jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anuar Bektemissov | A. Kassymov | Zh. K. Akishov | A. Zh. Adylkanova | T. N. Umyrzhan
Source: Bulletin of Shakarim University Technical Sciences (article, 2024-09-27)
Field: Materials Science — General Materials Science

INVESTIGATION OF THE HEAT CAPACITIES OF NANOFLUIDS BASED ON NANOPARTICLES OF Al2O3, TiO2 AND CuO BY THE ADDITIVE METHOD This study investigates the thermal properties of nanofluids, with a particular focus on their heat capacity when various nanoparticles are integrated into a base fluid. Nanofluids, which are composed of nanoparticles dispersed within a base fluid, are of significant interest due to their enhanced thermal characteristics compared to traditional fluids. The research employs the additive method, a widely used technique for estimating the effective heat capacity of nanofluids. This method posits that the total heat capacity of a nanofluid can be approximated by summing the contributions of each component according to its volume or mass fraction. This research represents the effect of nanopartilces concentration (1wt.%, 3 wt.%, 5 wt.%) on effective heat capacity of TiO 2 based nanofluid. The analysis reveals that key factors influencing the heat capacity of a nanofluid, as determined by the additive method, include the heat capacities of the individual components and the concentration of the nanoparticles. Specifically, the greater the disparity in heat capacities between the base fluid and the nanoparticles, and the higher the nanoparticle concentration, the more the nanofluid's heat capacity shifts toward that of the nanoparticles. The calculations in this study indicate that the most significant decrease in heat capacity occurs in a nanofluid containing 5 wt.% Al 2 O 3 nanoparticles with water as the base fluid. Conversely, the smallest reduction is observed in a nanofluid with 1 wt.% Al 2 O 3 nanoparticles in a 50% aqueous ethylene glycol solution. Nanofluid ; Nanoparticle ; Materials science ; Thermodynamics ; Nanotechnology ; Chemical engineering ; Physics ; Engineering Material Properties and Applications ; Advanced Materials and Semiconductor Technologies ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry
Authors: Marcel C. Forster | Kumar Tekwani Movellan | Eszter E. Najbauer | Stefan Becker | Loren B. Andreas
Source: Journal of Structural Biology X (article, 2024-02-21)
Field: Chemistry — Spectroscopy

Magic-angle spinning NMR structure of Opa60 in lipid bilayers Here we report the structure of Opa60 in lipid bilayers using proton-detected magic-angle spinning nuclear magnetic resonance (MAS NMR). Preparations including near-native oligosaccharide lipids reveal a consistent picture of a stable transmembrane beta barrel with a minor increase in the structured region as compared with the previously reported detergent structure. The large variable loops known to interact with host proteins could not be detected, confirming their dynamic nature even in a lipid bilayer environment. The structure provides a starting point for investigation of the functional role of Opa60 in gonococcal infection, which is understood to involve interaction with host proteins. At the same time, it demonstrates the recent advances in proton-detected methodology for membrane protein structure determination at atomic resolution by MAS NMR. Magic angle spinning ; Lipid bilayer ; Transmembrane protein ; Chemistry ; Nuclear magnetic resonance spectroscopy ; Bilayer ; Membrane protein ; Protein structure ; Nuclear magnetic resonance ; Model lipid bilayer ; Crystallography ; Biophysics ; Membrane ; Lipid bilayer phase behavior ; Physics ; Biochemistry ; Biology ; Stereochemistry Advanced NMR Techniques and Applications ; Protein Structure and Dynamics ; Lipid Membrane Structure and Behavior
Authors: Priya Priya | Mainak Sadhukhan
Source: arXiv (Cornell University) (preprint, 2024-07-11)
Field: Chemistry — Physical and Theoretical Chemistry

A new Green's function formalism for kinetic energy density functional for atomic and molecular system: Emergence of $N-$dependence using model potentials An accurate expression of the kinetic energy density of an electronic distribution in terms of the single particle reduced density matrix for atomic and molecular systems is a long-standing problem in electron structure theory. Existing kinetic energy density functionals are generally expressed as modifications over kinetic energy of homogeneous electron gas and/or von Weizsäcker kinetic energy. A large class of these functionals also require empirical parametrizations to make accurate predictions of the kinetic energy for atomic and molecular systems restricting their transferability. Moreover, the correct kinetic energy density which produces accurate local properties such as atomic shell structure is still an unsolved problem. In this work, we have developed an exact methodology that can be used to derive the kinetic energy of an electronic system of arbitrary spin multiplicity. One of the attractive features of this present analytical formalism is the possibility of systematic improvement of the kinetic energy by virtue of a novel perturbation series. Applying this methodology to simple model systems such as one-dimensional quantum harmonic oscillator and homogeneous electron gas produces a qualitatively correct $N$-dependence of kinetic energy as a result. A one-to-one correspondence between our formalism to the traditional Green's function formalism is also demonstrated. Formalism (music) ; Kinetic energy ; Physics ; Statistical physics ; Theoretical physics ; Classical mechanics ; Art Advanced Physical and Chemical Molecular Interactions ; Machine Learning in Materials Science ; Advanced Chemical Physics Studies
Authors: Jihan Nada Salsabila Erha | Dina Wahyu Indriani | Zaqlul Iqbal | Bambang Susilo | Dimas Firmanda Al Riza
Source: Research in Agricultural Engineering (article, 2024-12-31)
Field: Chemistry — Analytical Chemistry

Prediction of physicochemical characteristics of Lemon (Citrus limon cv. Montaji Agrihorti) using Vis-NIR spectroscopy and machine learning model Lemons are fruit products that grow well in Indonesia. Montaji Agrihorti is one of the lemon varieties found in Indonesia, a new variety developed by Balitjestro breeding. This lemon variety is seedless. In fact, lemons are harvested nearly all year-round. Equally important, evaluating the fruit's maturity level is crucial for determining the optimal harvest time. In this study, standardizing measurement on maturity level was conducted through Vis-NIR spectroscopy and machine learning models. In this case, non-destructive data from Vis-NIR spectroscopy were correlated with parameters related to fruit maturity and quality, such as soluble solid content (SSC), acidity, firmness, essential oil yield, and essential oil content. Non-destructive test involved capturing spectral data to be subsequently processed through machine learning models such as SVM, KNN, and random forest. The most accurate results were obtained using the SVM method for SSC and firmness parameters, withÂ accuracy of 72 and 78%, respectively. For visual and acidity parameters, the most accurate result was performed through random forest with visual accuracy value 94% for all features, all features-MA (moving averages) was 97%, 36-PCA (principal component analysis) was 94%, and 36-PCA-MA was 97%. As for acidity, the accuracy for all features was 89%, all features-MA was 81%, 36-PCA was 89%, and 36-PCA-MA was 83%. Principal component analysis ; Mathematics ; Support vector machine ; Random forest ; Artificial intelligence ; Horticulture ; Maturity (psychological) ; Yield (engineering) ; Machine learning ; Chemistry ; Pattern recognition (psychology) ; Statistics ; Computer science ; Materials science ; Biology Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Leaf Properties and Growth Measurement
Authors: Wei Cheng | Xiaoyu Lu | Xiaoming Wang | Weibing Li | Zhentao Xie | Jianan Zhang
Source: Journal of Physics Conference Series (article, 2024-12-01)
Field: Materials Science — Materials Chemistry

Study on predicting the stability of penetrating projectile charges via machine learning methods Abstract Due to the limitations of current theoretical research, numerical simulation, and experimental analysis for predicting the stability of penetrating projectile charge, in this work, we propose a method to predict the stability of charges by using machine learning methods. Three models are selected, including Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Tree (XGBoost). A practical sample dataset with inputs of the charge type, temperature and speed, and outputs of whether the charge is stabilized or not is constructed to train the model. The results indicate that using machine learning methods to predict the stability of charges is a feasible research direction. Projectile ; Stability (learning theory) ; Artificial intelligence ; Machine learning ; Computer science ; Materials science High-Velocity Impact and Material Behavior ; Anomaly Detection Techniques and Applications ; Advanced Measurement and Detection Methods
Authors: Cam Nhung Pham | Yaroslav Lebedev | Anna Drygval | Roman Gorbunov | Tatiana Gorbunova | Andrei Kuznetsov | Светлана А. Кузнецова | Dang Hoi Nguyen
Source: Journal of Degraded and Mining Lands Management (article, 2024-10-01)
Field: Materials Science — Biomaterials

Features of seasonal biogeochemical element migration in the "soil-plant" system: A case study of Bambusoideae in the Bidoup-Nui Ba National Park (Central Vietnam) The article presents unique research conducted in Bidoup-Nui Ba National Park, Vietnam, focusing on the biogeochemical element migration in soil and plants. The study aimed to identify element content changes, biological accumulation, and biogeochemical mobility during wet and dry seasons across different landscape conditions. The research revealed the active elements involved in migration and accumulation, assessed mobility and accumulation in bamboo organs, and highlighted the peculiarities within the "soil-plant" system. The study found that the uptake of certain microelements by plants is influenced by landscape facies and moisture conditions. For example, Zn, Cu, and Co were introduced through plant litter during the wet season and accumulated, while Mo accumulation was more pronounced in the dry season. Furthermore, the research observed variations in biological uptake by bamboo organs, with different landscape conditions and seasons playing a role. The biogeochemical mobility of elements in bamboo organs increased significantly with soil moisture during the wet season. Overall, the research provided insights into element accumulation and biogeochemical migration. Notably, the accumulation of element B was found to increase with soil moisture, while its reduction was associated with slope process activation during the wet season. Biogeochemical cycle ; National park ; Environmental science ; Element (criminal law) ; Geography ; Earth science ; Geology ; Ecology ; Archaeology ; Biology ; Political science Clay minerals and soil interactions
Authors: Ellisson H. de Paulo | Francine Dalapícola Dos Santos | Gabriely S. Folli | Márcia H.C. Nascimento | Mariana Kuster Moro | Pedro Henrique Pereira da Cunha | Samantha Ribeiro Campos da Silva | Eustáquio Vinícius Ribeiro de Castro | Álvaro Cunha Neto | Paulo R. Filgueiras | Marco Flôres Ferrão
Source: Revista Ifes Ciência (article, 2024-03-25)
Field: Chemistry — Spectroscopy

VARIABLE SELECTION METHODS APPLIED IN HTGC DATA TO DETERMINE PHYSICOCHEMICAL PROPERTIES OF CRUDE OILS High-temperature gas chromatography (HTGC) is an analytical technique employed in the petroleum industry for component separation. By incorporating chemometrics, HTGC data can be effectively utilized to predict various properties of crude oil. However, HTGC chromatograms generate a substantial number of variables, some of which may lack pertinent chemical information. Consequently, employing variable selection methods becomes crucial to reduce the number of variables and enhance the predictive capability of calibration models. In this study, the interval partial least squares (iPLS), synergy interval partial least squares (siPLS), and ordered predictors selection (OPS) methods were applied for variable selection to construct linear regression models. The main objective was to investigate the potential of these methods in predicting eight properties of crude oil: American Petroleum Institute (API) gravity, standardized kinematic viscosity at 50 °C (VISp), flash point (FP), Reid vapor pressure (RVP), micro carbon residue (MCR), saturates (SAT), aromatics (ARO), and polar (POL) content. While all variable selection methods yielded satisfactory results, the OPS-PLS regression models consistently exhibited the best performance in estimating these properties, achieving root mean squared error of prediction (RMSEP) values of 1.244 for API, 0.029 for VISp, 15.356 °C for FP, 0.324 kPa for RVP, 0.629 wt% for MCR, 3.691 wt% for SAT, 2.939 wt% for ARO, and 3.374 wt% for POL. Variable selection demonstrated remarkable effectiveness, significantly improving the accuracy of the models, and allowing for the creation of concise models with a focused set of variables. Crude oil ; Selection (genetic algorithm) ; Environmental science ; Petroleum engineering ; Computer science ; Geology ; Artificial intelligence Analytical Chemistry and Chromatography ; Petroleum Processing and Analysis
Authors: M.M. Anissova | Manshuk Mambetova | Gaukhar Yergaziyeva
Source: Neft i gaz (article, 2024-12-15)
Field: Materials Science — Materials Chemistry

INVESTIGATION OF THE PHYSICOCHEMICAL CHARACTERISTICS AND ADSORPTION PROPERTIES OF MgO/5A И Na2O/5A COMPOSITE SORBENTS This study investigates the physicochemical properties and sorption characteristics of composite sorbents based on 5A zeolite, modified with magnesium oxide (MgO) and sodium oxide (Na2O), in the process of carbon dioxide (CO2) adsorption. The sorbents were synthesized via a capillary impregnation method with varying active component contents (5, 10, and 15 wt.%). The findings revealed that the highest sorption capacity was achieved with 10 wt.% MgO (27.3%) and 10 wt.% Na2O (23.4%) at an adsorption temperature of 500 °C. X-ray phase analysis (XRD) and infrared spectroscopy (IR) confirmed the formation of carbonate phases (MgCO3 and Na2CO3) after CO2 sorption, along with changes in the structural properties of the sorbents. The cyclic stability study demonstrated a decrease in sorption capacity after 10 cycles: from 27.3% to 26.0% for 10 wt.% MgO/5A, and from 23.4% to 17.8% for 10 wt.% Na2O/5A. Composite number ; Adsorption ; Chemical engineering ; Materials science ; Chemistry ; Composite material ; Organic chemistry Magnesium Oxide Properties and Applications
Authors: Hani Cheikh Sleimana | Kevin M. Moerman | Diana Oliveira | Joseph Jacob | Nesrin Moğulkoç | Brian R Davidson | Simon Walker‐Samuel | Rebecca J. Shipley
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-06-28)
Field: Materials Science — Surfaces, Coatings and Films

Tube2FEM: a general-purpose highly-automated pipeline for flow related processes in (embedded) tubular objects Abstract This paper presents a comprehensive and highly-automated open-source pipeline for simulating flow and flow-related processes in (embedded) tubular structures. Addressing a critical gap in computational fluid dynamics (CFD) and simulation sciences, it facilitates the transition from raw three-dimensional imaging, graph networks, or CAD models of tubular objects to refined, simulation-ready meshes. This transition, traditionally labor-intensive and challenging, is streamlined and highly-automated through a series of innovative steps that include surface mesh processing, centre-line construction, anisotropic mesh generation, and volumetric meshing, leading to Finite Element Method (FEM) simulations. The pipeline leverages a range of open-source software and libraries, notably GIBBON , FEniCS , and Paraview , to provide flexibility and broad applicability across different simulation scenarios, ranging from biomedical to industrial applications. We demonstrate the versatility of our approach through five distinct applications, including the mesh generation for soil-root systems, lung airways, microcirculation networks, and portal vein networks, each originating from a different data source. Moreover, for several of these cases, we incorporate Computational Fluid Dynamics (CFD) simulations and strategies for 3D-1D coupling between the embedding domain and the embedded structures. Finally, we outline some future perspectives aimed at enhancing accuracy, reducing computational time, and incorporating advanced modeling and boundary condition strategies to further refine the framework’s capabilities. Computer science ; Computational fluid dynamics ; Polygon mesh ; Mesh generation ; Pipeline (software) ; Computational science ; Finite element method ; Embedding ; Fluid dynamics ; Software ; Distributed computing ; Engineering ; Aerospace engineering ; Computer graphics (images) ; Artificial intelligence ; Mechanics Surface Modification and Superhydrophobicity ; Computational Geometry and Mesh Generation
Authors: Paula S. Branco | Luı́s C. Branco | Flávia Leitão | Hugo Cruz
Source: Boletim da Sociedade Portuguesa de Química (article, 2024-12-31)
Field: Chemistry — Inorganic Chemistry

Quinonas Como Mediadores Redox Orgânicos em Baterias Redox de Caudal Quinones as Organic Redox Mediators in Redox Flow Batteries.Electrochemical processes underlie the operation of electrochemical devices for energy storage and conversion.Some of these systems pose challenges such as high cost, toxicity, use of scarce metals, and recyclability, among other issues.Organic redox flow batteries (RFB) have emerged as a significant area of research, presenting a promising alternative to expensive metal-based systems like vanadium redox flow batteries.This review delves into the discussion of organic redox mediators used in redox flow batteries.The family of quinones stands out, providing suitable organic redox mediators (ORM) due to the ease of modulating molecular structures through synthesis.This adaptability addresses challenges related to redox potentials, solubility (aqueous vs. non-aqueous solution), and stability of these compounds.Over the past five years, the period covered by this review, various research groups have developed systems based on the quinone nucleus for RFB that can open up excellent prospects for the future. Redox ; Chemistry ; Inorganic chemistry Pigment Synthesis and Properties ; Porphyrin and Phthalocyanine Chemistry ; TiO2 Photocatalysis and Solar Cells
Authors: John D. Martin | Fotios Mpekris | Vikash P. Chauhan | Margaret R. Martin | M. Walsh | Matthew D. Stuber | Donald M. McDonald | Fan Yuan | Triantafyllos Stylianopoulos | Rakesh K. Jain
Source: Drug Delivery (article, 2024-11-20)
Field: Materials Science — Biomaterials

Fixation alters the physical properties of tumor tissue that regulate nanomedicine transport To have the desired therapeutic effect, nanomedicines and macromolecular medications must move from the site of injection to the site of action, without having adverse effects. Transvascular transport is a critical step of this navigation, as exemplified by the Enhanced Permeability and Retention (EPR) effect in solid tumors, not found in normal organs. Numerous studies have concluded that passive, diffusion- and convection-based transport predominates over active, cellular mechanisms in this effect. However, recent work using a new approach reevaluated this principle by comparing tumors with or without fixation and concluded the opposite. Here, we address the controversy generated by this new approach by reporting evidence from experimental investigations and computer simulations that separate the contributions of active and passive transport. Our findings indicate that tissue fixation reduces passive transport as well as active transport, indicating the need for new methods to distinguish the relative contributions of passive and active transport. Nanomedicine ; Fixation (population genetics) ; Biophysics ; Materials science ; Injection site ; Biomedical engineering ; Cancer research ; Chemistry ; Medicine ; Nanotechnology ; Biology ; Biochemistry Nanoparticle-Based Drug Delivery ; Characterization and Applications of Magnetic Nanoparticles ; Polymer Surface Interaction Studies
Authors: Abdullah Sadık Tazegül | Mesut Bitkin | Ayşe Nur Öztekin | Ömer Sinan Şahin | Osman Babayiğit
Source: DergiPark (Istanbul University) (article, 2024-10-01)
Field: Materials Science — Polymers and Plastics

Çift Borulu Tip Eşanjörlerin Tasarım ve Performans Optimizasyonu CFD ve Ekonomik Analizlere Dayalı Sayısal Bir Çalışma Bu çalışmada çift boru tip ısı eşanjörü tasarımı için boyutsuz parametreler önerilmiş ve bu parametreler kullanılarak yanıt yüzeyi metodolojisi ile deneysel tasarım yapılmıştır. Elde edilen deney tasarım parametreleri kullanılarak sayısal modeller oluşturulmuş ve modeller Hesaplamalı akışkanlar dinamiği yazılımı kullanılarak çözülmüştür. Çeşitli tasarım parametreleri kullanılarak Çift Borulu Tip Isı Değiştiricilerin çıkış sıcaklığı ve basınç düşüşü değerlerini tahmin etmek için kuadratik modeller önerilmiştir. Her bir boyutsuz tasarım parametresinin çıkış sıcaklığı ve basınç düşüşü üzerindeki etkisi değerlendirilmiş ve minimum basınç kaybı ile maksimum ısı transferi için optimum bir tasarım sunulmuştur. Economics ; Business administration ; Business Textile materials and evaluations
Authors: Matthew J. Colbrook | Mark Embree | Jake Fillman
Source: arXiv (Cornell University) (preprint, 2024-07-29)
Field: Materials Science — Materials Chemistry

Optimal Algorithms for Quantifying Spectral Size with Applications to Quasicrystals We introduce computational strategies for measuring the ``size'' of the spectrum of bounded self-adjoint operators using various metrics such as the Lebesgue measure, fractal dimensions, the number of connected components (or gaps), and other spectral characteristics. Our motivation comes from the study of almost-periodic operators, particularly those that arise as models of quasicrystals. Such operators are known for intricate hierarchical patterns and often display delicate spectral properties, such as Cantor spectra, which are significant in studying quantum mechanical systems and materials science. We propose a series of algorithms that compute these properties under different assumptions and explore their theoretical implications through the Solvability Complexity Index (SCI) hierarchy. This approach provides a rigorous framework for understanding the computational feasibility of these problems, proving algorithmic optimality, and enhancing the precision of spectral analysis in practical settings. For example, we show that our methods are optimal by proving certain lower bounds (impossibility results) for the class of limit-periodic Schrödinger operators. We demonstrate our methods through state-of-the-art computations for aperiodic systems in one and two dimensions, effectively capturing these complex spectral characteristics. The results contribute significantly to connecting theoretical and computational aspects of spectral theory, offering insights that bridge the gap between abstract mathematical concepts and their practical applications in physical sciences and engineering. Based on our work, we conclude with conjectures and open problems regarding the spectral properties of specific models. Quasicrystal ; Algorithm ; Computer science ; Mathematics ; Geometry Quasicrystal Structures and Properties ; Phase-change materials and chalcogenides