jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jamaan E. Alassafi | Yas Al‐Hadeethi | M.S. Aïda | Iman S. Roqan | Samar Al-Shehri | Mohammad Omaish Ansari | Samer Alamodi | Mingguang Chen
Source: Scientific Reports (article, 2024-11-26)
Field: Materials Science — Materials Chemistry

Uniform blue emitting carbon nanodots synthesized from fig fruit using reverse diffusion purification In this investigation, blue-emitting carbon nanodots (B.CNDs) with exceptional color purity were successfully synthesized from fresh fig fruit using a one-step pyrolysis method. These B.CNDs are small and spherical (3.7 nm) with an amorphous carbon core encapsulated inside a passivated layer primarily composed of oxygen-related functional groups. They demonstrated an emission property that is independent of excitation, showing the highest emission intensity in the deep blue region at 450 nm with a narrow full-width at half maximum (FWHM) at 44 nm and a quantum yield of 15.5%. This exceptional value of FWHM is attributed to the remarkable uniformity in both morphological and chemical composition that was achieved through the utilization of the reverse diffusion technique combined with the dialysis method for purification and separation of B.CNDs. This work not only contributes to the expanding field of carbon nanomaterials but also introduces a novel and sustainable approach to fabricate CDs with unparalleled color purity and optical performance. Nanodot ; Diffusion ; Carbon fibers ; Chemical engineering ; Chemistry ; Materials science ; Nanotechnology ; Composite material ; Physics Carbon and Quantum Dots Applications ; Quantum Dots Synthesis And Properties ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Jinbao Shao | Yuexiao Lv | Zhenhua Xue | Yanfei Pan | Jinwei Liu | Mayin Dai | Fengqi Qiu
Source: Coatings (article, 2024-04-08)
Field: Chemistry — Spectroscopy

Preparation and Acoustic Performance of Porous Aerogel Composites of Graphene Oxide and Cellulose In this study, sound insulation materials with a high sound absorption coefficient were prepared. In this paper, using cellulose (CEL) and graphene oxide (GO) as the main raw materials and epichlorohydrin as the cross-linker, the CEL-GO composite aerogels were prepared via lyophilisation. The structure, molecular bonding, and acoustic absorption mechanisms of the composite aerogel were characterised and analysed using SEM, FTIR, XRD, BET, and Raman. In addition, corresponding molecular structure models were constructed. The acoustic attenuation of the CEL-GO composite aerogel was measured using a standing wave tube acoustic attenuation tester. The results show that the chemical bond between the GO and CEL composite is established, and the addition of graphene makes the pores of the composite more advanced, which is more favorable for sound absorption, and the acoustic absorption coefficient can reach up to 0.87. Aerogel ; Graphene ; Composite material ; Materials science ; Cellulose ; Porosity ; Oxide ; Chemical engineering ; Nanotechnology Aerogels and thermal insulation ; Advanced Cellulose Research Studies ; Advanced Sensor and Energy Harvesting Materials
Authors: Quang Truong Pham | Gia Long Ngo | Chi Thành Nguyên | Isabelle Ledoux‐Rak | Ngoc Diep Lai
Source: Photonics (article, 2024-07-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Unraveling the Dominant Size Effect in Polydisperse Solutions and Maximal Electric Field Enhancement of Gold Nanoparticles In this study, we systematically investigate theoretically and experimentally the plasmonic effect and roles of big and small gold nanoparticles (Au NPs) within a mixed solution. The polydisperse solution was initially prepared by mixing small (10, 30 nm) Au NPs with larger ones (50, 80 nm), followed by measuring the extinction using ultraviolet–visible (UV-vis) spectroscopy. The experimental results clearly showed that the extinction of the mixed solution is predominantly influenced by the presence of the larger NPs, even though their quantity is small. Subsequently, we conducted simulations to explore the plasmonic properties of Au NPs of different sizes as well as their mixings and to validate the experimental results. To explain the deviation of the extinction spectra between experimental observations and simulations, we elaborated a simulation model involving the mixture of spherical Au NPs with ellipsoidal NPs, thus showing agreement between the simulation and the experiment. By performing simulations of plasmonic near-field of NPs, our investigation revealed that the maximal electric field intensity does not occur precisely at the plasmonic resonant wavelength but rather at a nearby redder wavelength. The optimal size of the Au NP dispersed in water for achieving the highest field enhancement was found to be 60 nm, with an excitation wavelength of 553.7 nm. These interesting findings not only enrich our understanding of plasmonic NPs’ optical behavior but also guide researchers for potential applications in various domains. Electric field ; Materials science ; Nanoparticle ; Colloidal gold ; Nanotechnology ; Condensed matter physics ; Physics ; Quantum mechanics Gold and Silver Nanoparticles Synthesis and Applications ; Electrohydrodynamics and Fluid Dynamics ; Nanomaterials and Printing Technologies
Authors: Santiago Rigamonti | Maria Troppenz | Martin Kubáň | Axel Hübner | Claudia Draxl
Source: npj Computational Materials (article, 2024-08-30)
Field: Materials Science — Materials Chemistry

CELL: a Python package for cluster expansion with a focus on complex alloys Abstract We present the Python package , which provides a modular approach to the cluster expansion (CE) method. can treat a wide variety of substitutional systems, including one-, two-, and three-dimensional alloys, in a general multi-component and multi-sublattice framework. It is capable of dealing with complex materials comprising several atoms in their parent lattice . uses state-of-the-art techniques for the construction of training data sets, model selection, and finite-temperature simulations. The user interface consists of well-documented Python classes and modules ( http://sol.physik.hu-berlin.de/cell/ ). also provides visualization utilities and can be interfaced with virtually any ab initio package, total-energy codes based on interatomic potentials, and more. The usage and capabilities of are illustrated by a number of examples, comprising a Cu-Pt surface alloy with oxygen adsorption, featuring two coupled binary sublattices, and the thermodynamic analysis of its order-disorder transition; the demixing transition and lattice-constant bowing of the Si-Ge alloy; and an iterative CE approach for a complex clathrate compound with a parent lattice consisting of 54 atoms. Python (programming language) ; Computer science ; Programming language Machine Learning in Materials Science ; nanoparticles nucleation surface interactions ; Intermetallics and Advanced Alloy Properties
Authors: Saranyadevi Subburaj | Manikandan Paramasivam | Methaq Hadi Lafta | Lekshmi Gangadhar
Source: Environmental sciences (review, 2024-04-18)
Field: Chemistry — Analytical Chemistry

A Review on Elimination of Colour and Dye Products from Industrial Effluent Every industry now takes clean technology very seriously. Particularly in textile dying facilities, a lot of water, energy, dyeing colours, and chemicals are used. Significant issues with air and water pollution may result from this. The wastewater is quite colourful and smells poisonous. It also has high chemical oxygen demand (COD) and biochemical oxygen demand (BOD) levels. Reactive dyes found in wastewater include orange OGR, red DB-8, black DN, and turquoise DG. It has been demonstrated that the type of dye, the dosage of coagulant, and the pH of the sample all affect how effectively dye is removed. Also, the effectiveness of COD and colour elimination in single-stage and multi-stage ozonation-biological process methods were studied. The functional groups of azo dye are changed by ozonation to produce more readily removable biodegradable byproducts. Ozonation changes the functional groups in azo dye, resulting in more biologically degradable byproducts that are simply eliminated through biological treatment. Activated sludge treatment as well as the coagulation-flocculation technique with 80% waste water removal efficiency. Sequencing batch reactor is a fill-and- draw activated sludge-based system for wastewater treatment and has been proposed as an alternative technique for treating industrial effluents. We briefed a promising novel technology for textile effluent de-colorisation in this chapter. Effluent ; Industrial effluent ; Pulp and paper industry ; Environmental science ; Business ; Waste management ; Process engineering ; Engineering ; Environmental engineering Dye analysis and toxicity ; Water Quality Monitoring and Analysis ; Adsorption and biosorption for pollutant removal
Authors: Hexin Wang | Julien Guénolé | Sandra Korte‐Kerzel | Talal Al‐Samman | Zhuocheng Xie
Source: Computational Materials Science (article, 2024-04-16)
Field: Materials Science — Biomaterials

Defects in magnesium and its alloys by atomistic simulation: Assessment of semi-empirical potentials Dislocation and grain boundary properties of Mg and its alloys were assessed by atomistic simulations using various semi-empirical potentials. The results were compared with available experimental data and first-principles calculations. It was observed that embedded-atom method (EAM) potentials notably deviated from experimental observations in dislocation properties, especially for pyramidal dislocations. For the coincident site lattice (CSL) Σ7 grain boundary, the choice of interatomic potential significantly influences the minimum energy structures, namely, the T-type structure is stable when using modified embedded-atom method (MEAM) potentials, whereas the A-type structure demonstrates stability when EAM potentials are applied. Furthermore, a strong correlation between the per-site segregation energies of alloying elements and the excess free volumes at grain boundaries was identified across all tested potentials. The outcomes of this work pave the way for potential selection in future large-scale modeling of small-scale plasticity in Mg and its alloys. Interatomic potential ; Grain boundary ; Embedded atom model ; Materials science ; Molecular dynamics ; Dislocation ; Atom (system on chip) ; Atomic units ; Lattice (music) ; Work (physics) ; Condensed matter physics ; Thermodynamics ; Metallurgy ; Chemistry ; Computational chemistry ; Physics ; Microstructure Magnesium Alloys: Properties and Applications ; Microstructure and mechanical properties ; Aluminum Alloys Composites Properties
Authors: Daniel González‐Mancebo | Ana Isabel Becerro | Carlos Caro | Elisabet Gómez-González | Maria Luisa García‐Martín | Manuel Ocaña
Source: Inorganic Chemistry (article, 2024-05-29)
Field: Materials Science — Materials Chemistry

Nanoparticulated Bimodal Contrast Agent for Ultra-High-Field Magnetic Resonance Imaging and Spectral X-ray Computed Tomography Bimodal medical imaging based on magnetic resonance imaging (MRI) and computed tomography (CT) is a well-known strategy to increase the diagnostic accuracy. The most recent advances in MRI and CT instrumentation are related to the use of ultra-high magnetic fields (UHF-MRI) and different working voltages (spectral CT), respectively. Such advances require the parallel development of bimodal contrast agents (CAs) that are efficient under new instrumental conditions. In this work, we have synthesized, through a precipitation reaction from a glycerol solution of the precursors, uniform barium dysprosium fluoride nanospheres with a cubic fluorite structure, whose size was found to depend on the Ba/(Ba + Dy) ratio of the starting solution. Moreover, irrespective of the starting Ba/(Ba + Dy) ratio, the experimental Ba/(Ba + Dy) values were always lower than those used in the starting solutions. This result was assigned to lower precipitation kinetics of barium fluoride compared to dysprosium fluoride, as inferred from the detailed analysis of the effect of reaction time on the chemical composition of the precipitates. A sample composed of 34 nm nanospheres with a Ba<sub>0.51</sub>Dy<sub>0.49</sub>F<sub>2.49</sub> stoichiometry showed a transversal relaxivity (<i>r</i><sub>2</sub>) value of 147.11 mM<sup>-1</sup>·s<sup>-1</sup> at 9.4 T and gave a high negative contrast in the phantom image. Likewise, it produced high X-ray attenuation in a large range of working voltages (from 80 to 140 kVp), which can be attributed to the presence of different K-edge values and high Z elements (Ba and Dy) in the nanospheres. Finally, these nanospheres showed negligible cytotoxicity for different biocompatibility tests. Taken together, these results show that the reported nanoparticles are excellent candidates for UHF-MRI/spectral CT bimodal imaging CAs. Chemistry ; Magnetic resonance imaging ; Nuclear magnetic resonance ; Contrast (vision) ; Computed tomography ; X-ray ; Radiology ; Optics ; Physics Luminescence Properties of Advanced Materials ; Lanthanide and Transition Metal Complexes ; Atomic and Subatomic Physics Research
Authors: Heydar Khadem | Hoda Nemat | Daisy Elliott | Mohammed Benaissa
Source: Heliyon (article, 2024-05-01)
Field: Chemistry — Analytical Chemistry

In Vitro Glucose Measurement from NIR and MIR Spectroscopy: Comprehensive Benchmark of Machine Learning and Filtering Chemometrics The quantitative analysis of glucose using spectroscopy is a topic of great significance and interest in science and industry. One conundrum in this area is deploying appropriate preprocessing and regression tools. To contribute to addressing this challenge, in this study, we conducted a comprehensive and novel comparative analysis of various machine learning and preprocessing filtering techniques applied to near-infrared, mid-infrared, and a combination of near-infrared and mid-infrared spectroscopy for glucose assay. Our objective was to evaluate the effectiveness of these techniques in accurately predicting glucose levels and to determine which approach was most optimal. Our investigation involved the acquisition of spectral data from samples of glucose solutions using the three aforementioned spectroscopy techniques. The data was subjected to several preprocessing filtering methods, including convolutional moving average, Savitzky-Golay, multiplicative scatter correction, and normalisation. We then applied representative machine learning algorithms from three categories: linear modelling, traditional nonlinear modelling, and artificial neural networks. The evaluation results revealed that linear models exhibited higher predictive accuracy than nonlinear models, whereas artificial neural network models demonstrated comparable performance. Additionally, the comparative analysis of various filtering methods demonstrated that the convolutional moving average and Savitzky-Golay filters yielded the most precise outcomes overall. In conclusion, our study provides valuable insights into the efficacy of different machine learning techniques for glucose measurement and highlights the importance of applying appropriate filtering methods in enhancing predictive accuracy. These findings have important implications for the development of new and improved glucose quantification technologies. Chemometrics ; Benchmark (surveying) ; Spectroscopy ; Machine learning ; Computer science ; Artificial intelligence ; Analytical Chemistry (journal) ; Chemistry ; Chromatography ; Physics ; Geography Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Water Quality Monitoring and Analysis
Authors: Lu Zhu | Wei Hua | Cong Lv | Yuanyuan Liu
Source: Journal of Lightwave Technology (article, 2024-04-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Rapid Inverse Design of High Degree of Freedom Meta-Atoms Based on the Image-Parameter Diffusion Model The inverse design of metamaterials is the mapping of spectral response (low dimensions) to the structure (high dimensions). In the process of inverse design, there will be a “one-to-many” problem (similar spectral responses are generated by multiple meta-atoms), especially for designs with high degrees of freedom (DOFs). Although traditional generative models (VAE, GAN) combined with optimization algorithms can convert inverse design into forward prediction to solve the “one-to-many” problem, this method requires multiple iterative calculations and has low design efficiency, making it difficult to achieve fast and accurate inverse design. This paper proposes a novel inverse design method based on the image-parameter diffusion model. Through a step-by-step process of adding noise that transforms the structural parameters and images into Gaussian distributions, our method can gradually remove the noise starting from the distribution and generate high DOFs meta-atoms that satisfy the transmission coefficient of additional inputs. Moreover, this method avoids multiple iterative optimizations and ensures more efficient and high-quality generation results. The experimental results show that our method solves the “one-to-many” problem of high-DOFs meta-atoms and can generate free-form structures with only one design iteration, which is superior to conventional design methods in terms of model generation speed, generation accuracy, and quality. Inverse ; Diffusion ; Degree (music) ; Estimation theory ; Inverse problem ; Image (mathematics) ; Optics ; Physics ; Mathematics ; Computer science ; Statistical physics ; Algorithm ; Mathematical analysis ; Computer vision ; Geometry ; Acoustics ; Quantum mechanics Metamaterials and Metasurfaces Applications ; Quasicrystal Structures and Properties
Authors: Francesco Serse | Antoniu Bjola | Matteo Salvalaglio | Matteo Pelucchi
Source: Journal of Chemical Theory and Computation (article, 2024-07-03)
Field: Chemistry — Organic Chemistry

Unveiling Solvent Effects on β-Scissions through Metadynamics and Mean Force Integration This study introduces a methodology that combines accelerated molecular dynamics and mean force integration to investigate solvent effects on chemical reaction kinetics. The newly developed methodology is applied to the β-scission of butyl acrylate (BA) dimer in polar (water) and nonpolar (xylene and BA monomer) solvents. The results show that solvation in both polar and nonpolar environments reduces the free energy barrier of activation by ∼4 kcal/mol and decreases the pre-exponential factor 2-fold. Employing a hybrid quantum mechanics/molecular mechanics approach with explicit solvent modeling, we compute kinetic rate constants that better match experimental measurements compared to previous gas-phase calculations. This methodology presents promising potential for accurately predicting kinetic rate constants in liquid-phase polymerization and depolymerization processes. Reaction rate constant ; Solvation ; Depolymerization ; Molecular dynamics ; Chemistry ; Kinetic energy ; Thermodynamics ; Potential of mean force ; Solvent ; Solvent effects ; Kinetics ; Computational chemistry ; Materials science ; Organic chemistry ; Physics Chemical Reaction Mechanisms ; Advanced Physical and Chemical Molecular Interactions ; Chemical Reactions and Mechanisms
Authors: Tayssir Hamieh
Source: Molecules (article, 2024-04-09)
Field: Chemistry — Spectroscopy

Temperature Dependence of the Polar and Lewis Acid–Base Properties of Poly Methyl Methacrylate Adsorbed on Silica via Inverse Gas Chromatography The adsorption of polymers on solid surfaces is common in many industrial applications, such as coatings, paints, catalysis, colloids, and adhesion processes. The properties of absorbed polymers commonly vary with temperature. In this paper, inverse gas chromatography at infinite dilution was used to determine the physicochemical characterization of PMMA adsorbed on silica. A new method based on the London dispersion equation was applied with a new parameter associating the deformation polarizability with the harmonic mean of the ionization energies of the solvent. More accurate values of the dispersive and polar interaction energies of the various organic solvents adsorbed on PMMA in bulk phase and PMMA/silica at different recovery fractions were obtained, as well as the Lewis acid-base parameters and the transition temperatures of the different composites. It was found that the temperature and the recovery fraction have important effects on the various physicochemical and thermodynamic properties. The variations in all the interaction parameters showed the presence of three transition temperatures for the different PMMA composites adsorbed on silica with various coverage rates, with a shift in these temperatures for a recovery fraction of 31%. An important variation in the polar enthalpy and entropy of adsorption, the Lewis acid-base parameters and the intermolecular separation distance was highlighted as a function of the temperature and the recovery fraction of PMMA on silica. Inverse gas chromatography ; Polar ; Lewis acids and bases ; Adsorption ; Gas chromatography ; Methyl methacrylate ; Chemistry ; Polymer chemistry ; Poly(methyl methacrylate) ; Inverse ; Base (topology) ; Methacrylate ; Organic chemistry ; Materials science ; Chromatography ; Polymer ; Copolymer ; Catalysis Adsorption, diffusion, and thermodynamic properties of materials ; Chemical Thermodynamics and Molecular Structure ; Chemistry and Stereochemistry Studies
Authors: Haoyu Li | Hongyi Xiao | T. Egami | Yue Fan
Source: Materials Today Physics (article, 2024-11-07)
Field: Materials Science — Materials Chemistry

Infinitely rugged intra-cage potential energy landscape in metallic glasses caused by many-body interaction Materials science ; Cage ; Energy landscape ; Metal ; Energy (signal processing) ; Nanotechnology ; Chemical physics ; Metallurgy ; Physics ; Structural engineering ; Thermodynamics ; Quantum mechanics Material Dynamics and Properties ; Theoretical and Computational Physics ; Metallic Glasses and Amorphous Alloys
Authors: Edinei Locks | Qianxi He | Jose M. DePaiva | Monica Costa Rodrigues Guimarães | Abul Fazal M. Arif | Stephen C. Veldhuis | Joey Kish
Source: Coatings (article, 2024-02-28)
Field: Materials Science — Metals and Alloys

Investigating the Impact of Physical Vapour Deposition (PVD)-Coated Cutting Tools on Stress Corrosion Cracking Susceptibility in Turning Super Duplex Stainless Steel This work aimed to ascertain the corresponding influences of several PVD-coated cutting tools on the susceptibility of the machined surface of super duplex stainless steel (SDSS) to stress corrosion cracking. Coatings comprised of AlCrN, AlCrN/TiSiN, and AlTiN were applied to cemented carbide cutting tools using the PVD method; these were then used to turn the outer surface of the SDSS tube section. During the cutting process, the material presents the following combination of features: (i) a tendency for strain hardening, reflected in microstructural modifications and residual stresses of the machined surface and (ii) high temperatures in the cutting region, reducing the tool life. The goal of this work was to evaluate the surface integrity (work hardening and corrosion behaviour) of the SDSS obtained after the machining process (finish turning) with cemented carbide tools coated with three different PVD coatings. Duplex (building) ; Materials science ; Stress corrosion cracking ; Physical vapor deposition ; Metallurgy ; Corrosion ; Cracking ; Stress (linguistics) ; Deposition (geology) ; Composite material ; Geology ; Coating Hydrogen embrittlement and corrosion behaviors in metals ; Advanced Machining and Optimization Techniques ; Erosion and Abrasive Machining