jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Elena Adam | Waled . Y. - | Alsalhin. G. - | Jamal Abdulrasul - | Татьяна Мерцалова
Source: International Journal For Multidisciplinary Research (article, 2025-02-20)
Field: Materials Science — Materials Chemistry

Study in Tribology Science and Its Importance in Mechanical Engineering Tribology is the science of interacting surfaces in relative motion, which makes it particularly important in mechanical engineering because so much energy is lost to friction in mechanical components. In this research, the study of tribology technology will be addressed in detail in mechanical engineering by introducing the technology and its development throughout history, as well as talking at length about its basic elements friction, wear and lubrication in addition to ways of test and measurement methods, some applications of tribology technology will be explained, also advanced research in this field will be discussed and finally we will be talk about future of tribology. Tribology ; Engineering ; Engineering ethics ; Mechanical engineering ; Forensic engineering Metal Alloys Wear and Properties ; Tribology and Wear Analysis ; Lubricants and Their Additives
Authors: Xuan Gong | Jiang Wang | Simin Liu | Huanwen Chen
Source: Chinese Science Bulletin (Chinese Version) (article, 2025-11-01)
Field: Chemistry — Spectroscopy

Mass spectrometry techniques for pharmaceutical analysis without sample pretreatment 药物是人类对抗疾病、维护健康的重要保障。药物分析在药物质量控制、疗效评价等过程中发挥着关键的作用。广泛采用的经典药品分析方法包括光谱法、高效液相色谱-质谱法(HPLC-MS)、气相色谱-质谱法(GC-MS)、核磁共振波谱（NMR）、电化学方法等。在实际生产中，相关分析方法存在易受多组分干扰、样品预处理时间长、整体分析效率低等缺点。近年来，直接质谱分析技术因具有无需样品预处理、分析速度快、灵敏度高、适用性强等特点，可在保持色质联用技术性能的同时直接分析各种常见样品，极大的缩短分析时间，提高分析速率，在药物分析领域中发挥着重要的作用。本文主要介绍了不同类别的直接质谱分析技术及其在药物分析中的应用，旨在为研究人员介绍不同直接质谱分析技术的分析特点，在药代动力学分析、化药分析、中药分析等方面提供参考。 Sample (material) ; Mass spectrometry ; Analyte ; Quantitative analysis (chemistry) ; Sample preparation Mass Spectrometry Techniques and Applications ; Forensic Toxicology and Drug Analysis ; Analytical chemistry methods development
Authors: Tsega Asresa | Melaku Bayih | Shashi Kant Gupta | Eman Abdullah Aldakheel | Diaa Salama AbdElminaam
Source: Research Square (preprint, 2025-05-07)
Field: Chemistry — Analytical Chemistry

Efficient Multi-Class Image-Based Rosemary Variety Verification and Classification Model Using Deep Learning: A Scientific Investigational Study Class (philosophy) ; Variety (cybernetics) ; Artificial intelligence ; Computer science ; Deep learning ; Machine learning ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Traditional Chinese Medicine Studies
Authors: E. V. Naydenkin | I. P. Mishin | Vladimir Oborin | A. I. Manisheva
Source: Fatigue & Fracture of Engineering Materials & Structures (article, 2025-05-19)
Field: Materials Science — Materials Chemistry

The Alpha‐Case Formation Effect on Very High Cycle Fatigue and Fracture of Ultrafine‐Grained Near β Titanium Alloy ABSTRACT Ultrasonic testing was conducted to investigate for the first time the impact of alpha‐case formation during air aging (450°C, 5 h) on the very high cycle fatigue (VHCF) and failure of an ultrafine‐grained (UFG) near β Ti‐5Al‐5V‐5Mo‐1Cr‐1Fe alloy. The research findings indicate that air aging results in the development of an alpha‐case layer, diminishing the fatigue properties of the UFG titanium alloy produced by radial shear rolling during VHCF testing. The fatigue limit of the alloy samples with an oxide layer decreased from approximately 620 to 520 MPa based on 10 9 cycles. Examination of the fatigue failure mechanisms revealed that the alpha‐case layer does not significantly impact crack initiation at stress amplitudes below 650 MPa but does accelerate crack propagation. In the alloy without an oxide layer, at all stress amplitudes, the crack initiation is internal. Oxidation leads to a change in the crack initiation mechanism from internal to subsurface at stress amplitudes above 650 MPa with low‐cycle fatigue failure. Materials science ; Alloy ; Metallurgy ; Titanium alloy ; Fracture (geology) ; Low-cycle fatigue ; Titanium ; Composite material Titanium Alloys Microstructure and Properties ; Microstructure and mechanical properties ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Thilina Weerakkody | Elio Matteo Curcio | Giuseppe Carbone | Carmine Maletta | Emanuele Sgambitterra | Caterina Lamuta
Source: Shape Memory and Superelasticity (article, 2025-12-02)
Field: Materials Science — Materials Chemistry

Robust Control of Shape Memory Alloys for Assistive Robotics Applications Abstract Shape Memory Alloys (SMAs) are a popular class of actuators widely used in complex soft robotics applications due to their shape memory effect, high recoverable strain, and stress. However, most existing actuation models frequently fail to accurately capture hysteresis and dynamic loading behavior while remaining computationally efficient. Moreover, current control strategies often lack adaptability, robustness, and the ability to generalize to varying system dynamics. This paper presents a robust adaptive closed-loop controller for electro-thermally actuated Ni–Ti SMAs, developed based on a Finite State Machine framework to address these challenges. The proposed controller is designed to compensate for disturbances and uncertainties in the SMA behavior. Experimental validation and statistical analysis have demonstrated the effectiveness of the $${\mathcal {L}}_{1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>L</mml:mi> <mml:mn>1</mml:mn> </mml:msub> </mml:math> adaptive controller across various SMA configurations, enabling precise strain and stress target tracking. Finally, the controller is deployed to a case study involving a Ni–Ti SMA-powered assistive robotic device, where it successfully manages position tracking with enhanced performance. Robotics ; SMA* ; Controller (irrigation) ; Actuator ; Robust control ; Shape-memory alloy ; Robot ; Adaptive control Shape Memory Alloy Transformations ; Piezoelectric Actuators and Control ; Soft Robotics and Applications
Authors: Héctor M. Iga-Buitrón | Tom G. Mackay | Akhlesh Lakhtakia
Source: Journal of Applied Physics (article, 2025-09-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Cubic-nonlinearity enhancement via homogenization of a composite material containing truncated spheroidal particles with distributions of shapes Closed-form expressions were derived for depolarization dyadics relevant to electrically small particles immersed in a cubically nonlinear uniaxial dielectric ambient medium. The particles considered were spheroids, hemispheroids, doubly truncated spheroids, and singly truncated spheres. These depolarization dyadics were implemented within the Bruggeman homogenization formalism to predict the linear and nonlinear constitutive parameters of a homogenized composite material (HCM) composed of a randomly distributed mixture of oriented particles with a distribution of shapes. Numerical simulations were performed to investigate (i) the influence of particle shape and distribution of shapes upon the constitutive parameters of the HCM and (ii) the degree of cubic nonlinearity exhibited by the HCM relative to that exhibited by the component materials. In general, the enhancement in the degree of cubic nonlinearity due to homogenization was found to increase as the diversity of particle shapes increased and also as the contrast between the linear parts of the permittivity scalars for the component materials increased. Greater degrees of cubic-nonlinearity enhancement arose for truncated spheroidal particles, as compared to spheroidal particles. Also, the manner in which the shapes of the component particles were distributed influenced the degree of loss exhibited by the HCM as well as its anisotropy. Homogenization (climate) ; Composite number ; Materials science ; Composite material ; Nonlinear system ; Physics Liquid Crystal Research Advancements ; Photonic Crystals and Applications ; Composite Material Mechanics
Authors: Shiyu Song | Zhenjie Wang | Leiqing Pan | Kang Tu
Source: Foods (article, 2025-06-14)
Field: Chemistry — Analytical Chemistry

A Novel Hyperspectral Microscope Imaging Technology for the Evaluation of Physicochemical Properties and Heterogeneity in ‘Xia Hui 6’ Peaches Hyperspectral microscope imaging (HMI) was employed to evaluate the physiochemical properties of and the large intra-variability in individual fruit of 'Xia Hui 6' peaches during storage, which gave insights into the heterogeneity of peach fruits at the microscale. The physicochemical characteristics such as firmness (FI), soluble sugar content (SSC), and <i>L</i>* value of peaches showed significant changes, while the microstructure of the tissues broke down. Principal component analysis (PCA) was applied to peach tissues from the sunny side and shady side at different storage stages, which allowed us to clearly visualize the distribution of sugars, water, and pigments at the cellular scale. Single-feature variables were constructed to clarify the correlation between the characteristic bands and physicochemical parameters based on Pearson correlation analysis, with an R<sup>2</sup> of 0.99 for firmness at 588 nm, 0.98 for titratable acidity (TA) at 432 nm, 0.88 for the <i>L</i>* value at 430 nm and 0.83 for the <i>b</i>* value at 426 nm. This work demonstrated that HMI technology as an accurate and highly effective tool in evaluating the quality of 'Xia Hui 6' peaches and targeting, allowing us to visualize the spatial heterogeneity within peach fruit tissues. Hyperspectral imaging ; Microscope ; Chemical imaging ; Nanotechnology ; Materials science ; Artificial intelligence ; Computer science ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Food Quality and Safety Studies
Authors: Rodica‐Mariana Ion | Cornel Marin | Vasile Bratu | Florin Ion Popa
Source: The Scientific Bulletin of "Valahia" University. Materials and Mechanics (article, 2025-10-01)
Field: Materials Science — Materials Chemistry

Editorial The materials science community is living a moment of extraordinary transformation.As global priorities shift toward sustainability, resilience, and the preservation of both built and cultural environments, our discipline continues to redefine itself-integrating advanced characterization, digitalization, and circular-economy principles.This issue of the journal reflects this vibrant evolution, showcasing research that expands our understanding of materials, their behavior, and their applications across modern engineering and heritage conservation. Cultural heritage ; Work (physics) ; Moment (physics) ; Field (mathematics) Material Selection and Properties ; Cultural Heritage Management and Preservation ; Conservation Techniques and Studies
Authors: V. Lavanya | R. Gangai Selvi | S. G. Patil | J Auxcilia | V Karthick | S. Vishnu Shankar
Source: Plant Science Today (article, 2025-05-17)
Field: Chemistry — Analytical Chemistry

Wavelet enhanced time series forecasting for tomato price volatility in South Indian markets Accurate price forecasting is crucial in the agricultural sector, where farmers face significant challenges due to price volatility. Price fluctuations directly influence the livelihoods of producers and the affordability for consumers, making crop management difficult for farmers. Agricultural time series data are often highly complex and nonlinear, making price prediction, a challenging task. While various forecasting approaches, including stochastic models, machine-learning techniques and hybrid models, have been explored, their effectiveness is often limited due to the inherent complexity of agricultural datasets. Recently, wavelet-enhanced models have emerged as a robust approach, effectively capturing both short-term fluctuations and long-term trends. Wavelet decomposition plays a vital role in denoising data and extracting inherent patterns, thereby improving predictive accuracy. This study investigates the application of wavelet-based models for forecasting the monthly wholesale tomato prices in key South Indian markets such as Bangalore, Chennai and Trivandrum. The findings address the forecasting challenges posed by the volatility of tomato prices, providing valuable insights for stakeholders, including farmers, traders and policymakers, to facilitate informed decision-making. Further, the study highlights the necessity of a robust price policy to stabilize market fluctuations, safeguard farmers’ livelihoods and ensure fair returns. Hence, incorporating advanced forecasting techniques, such as wavelet-based models can significantly improve market stability and promote sustainable agricultural development. Volatility (finance) ; Wavelet ; Series (stratigraphy) ; Time series ; Econometrics ; Economics ; Environmental science ; Mathematics ; Computer science ; Statistics ; Geology ; Artificial intelligence ; Paleontology Spectroscopy and Chemometric Analyses ; Stock Market Forecasting Methods
Authors: Yana Koleva
Source: Springer Link (Chiba Institute of Technology) (article, 2025-12-16)
Field: Materials Science — Materials Chemistry

Toxicological profile of porphyrin derivative from petroleum Porphyrins and chlorins are both tetrapyrrole macrocycles, but chlorins are partially hydrogenated porphyrins, meaning they have one pyrroline ring instead of four pyrrole rings. Porphyrins are the foundational structure, while chlorins are derived from them through hydrogenation. Chlorophylls are the primary pigments used by photosynthetic organisms to absorb light, transfer energy, and initiate charge separation, a process essential for life. The CompTox Chemistry Dashboard is a tool for predicting intrinsic chemical and toxicological properties of a single, isolated molecule in a standardized environment. The goal is to use the US Environmental Protection Agency’s (EPA) CompTox Chemicals Dashboard to predict the toxicological properties of a chlorin (porphyrin derivative) by inputting its chemical information and leveraging the platform’s predictive tools. This will help assess the compound’s potential hazards by using the Dashboard’s integrated data on chemistry, toxicity, and exposure for a vast number of chemicals. Tetrapyrrole ; Porphyrin ; Chlorin ; Pyrrole ; Derivative (finance) ; Photosensitizer ; Molecule Porphyrin and Phthalocyanine Chemistry ; Porphyrin Metabolism and Disorders ; Photodynamic Therapy Research Studies
Authors: Yaohai Lin | Edward S. Yang | Wei Chen | Changkai Lin | Allen Chen | Chen Yang | Liusuo Wu
Source: Applied Engineering in Agriculture (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Volume Prediction Method for Pomelo Based on Symmetry Axial Highlights Multi-angle based approach for pomelo dataset collection improves the robustness of volume estimation models. Symmetry axis feature extraction is more suitable for volume estimation of pomelo fruit shape. BP Neural Network-based estimation model shows better volume estimation ability. Abstract. Pomelo quality grading helps to control the quality of pomelo production and promotes a standardized production. The realization of automated pomelo quality grading relies on the acquisition of several phenotypic parameters, with pomelo volume being a crucial one. Fruit phenotypic features, such as projected area, perimeter, radial distance, and the maximum radius of the tangent circle, are often used to estimate fruit volume through image processing. To enhance the accuracy of volume estimation, this article introduces a pomelo volume estimation model that relies on image features. This model is based on an analysis of the fruits’ symmetry axis and combines various features, including the projected area, perimeter, radial distance, and the maximum radius of the tangent circle. In this study, we collected a dataset of 3,200 pomelo images and compared the prediction results under different parameter combinations. After incorporating the parameters associated with the symmetry axis, the root mean square error of volume prediction was 159.82. The coefficient of determination was 0.84, with a mean absolute error of 142.67 and a mean absolute percentage error of 0.23. Notably, the coefficient of determination was improved by 0.26 compared to the results obtained without considering the symmetry axis features. The prediction error falls within the acceptable range, meeting the requirements of practical application. Overall, the proposed method provides a valuable technical reference for pomelo quality grading. Keywords: Axis of symmetry, Feature parameters, Machine learning, Volume prediction. Volume (thermodynamics) ; Symmetry (geometry) ; Mathematics ; Materials science ; Engineering ; Environmental science ; Physics ; Thermodynamics ; Geometry Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement
Authors: Narae Kim | Chayanee Chairattanawat | Jaewook Kim
Source: Journal of Plant Biotechnology (article, 2025-11-19)
Field: Chemistry — Organic Chemistry

Orangebark: The simplest AI model to discriminate tree species from bark images Research on artificial intelligence (AI)-assisted discrimination of tree species using simple images is ongoing.Evaluation of the performance of almost all such models developed to date poses a significant technical hurdle.Thus, there is an urgent need for an easy-to-use AI model or pipeline for AI model development.Using the Orange3 visual programming environment, we developed an AI model called Orangebark, which is capable of identifying tree species from RGB images of their bark.To develop Orangebark, we utilized two independent public image datasets comprising thousands of images.We constructed a systematic pipeline to examine each step involved in constructing AI models using Orange3.Using this pipeline, we developed Orangebark, which can distinguish 18 tree species with an area under the ROC curve greater than 0.99 and a recall value of 0.873.The pipeline will enable plant biology researchers to readily optimize the parameters for development of AI models, thereby enhancing the pace of AI model development, and provides an easy-to-use model for discrimination of tree species.We anticipate that Orangebark will be widely utilized owing to its extreme ease of use. Bark (sound) ; Pattern recognition (psychology) ; Tree (set theory) ; Key (lock) Wood and Agarwood Research ; Smart Agriculture and AI ; Remote Sensing and LiDAR Applications
Authors: Hao Yin | Mark Hutter | Christian Wagner | F. Stefan Tautz | François C. Bocquet | Christian Kumpf
Source: Physical Review Materials (article, 2025-04-09)
Field: Materials Science — Materials Chemistry

Epitaxial growth of mono- and (twisted) multilayer graphene on SiC(0001) To take full advantage of twisted bilayers of graphene or other two-dimensional materials, it is essential to precisely control the twist angle between the stacked layers, as this parameter determines the properties of the heterostructure. In this context, a growth routine using borazine as a surfactant molecule on SiC(0001) surfaces has been reported, leading to the formation of high-quality epitaxial graphene layers that are unconventionally oriented, i.e., aligned with the substrate lattice <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mrow><a:mo>(</a:mo><a:mi mathvariant="normal">G</a:mi><a:mtext>−</a:mtext><a:mi>R</a:mi><a:msup><a:mn>0</a:mn><a:mo>∘</a:mo></a:msup><a:mo>)</a:mo></a:mrow></a:math> [Bocquet ]. Since the <c:math xmlns:c="http://www.w3.org/1998/Math/MathML"><c:mrow><c:mi mathvariant="normal">G</c:mi><c:mtext>−</c:mtext><c:mi>R</c:mi><c:msup><c:mn>0</c:mn><c:mo>∘</c:mo></c:msup></c:mrow></c:math> layer sits on a buffer layer, also known as zeroth-layer graphene (ZLG), which is rotated <e:math xmlns:e="http://www.w3.org/1998/Math/MathML"><e:msup><e:mn>30</e:mn><e:mo>∘</e:mo></e:msup></e:math> with respect to the SiC substrate and still covalently bonded to it, decoupling the <f:math xmlns:f="http://www.w3.org/1998/Math/MathML"><f:mrow><f:mi>ZLG</f:mi><f:mtext>−</f:mtext><f:mi>R</f:mi><f:msup><f:mn>30</f:mn><f:mo>∘</f:mo></f:msup></f:mrow></f:math> from the substrate can lead to high-quality twisted bilayer graphene (tBLG). Here, we report the decoupling of <g:math xmlns:g="http://www.w3.org/1998/Math/MathML"><g:mrow><g:mi>ZLG</g:mi><g:mtext>−</g:mtext><g:mi>R</g:mi><g:msup><g:mn>30</g:mn><g:mo>∘</g:mo></g:msup></g:mrow></g:math> by increasing the temperature during annealing in a borazine atmosphere. While this converts <h:math xmlns:h="http://www.w3.org/1998/Math/MathML"><h:mrow><h:mi>ZLG</h:mi><h:mtext>−</h:mtext><h:mi>R</h:mi><h:msup><h:mn>30</h:mn><h:mo>∘</h:mo></h:msup></h:mrow></h:math> to <i:math xmlns:i="http://www.w3.org/1998/Math/MathML"><i:mrow><i:mi mathvariant="normal">G</i:mi><i:mtext>−</i:mtext><i:mi>R</i:mi><i:msup><i:mn>30</i:mn><i:mo>∘</i:mo></i:msup></i:mrow></i:math> and thus produces tBLG, the growth process at elevated temperature is no longer self-limiting, so that the surface is covered by a patchwork of graphene multilayers of different thicknesses. We find a 20% coverage of tBLG on ZLG, while on the rest of the surface tBLG sits on one or more additional graphene layers. In order to achieve complete coverage with tBLG only, alternative ways of decoupling the ZLG, e.g., by intercalation with suitable atoms, may be advantageous. Materials science ; Epitaxy ; Graphene ; Nanotechnology ; Optoelectronics ; Layer (electronics) Graphene research and applications ; Boron and Carbon Nanomaterials Research ; Graphene and Nanomaterials Applications
Authors: Angel Hernandez-Mejias | Gabriel D. Jimenez-Nieves | Eduardo J. E. Caro‐Diaz
Source: ChemRxiv (preprint, 2025-04-06)
Field: Materials Science — Biomaterials

In Silico Design and Analysis of Cyanobacterial Pseudo-Natural Products Marine cyanobacteria give rise to natural products (NPs) that exhibit potent and selective bioactivity towards a broad spectrum of diseases. Nonetheless, like many other NPs, most of these compounds suffer from poor drug-like physicochemical properties while the percentage of structurally novel NPs steadily declines. To address this, we have created a library in silico of 2,415 cyanobacterial pseudo-NPs, where cyanobacterial NP fragments were tethered with privileged scaffolds from a variety of non-cyanobacterial NPs via a hypothetical peptide bond formation. Our pseudo-NP library was analyzed using various computational platforms to provide predicted physicochemical properties, lead-likeness penalties, NP-likeness scores, and Tanimoto coefficients when compared to publicly available compound libraries. Upon comparative analysis, our results demonstrate that most of the cyanobacterial pseudo-NPs created are predicted to possess drug- and lead-like properties, populate low density chemical space in terms of their NP-likeness, and provide structurally unique scaffolds when compared to publicly available small-molecule databases. We predict that our cyanobacterial pseudo-NP library will provide suitable synthetic targets for drug discovery and development, and a platform to be expanded upon using AI fragment harvesting tools for the creation of larger pseudo-NP libraries, creating synthetically tractable NP-like compound for drug discovery. In silico ; Natural (archaeology) ; Biochemical engineering ; Biology ; Geography ; Engineering ; Archaeology Diatoms and Algae Research