable metasurfaces offer various possibilities in programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing great potential for enhancing terahertz applications. However, they are hindered by limited tunability, particularly evident in relatively small phase tuning over 270o, due to the design constraints with time-intensive forward design methodologies. Here, we demonstrate a multi-bit programmable metasurface capable of terahertz beam steering, facilitated by a developed physics-informed inverse design (PIID) approach. Through integrating a modified coupled mode theory (MCMT) into residual neural networks, our PIID algorithm not only significantly increases the design accuracy compared to conventional neural networks but also elucidates the intricate physical relations between the geometry and the modes. Without decreasing the reflection intensity, our method achieves the enhanced phase tuning as large as 300o. Additionally, we experimentally validate the inverse designed programmable beam steering metasurface, which is adaptable across 1-bit, 2-bit, and tri-state coding schemes, yielding a deflection angle up to 68o and broadened steering coverage. Our demonstration provides a promising pathway for rapidly exploring advanced metasurface devices, with potentially great impact on communication and imaging technologies. Bit (key) ; Inverse ; Physics ; Computer science ; Electronic engineering ; Mathematics ; Engineering ; Geometry Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Photonic and Optical Devices
Authors: Krzysztof Kacprzyk | Mihaela van der Schaar
Source: arXiv (Cornell University) (preprint, 2024-04-15)
Field: Materials Science — Materials Chemistry

Shape Arithmetic Expressions: Advancing Scientific Discovery Beyond Closed-Form Equations Symbolic regression has excelled in uncovering equations from physics, chemistry, biology, and related disciplines. However, its effectiveness becomes less certain when applied to experimental data lacking inherent closed-form expressions. Empirically derived relationships, such as entire stress-strain curves, may defy concise closed-form representation, compelling us to explore more adaptive modeling approaches that balance flexibility with interpretability. In our pursuit, we turn to Generalized Additive Models (GAMs), a widely used class of models known for their versatility across various domains. Although GAMs can capture non-linear relationships between variables and targets, they cannot capture intricate feature interactions. In this work, we investigate both of these challenges and propose a novel class of models, Shape Arithmetic Expressions (SHAREs), that fuses GAM's flexible shape functions with the complex feature interactions found in mathematical expressions. SHAREs also provide a unifying framework for both of these approaches. We also design a set of rules for constructing SHAREs that guarantee transparency of the found expressions beyond the standard constraints based on the model's size. Interpretability ; Representation (politics) ; Flexibility (engineering) ; Computer science ; Class (philosophy) ; Set (abstract data type) ; Generalized additive model ; Feature (linguistics) ; Theoretical computer science ; Mathematics ; Artificial intelligence ; Machine learning ; Programming language Machine Learning in Materials Science ; Generative Adversarial Networks and Image Synthesis ; 3D Shape Modeling and Analysis
Authors: Haris Suhendar | Michael Setiyanto Silambi | Muhammad Ridho Pratama
Source: Journal of Physics Conference Series (article, 2024-10-01)
Field: Chemistry — Analytical Chemistry

Design of a Portable Spectrophotometer Based on Raspberry Pi for Tea Type Classification Using Machine Learning Abstract The use of spectrophotometers in food and beverage quality analysis has become common. However, portability and high cost have long been a problem for food industry players and small-scale laboratories. In this study, a more compact and low-cost spectrophotometer has been developed using raspberry pi. To validate its performance, the prototype was used to classify green tea, black tea, and oolong tea types. The research started with designing and assembling the hardware using a raspberry pi camera with Complementary Metal Oxide Semiconductor (CMOS) sensor, Digital Versatile Disk (DVD) as diffraction grating, white LED as light source and 3D printer as casing. The prototype was then used to acquire data from green tea, black tea and oolong tea solutions. In the tea type identification process, Principal Component Analysis (PCA) was applied to the data obtained. The experiment involved 30 solution samples of each of the three types of tea. The light source was directed past the sample towards the slit and DVD, then the spectrum image of the light source was displayed through a user interface built using python programming. This research resulted in a spectrophotometer with dimensions of 260 mm x 120 mm x 63 mm that is capable of capturing light spectra in the range of 400 - 700 nm. Based on the experimental results, the classification accuracy of the three types of tea using CNN and Decision Tree reached 100%. Raspberry pi ; Blowing a raspberry ; Computer science ; Artificial intelligence ; Chromatography ; Chemistry ; Food science ; Embedded system Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Food Quality and Safety Studies
Authors: Indrajeet Kumar | Himani S. Bhatt | Kashif Raza | Abhishek Maithani | Teekam Singh
Source: AIP conference proceedings (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Computational analysis of clothing detection and segmentation in virtual dressing room Virtual Dressing Room (VDR) is an innovative technology that empowers users to attempt on attires virtually in a virtual atmosphere. The developed system eradicates the need for physical trial rooms at shopping store and delivers a continuous shopping experience. This system makes use of computer vision techniques to recognize and trace human body movements and overlaps a virtual clothing on the user's body. The proposed model is developed with the help of library imported from OpenCV and Python. The designed system encompasses of two major components, namely the human body detection and other one is the virtual garment overlay module. The user can interrelate with the developed model through a graphical user interface GUI) that permits the users to hand-picked outfits from a virtual wardrobe. The system's accuracy and performance were appraised on various test cases like specs, t-shirt, earring, pendants and the consequences showed promising results. The VDR system can transform the way people shop for clothes and provide a more immersive and convenient shopping experience. Clothing ; Computer science ; Segmentation ; Computer graphics (images) ; Computer vision ; Artificial intelligence ; Geography ; Archaeology Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Face recognition and analysis
Authors: Shad Abdelmoumen Serroune | I Rahman KHASANI | Sandra Merrier | Stéphane Devilliers | Tadeshi Ryushi
Source: World Journal of Biology Pharmacy and Health Sciences (article, 2024-11-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Next-Gen Magnetocaloric Cooling: MnFePSi Nanoparticles for Compact and Sustainable MCHP Systems This study introduces a groundbreaking magnetocaloric heat pump (MCHP) system that replaces traditional rare earth-dependent fixed-bed regenerators with a MnFePSi nanoparticle slurry (50 nm, 10% vol.), achieving simultaneous refrigerant and heat transfer functions. Experimental evaluations under controlled conditions (23°C ±0.2°C, 10 K span) demonstrate a 14.6% improvement in coefficient of performance (COP), 33.4% higher specific power density, and 24.8% system mass reduction compared to conventional gadolinium-based systems. The slurry’s non-Newtonian rheology enables rapid thermal response (56.3% faster) and exceptional temperature uniformity (±0.8°C), while operating at frequencies up to 7.6 Hz. Key innovations include a proprietary experimental platform integrating real-time spin-state monitoring, nano-Hall magnetic field mapping, and coupled CFD-ML modeling. Extended stability tests reveal minimal performance degradation (1.3% COP reduction over 48 hours) and negligible nanoparticle agglomeration (&lt;2%). The complete elimination of rare earth elements reduces lifecycle environmental impact by 60%, addressing critical sustainability challenges in cooling technology. These results establish the first practical demonstration of a rare-earth-free magnetocaloric cooling system with superior efficiency, scalability, and material utilization—setting a new benchmark for sustainable thermal management solutions. The technology’s compact design and enhanced heat transfer coefficients (22% improvement over fixed beds) position it as a transformative approach for next-generation refrigeration, air conditioning, and waste heat recovery applications. Magnetic refrigeration ; Materials science ; Thermodynamics ; Physics Magnetic and transport properties of perovskites and related materials
Authors: Levi D. Palmer | Wonseok Lee | J.C. Fajardo | Fajardo,, Javier | Liu, Yuzi | A. Alec Talin | Thomas E. Gage | Scott K. Cushing
Source: arXiv (Cornell University) (preprint, 2024-11-01)
Field: Materials Science — Surfaces, Coatings and Films

Nanoscale and Element-Specific Lattice Temperature Measurements using Core-Loss Electron Energy-Loss Spectroscopy Measuring nanoscale local temperatures, particularly in vertically integrated and multi-component systems, remains challenging. Spectroscopic techniques like X-ray absorption and core-loss electron energy-loss spectroscopy (EELS) are sensitive to lattice temperature, but understanding thermal effects is nontrivial. This work explores the potential for nanoscale and element-specific core-loss thermometry by comparing the Si L2,3 edge's temperature-dependent redshift against plasmon energy expansion thermometry (PEET) in a scanning TEM. Using density functional theory (DFT), time-dependent DFT, and the Bethe-Salpeter equation, we ab initio model both the Si L2,3 and plasmon redshift. We find that the core-loss redshift occurs due to bandgap reduction from electron-phonon renormalization. Our results indicate that despite lower core-loss signal intensity compared to plasmon features, core-loss thermometry has key advantages and can be more accurate through standard spectral denoising. Specifically, we show that the Varshni equation easily interprets the core-loss redshift for semiconductors, which avoids plasmon spectral convolution for PEET in complex junctions and interfaces. We also find that core-loss thermometry is more accurate than PEET at modeling thermal lattice expansion in semiconductors, unless the specimen's temperature-dependent dielectric properties are fully characterized. Furthermore, core-loss thermometry has the potential to measure nanoscale heating in multi-component materials and stacked interfaces with elemental specificity at length scales smaller than the plasmon's wavefunction. Electron energy loss spectroscopy ; Nanoscopic scale ; Spectroscopy ; Materials science ; Lattice (music) ; Electron ; Core (optical fiber) ; Condensed matter physics ; Nanotechnology ; Physics ; Nuclear physics ; Composite material ; Transmission electron microscopy ; Quantum mechanics Electron and X-Ray Spectroscopy Techniques ; Semiconductor materials and devices ; Molecular Junctions and Nanostructures
Authors: Rajeev Kumar | Vijay Paul | Rakesh Pandey
Source: Current Horticulture (review, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Hyperspectral imaging/reflectance as a tool for assessment of nutritional and quality-related parameters in tomato (Solanum lycopersicum) fruits - A review Tomato (Solanum lycopersicum L.) is most important vegetable crop for human health. The postharvest handling and management of tomato is prime concern in India because the annual postharvest losses for tomato can reach up to 25 - 40 %. Non-destructive approaches for quantification and monitoring of nutritional and quality aspects of horticultural commodities have come up in a big way in the recent past that can also serves towards better postharvest management. Out of various non-destructive approaches, optical method based on visible-near infrared (Vis-NIR) spectroscopy (hyperspectral imaging and reflectance) is the most important analytical tool that provides spatial and spectral information simultaneously for a commodity towards non- destructive assessment of food quality-related parameters. Therefore, an overview with latest developments and applications of hyperspectral imaging and reflectance techniques for assessment of nutritional and quality parameters of tomato fruits have been discussed. The advantages and disadvantages of this tool along with the future perspectives are also highlighted. Hyperspectral imaging ; Solanum ; Reflectivity ; Remote sensing ; Quality (philosophy) ; Environmental science ; Horticulture ; Biology ; Geography ; Optics ; Physics Spectroscopy and Chemometric Analyses
Authors: Wei Liu | Yang Liu | Fei Hong | Jiaming Li | Quan Jiang | Lingfei Kong | Changhong Liu | Lei Zheng
Source: Research Square (preprint, 2024-02-19)
Field: Chemistry — Analytical Chemistry

Identification of varieties of wheat seeds based on multispectral imaging combined with improved YOLOv5 Abstract The identification of seed variety is important in wheat production because the growth and yield are highly related with its variety. Traditional discrimination methods for wheat seed varieties were suffered with time consuming and contamination. In this study, multispectral imaging technology combined with improved YOLOv5s was proposed. Three optimal spectral bands images were selected from all 19 bands using Genetic algorithm and confusion matrix and then the new images were fused with the three band images. The improved YOLOv5s with CBAM module was developed to train the identification model of wheat varieties using fusion images. The experimental results showed that the average precision of the model from proposed method in test set reached 99.38% that were better than the traditional YOLOv5s model. Meanwhile, the evaluation indexes of the model such as P/%, R/%, F1/% and mAP/% were all higher than 90%. The results showed that the method could be used for wheat variety identification rapidly and non-destructively. Multispectral image ; Identification (biology) ; Agronomy ; Remote sensing ; Agricultural engineering ; Biology ; Geography ; Botany ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing and Land Use
Authors: Carla Kirschbaum | Kim Greis | América Y. Torres‐Boy | Jerome Riedel | Sandy Gewinner | Wieland Schöllkopf | Gerard Meijer | Gert von Helden | Kevin Pagel
Source: Journal of the American Society for Mass Spectrometry (article, 2024-07-01)
Field: Chemistry — Spectroscopy

Studying the Intrinsic Reactivity of Chromanes by Gas-Phase Infrared Spectroscopy Tandem mass spectrometry is routinely used for the structural analysis of organic molecules, but many fragmentation reactions are not well understood. Because several potential structures can correspond to a measured mass, the assignment of product ions is ambiguous using mass spectrometry alone. Here, we combine mass spectrometry with high-resolution gas-phase infrared spectroscopy and computational chemistry tools to identify product ion structures and derive collision-induced fragmentation mechanisms of the chromane derivatives Trolox and Methyltrolox. We find that protonated Trolox and Methyltrolox fragment identically via dehydration and decarbonylation, while deprotonated ions display substantially diverging reactivities. For deprotonated Methyltrolox, we observe unusual radical fragmentation reactions and suggest a [1,2]-Wittig rearrangement involving aryl migration in the gas phase. Overall, the combined experimental and theoretical approach presented here revealed complex proton dynamics and intramolecular rearrangement reactions, which expand our understanding on structure-reactivity relationships of isolated molecules in different protonation states. Chemistry ; Mass spectrometry ; Fragmentation (computing) ; Protonation ; Deprotonation ; Decarbonylation ; Tandem mass spectrometry ; Intramolecular force ; Photochemistry ; Molecule ; Collision-induced dissociation ; Reactivity (psychology) ; Infrared spectroscopy ; Computational chemistry ; Analytical Chemistry (journal) ; Ion ; Stereochemistry ; Organic chemistry Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Advanced Chemical Physics Studies
Authors: Yu Zhang | Weijun Zhang | Shuhui Bo | Wenlong He | Chuying Liu | Jiahai Wang | Fenggang Liu
Source:  (preprint, 2024-07-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Highly stable binary cross-linkable organic nonlinear optical materials using different acceptors based on Huisgen cycloaddition reaction How to obtain organic electro-optic materials with large electro-optic coefficients, high glass transition temperature, and good optical transparency remains a challenge in this field. To solve this problem, we introduce groups that can undergo Huisgen cycloaddition reactions into the donor and electron bridge of chromophores with large hyperpolarizability using tetrahydroquinoline as the donor. Binary cross-linkable chromophores TLD1-2 with CF3-TCF as the acceptor and chromophores TLD3-4 with 5Fph-TCF as the acceptor were synthesized. After poling and crosslinking, the Tg of TLD1/TLD2 and TLD3/TLD4 were raised to 152 and 174 °C, respectively. The electro-optical coefficients of chromophores TLD1/TLD2 and TLD3/TLD4 were as high as 312 pm/V and 287 pm/V, respectively. The long-term alignment stability test showed that after being left at 85 °C for 500 hours, the cross-linked film TLD3/TLD4 can still maintain more than 98% of the original electro-optical coefficient value, which is higher than that of TLD1/TLD2 (93%). The chromophore TLD3-4 exhibited much blue-shifted maximum absorption wavelengths (~40nm) compared to TLD1-2 which was beneficial for reducing optical loss in the device. The combination of high electro-optic coefficient, strong stability, and excellent optical transparency makes the TLD series of binary cross-linked materials very promising for practical high-performance electro-optic devices. Cycloaddition ; Binary number ; Nonlinear optical ; Nonlinear system ; Materials science ; Chemistry ; Organic chemistry ; Mathematics ; Physics ; Catalysis Nonlinear Optical Materials Research ; Photonic and Optical Devices ; Synthesis and properties of polymers
Authors: Pierre Michel
Source: theses.fr (ABES) (article, 2024-11-18)
Field: Chemistry — Spectroscopy

Chemical detection of homemade explosives and their precursors in wastewater systems Depuis les années 2000, la prolifération d’attaques terroristes utilisant les explosifs artisanaux, en particulier ceux à base de peroxyde, constitue une menace importante pour la sécurité publique et nationale. Ce sujet de recherche répond au besoin urgent de recherche de méthodes de détection avancées en se concentrant sur l'identification et la quantification de ces explosifs et de leurs précurseurs avant passage à l’acte par le biais de la matrice des eaux usées. Ces enjeux majeurs ont grandement suscité l’intérêt de l’acteur majeur de la recherche défense : l’Agence de l’Innovation de Défense – AID, branche de recherche du ministère des armées et a permis une collaboration avec l’UMR CNRS 7376 afin de répondre aux objectifs majeurs de ce sujet de thèse.L’analyse en ligne des réseaux d’eaux usées par un analyseur in-situ, sensible, miniature permettra la détection précoce des rejets des laboratoires clandestins terroristes. La multiplication de cet analyseur sur des points stratégiques du maillage des eaux usées permettra de faciliter la localisation par les forces de l’ordre de ces laboratoires clandestins par réduction du périmètre de recherche.La première étape de ce travail de recherche a été d’établir un état de l’art critique des méthodologies existantes, identifiant leurs limites et proposant des stratégies innovantes ou d’optimisations adaptées aux spécificités du projet. Les objectifs majeurs de la thèse visent à lever les verrous scientifiques du projet, liés à la détection sensible, sélective et miniaturisable des précurseurs des explosifs par dérivation dans la matrice des eaux usées. Les molécules cibles (précurseurs ou molécules dérivées) seront préconcentrés par extraction en phase solide (SPE) afin d’éliminer les interférences et d’améliorer la sensibilité des méthodes. Une étude sur la transformation des molécules d’explosifs artisanaux été menée afin de les quantifier par dérivation des produits de dégradations. Le dernier objectif de la thèse étant la conception préliminaire d’un prototype laboratoire d’analyseur en ligne afin de montrer la possibilité de l’automatisation des méthodes chimiques développées ainsi que ses paramétrages et ses performances. La finalité de cette thèse vise à proposer le développement analytique d’un couplage automatisé de la détection et de la préparation de l’échantillon afin de quantifier les molécules cibles de l’étude dans la matrice d’étude en répondant au cahier des charges du projet Blood preservation ; Medical screening Mass Spectrometry Techniques and Applications ; Energetic Materials and Combustion ; Forensic Fingerprint Detection Methods