jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Valerie Xinhui Teo | Savitha Dhandapani | Randall Ang Jie | Vidya Susan Philip | Mark Teo Ju Teng | Shuyan Zhang | Bong Soo Park | Malini Olivo | U. S. Dinish
Source: Frontiers in Photonics (article, 2024-09-03)
Field: Chemistry — Analytical Chemistry

Early detection of N, P, K deficiency in Choy Sum using hyperspectral imaging-based spatial spectral feature mining Leafy vegetables are widely consumed around the world for their rich nutritional qualities. To ensure a reliable and cost-effective supply of leafy vegetables in the future, advancements in their production are essential. Deficiencies of nitrogen (N), phosphorus (P), and potassium (K) impair growth of leafy vegetables and the ensuing visual symptoms make the plants unmarketable. We studied the use of non-contact large area hyperspectral imaging (HSI) for early detection of N, P and K deficiencies in the leafy vegetable, Choy Sum, before the appearance of visual symptoms. The wide spectral data of 500–900 nm extracted from the plants were subjected to advanced feature mining, facilitating the creation of novel spectral indices tailored to each vital nutrient by leveraging the Pearson’s correlations of 0.85 for N, 0.64 for P, and 0.68 for K with gold standard elemental concentration data. Early detection of deficiencies and timely replenishment of macronutrient(s) can prevent the development of obvious symptoms and thus maintain the visual quality of Choy Sum. These newly created spectral indices hold the potential to provide non-destructive estimation of nutrient content in plants, offering a promising avenue for future advancements in precision agriculture and resource-efficient crop management. Hyperspectral imaging ; Pattern recognition (psychology) ; Feature (linguistics) ; Artificial intelligence ; Mathematics ; Remote sensing ; Computer science ; Geography Spectroscopy and Chemometric Analyses ; GABA and Rice Research ; Phytochemicals and Antioxidant Activities
Authors: Soykan Ağar | Mohaddeseh Mokhtari | Muhammed Yanik | Barbaros Akkurt | Engı̇n Ulukaya | Rabia Terzi
Source: Asian Pacific Journal of Cancer Prevention (article, 2024-08-01)
Field: Chemistry — Organic Chemistry

De novo Antineoplastic Drug Design to Suppress Head, Neck and Oral Cancer using Theoretical Organic and Biochemistry via Comprehensive Molecular Docking and Dynamics We have effectively created a novel medication using principles of theoretical chemistry, biochemistry, pharmaceutical chemistry and organic chemistry and organic chemistry to inhibit Head, Neck, and Oral Cancer. This medication should further undergo experimental testing in various stages, including in vitro, in vivo, and human clinical phases. It exhibits significant effectiveness in inhibiting the progression of cancer by simultaneously targeting TGF-β and KRTAP2-3, thereby impeding metastasis and suppressing the disease. Docking (animal) ; Head and neck cancer ; Head and neck ; Drug ; Chemistry ; Computational biology ; Medicine ; Pharmacology ; Cancer ; Biology ; Internal medicine ; Surgery Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and biological activity ; Synthesis of heterocyclic compounds
Authors: Paul Mrkwitschka | Bastian Rühle | Petra Kuchenbecker | Oliver Löhmann | Franziska Lindemann | Vasile‐Dan Hodoroaba
Source: Scientific Reports (article, 2024-01-04)
Field: Materials Science — Materials Chemistry

Embedding and cross-sectioning as a sample preparation procedure for accurate and representative size and shape measurement of nanopowders Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer-Emmet-Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed. Agglomerate ; Dispersity ; Particle size ; Sample size determination ; Materials science ; Nanoparticle ; Aggregate (composite) ; Embedding ; Particle-size distribution ; Computer science ; Sample preparation ; Sample (material) ; Characterization (materials science) ; Biological system ; Nanotechnology ; Statistics ; Chemical engineering ; Mathematics ; Chromatography ; Chemistry ; Artificial intelligence ; Composite material Nanoparticles: synthesis and applications ; Adsorption, diffusion, and thermodynamic properties of materials ; Material Dynamics and Properties
Authors: Mizuki Kimura | Shinkoh Nanbu
Source: Physical Chemistry Chemical Physics (article, 2024-11-20)
Field: Chemistry — Organic Chemistry

Nonadiabatic <i>ab initio</i> chemical reaction dynamics for the photoisomerization reaction of 3,5-dimethylisoxazole <i>via</i> the S<sub>1</sub> electronic state Nonadiabatic <i>ab initio</i> molecular dynamics simulations were performed to explore the photoisomerization pathway from isoxazole (iso-OXA) to oxazole (OXA), considering four electronic states. The XMS-CASPT2 and SA4-CASSCF theories were employed to describe these electronic structures, which were caused by 12 electrons in 11 orbitals with the cc-pVDZ + sp diffuse basis set; the Gaussian s- and p-type diffuse functions were extracted from Dunning's aug-cc-pVDZ function. The potential energy and its gradient at each time step were computed on-the-fly at these levels in the time evolution of the classical trajectory. When the two electronic states were close to each other, the trajectory surface hopping (TSH) judgment between the two adjacent states was carried out by the anteater procedure based on the Zhu-Nakamura formula (ZN-TSH). The two different excited state lifetimes were found to exist in the first electronic state (S<sub>1</sub>), estimated at 10.77 and 119.81 fs. Upon photoexcitation, the N-O bond breaks and energetically relaxes to the ground state (S<sub>0</sub>). In the pathway leading to the main product, azirine formation, the 5-membered ring retains a planar structure while undergoing a non-adiabatic transition with an increasing N-O bond distance. Furthermore, it was verified that a 1,2-shift takes place in the pathway that results in the production of ketenimine, causing a nonadiabatic transition. Photoisomerization ; Ab initio ; Computational chemistry ; Relaxation (psychology) ; Chemical Dynamics ; Dynamics (music) ; Molecular dynamics ; Reaction dynamics ; Chemistry ; Chemical physics ; Ab initio quantum chemistry methods ; Isomerization ; Physics ; Molecule ; Catalysis ; Organic chemistry Organic Chemistry Cycloaddition Reactions ; Photochemistry and Electron Transfer Studies ; Advanced Chemical Physics Studies
Authors: Daniele Tanzilli | Lorenzo Strani | Francesco Bonacini | Angelo Ferrando | Marina Cocchi | Caterina Durante
Source: Analytica Chimica Acta (article, 2024-06-12)
Field: Chemistry — Analytical Chemistry

Implementing multiblock techniques in a full-scale plant scenario: On-line prediction of quality parameters in a continuous process for different acrylonitrile butadiene styrene (ABS) products This study contributes valuable insights for continuous production processes, aiding plant operators and paving the way for advancements in online quality prediction and control. Furthermore, it is implemented as a locally weighted extension of MB-PLS. Chemistry ; Acrylonitrile butadiene styrene ; Acrylonitrile ; Styrene ; Scale (ratio) ; Process engineering ; Process (computing) ; SCALE-UP ; Quality (philosophy) ; 1,3-Butadiene ; Line (geometry) ; Organic chemistry ; Polymer ; Copolymer ; Catalysis ; Computer science ; Engineering Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Advanced Statistical Process Monitoring
Authors: Leonie Beek | Jan-Eric Skirde | Musa Akdere | Thomas Gries
Source: Biomimetics (article, 2024-04-25)
Field: Materials Science — Surfaces, Coatings and Films

Bio-Inspired Textiles for Self-Driven Oil–Water Separation—A Simulative Analysis of Fluid Transport In addition to water repellency, superhydrophobic leaves of plants such as <i>Salvinia molesta</i> adsorb oil and separate it from water surfaces. This phenomenon has been the inspiration for a new method of oil-water separation, the bionic oil adsorber (BOA). In this paper, we show how the biological effect can be abstracted and transferred to technical textiles, in this case knitted spacer textiles hydrophobized with a layered silicate, oriented at the biology push approach. Subsequently, the transport of the oil within the bio-inspired textile is analyzed by a three-dimensional fluid simulation. This fluid simulation shows that the textile can be optimized by reducing the pile yarn length, increasing the pile yarn spacing, and increasing the pile yarn diameter. For the first time, it has been possible with this simulation to optimize the bio-inspired textile with regard to oil transport with little effort and thus enable the successful implementation of a self-driven and sustainable oil removal method. Water transport ; Chemical engineering ; Chemistry ; Materials science ; Nanotechnology ; Environmental science ; Environmental engineering ; Engineering ; Water flow Surface Modification and Superhydrophobicity ; Electrohydrodynamics and Fluid Dynamics ; Fluid Dynamics and Heat Transfer
Authors: Sabrina Vantadori | Camilla Ronchei | Daniela Scorza | Andrea Zanichelli
Source: Fatigue & Fracture of Engineering Materials & Structures (article, 2024-11-12)
Field: Materials Science — Materials Chemistry

Mechanical Behavior of Multiple Edge‐Cracked Nanobeams by Taking Into Account the Multiple Cracks Effects ABSTRACT By exploiting the stress‐driven model, within the Euler–Bernoulli beam theory, a novel nonlocal analytical model is proposed in order to simulate the mechanical behavior of multiple edge–cracked nanobeams by taking into account the multiple cracks effects. According to the present model, the nanobeam is split in correspondence with each of the edge cracks, thus obtaining beam segments, connected to each other by means of massless elastic rotational springs. Firstly, the proposed model is validated by considering experimental data available in the literature, related to bending tests on two cantilever microbeams, each of them containing a single edge crack (i.e., ). Then, the model is employed to simulate a bending test on a cracked cantilever microbeam containing two edge cracks (i.e., ) and a parametric study is performed by varying both the crack depth, the distance between cracks, and the characteristic length of the material in order to investigate the influence of such parameters on the microbeam mechanical response. Enhanced Data Rates for GSM Evolution ; Materials science ; Composite material ; Structural engineering ; Engineering Nonlocal and gradient elasticity in micro/nano structures ; Force Microscopy Techniques and Applications ; Microstructure and mechanical properties
Authors: Biao Lu | Shilong Wu | Deliang Liu | Wenping Wu | Wei Zhou | Leiming Yuan
Source: Molecules (article, 2024-03-22)
Field: Chemistry — Analytical Chemistry

Unsupervised Clustering-Assisted Method for Consensual Quantitative Analysis of Methanol–Gasoline Blends by Raman Spectroscopy Methanol-gasoline blends have emerged as a promising and environmentally friendly bio-fuel option, garnering widespread attention and promotion globally. The methanol content within these blends significantly influences their quality and combustion performance. This study explores the qualitative and qualitative analysis of methanol-gasoline blends using Raman spectroscopy coupled with machine learning methods. Experimentally, methanol-gasoline blends with varying methanol concentrations were artificially configured, commencing with initial market samples. For qualitative analysis, the partial least squares discriminant analysis (PLS-DA) model was employed to classify the categories of blends, demonstrating high prediction performance with an accuracy of nearly 100% classification. For the quantitative analysis, a consensus model was proposed to accurately predict the methanol content. It integrates member models developed on clustered variables, using the unsupervised clustering method of the self-organizing mapping neural network (SOM) to accomplish the regression prediction. The performance of this consensus model was systemically compared to that of the PLS model and uninformative variable elimination (UVE)-PLS model. Results revealed that the unsupervised consensus model outperformed other models in predicting the methanol content across various types of methanol gasoline blends. The correlation coefficients for prediction sets consistently exceeded 0.98. Consequently, Raman spectroscopy emerges as a suitable choice for both qualitative and quantitative analysis of methanol-gasoline blend quality. This study anticipates an increasing role for Raman spectroscopy in analysis of fuel composition. Gasoline ; Methanol ; Partial least squares regression ; Raman spectroscopy ; Cluster analysis ; Linear discriminant analysis ; Artificial intelligence ; Pattern recognition (psychology) ; Methanol fuel ; Computer science ; Biological system ; Materials science ; Machine learning ; Chemistry ; Physics ; Organic chemistry Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Petroleum Processing and Analysis
Authors: Mitja Jančič | Miha Založnik | Gregor Kosec
Source: Journal of Computational Physics (article, 2024-03-28)
Field: Materials Science — Materials Chemistry

Meshless interface tracking for the simulation of dendrite envelope growth The growth of dendritic grains during solidification is often modelled using the Grain Envelope Model (GEM), in which the envelope of the dendrite is an interface tracked by the Phase Field Interface Capturing (PFIC) method. In the PFIC method, an phase-field equation is solved on a fixed mesh to track the position of the envelope. While being versatile and robust, PFIC introduces certain numerical artefacts. In this work, we present an alternative approach for the solution of the GEM that employs a Meshless (sharp) Interface Tracking (MIT) formulation, which uses direct, artefact-free interface tracking. In the MIT, the envelope (interface) is defined as a moving domain boundary and the interface-tracking nodes are boundary nodes for the diffusion problem solved in the domain. To increase the accuracy of the method for the diffusion-controlled moving-boundary problem, an h -adaptive spatial discretization is used, thus, the node spacing is refined in the vicinity of the envelope. MIT combines a parametric surface reconstruction, a mesh-free discretization of the parametric surfaces and the space enclosed by them, and a high-order approximation of the partial differential operators and of the solute concentration field using radial basis functions augmented with monomials. The proposed method is demonstrated on a two-dimensional h -adaptive solution of the diffusive growth of dendrite and evaluated by comparing the results to the PFIC approach. It is shown that MIT can reproduce the results calculated with PFIC, that it is convergent and that it can capture more details in the envelope shape than PFIC with a similar spatial discretization. • MIT is a novel method for the solution of the Grain Envelope Model (GEM) of solidification, built on meshless principles. • MIT uses h -adaptive spatial discretization on a diffusion-controlled moving boundary problem. • MIT avoids numerical artefacts linked to the use of a phase field for interface capturing. • Less computational nodes are required to capture the details in the dendrite envelope shape. Discretization ; Envelope (radar) ; Stefan problem ; Mathematical analysis ; Dendrite (mathematics) ; Geometry ; Tracking (education) ; Mathematics ; Parametric statistics ; Diffusion ; Boundary (topology) ; Phase (matter) ; Position (finance) ; Computer science ; Physics Solidification and crystal growth phenomena ; Aluminum Alloy Microstructure Properties ; Fluid Dynamics and Thin Films
Authors: Liangzhong Lim | Jianxing Song
Source: International Journal of Molecular Sciences (article, 2024-08-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

NMR Dynamic View of the Stabilization of the WW4 Domain by Neutral NaCl and Kosmotropic Na2SO4 and NaH2PO4 The Hofmeister series categorizes ions based on their effects on protein stability, yet the microscopic mechanism remains a mystery. In this series, NaCl is neutral, Na<sub>2</sub>SO<sub>4</sub> and Na<sub>2</sub>HPO<sub>4</sub> are kosmotropic, while GdmCl and NaSCN are chaotropic. This study employs CD and NMR to investigate the effects of NaCl, Na<sub>2</sub>SO<sub>4</sub>, and Na<sub>2</sub>HPO<sub>4</sub> on the conformation, stability, binding, and backbone dynamics (ps-ns and µs-ms time scales) of the WW4 domain with a high stability and accessible side chains at concentrations ≤ 200 mM. The results indicated that none of the three salts altered the conformation of WW4 or showed significant binding to the four aliphatic hydrophobic side chains. NaCl had no effect on its thermal stability, while Na<sub>2</sub>SO<sub>4</sub> and Na<sub>2</sub>HPO<sub>4</sub> enhanced the stability by ~5 °C. Interestingly, NaCl only weakly interacted with the Arg27 amide proton, whereas Na<sub>2</sub>SO<sub>4</sub> bound to Arg27 and Phe31 amide protons with Kd of 32.7 and 41.6 mM, respectively. Na<sub>2</sub>HPO<sub>4</sub>, however, bound in a non-saturable manner to Trp9, His24, and Asn36 amide protons. While the three salts had negligible effects on ps-ns backbone dynamics, NaCl and Na<sub>2</sub>SO<sub>4</sub> displayed no effect while Na<sub>2</sub>HPO<sub>4</sub> significantly increased the µs-ms backbone dynamics. These findings, combined with our recent results with GdmCl and NaSCN, suggest a microscopic mechanism for the Hofmeister series. Additionally, the data revealed a lack of simple correlation between thermodynamic stability and backbone dynamics, most likely due to enthalpy-entropy compensation. Our study rationalizes the selection of chloride and phosphate as the primary anions in extracellular and intracellular spaces, as well as polyphosphate as a primitive chaperone in certain single-cell organisms. Domain (mathematical analysis) ; Chemistry ; Mathematics Organic and Molecular Conductors Research ; Solid-state spectroscopy and crystallography ; Crystallography and molecular interactions
Authors: Ingi Agnarsson
Source: Current Biology (article, 2024-01-01)
Field: Materials Science — Biomaterials

Biomechanics: Rain yields tougher spider silks Spider ; Spider silk ; Habitat ; SILK ; Ecology ; Orb (optics) ; Biology ; Materials science ; Composite material ; Computer science Silk-based biomaterials and applications ; Silkworms and Sericulture Research ; Aquatic life and conservation
Authors: Blake D. Fonda | Masato Kato | Yang Li | Dylan T. Murray
Source: Protein Science (article, 2024-09-14)
Field: Chemistry — Spectroscopy

Cryo‐ <scp>EM</scp> and solid state <scp>NMR</scp> together provide a more comprehensive structural investigation of protein fibrils The tropomyosin 1 isoform I/C C-terminal domain (Tm1-LC) fibril structure is studied jointly with cryogenic electron microscopy (cryo-EM) and solid state nuclear magnetic resonance (NMR). This study demonstrates the complementary nature of these two structural biology techniques. Chemical shift assignments from solid state NMR are used to determine the secondary structure at the level of individual amino acids, which is faithfully seen in cryo-EM reconstructions. Additionally, solid state NMR demonstrates that the region not observed in the reconstructed cryo-EM density is primarily in a highly mobile random coil conformation rather than adopting multiple rigid conformations. Overall, this study illustrates the benefit of investigations combining cryo-EM and solid state NMR to investigate protein fibril structure. Solid-state nuclear magnetic resonance ; Random coil ; Cryo-electron microscopy ; Chemistry ; Crystallography ; Nuclear magnetic resonance spectroscopy ; Fibril ; Structural biology ; Protein structure ; Biophysics ; Nuclear magnetic resonance ; Biochemistry ; Stereochemistry ; Physics ; Circular dichroism ; Biology Advanced NMR Techniques and Applications ; RNA modifications and cancer ; Advanced MRI Techniques and Applications
Authors: Hao Liu | Lei Jin | Zhongzhou Ren
Source: arXiv (Cornell University) (preprint, 2024-07-30)
Field: Materials Science — Materials Chemistry

From Complexity to Clarity: Kolmogorov-Arnold Networks in Nuclear Binding Energy Prediction This study explores the application of Kolmogorov-Arnold Networks (KANs) in predicting nuclear binding energies, leveraging their ability to decompose complex multi-parameter systems into simpler univariate functions. By utilizing data from the Atomic Mass Evaluation (AME2020) and incorporating features such as atomic number, neutron number, and shell effects, KANs achieved a significant lower root mean square error (0.26~MeV), surpassing traditional models. The symbolic regression analysis yielded simplified analytical expressions for binding energies, aligning with classical models like the liquid drop model and the Bethe-Weizsäcker formula. These results highlight KANs' potential in enhancing the interpretability and understanding of nuclear phenomena, paving the way for future applications in nuclear physics and beyond. CLARITY ; Energy (signal processing) ; Statistical physics ; Kolmogorov complexity ; Computer science ; Physics ; Biology ; Quantum mechanics ; Algorithm Machine Learning in Materials Science
Authors: Rajesh Tamang | Sunita Gurung | Divya Rai | Samy Brahimi | Samir Lounis
Source: arXiv (Cornell University) (review, 2024-12-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Newly discovered magnetic phase: A brief review on Altermagnets Recently, a new magnetic phase, termed altermagnetism, has caught the attention of the magnetism and spintronics community. This newly discovered magnetic phenomenon differs from traditional ferromagnetism and antiferromagnetic. It generally lacks net magnetization and is characterized by unusual non-relativistic spin-splitting and broken time-reversal symmetry. This leads to novel transport properties such as the anomalous Hall effect, the crystal Nernst effect, and spin-dependent phenomena that cannot be fully explained by traditional magnetic theories. Spin-dependent phenomena such as spin currents, spin-splitter torques, and high-frequency dynamics emerge as key characteristics in altermagnets. This paper reviews the main aspects pertaining to altermagnets by providing an overview of theoretical investigations and experimental realizations. We discuss the most recent developments in altermagnetism, its comparison to other magnetic orders, and future prospects for exploiting its unique properties in next-generation devices. Phase (matter) ; Physics Magnetic Properties of Alloys