jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Somar Shekh Alshabab | Zhao Wu | Bernd Markert | Franz Bamer
Source: PAMM (article, 2024-12-30)
Field: Materials Science — Ceramics and Composites

Mapping Shear Transformation Zones in Silica Network Glass ABSTRACT Understanding nanoscale behavior in glasses is challenging due to their inherent long‐range disorder and the absence of clearly defined defect regions. However, shear transformation zone theory suggests that certain “soft spots,” which are prone to plastic rearrangements, can be identified even in stress‐free configurations. Various predictive methods, such as energy approximations and local structural indicators, have been proposed with varying success. The local yield stress (LYS) method, however, has demonstrated strong potential by identifying these soft spots based on local mechanical properties. In this study, we use the LYS method to analyze the distribution of soft spots in 2D silica network glass, where the local critical stresses are probed using mechanical simulations. Samples with different heterogeneities are generated through a Monte Carlo bond‐switching algorithm and subjected to shear via an athermal quasistatic (AQS) deformation protocol. Our results reveal a high correlation between regions with low critical stresses and the locations of rearrangement events, especially for events that happen early in the shear simulations, though this correlation decreases as the system approaches failure. These findings highlight the method's effectiveness in predicting plastic activity in structural glasses, and confirming that soft spots can be identified from the initial configuration. Additionally, we optimized the probing length scale for different levels of heterogeneity and analyzed the resulting statistical distributions of the local critical stresses, which are essential for accurate macroscopic modeling of silica glass. Transformation (genetics) ; Shear (geology) ; Shear matrix ; Materials science ; Silica glass ; Geology ; Composite material ; Amorphous metal Glass properties and applications ; Cultural Heritage Materials Analysis ; Metallic Glasses and Amorphous Alloys
Authors: Hesti Lina Wiraswati | Muhammad Hasan Bashari | Nayla Majeda Alfarafisa | Ilma Fauziah Ma’ruf | Eti Nurwening Sholikhah | Tutik Dwi Wahyuningsih | Pamungkas Bagus Satriyo | Mustofa Mustofa | Denny Satria | Ema Damayanti
Source: Advances and Applications in Bioinformatics and Chemistry (article, 2024-02-01)
Field: Chemistry — Organic Chemistry

Pyrazoline B-Paclitaxel or Doxorubicin Combination Drugs Show Synergistic Activity Against Cancer Cells: In silico Study The results show that this combination is promising for further in vitro and in vivo studies. Paclitaxel ; Doxorubicin ; Pharmacology ; In silico ; In vivo ; Chemistry ; Cancer cell ; Drug ; Ascorbic acid ; In vitro ; Cancer ; Chemotherapy ; Medicine ; Biochemistry ; Biology ; Internal medicine Synthesis and biological activity ; Cancer therapeutics and mechanisms ; Computational Drug Discovery Methods
Authors: T. J. Herman | R. Ravi | Michael S. Schuurman | Nathan J. DeYonker | Robert W. Field | L. M. Ziurys
Source: The Journal of Physical Chemistry A (article, 2024-11-13)
Field: Chemistry — Spectroscopy

Probing the Electronic Manifold of MgCl with Millimeter-Wave Spectroscopy and Theory: (3) <sup>2</sup> Σ <sup>+</sup> and (4) <sup>2</sup> Σ <sup>+</sup> States The millimeter/submillimeter spectrum of magnesium chloride (MgCl) has been observed in two new electronic excited states, (3)<sup>2</sup>Σ<sup>+</sup> and (4)<sup>2</sup>Σ<sup>+</sup>, using direct absorption methods. The molecule was synthesized in a mixture of Cl<sub>2</sub>, argon, and magnesium vapor. For the (3)<sup>2</sup>Σ<sup>+</sup> state, multiple rotational transitions were measured in the <i>v</i> = 0 level for all six isotopologues (<sup>24</sup>Mg<sup>35</sup>Cl, <sup>24</sup>Mg<sup>37</sup>Cl, <sup>25</sup>Mg<sup>35</sup>Cl, <sup>25</sup>Mg<sup>37</sup>Cl, <sup>26</sup>Mg<sup>35</sup>Cl, and <sup>26</sup>Mg<sup>37</sup>Cl), as well as up to <i>v</i> = 13 for <sup>24</sup>Mg<sup>35</sup>Cl. For the (4)<sup>2</sup>Σ<sup>+</sup> state, less intense spectra were recorded for <sup>24</sup>Mg<sup>35</sup>Cl (<i>v</i> = 0-2). Equilibrium rotational parameters were determined for both states for <sup>24</sup>Mg<sup>35</sup>Cl, as well as rotational constants and <sup>25</sup>Mg hyperfine parameters for the other isotopologues. A perturbation was observed between rotational levels of the two states due to an avoided crossing. Computations were also carried out at the CASPT2 and MRCISD+Q levels, and the resulting bond lengths for (3)<sup>2</sup>Σ<sup>+</sup> and (4)<sup>2</sup>Σ<sup>+</sup> states agree well with the experimental values of <i>r</i><sub>e</sub> = 2.536 and 2.361 Å. The computations show that the (3)<sup>2</sup>Σ<sup>+</sup> state has a double-well potential; however, the state behaves as a single well with unperturbed vibrational levels up to <i>v</i> = 13 due to nonadiabatic interactions with the (4)<sup>2</sup>Σ<sup>+</sup> state. Physics ; Spectroscopy ; Atomic physics ; Chemistry ; Analytical Chemistry (journal) ; Quantum mechanics Molecular Spectroscopy and Structure ; Advanced Chemical Physics Studies ; Quantum, superfluid, helium dynamics
Authors: Katharina Schuh | Peter A. Whalley
Source: arXiv (Cornell University) (preprint, 2024-05-16)
Field: Materials Science — Materials Chemistry

Convergence of kinetic Langevin samplers for non-convex potentials We study three kinetic Langevin samplers including the Euler discretization, the BU and the UBU splitting scheme. We provide contraction results in $L^1$-Wasserstein distance for non-convex potentials. These results are based on a carefully tailored distance function and an appropriate coupling construction. Additionally, the error in the $L^1$-Wasserstein distance between the true target measure and the invariant measure of the discretization scheme is bounded. To get an $\varepsilon$-accuracy in $L^1$-Wasserstein distance, we show complexity guarantees of order $\mathcal{O}(\sqrt{d}/\varepsilon)$ for the Euler scheme and $\mathcal{O}(d^{1/4}/\sqrt{\varepsilon})$ for the UBU scheme under appropriate assumptions on the target measure. The results are applicable to interacting particle systems and provide bounds for sampling probability measures of mean-field type. Convergence (economics) ; Kinetic energy ; Langevin dynamics ; Regular polygon ; Statistical physics ; Physics ; Mathematics ; Classical mechanics ; Economics ; Geometry Machine Learning in Materials Science ; Nanopore and Nanochannel Transport Studies ; Advanced MRI Techniques and Applications
Authors: Pradeep Mulabagal | A. Kumaraswamy | Sunil Nimje
Source: Discover Applied Sciences (article, 2024-09-28)
Field: Materials Science — Materials Chemistry

Damage of thin target plates impacted by conical projectiles with varying apex angles in ballistic application: experimental, FEA and ANN integrated approach In the current study, an experimental setup consisting of smoothbore 30-caliber powder gun was employed to launch spherical projectiles (3 g/ϕ9) in the ballistic range of velocities from 500 to 1700 m/s and obliquity (0, 33 and 65°), impacting 2 mm thin Steel 1006 target plates. Crater dimensions (major and minor dia.) obtained from series of FE simulations run for the above configuaration was validated by corresponding experimental data. Subsequently, a fullscale 3D FE model considering 8-noded hexahedral elements was used to discretize SS304 conical projectiles (replacing spherical projectile) with various apex angles viz. 40°, 60°, 80° and 100° impacting on single (3 mm) and double layer (1.5 mm each) steel 1006 targets (replacing 2 mm target) in LS dyna. The material behavior was characterized using J–C strength and damage models, along with Gruneisen Equation of State. An erosion algorithm was used in the explicit FE code LS-DYNA to remove undesirable elements. In the next stage, Adam and Nadam optimizers have been employed in ANN models developed using Python code within the Tensor-Flow framework. The Keras Tuner library in the Tensor-Flow framework was used for hyper parameter tuning. The ANN models trained using simulation data successfully predicted the residual KE of conical projectiles with intermediate apex angles of 90°, 70°, and 50° across twelve different impact scenarios. The models with Adam and Nadam optimizers achieved mean squared error (MSE)/coefficient of determination (R2)/mean absolute percentage error (MAPE) values of 109.44/0.998/6.72 and 91.19/0.998/7.76, respectively. Conical surface ; Projectile ; Apex (geometry) ; Materials science ; Finite element method ; Structural engineering ; Engineering ; Composite material ; Geometry ; Mathematics High-Velocity Impact and Material Behavior ; Energetic Materials and Combustion ; Structural Response to Dynamic Loads
Authors: Alice Ishwarbhai Kothari | Sumit Kumar | Ishita Auddy | Sahil Shiraj Shaikh
Source: International Journal of Advanced Biochemistry Research (article, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Effect of storage period on physico-chemical properties of coconut water at different maturity stages Effect of storage period on physico-chemical properties of coconut water at different maturity stages Maturity (psychological) ; Period (music) ; Food science ; Chemistry ; Environmental science ; Psychology ; Physics Coconut Research and Applications ; Herbal Medicine and Trade Cooperation ; Innovations in Aquaponics and Hydroponics Systems
Authors: V. O. Alexenko | Defang Tian | С. В. Панин | С. А. Бочкарева | I. L. Panov
Source: Frattura ed Integrità Strutturale (article, 2024-03-15)
Field: Materials Science — General Materials Science

Ultrasonic welding of lap joints of PEI plates with PEI/CF-fabric prepregs In this study, ultrasonic welding (USW) of lap joints of polyetherimide (PEI) plates (adherends) with carbon fiber (CF) prepregs impregnated with PEI was investigated. No energy director (ED) was used, so binder contents were varied in the prepregs to compensate for the lack of the polymer in the fusion zone. In addition, the effect of the USW parameters on the structure and the mechanical properties of the lap-joints were analyzed. The most homogeneous macrostructure, the maintained structural integrity of both the CF-fabric in the prepregs and the lap-joined PEI adherends, as well as the maximum strength properties (tensile strength) were revealed for the USW joints with the minimum polymer content in the prepreg. In this case, rising the USW time from 400 up to 800 ms radically changed the macrostructure of the fusion zone, while the strength properties did not vary significantly (shear stresses were 42–48 MPa). Computer simulation of the influence of the PEI/CF-fabric ratios in the prepregs on the deformation response of the USW joints showed that the prepreg thicknesses and, accordingly, the PEI/CF ratios did not exert a noticeable effect on the strain–stress (tensile) diagrams, while the determining factor was the adhesion level. Materials science ; Welding ; Composite material ; Ultrasonic sensor ; Structural engineering ; Engineering ; Acoustics Material Properties and Applications ; Advanced Welding Techniques Analysis ; Mechanical Behavior of Composites
Authors: Essam Sheta | Adrian Sutinjo
Source: Crystals (article, 2024-04-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Layered Structure Based on PANi and SiO2 to Absorb HPM to Protect Systems and Devices A layered structure composed of polyaniline (PANI) and silicon dioxide (SiO2) is proposed in this article. It was developed to obtain ultra-wideband and high-power microwave absorption. Due to the high thermal stability of PANi and SiO2 above 400 °C, the proposed structure is able to absorb high amounts of power. The electromagnetic behavior of the structure is examined by full-wave simulation to investigate its ability to absorb microwave frequencies ranging from 1 to 20 GHz under both normal and oblique incidences of electromagnetic waves. Recent studies have produced results with a limited absorption range and a less consistent angular incidence than the structure presently being examined. Also, the layer-by-layer deposition of thin film facilitates the manufacturing procedure. Furthermore, owing to the high thermal stability of the proposed structure, the absorption of high-power microwaves is superior to that of alternative methodologies. Microwave ; Polyaniline ; Materials science ; Absorption (acoustics) ; Thermal stability ; Optoelectronics ; Wideband ; Electromagnetic radiation ; Layer (electronics) ; Thermal ; Power (physics) ; Optics ; Composite material ; Computer science ; Chemical engineering ; Telecommunications ; Physics ; Polymer ; Engineering Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Yun Chen | Jiang‐Bo Hu | Shan Yin | Wentao Zhang | Wei Huang
Source: Materials (article, 2024-07-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Bimodal Absorber Frequencies Shift Induced by the Coupling of Bright and Dark Modes In this paper, we demonstrate that the absorption frequencies of the bimodal absorber shift with the coupling strength of the bright and dark modes. The coupling between the bright mode and the dark mode can acquire electromagnetically induced transparency, we obtain the analytical relationship between the absorbing frequencies, the resonant frequencies, losses of the bright mode and dark mode, and the coupling strength between two modes by combining the coupled mode theory with the interference theory. As the coupling strength between the bright mode and the dark mode decreases, the two absorption peaks gradually move closer to each other, inversely, they will move away from each other. The simulation employs three distinct metasurface structures with coupling of the bright and dark modes, thereby verifying the generality of the theoretical findings. Coupling strength ; Coupling (piping) ; Physics ; Mode (computer interface) ; Mode coupling ; Electromagnetically induced transparency ; Interference (communication) ; Optics ; Absorption (acoustics) ; Dark state ; Materials science ; Condensed matter physics ; Telecommunications ; Engineering Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Plasmonic and Surface Plasmon Research
Authors: Ashwini B.T. | Vijaya Kumar Y M | Keerthi Gowda B.S | Naveen Kumar D.T
Source: Research Square (preprint, 2024-03-27)
Field: Materials Science — Polymers and Plastics

Prognostication of mechanical properties of Banana and Jute fiber reinforced concrete using AI <title>Abstract</title> In the present study, using data from experiments, an artificial neural network (ANN) model has been created to predict the strengths of concrete with banana and jute fibers at concrete ages of 7 and 28 days. The parameters considered for the ANN inputs are Grade of Concrete, FA, CA, W/C, Super Plasticizer, length, diameter and Density of fiber, curing in days, NaOH Concentration, Fiber treatment in hours, percentage of fiber added. The results from training and testing models have shown the great potential of ANN in predicting the compressive and flexural strengths of banana and jute fiber reinforced concrete. Fiber ; Composite material ; Reinforced concrete ; Materials science ; Pulp and paper industry ; Structural engineering ; Engineering Natural Fiber Reinforced Composites ; Innovative concrete reinforcement materials ; Structural Behavior of Reinforced Concrete
Authors: Cornelius von Morze | Tyler Blazey | Ashley Shaw | William M. Spees | Kooresh I. Shoghi | Michael A. Ohliger
Source: Scientific Reports (article, 2024-06-27)
Field: Chemistry — Spectroscopy

Detection of early-stage NASH using non-invasive hyperpolarized 13C metabolic imaging Non-alcoholic steatohepatitis (NASH) is characterized from its early stages by a profound remodeling of the liver microenvironment, encompassing changes in the composition and activities of multiple cell types and associated gene expression patterns. Hyperpolarized (HP) <sup>13</sup>C MRI provides a unique view of the metabolic microenvironment, with potential relevance for early diagnosis of liver disease. Previous studies have detected changes in HP <sup>13</sup>C pyruvate to lactate conversion, catalyzed by lactate dehydrogenase (LDH), with experimental liver injury. HP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>∝</mml:mo></mml:math> -ketobutyrate ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>∝</mml:mo></mml:math> KB) is a close molecular analog of pyruvate with modified specificity for LDH isoforms, specifically attenuated activity with their LDHA-expressed subunits that dominate liver parenchyma. Building on recent results with pyruvate, we investigated HP <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>∝</mml:mo></mml:math> KB in methionine-choline deficient (MCD) diet as a model of early-stage NASH. Similarity of results between this new agent and pyruvate (~ 50% drop in cytoplasmic reducing capacity), interpreted together with gene expression data from the model, suggests that changes are mediated through broad effects on intermediary metabolism. Plausible mechanisms are depletion of the lactate pool by upregulation of gluconeogenesis (GNG) and pentose phosphate pathway (PPP) flux, and a possible shift toward increased lactate oxidation. These changes may reflect high levels of oxidative stress and/or shifting macrophage populations in NASH. Stage (stratigraphy) ; Nuclear magnetic resonance ; Magnetic resonance imaging ; Medicine ; Chemistry ; Computer science ; Radiology ; Biology ; Physics Advanced NMR Techniques and Applications ; Liver Disease Diagnosis and Treatment ; Advanced MRI Techniques and Applications
Authors: Tong Lu | Yating Liu | Xin Shu | Zhen Li | Xia Wang | Lingqi Li | Xinglian Xu | Peng Wang
Source: Food Science of Animal Products (article, 2024-09-01)
Field: Chemistry — Analytical Chemistry

Deep-learning classification of chicken woody breast based on bioelectrical impedance characteristics As a serious threat to the broiler industry, woody breast (WB) requires precise classification that is theoretically aligned with the advantage of bioelectrical impedance detection. This research used normal chicken breast (NORM) and three levels of WB condition, namely, mild, moderate and severe (SEV), based on sensory evaluation. The basic objective quality indicators and impedance characteristics of the samples were detected, and then the various levels of WB were categorized by model-classification approach. At a consistent frequency, the impedance amplitude of samples decreased with increased WB level. Significant differences in the absolute value of the phase angle existed among different levels of WB. The increase in WB level led to a considerable increase in intracellular resistance (<i>R</i><sub>i</sub>) and in the characteristic frequency (<i>f</i><sub>c</sub>). However, four other indices including the radius of Cole-Cole curve arc, the extracellular resistance (<i>R</i><sub>e</sub>), the polarization coefficient (<i>K</i>), and the relaxation factor (<i>α</i>) substantially dropped with increased WB level. The accuracy of SEV training, NORM and SEV test samples achieved a perfect score of 100% according to the partial least squares (PLS) prediction model. The PLS model also exhibited an overall accuracy of 91.70% for training samples compared with the value of 88.35% from limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) deep-learning prediction model. However, the L-BFGS model achieved a higher overall correct rate for test samples (90.00%) than PLS model (80.00%). These results provided valuable information for the classification of WB based on the characteristics of bioelectrical impedance. Bioelectrical impedance analysis ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Medicine ; Internal medicine Spectroscopy and Chemometric Analyses ; Body Composition Measurement Techniques ; Infrared Thermography in Medicine
Authors: Zsombor Ritter | Georg Oeltzschner | Lilja B. Sólnes | Guanshu Liu | David Kamson
Source: Advances in Oncology (article, 2024-01-29)
Field: Materials Science — Materials Chemistry

Diagnostic and Theranostic Opportunities in Neuro-Oncology Radiation oncology ; Medical physics ; Medicine ; Radioligand ; Radiation therapy ; Internal medicine Lanthanide and Transition Metal Complexes ; Radiopharmaceutical Chemistry and Applications ; Advanced MRI Techniques and Applications
Authors: Saadin Oyucu | Münür Sacit Herdem
Source: Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi (article, 2024-08-28)
Field: Materials Science — Materials Chemistry

HİBRİT DERİN ÖĞRENME ALGORİTMALARI KULLANILARAK BİYOGAZ REFORM SÜREÇLERİNİN OPTİMİZASYONU: CNN-LSTM MODELİ İLE ÇIKTI PARAMETRELERİNİN TAHMİNİ Bu çalışma, biyogaz reform süreçlerinde çeşitli çıktı parametrelerini tahmin etmek için Evrişimli Sinir Ağları (CNN: Convolutional Neural Networks) ve Uzun Kısa Süreli Bellek (LSTM: Long Short-Term Memory) algoritmalarını birleştiren hibrit bir derin öğrenme modelinin uygulamasını incelemektedir. Çalışmanın amacı, bu süreçlerin yönetimini iyileştiren tahmine dayalı modeller geliştirmektir. CNN-LSTM modeli, zaman serisi verilerindeki uzun vadeli bağımlılıkları ve karmaşık özellikleri yakalama konusundaki yeterliliği nedeniyle seçilmiş ve Destek Vektör Regresyonu (SVR: Support Vector Regression) gibi diğer modellerle karşılaştırılmıştır. Araştırma metan dönüşüm oranı, hidrojen-karbon monoksit oranı ve sentez gazı bileşimi gibi biyogaz reformunun önemli çıktılarını değerlendirmektedir. Modelin etkinliği RMSE, MAE ve MAPE ölçümleri kullanılarak değerlendirilmiştir. Farklı eğitim dönemleri sonrasında, metan dönüşüm oranı için RMSE 0,1905, MAE 0,1311 ve MAPE 0,0036 olarak kaydedilmiştir. Elde edilen sonuçlar, modelin tahmin başarısındaki yüksek doğruluğu ortaya koymaktadır. Bu çalışma, makine öğrenimi tekniklerinin endüstriyel uygulamalarda biyogaz reform süreçlerinin optimize edilmesi ve kontrol edilmesine katkı sağlayabileceğini göstermektedir. CNN-LSTM modelinin özellikle karmaşık biyokimyasal süreçleri yönetmedeki başarısı, derin öğrenme tekniklerinin potansiyelini vurgulamaktadır. Gelecekteki çalışmalar, modelin farklı biyogaz tesislerinde uygulanmasını ve optimizasyon parametrelerinin daha da iyileştirilmesini amaçlayacaktır. Mathematics ; Artificial intelligence ; Physics ; Computer science Machine Learning in Materials Science ; Reservoir Engineering and Simulation Methods
Authors: Ayon Tarafdar | Barjinder Pal Kaur
Source: Journal of Food Science and Technology (article, 2024-05-27)
Field: Chemistry — Analytical Chemistry

Intelligent modelling of sugarcane juice quality characteristics based on microfluidization processing conditions Food science ; Quality (philosophy) ; Chemistry ; Process engineering ; Engineering ; Physics Spectroscopy and Chemometric Analyses ; Sugarcane Cultivation and Processing ; Natural Products and Biological Research