jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Diego Gómez‐Díaz | Lidia Domínguez-Ramos | Giulio Malucelli | M. Sonia Freire | Julia González‐Álvarez | Massimo Lazzari
Source: Preprints.org (preprint, 2023-12-25)
Field: Materials Science — Materials Chemistry

Hierarchically Porous S/N/O Enriched Carbons From Polyacrylonitrile-Based Block Copolymers for Selective Separation of Gas Streams A series of polyacrylonitrile (PAN)-based block copolymers with poly(methyl methacrylate) (PMMA) as sacrificial bock were synthesized by atom transfer radical polymerization and used as precursors for the synthesis of porous carbons. The carbons enriched with O- and S-containing groups, introduced by controlled oxidation and sulphuration, respectively, were characterized by Raman spectroscopy, scanning electron microscopy, and X-ray photoelectron spectrometry, and their surface textural properties were measured by a volumetric analyzer. We observed that the presence of sulphur tends to modify the structure of the carbons, from microporous to mesoporous, while the use of copolymers with a range of molar composition PAN/PMMA between 10/90 to 47/53 allows the obtainment of carbons with different degrees of porosity. The amount of sacrificial block only affects the morphology of carbons stabilized in oxygen, inducing their nanostructuration, but has not effect on their chemical composition. We also demonstrated their suitability for separating a typical N2/CO2 post-combustion stream. Polyacrylonitrile ; Copolymer ; Microporous material ; Atom-transfer radical-polymerization ; Mesoporous material ; Chemical engineering ; Polymerization ; Materials science ; X-ray photoelectron spectroscopy ; Porosity ; Polymer chemistry ; Scanning electron microscope ; Raman spectroscopy ; Chemistry ; Organic chemistry ; Polymer ; Catalysis ; Composite material Covalent Organic Framework Applications ; Membrane Separation and Gas Transport ; Carbon dioxide utilization in catalysis
Authors: M. Sakthivel | D. Buvisa | B. GokulaVani | M. Jeyapriya | Rahmayuni Sri
Source: Journal of Engineering Management and Information Technology (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

FOOD PRODUCTS DEFILEMENT ANALYZER USING IOT In order to make additional, quick profits, shopkeepers frequently adulterate food today. Foods are adulterated by adding things like ripening mangoes, chalk powder to turmeric, starch to curry powder, papaya seeds to black pepper, and other things. Adulteration is a common practise to increase profits, but it can have extremely harmful effects on people. The qualitative spectroscopic method offers a better way to identify the toxic components in milk and other things. The goal of this research is to develop a low-cost, portable, AI-based, non-destructive sensor system that can be used to detect the adulterant in real-time in order to solve this problem. The users can access a dedicated site with an Iot platform from anywhere to view the adulterant that has been found.In this study, the conductivity and pH meter methods were used to examine the food products in order to determine the degree of adulteration present. Adulterant ; Internet of Things ; Food products ; Pepper ; Food science ; Computer science ; Business ; Computer security ; Chemistry Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food
Authors: Yahya Saleh | Álvaro Fernández Corral | Vogt, Emil | Armin Iske | Jochen Küpper | Andrey Yachmenev
Source: arXiv (Cornell University) (preprint, 2023-08-31)
Field: Chemistry — Spectroscopy

Computing excited states of molecules using normalizing flows Calculations of highly excited and delocalized molecular vibrational states are computationally challenging tasks, which strongly depends on the choice of coordinates for describing vibrational motions. We introduce a new method that leverages normalizing flows -- parametrized invertible functions -- to learn optimal vibrational coordinates that satisfy the variational principle. This approach produces coordinates tailored to the vibrational problem at hand, significantly increasing the accuracy and enhancing basis-set convergence of the calculated energy spectrum. The efficiency of the method is demonstrated in calculations of the 100 lowest excited vibrational states of H$_2$S, H$_2$CO, and HCN/HNC. The method effectively captures the essential vibrational behavior of molecules by enhancing the separability of the Hamiltonian and hence allows for an effective assignment of approximate quantum numbers. We demonstrate that the optimized coordinates are transferable across different levels of basis-set truncation, enabling a cost-efficient protocol for computing vibrational spectra of high-dimensional systems. Excited state ; Wave function ; Basis set ; Triatomic molecule ; Basis (linear algebra) ; Basis function ; Hydrogen atom ; Electron ; Physics ; Atom (system on chip) ; Atomic physics ; Quantum ; Quantum mechanics ; Molecule ; Mathematics ; Computer science ; Geometry Spectroscopy and Laser Applications ; Spectroscopy and Quantum Chemical Studies ; Advanced Chemical Physics Studies
Authors: Bolaji Ismail Olalere | Temiloluwa O. Scott | Joachim Osheyor Gidiagba | Akeeb Adepoju Fawole | Blessed Afeyokalo Egbokhaebho | Nwakamma Ninduwezuor -Ehiobu | Jonathan Izuchukwu Okparaeke
Source: Materials and Corrosion Engineering Management (review, 2023-09-13)
Field: Materials Science — Materials Chemistry

MAXIMIZING ALLOY PIPELINE LIFESPAN IN ENERGY INFRASTRUCTURE: A REVIEW Energy infrastructure systems’ efficient and reliable operation relies heavily on alloy pipelines’ integrity and lifespan. These pipelines serve as vital conduits for transporting various energy resources, and ensuring their longevity is crucial for maintaining sustainable and safe energy practices. This research paper presents a comprehensive review of strategies to maximize the lifespan of alloy pipelines in energy infrastructure. The paper begins with an introduction highlighting the significance of alloy pipelines in the energy sector and the importance of extending their operational lifespan. A thorough literature review explores existing research on alloy pipelines, corrosion, erosion, stress, and temperature factors that influence their degradation. The selection of appropriate materials and alloys for pipeline construction is analyzed, considering their mechanical, chemical, and corrosion-resistant properties. Corrosion is identified as a major challenge affecting the durability of alloy pipelines. Various corrosion mitigation strategies, such as protective coatings, cathodic protection, and inhibitors, are discussed in detail. The role of advanced monitoring and inspection techniques, including ultrasonic testing and predictive maintenance, in identifying potential issues and ensuring timely repairs is examined. Operational and maintenance best practices are emphasized to avoid premature pipeline failure. Case studies are presented to demonstrate successful implementations of strategies that have prolonged the lifespan of alloy pipelines in energy infrastructure projects. Additionally, the paper discusses future directions and challenges, identifying areas that require further research and development. The findings of this research highlight the importance of proper alloy selection, corrosion management, and regular maintenance in maximizing the lifespan of alloy pipelines in energy infrastructure. The proposed strategies and insights are expected to contribute to the sustainability and efficiency of the energy industry while addressing the pressing need to minimize environmental impacts and ensure a secure energy supply. Pipeline transport ; Pipeline (software) ; Risk analysis (engineering) ; Corrosion ; Integrity management ; Cathodic protection ; Forensic engineering ; Computer science ; Construction engineering ; Engineering ; Business ; Materials science ; Mechanical engineering Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Non-Destructive Testing Techniques
Authors: Samantha Durdy | Cameron J. Hargreaves | Mark Dennison | B.J. Wagg | Michael D. Moran | Jon A. Newnham | Michael W. Gaultois | Matthew J. Rosseinsky | Matthew S. Dyer
Source: ChemRxiv (preprint, 2023-05-18)
Field: Materials Science — Materials Chemistry

The Liverpool Materials Discovery Server: A suite of computational tools for the collaborative discovery of materials The discovery of new materials often requires collaboration between experimental and computational chemists. Web based platforms allow more flexibility in this collaboration by giving access to computational tools without the need for access to computational researchers. We present Liverpool Materials Discovery Server (lmds.liverpool.ac.uk), one such platform which currently hosts six state of the art computational tools in an easy to use format. We describe the development of this platform, highlighting the advantages and disadvantages the methods used. In addition, we provide source code, and setup scripts to enable other research groups to create similar platforms, to promote collaboration both within and between research groups. Suite ; Computer science ; Scripting language ; Flexibility (engineering) ; World Wide Web ; Data science ; Drug discovery ; Software engineering ; Bioinformatics ; Operating system Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Scientific Computing and Data Management
Authors: Imad‐Eddine Fahs | Majid Ghassemi | Hussein Fahs
Source: Environmental Progress & Sustainable Energy (article, 2023-09-02)
Field: Materials Science — Materials Chemistry

Distribution of <scp>SOFC</scp> thermal stress via helium gas (He) based cooling system Abstract Some electrochemical devices, such as fuel cells, transforms chemical energy to electricity. The main issue of SOFC's is the thermal stress caused by high operating temperature (700–1000°C). Thermal stress leads to crack initiation and propagation that in turn leads to gas leakage, structure instability and abrupt termination of the fuel cell (estimated in our previous work; 1.5% displacement of cathode electrode and the lifetime decreases by 40%–50%). The purpose of the current study is to show the influence of helium gas cooling system on SOFC cell performance. Using the coupled governing nonlinear differential equations, heat transfer, fluid flow, mass transfer, mass continuity, tortuosity effects and momentum. An in‐house computer code based on finite element method (FEM), computational structural mechanics, and the computational fluid dynamics (CFD) was utilized. The temperature and stress distribution are calculated using the Navier–Stokes thermo‐fluid, Darcy and energy models. The Results demonstrate that there is a high thermal stress and displacement in the absence of He gas cooling system, but in the case of He cooling system, thermal stress is much less and no displacement is noticed, which leads to an increase of the fuel cell's lifetime up to 35%–40%. Mechanics ; Heat transfer ; Helium ; Materials science ; Fluid dynamics ; Stress (linguistics) ; Thermal ; Computational fluid dynamics ; Thermodynamics ; Chemistry ; Physics Advancements in Solid Oxide Fuel Cells ; Fuel Cells and Related Materials ; Chemical Looping and Thermochemical Processes
Authors: Lina Yang | Baosheng Yang | Baowen Li
Source: arXiv (Cornell University) (preprint, 2023-06-27)
Field: Materials Science — Materials Chemistry

Enhancing interfacial thermal conductance of amorphous interface by optimized interfacial mass distribution Interfacial thermal resistance arises challenges for the thermal management as the modern semiconductors are miniatured to nanoscale. Previous studies found that graded mass distribution in interface can maximumly enhance the interfacial thermal conductance of crystalline interface, however, whether this strategy is effective for amorphous interface is less explored. In this work, graded mass distribution in the amorphous interface between crystalline Si and crystalline Ge is optimized to increase the interfacial thermal conductance by the extended atomistic Greens function method. Materials science ; Amorphous solid ; Thermal ; Work (physics) ; Conductance ; Interface (matter) ; Thermal conductivity ; Semiconductor ; Chemical physics ; Interfacial thermal resistance ; Mass distribution ; Nanoscopic scale ; Nanotechnology ; Condensed matter physics ; Thermal resistance ; Composite material ; Thermodynamics ; Crystallography ; Chemistry ; Optoelectronics ; Physics Thermal properties of materials ; Advanced Thermoelectric Materials and Devices ; Adhesion, Friction, and Surface Interactions
Authors: Shanjian Li | Guotao Cui | Panfeng Wu | Yan Feng
Source: Nature Environment and Pollution Technology (article, 2023-03-02)
Field: Materials Science — Materials Chemistry

Corrosion Behavior of Petroleum Pipeline Steel in the Sulfur Ion Enriched Solution with Quinoline Localized corrosion is a serious, hazardous destroyer of steel petroleum pipelines meant for long-time use. However, previous studies on localized corrosion primarily focused on local corrosion morphology and corrosion rate of bulk metals because detecting the corrosion state of occlusive metals is difficult. Herein, we employ a simulating occluded battery unit to disclose the local corrosion behavior of the steel petroleum pipeline (N80 steel) in an occlusive S2–-enriched solution. After simulating localized corrosion in the S2–- containing corrosion solution using the occluded battery unit, the occlusive solution was acidified and the migration amount of S2– to the occluded area increased. Despite the increase of S2– concentration, the addition of quinoline corrosion inhibitor (0.8 wt%) still effectively impedes the corrosion of the occluded metal. Moderately raising the environmental temperature can stimulate the activity of the inhibitor and promote the inhibition effect. The quinoline corrosion inhibitor displays the maximum inhibition rate at an elevated temperature of 50°C. Meanwhile, a maximum over the temperature of 60°C-70°C will likely accelerate the failure of the inhibitor. Corrosion ; Corrosion inhibitor ; Quinoline ; Metallurgy ; Materials science ; Metal ; Petroleum ; Electrochemistry ; Pipeline transport ; Chemistry ; Environmental science ; Environmental engineering ; Organic chemistry ; Electrode Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Concrete Corrosion and Durability
Authors: Denis G. Artiukhin | Ian H. Godtliebsen | Gunnar Alexander Schmitz | Ove Christiansen
Source: arXiv (Cornell University) (preprint, 2023-03-27)
Field: Materials Science — Materials Chemistry

Gaussian Process Regression Adaptive Density-Guided Approach: Towards Calculations of Potential Energy Surfaces for Larger Molecules We present a new program implementation of the gaussian process regression adaptive density-guided approach [J. Chem. Phys. 153 (2020) 064105] in the MidasCpp program. A number of technical and methodological improvements made allowed us to extend this approach towards calculations of larger molecular systems than those accessible previously and maintain the very high accuracy of constructed potential energy surfaces. We demonstrate the performance of this method on a test set of molecules of growing size and show that up to 80 % of single point calculations could be avoided introducing a root mean square deviation in fundamental excitations of about 3 cm$^{-1}$. A much higher accuracy with errors below 1 cm$^{-1}$ could be achieved with tighter convergence thresholds still reducing the number of single point computations by up to 68 %. We further support our findings with a detailed analysis of wall times measured while employing different electronic structure methods. Our results demonstrate that GPR-ADGA is an effective tool, which could be applied for cost-efficient calculations of potential energy surfaces suitable for highly-accurate vibrational spectra simulations. Kriging ; Convergence (economics) ; Gaussian process ; Gaussian ; Energy (signal processing) ; Process (computing) ; Set (abstract data type) ; Computer science ; Statistical physics ; Point (geometry) ; Regression ; Computation ; Algorithm ; Mathematical optimization ; Mathematics ; Physics ; Statistics ; Quantum mechanics ; Machine learning Machine Learning in Materials Science ; Spectroscopy Techniques in Biomedical and Chemical Research ; Metabolomics and Mass Spectrometry Studies
Authors: Shucayat Aman Zeynalov | F. Kerimov | S. I. Safarova | Babakishi Garaja Garajaev | G. S. Jafarova
Source: Scientific Herald of Uzhhorod University Series Physics (article, 2023-11-23)
Field: Materials Science — Polymers and Plastics

Effect of phenol-formaldehyde resin on mechanical durability and structure of low-density polyethylene Relevance. The development of technology for producing new polymer modifications with specific properties, which remain stable even when exposed to external factors, is a key area of focus for researchers in the field of high-molecular compounds. Purpose. The purpose of this study was to create new composite materials based on low-density polyethylene. Methodology. The extrusion blowing method on an industrial URP 1500 unit was used for processing low-density polyethylene (LDPE) and its modified films. Electron microscopic images of the surface were captured using a S-570 scanning microscope (Japan) at X1000 magnifications. Results. The composition and quantity of a low-molecular organic additive that alters the electrical characteristics of low-density polyethylene grade 10803-020 was ascertained. The modified low-density polyethylene is noteworthy for its minimal usage of additives and their compatibility with technology. Based on experimental data, it was found that the inclusion of 0.05 wt% phenol-formaldehyde resin in low-density polyethylene increases its mechanical strength to the highest level when compared to both the unaltered low-density polyethylene and low-density polyethylene with other additives. Furthermore, the study found that the addition of phenol-formaldehyde resin in small proportions (0.05 wt%) substantially enhances mechanical strength at varying temperatures. Conclusions. The electrophysical characteristics of low-density polyethylene and its modified versions were comprehensively investigated. The adequately altered low-density polyethylene exhibits considerably improved mechanical durability. It was indicated that the additives used, at optimal levels, influence the physical framework of low-density polyethylene, highlighting their technological compatibility differences Low-density polyethylene ; Polyethylene ; Materials science ; Composite material ; Formaldehyde ; Polymer ; Phenol ; Phenol formaldehyde resin ; Extrusion ; Chemistry ; Organic chemistry Natural Fiber Reinforced Composites ; Material Properties and Applications ; Polymer Nanocomposites and Properties
Authors: Max Kerr Winter | Ilian Pihlajamaa | Vincent E. Debets | Liesbeth M. C. Janssen
Source: arXiv (Cornell University) (preprint, 2023-02-27)
Field: Materials Science — Materials Chemistry

A deep learning approach to the measurement of long-lived memory kernels from Generalised Langevin Dynamics Memory effects are ubiquitous in a wide variety of complex physical phenomena, ranging from glassy dynamics and metamaterials to climate models. The Generalised Langevin Equation (GLE) provides a rigorous way to describe memory effects via the so-called memory kernel in an integro-differential equation. However, the memory kernel is often unknown, and accurately predicting or measuring it via e.g. a numerical inverse Laplace transform remains a herculean task. Here we describe a novel method using deep neural networks (DNNs) to measure memory kernels from dynamical data. As proof-of-principle, we focus on the notoriously long-lived memory effects of glassy systems, which have proved a major challenge to existing methods. Specifically, we learn a training set generated with the Mode-Coupling Theory (MCT) of hard spheres. Our DNNs are remarkably robust against noise, in contrast to conventional techniques which require ensemble averaging over many independent trajectories. Finally, we demonstrate that a network trained on data generated from analytic theory (hard-sphere MCT) generalises well to data from simulations of a different system (Brownian Weeks-Chandler-Andersen particles). We provide a general pipeline, KernelLearner, for training networks to extract memory kernels from any non-Markovian system described by a GLE. The success of our DNN method applied to glassy systems suggests deep learning can play an important role in the study of dynamical systems that exhibit memory effects. Computer science ; Statistical physics ; Artificial intelligence ; Dynamical systems theory ; Laplace transform ; Deep learning ; Kernel (algebra) ; Algorithm ; Theoretical computer science ; Physics ; Mathematics ; Mathematical analysis Material Dynamics and Properties ; Plant Water Relations and Carbon Dynamics ; Thermoregulation and physiological responses
Authors: Danilo Di Genova | Dmitry Bondar | Alessio Zandonà | Pedro Valdivia | Raschid Al-Mukadam | Hongzhan Fei | Anthony C. Withers | Tiziana Boffa Ballaran | Alexander Kurnosov | Catherine McCammon | Joachim Deubener | Tomoo Katsura
Source:  (preprint, 2023-03-24)
Field: Materials Science — Ceramics and Composites

Viscosity of anhydrous and hydrous peridotite melts The melt viscosity (η) of anhydrous and hydrous peridotite was investigated using a multipronged approach combining micropenetration viscometry, conventional DSC, flash DSC and Brillouin spectroscopy. Raman spectroscopy measurements were used to verify the absence of crystallization and/or degassing during high-temperature measurements of these extremely reactive glasses and melts, ensuring that the data corresponded to the crystal-free melt viscosity. Based on the experimental data, an accurate description of the viscosity of peridotite melts over thirteen orders of magnitude (from Tg to η ≈ 10−1 Pa s) is provided in a broad range of compositions and oxidation states. Since empirical models predict viscosities that can significantly deviate from measured data to varying degrees, a new model was developed for the temperature- and H2O-dependent viscosity of peridotite melts (up to 12 mol% H2O content). Peridotite ; Anhydrous ; Viscometer ; Viscosity ; Raman spectroscopy ; Crystallization ; Mineralogy ; Atmospheric temperature range ; Analytical Chemistry (journal) ; Thermodynamics ; Materials science ; Chemistry ; Geology ; Organic chemistry ; Mantle (geology) ; Geochemistry ; Composite material Glass properties and applications ; Mineralogy and Gemology Studies ; Material Dynamics and Properties