jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jingmiao Ma | Seung-Soo Baek
Source: Journal of Nanomaterials (article, 2022-01-01)
Field: Materials Science — Biomaterials

[Retracted] Electrospinning of Nanofiber‐Based Materials and Application of the Technology to Lower Extremity Joint Exercise Rehabilitation This study mainly explores the electrospinning of nanofiber‐based materials and the application of the technology to lower extremity joint exercise rehabilitation. In response to people’s concerns, this study mainly discusses electrospinning technology from the aspects of the safety of nanomaterials prepared by electrospinning technology and the application of nanomaterials prepared by electrospinning technology in lower limb joints. In the safety study of nanomaterials, six groups of experiments were set up to measure the joints of nanomaterials prepared by electrospinning technology under pressures of 500 N, 510 N, 520 N, 530 N, 540 N, and 550 N. For compression resistance, when the pressure is 540 N, the compressive performance of the nanomaterial is preferably 96%. In terms of the application of nanomaterials, 100 patients with lower extremity sprains in the Affiliated Hospital of Sun Yat‐sen University were divided into 5 groups and then divided into 6 groups. Patient recovery rate when the device is applied to the patient’s lower extremity joint. Patients had the best recovery rate of 92% when the immobilization device was used for 6 days. The use of arthrodesis did not affect the patient’s other factors. The experimental results show that when the pressure is 540 N and the fixation device is used for 6 days, the nanofiber material prepared by electrospinning technology has the best rehabilitation effect on lower limb joint movement. Electrospinning ; Nanomaterials ; Materials science ; Nanofiber ; Composite material ; Polymer ; Nanotechnology Electrospun Nanofibers in Biomedical Applications ; Stroke Rehabilitation and Recovery ; Muscle activation and electromyography studies
Authors: B Harinesh | Rathin Sajit | M.P. Jenarthanan | M Ramachandran | Chinnasami Sivaji
Source:  (article, 2022-01-31)
Field: Materials Science — Polymers and Plastics

Mechanical, Thermal and Morphological Characterisation of Polybutylene based Composites The active substance of Catalyst TiCl4 and support The microcrystalline is MgCl2. Has been Polybutylene composites, Mechanical properties, Thermal properties, Nano composites, Biodegradability, Morphology, these catalysts contain organic compounds belonging to the class of special modifiers, esters or ethers. Pre-catalysts organoaluminum alloys and other types of organic or organometallic Are activated by a combination of converters. Two of the most important technologies of catalysts support the advantages High productivity and high content of crystal isotope polymer are manufactured under stable polymerization conditions at 70-80 C This product is designed to combine your rainwater tank with washing machine and household appliances Toilet bowl. The polypropylene pipe should be physically protected from direct sunlight to avoid long-term UV decay. Bb pipe lightweight, It has the advantages of being flexible and easy to install. Polybutene is 1-butane, 2-butane and An organic made from is protein compound Is polymer. It is similar to polyispropylene (PIB), It is made from pure is protein produced on the C4 premises of a large refinery. Materials science ; Polypropylene ; Butane ; Catalysis ; Microcrystalline ; Composite material ; Polymer ; Biodegradation ; Chemical engineering ; Organic chemistry ; Chemistry Natural Fiber Reinforced Composites ; Additive Manufacturing and 3D Printing Technologies ; Polymer Nanocomposites and Properties
Authors: F Kassir | M-A Azoury | P Damacet | al et
Source: Portugaliae electrochimica acta (article, 2022-11-07)
Field: Chemistry — Analytical Chemistry

Characterization and Performance of TiO2 Nanoparticles Prepared by Microwave in Different Mixtures of Water and Ethylene Glycol for the Food Dye E131 VF Degradation In this research, TiO2 NP were prepared by MW-R and conventional SG methods, using TTIP as Ti precursor, in the presence of different mixtures of distilled H2O and ETG (0 < H2O/ETG < 100%), as a solvent. The prepared samples were characterized by XRD, Raman, FTIR, EDX/ SEM, N2 physisorption, DLS and UV/visible DRS techniques. XRD and Raman analyses showed that Ant phase dominated, with traces of Rt or Brk phases, in some samples. According to K-M curves, TiO2 calculated EG decreased with an increase in Rt phase percentage. PC performance of the prepared samples was tested on E131 VF. Kinetic evaluations showed that Rt percentage and surface area had a significant role in TiO2 NP PC performance. E131 VF degradation high RC were obtained in an AU by 0% ETG SG (0.130 (AU)) and 0% ETG MW-R (0.113 (AU)), due to the high surface area and Rt absence. The samples (x% ETG) synthesized by the MW-R method showed low pore volume and PC performance that might have been be due to a blockage of the pores and screening effect of some combustion products or residual ETG, which carried UV irradiation to the catalyst surface. Ethylene glycol ; Degradation (telecommunications) ; Characterization (materials science) ; Microwave ; Materials science ; Nanoparticle ; Chemical engineering ; Ethylene ; Chemistry ; Nanotechnology ; Organic chemistry ; Catalysis ; Computer science ; Telecommunications Dye analysis and toxicity ; Water Quality Monitoring and Analysis
Authors: K Devadasa | Laxminarayana N.H
Source: ShodhKosh Journal of Visual and Performing Arts (article, 2022-12-31)
Field: Chemistry — Organic Chemistry

GREEN CATALYSIS: INNOVATIONS AND APPLICATIONS IN SUSTAINABLE CHEMISTRY Green catalysis represents a transformative approach to chemical processes, emphasizing sustainability, efficiency, and environmental responsibility. This paper explores the innovations and applications of green catalysis in the context of sustainable chemistry, highlighting its potential to minimize waste, reduce energy consumption, and eliminate the use of hazardous substances. Traditional catalysis often involves toxic or rare metals, posing significant environmental and economic challenges. Green catalysis, however, focuses on utilizing eco-friendly materials, such as biocatalysts, organocatalysts, and earth-abundant metals, to drive reactions that align with the principles of green chemistry. The paper reviews recent advancements in catalytic systems, including heterogeneous and homogeneous catalysts, and their applications in key sectors such as pharmaceuticals, energy, and materials science. It also examines the role of green catalysis in renewable energy production, particularly in biomass conversion and the development of sustainable fuel cells. Innovations like photocatalysis and electrocatalysis are also explored for their potential in harnessing solar and electrical energy in chemical transformations. Furthermore, the paper addresses the economic and regulatory factors influencing the adoption of green catalysis in industrial processes. By focusing on sustainable approaches, green catalysis not only contributes to reducing the chemical industry's environmental footprint but also opens new avenues for the development of cleaner, safer, and more efficient chemical processes. This research underscores the critical role of green catalysis in advancing global sustainability goals and highlights future directions for innovation in this rapidly evolving field. Green chemistry ; Catalysis ; Chemistry ; Nanotechnology ; Biochemical engineering ; Engineering ; Materials science ; Organic chemistry ; Reaction mechanism Nanomaterials for catalytic reactions ; Chemical Synthesis and Reactions ; Catalysis for Biomass Conversion
Authors: Yuan Liu | Shizhong Wei
Source: Journal of Mechanical Engineering (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Review on Data-driven Method for Property Prediction of Iron and Steel Wear-resistant Materials 摘要： 数据驱动方法利用机器学习算法挖掘数据中隐藏的规则,是一种符合"第四范式"的研究方法。该研究方法的开展基于大量材料基础数据。通过对比国内外材料基础数据平台,分析利用现有数据平台已开展的研究,指出钢铁耐磨材料基础数据存在数据匮乏和缺乏统一采集标准两个问题。针对此,介绍符合材料基因组计划的数据采集标准,并给出钢铁耐磨材料专用数据平台的框架以及数据来源。分析钢铁耐磨材料性能的影响因素,讨论各种特征选择技术的特点。回顾在材料科学研究中成功应用的几种机器学习算法,分析每种算法的应用场景,讨论它们的优缺点,并对算法性能进行了比较。最后总结一些建议为特征提取和机器学习算法选择提供指导,并指出数据驱动方法在性能预测、发现新材料和自动化自主试验等方面具有良好的应用前景。 Property (philosophy) ; Metallurgy ; Materials science ; Computer science ; Forensic engineering ; Engineering ; Philosophy Metal Alloys Wear and Properties
Authors: Daniel Riba-López | Rosa Letizia Zaffino | Daniel Herrera | Roc Matheu | Francesco Silvestri | Jesse Ferreira da Silva | E. Carolina Sañudo | Marta Mas‐Torrent | Esther Barrena | Raphael Pfattner | Eliseo Ruíz | Arántzazu González‐Campo | Núria Aliaga‐Alcalde
Source: iScience (article, 2022-12-01)
Field: Chemistry — Organic Chemistry

Dielectric behavior of curcuminoid polymorphs on different substrates by direct soft vacuum deposition Our work examines the structural-electronic correlation of a new curcuminoid, AlkCCMoid, as a dielectric material on different substrates. For this purpose, we show a homemade sublimation method that allows the direct deposition of molecules on any type of matrix. The electronic properties of AlkCCMoid have been evaluated by measurements on single crystals, microcrystalline powder, and sublimated samples, respectively. GIWAXS studies on surfaces and XRD studies on powder have revealed the existence of polymorphs and the effect that substrates have on curcuminoid organization. We describe the dielectric nature of our system and identify how different polymorphs can affect electronic parameters such as permittivity, all corroborated by DFT calculations. Curcuminoid ; Dielectric ; Microcrystalline ; Materials science ; Sublimation (psychology) ; Crystallography ; Nanotechnology ; Chemistry ; Optoelectronics Polydiacetylene-based materials and applications ; Corrosion Behavior and Inhibition ; Carbon Nanotubes in Composites
Authors: Scott Habershon
Source: Journal of Chemical Theory and Computation (article, 2022-03-16)
Field: Materials Science — Materials Chemistry

Program Synthesis of Sparse Algorithms for Wave Function and Energy Prediction in Grid-Based Quantum Simulations We have recently shown how program synthesis (PS), or the concept of "self-writing code", can generate novel algorithms that solve the vibrational Schrödinger equation, providing approximations to the allowed wave functions for bound, one-dimensional (1-D) potential energy surfaces (PESs). The resulting algorithms use a grid-based representation of the underlying wave function ψ(<i>x</i>) and PES <i>V</i>(<i>x</i>), providing codes which represent approximations to standard discrete variable representation (DVR) methods. In this Article, we show how this inductive PS strategy can be improved and modified to enable prediction of both vibrational wave functions <i>and</i> energy eigenvalues of representative model PESs (both 1-D and multidimensional). We show that PS can generate algorithms that offer some improvements in energy eigenvalue accuracy over standard DVR schemes; however, we also demonstrate that PS can identify accurate numerical methods that exhibit desirable computational features, such as employing very sparse (tridiagonal) matrices. The resulting PS-generated algorithms are initially developed and tested for 1-D vibrational eigenproblems, before solution of multidimensional problems is demonstrated; we find that our new PS-generated algorithms can reduce calculation times for grid-based eigenvector computation by an order of magnitude or more. More generally, with further development and optimization, we anticipate that PS-generated algorithms based on effective Hamiltonian approximations, such as those proposed here, could be useful in direct simulations of quantum dynamics via wave function propagation and evaluation of molecular electronic structure. Algorithm ; Eigenvalues and eigenvectors ; Hamiltonian (control theory) ; Computer science ; Wave function ; Tridiagonal matrix ; Grid ; Representation (politics) ; Function (biology) ; Mathematical optimization ; Mathematics ; Quantum mechanics ; Physics Machine Learning in Materials Science ; Quantum Computing Algorithms and Architecture ; Advanced Chemical Physics Studies
Authors: Khalida Abbas Omran
Source: Journal of Environmental and Public Health (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

[Retracted] The Construct and Interpretation of Chelated Coordination Polymers and Their Use in Nanomaterials Research Presently, an important step from basic research to practical applications is synthesizing nanostructured materials. Metal-organic structures, as well as coordination polymers, are a diverse group of materials with a wide range of potential and properties applications. It has been difficult to get these materials into commercial use because of many drawbacks. Polymers containing chelated units are described and assessed for their advancements and problems in preparation, properties, and structure. Here, a proposed approach based on designing coordination polymeric materials with chelated units using the metal-ligand approach (CPM-CU-MA) has been introduced for a columnar-layered plan, supramolecular components, and building levels. Nanocomposite materials can be formed through the thermal transformation of coordination polymers based on donor atoms. The polymeric metal chelates (PMCs) are categorized according to luminescent coordination polymer (LCoP) development. It is classified as macrocyclic intracomplex, polynuclear, and molecular according to its macrostructure. Supramolecular networks (SMNs) can be transformed into a coordination polymer by introducing cyclo-dehydrogenation of natural building blocks on a surface. The structure-property connections of LCPs can influence a framework of liquid crystal display (LCP) that has been given based on LC phase modulators with a large modulation depth and has useful applications in LC lens. In the spatial organization of PMCs, the main focus is on the commonalities and contrasts between higher- and lower-molecular-weight chelates based on molecularly imprinted sensors (MISs) and nanomaterial sensors for a wide range of uses. New functional nanoparticles based on the molecular components have exciting potential, as demonstrated by these findings based on parameters risk factors for human health, hazards reduction in the environment, lack of cost-effectiveness, environmental sustainability, and bioavailability of polymers with an overall performance of 95.3%. Supramolecular chemistry ; Nanomaterials ; Materials science ; Polymer ; Nanotechnology ; Ligand (biochemistry) ; Chelation ; Molecularly imprinted polymer ; Nanocomposite ; Coordination polymer ; Combinatorial chemistry ; Molecule ; Chemistry ; Organic chemistry ; Selectivity ; Composite material Lanthanide and Transition Metal Complexes ; Metal-Organic Frameworks: Synthesis and Applications ; Luminescence and Fluorescent Materials
Authors: Charlie Maier | Nicholas E. Jackson
Source: ChemRxiv (preprint, 2022-05-30)
Field: Materials Science — Materials Chemistry

Bypassing Backmapping: Coarse-Grained Electronic Property Distributions Using Heteroscedastic Gaussian Processes We employ deep kernel learning electronic coarse-graining (DKL-ECG) with approximate Gaussian Processes as a flexible and scalable framework for learning heteroscedastic electronic property distributions as a smooth function of coarse-grained (CG) configuration. The appropriateness of the Gaussian prior on the predictive CG property distributions is justified as a function of CG model resolution by examining the statistics of the target distributions. The certainties of the predictive CG distributions are shown to be limited by CG model resolution, with DKL-ECG predictive noise converging to the intrinsic physical noise induced by the CG mapping operator for multiple chemistries. Further analysis of the resolution dependence of the learned CG property distributions allows for the identification of CG mapping operators that capture CG degrees of freedom with strong electron-phonon coupling. We further demonstrate the ability to construct the exact quantum chemical valence electronic density of states (EDOS), including behavior in the tails of the EDOS, from an entirely CG model by combining iterative boltzmann inversion and DKL-ECG. DKL-ECG provides a means of learning CG distributions of all-atom properties that are traditionally ``lost" in CG model development, introducing a robust methodological alternative to backmapping algorithms commonly employed to recover all-atom property distributions from CG simulations. Gaussian ; Statistical physics ; Computer science ; Gaussian process ; Granularity ; Algorithm ; Artificial intelligence ; Physics ; Quantum mechanics Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Electron and X-Ray Spectroscopy Techniques
Authors: Abdolreza Karbul | Mohammad Kazem Mohammadi | Reza Jalilzadeh Yengejeh | Forouzan Farrokhian
Source: Journal of Advances in Environmental Health Research (article, 2022-04-01)
Field: Chemistry — Organic Chemistry

Nanocomposite Fe-Co-V/Zeolite: Highly Efficient Composite for Removal of Methyl Orange Dye Background: In recent years, the dye industry has rapidly been developed. Dyes are one in all the foremost dangerous groups of chemical compounds found in industrial effluents, which are of considerable importance for reasons like reduced light permeability and therefore the subsequent disruption of the method of photosynthesis in water sources. This study was performed to remove dye using Fe-Co-V /Zeolite from a synthetic wastewater. Methods: After chemical synthesis of the nanocomposite, its structure was studied by spectroscopic techniques. The experiments were performed under different pH values (3-11), contact times (5-50 min), absorbent dose (0.5-0.6g), stirring speed (240-60 rpm), and different concentrations. Results: The results showed that the optimal and final conditions affecting the removal of methyl orange dye in the most suitable conditions for 200 mL of the solution with a concentration of 20 mg/L at pH equal to 3, contact time 20 min, adsorbent dose 0.2 g, jar speed 180 rpm and temperature 25°C, which finally with the application of the optimal data, at a concentration of 2.5 mg/L, the best efficiency was obtained. The examination of isotherm diagrams and isotherm coefficients showed that the adsorption process follows the Freundlich equation. Conclusion: According to the obtained results and physical and chemical properties of the synthesized nanocomposite, it can be used to remove pollutants from the environment such as wastewater and air. Freundlich equation ; Nanocomposite ; Adsorption ; Methyl orange ; Effluent ; Zeolite ; Wastewater ; Materials science ; Composite number ; Chemical engineering ; Nuclear chemistry ; Orange (colour) ; Pollutant ; Chemistry ; Waste management ; Composite material ; Photocatalysis ; Organic chemistry ; Catalysis Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal
Authors: Haider Shanshool Mohammed | Nuha Hussain Al-Saadawy
Source: Indonesian Journal of Chemistry (article, 2022-12-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Synthesis, Characterization, and Theoretical Study of Novel Charge-Transfer Complexes Derived from 3,4-Selenadiazobenzophenone In the current study, a direct method was used to synthesize a new series of charge-transfer complex compounds. Reaction of different quinones with 3,4-selenadiazo benzophenone in a 1:1 mole ratio by acetonitrile gave a unique charge-transfer complex compound in a good yield. All compounds were characterized by UV-Vis, FTIR, 1H-NMR, and 13C-NMR. The analysis findings agreed with the produced compound’s proposed chemical structures. The molecular structure of the produced charge-transfer complex compounds has been investigated using density functional theory. The basis set of 3–21G geometrical designs throughout the geometry optimization, HOMO surfaces, LUMO surfaces, and energy gap has been created. The acceptor and donor have also been studied by comparing the HOMO energies of the charge-transfer complexes. The lower case, electron affinity, ionization potential, electronegativity, and electrophilicity where the total energies of donor-acceptor system and geometric structures demonstrate this structure’s stability. Additionally, the donor-acceptor system has higher reactivity than other systems and larger average polarizability when compared to the donor and acceptor. The findings of this study enable us to choose the kind of bridge that will interact with the donor and acceptor to determine the physical characteristics of the donor-bridge-acceptor. Chemistry ; Electronegativity ; Acceptor ; HOMO/LUMO ; Density functional theory ; Electrophile ; Computational chemistry ; Polarizability ; Charge (physics) ; Ionization energy ; Acetonitrile ; Reactivity (psychology) ; Benzophenone ; Physical chemistry ; Photochemistry ; Molecule ; Ionization ; Organic chemistry ; Catalysis Nonlinear Optical Materials Research ; Photochemistry and Electron Transfer Studies ; Free Radicals and Antioxidants
Authors: Daniel Gaissmaier | Matthias van den Borg | Donato Fantauzzi | Timo Jacob
Source: ChemRxiv (preprint, 2022-07-04)
Field: Materials Science — Materials Chemistry

KVIK Optimiser - An Enhanced ReaxFF Force Field Training Approach In this work, we demonstrate the superior exploration capabilities of the population-based methods over the sequential one-parameter parabolic interpolation (SOPPI) approach to optimise ReaxFF force field parameters. Evolutionary algorithms (EAs) are heuristic-based approaches using a population of concurrent models in the search space to evolve towards the global best through stochastic operations. The parallelisation of EAs scales almost linearly, and no differentiable objective function is required. These methods were tested for their search performance and convergence behaviour on different multi-dimensional, multimodal benchmark functions. The developed KVIK (Icelandic for: dynamic, in motion) optimisation framework features an extended training 1routine designed to parameterise solid-state systems efficiently. The optimisation routine was applied to train a reactive force field potential for metallic lithium and sodium and their interaction parameters. The KVIK-optimised ReaxFF potential function parameter set reproduces relative energy results from the density functional theory (DFT) reference data set within the standard deviation range established using the error estimation routine provided by the BEEF-vdW density functional. Finally, thermodynamically and kinetically driven surface growth phenomena on metallic Li- and Na-electrodes were investigated using coupled ReaxFF/Monte Carlo (MC) approaches. ReaxFF ; Force field (fiction) ; Density functional theory ; Computer science ; Population ; Simulated annealing ; Mathematical optimization ; Benchmark (surveying) ; Statistical physics ; Algorithm ; Mathematics ; Molecular dynamics ; Physics ; Computational chemistry ; Artificial intelligence ; Chemistry Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Electrocatalysts for Energy Conversion