jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: L. Luzzi | A. Magni | S. Billiet | M. Di Gennaro | Gregory Leinders | Leandro Mariano | D. Pizzocri | Marco Zanetti | G. Zullo
Source: Nuclear Engineering and Design (article, 2024-02-29)
Field: Materials Science — Materials Chemistry

Performance analysis and helium behaviour of Am-bearing fuel pins for irradiation in the MYRRHA reactor Minor actinides are the main contributors to medium- and long-term radiotoxicity and heat production in spent nuclear fuels. Research efforts are currently ongoing to explore different options to dispose of such radionuclides, e.g., their burning in fast reactors within mixed-oxide fuels. The MYRRHA sub-critical reactor is one of the future facilities with envisaged burning and transmutation capabilities. This work assesses the thermal–mechanical performance of a homogeneous Am-bearing fuel pin both in the In-Pile test Section position of the MYRRHA “Revision 1.8” core and under driver irradiation. The normal operating conditions of MYRRHA are considered, with a focus on the safety design limits and involving sensitivity analyses to evaluate the impact of increasing americium contents (in the range 0–5 wt%) on safety-relevant simulation outcomes. The simulations are performed with the TRANSURANUS fuel performance code (version v1m4j22) coupled with the SCIANTIX physics-based module for inert gas behaviour, and rely on a dedicated surrogate model for the helium source term during MYRRHA irradiation accounting for the relevant contribution of the fuel americium enrichment, besides advanced models for the properties and behaviour of the specific pin materials. The analyses reveal the suitability and safety under irradiation of MOX fuels with low Am enrichments according to the current MYRRHA design. Nuclear transmutation ; Nuclear engineering ; Americium ; MOX fuel ; Materials science ; Nuclear fuel ; Waste management ; Plenum space ; Engineering ; Environmental science ; Actinide ; Radiochemistry ; Mechanical engineering ; Nuclear physics ; Nuclear chemistry ; Plutonium ; Chemistry ; Neutron ; Physics Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Thermodynamic and Structural Properties of Metals and Alloys
Authors: Mohammed Alqarni | Ali Alqarni
Source: Chinese Journal of Physics (article, 2024-12-20)
Field: Materials Science — Materials Chemistry

Computational intelligence investigations on the correlation of pharmaceutical solubility in mixtures of binary solvents: Effect of composition and temperature Solubility ; Binary number ; Materials science ; Composition (language) ; Thermodynamics ; Chemistry ; Organic chemistry ; Mathematics ; Physics Crystallization and Solubility Studies ; Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods
Authors: Qiaohan Liu | Naixing Feng | Yi Zou | Chuanqiang Fan | Jingang Wang
Source: Scientific Reports (article, 2024-03-13)
Field: Materials Science — Materials Chemistry

Exploring the impact of stress on the electronic structure and optical properties of graphdiyne nanoribbons for advanced optoelectronic applications Graphdiyne (GDY), a two-dimensional carbon material with sp- and sp<sup>2</sup>-hybridization, is recognized for its unique electronic properties and well-dispersed porosity. Its versatility has led to its use in a variety of applications. The precise control of this material's properties is paramount for its effective utilization in nano-optical devices. One effective method of regulation, which circumvents the need for additional disturbances, involves the application of external stress. This technique provides a direct means of eliciting changes in the electronic characteristics of the material. For instance, when subjected to uniaxial stress, electron transfer occurs at the triple bond. This results in an armchair-edged graphdiyne nanoribbon (A(3)-GDYNR) with a planar width of 2.07 nm, which exhibits a subtle plasmon effect at 500 nm. Conversely, a zigzag-edged graphdiyne nanoribbon (Z(3)-GDYNR) with a planar width of 2.86 nm demonstrates a pronounced plasmon effect within the 250-1200 nm range. This finding suggests that the zigzag nanoribbon surpasses the armchair nanoribbon in terms of its plasmon effect. First principles calculations and ab initio molecular dynamics further confirmed that under applied stress Z(3)-GDYNR exhibits less deformation than A(3)-GDYNR, indicating superior stability. This work provides the necessary theoretical basis for understanding graphene nanoribbons (GDYNRs). Zigzag ; Materials science ; Plasmon ; Planar ; Graphene ; Stress (linguistics) ; Optoelectronics ; Nanotechnology ; Deformation (meteorology) ; Graphene nanoribbons ; Electronic structure ; Condensed matter physics ; Composite material ; Physics ; Computer science Graphene research and applications ; 2D Materials and Applications ; Advancements in Battery Materials
Authors: Jehad Abed | Yang Bai | Daniel Ethan Persaud | Jiheon Kim | Julia Witt | Jason Hattrick‐Simpers | Edward H Sargent
Source: Digital Discovery (article, 2024-01-01)
Field: Chemistry — Electrochemistry

AMPERE: automated modular platform for expedited and reproducible electrochemical testing AMPERE automates sample preparation and electrochemical testing at large scale, enhancing speed, reliability, and openness. It uses a liquid-handling robot with modular reactors to measure metal dissolution for electrochemical stability assessment. Modular design ; Computer science ; Ampere ; Embedded system ; Engineering ; Electrical engineering ; Operating system ; Current (fluid) Electrochemical Analysis and Applications ; Fuel Cells and Related Materials ; Machine Learning in Materials Science
Authors: Alex Saad–Falcon | Christopher J. Howard | Justin Romberg | Kenneth W. Allen
Source: Scientific Reports (article, 2024-07-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Level set methods for gradient-free optimization of metasurface arrays Global optimization techniques are increasingly preferred over human-driven methods in the design of electromagnetic structures such as metasurfaces, and careful construction and parameterization of the physical structure is critical in ensuring computational efficiency and convergence of the optimization algorithm to a globally optimal solution. While many design variables in physical systems take discrete values, optimization algorithms often benefit from a continuous design space. This work demonstrates the use of level set functions as a continuous basis for designing material distributions for metasurface arrays and introduces an improved parameterization which is termed the periodic level set function. We explore the use of alternate norms in the definition of the level set function and define a new pseudo-inverse technique for upsampling basis coefficients with these norms. The level set method is compared to the fragmented parameterization and shows improved electromagnetic responses for two dissimilar cost functions: a narrowband objective and a broadband objective. Finally, we manufacture an optimized level set metasurface and measure its scattering parameters to demonstrate real-world performance. Computer science ; Set (abstract data type) ; Mathematical optimization ; Upsampling ; Broadband ; Function (biology) ; Basis function ; Algorithm ; Optimization problem ; Inverse ; Narrowband ; Mathematics ; Telecommunications ; Artificial intelligence ; Mathematical analysis Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Hasan M. Sayeed | Wade Smallwood | Sterling G. Baird | Taylor D. Sparks
Source: Matter (article, 2024-03-01)
Field: Materials Science — Materials Chemistry

NLP meets materials science: Quantifying the presentation of materials data in literature Leverage (statistics) ; Computer science ; Data science ; Information extraction ; Presentation (obstetrics) ; Data extraction ; Information retrieval ; Natural language processing ; Artificial intelligence ; MEDLINE ; Chemistry Machine Learning in Materials Science ; Topic Modeling ; Software Engineering Research
Authors: Navid Ansari | Vahid Babaei | Mohammad Mahdi Najafpour
Source: Dalton Transactions (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Enhancing catalysis studies with chat generative pre-trained transformer (ChatGPT): Conversation with ChatGPT The progress made in natural language processing (NLP) and large language models (LLMs), such as generative pre-trained transformers, (GPT) has provided exciting opportunities for enhancing research across various fields. Within the realm of catalysis studies, GPT-driven models present valuable support in expediting the exploration and comprehension of catalytic processes. This research underscores the significance of ChatGPT in catalysis research, emphasizing its prowess as a valuable tool for furthering scientific inquiries. It suggests that for an outstanding oxygen evolution reaction (OER) catalyst as a case study, scientists can leverage ChatGPT to extract deeper insights and brainstorm innovative approaches to grasp the mechanism better and refine current systems. Generative grammar ; Transformer ; Conversation ; Catalysis ; Computer science ; Chemistry ; Psychology ; Communication ; Engineering ; Artificial intelligence ; Organic chemistry ; Electrical engineering Machine Learning in Materials Science ; Topic Modeling ; Ferroelectric and Negative Capacitance Devices
Authors: Yuqi Gu | Lifang Shi | Jianhua Wu | Sheng Hu | Yuqian Shang | Muhammad Hassan | Chao Zhao
Source: Foods (article, 2024-10-12)
Field: Chemistry — Analytical Chemistry

Quantitative Prediction of Acid Value of Camellia Seed Oil Based on Hyperspectral Imaging Technology Fusing Spectral and Image Features Acid value (AV) serves as an important indicator to assess the quality of oil, which can be used to judge the deterioration of edible oil. In order to realize the quantitative prediction of the AV of camellia seed oil, which was made from camellia oleifolia, hyperspectral data of 168 camellia seed oil samples were collected using a hyperspectral imaging system, which were related to their AV content measured via classical chemical titration. On the basis of hyperspectral full wavelengths, characteristic wavelengths, and fusing spectral and image features, the quantitative prediction AV models for camellia seed oil were established. The results demonstrating the 2Der-SPA-GLCM-PLSR model fusing spectral and image features stood out as the optimal choices for the AV prediction of camellia seed oil, with the correlation coefficient of calibration set (Rc2) and the correlation coefficient of prediction set (Rp2) at 0.9698 and 0.9581, respectively. Compared with those of 2Der-SPA-PLSR, the Rc2 and Rp2 were improved by 2.11% and 2.57%, respectively. Compared with those of 2Der-PLSR, the Rc2 and Rp2 were improved by 5.02% and 5.31%, respectively. Compared with the model based on original spectrum, the Rc2 and Rp2 were improved by 32.63% and 40.11%, respectively. After spectral preprocessing, characteristic wavelength selection, and fusing spectral and image features, the correlation coefficient of the optimal AV prediction model was continuously improved, while the root mean square error was continuously decreased. The research demonstrated that hyperspectral imaging technology could precisely and quantitatively predict the AV of camellia seed oil and also provide a new environmental method for detecting the AV of other edible oils, which is conducive to sustainable development. Hyperspectral imaging ; Correlation coefficient ; Camellia ; Partial least squares regression ; Mean squared error ; Preprocessor ; Coefficient of determination ; Mathematics ; Artificial intelligence ; Remote sensing ; Pattern recognition (psychology) ; Biological system ; Computer science ; Statistics ; Biology ; Geography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Emanuele Marino | Thi Vo | Cristian D. Gonzalez | Daniel J. Rosen | Steven J. Neuhaus | Alice Sciortino | Harshit Bharti | Austin W. Keller | Cherie R. Kagan | M. Cannas | Fabrizio Messina | Sharon C. Glotzer | Christopher B. Murray
Source: Chemistry of Materials (article, 2024-04-02)
Field: Materials Science — Materials Chemistry

Porous Magneto-Fluorescent Superparticles by Rapid Emulsion Densification Porous superstructures are characterized by a large surface area and efficient molecular transport. Although methods aimed at generating porous superstructures from nanocrystals exist, current state-of-the-art strategies are limited to single-component nanocrystal dispersions. More importantly, such processes afford little control over the size and shape of the pores. Here, we present a new strategy for the nanofabrication of porous magneto-fluorescent nanocrystal superparticles that are well controlled in size and shape. We synthesize these composite superparticles by confining semiconductor and superparamagnetic nanocrystals within oil-in-water droplets generated using microfluidics. The rapid densification of these droplets yields spherical, monodisperse, and porous nanocrystal superparticles. Molecular simulations reveal that the formation of pores throughout the superparticles is linked to repulsion between nanocrystals of different compositions, leading to phase separation during self-assembly. We confirm the presence of nanocrystal phase separation at the single superparticle level by analyzing the changes in the optical and photonic properties of the superstructures as a function of nanocrystal composition. This excellent agreement between experiments and simulations allows us to develop a theory that predicts superparticle porosity from experimentally tunable physical parameters, such as nanocrystal size ratio, stoichiometry, and droplet densification rate. Our combined theoretical, computational, and experimental findings provide a blueprint for designing porous, multifunctional superparticles with immediate applications in catalytic, electrochemical, sensing, and cargo delivery applications. Emulsion ; Fluorescence ; Porosity ; Materials science ; Porous medium ; Composite material ; Chemical engineering ; Physics ; Optics Pickering emulsions and particle stabilization ; Characterization and Applications of Magnetic Nanoparticles ; Nanoparticle-Based Drug Delivery
Authors: H. M. Ragab | N. S. Diab | Jumana N. Dawoud | Mahmoud Al Elaimi | Shimaa Mohammed Aboelnaga | M. O. Farea
Source: RSC Advances (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Novel HPMC/PEDOT:PSS nanocomposite for optoelectronic and energy storage applications This study investigates a class of materials known as polymer nanodielectrics, which are formed by incorporating ceramic fillers into polymers. These materials offer the unique advantage of tunable electrical and optical properties. The research focuses on the incorporation of high-purity stannic oxide nanoparticles (SnO<sub>2</sub> NPs) into a ternary blend matrix of hydroxypropyl methylcellulose (HPMC) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) using a solution casting method. Characterization techniques like X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FT-IR) revealed alterations in the amorphous nature of the HPMC/PEDOT:PSS blend upon the introduction of SnO<sub>2</sub> NPs. These analyses also suggest the formation of interactions between the polymer and nanoparticles. Scanning electron microscopy (SEM) images confirmed the successful dispersion of SnO<sub>2</sub> NPs on the surface of the polymer blend, particularly at lower concentrations. The optical properties of the nanocomposite films were investigated using UV-vis spectrophotometry. This analysis allowed for the calculation of optical constants like the bandgap and refractive index. The results showed a dual-bandgap structure, with the direct and indirect bandgaps ranging from 4.92 eV to 4.26 eV and 3.52 eV to 1.68 eV, respectively. Electrical characterization using AC conductivity and dielectric permittivity measurements revealed a dependence on the SnO<sub>2</sub> NPs concentration within the frequency range of 0.1 Hz to 10 MHz. The relaxation processes and interfacial polarization effects within these nanocomposites are further discussed in the study. At a frequency of 10 Hz, the AC conductivity exhibited a significant increase, rising from 1.85 × 10<sup>-12</sup> S m<sup>-1</sup> to 1.04 × 10<sup>-9</sup> S m<sup>-1</sup> upon the addition of 0.7 wt% SnO<sub>2</sub> NPs. These findings highlight the multifunctional nature of the developed nanocomposites. They hold promise for various applications, including UV blockers, optical bandgap tuners, and optical coatings in advanced optoelectronic devices. Additionally, their tunable high permittivity suggests potential use as dielectric substrates for next-generation, high-performance energy storage devices. PEDOT:PSS ; Nanocomposite ; Materials science ; Polymer ; Ceramic ; Energy storage ; Chemical engineering ; Nanotechnology ; Composite material Conducting polymers and applications ; Dielectric materials and actuators ; Polymer Nanocomposite Synthesis and Irradiation
Authors: Simona Baluchová | Stach van Leeuwen | Barış Kumru | Josephus G. Buijnsters
Source: ACS Applied Polymer Materials (article, 2024-11-19)
Field: Materials Science — Polymers and Plastics

Advanced 3D-Printed Flexible Composite Electrodes of Diamond, Carbon Nanotubes, and Thermoplastic Polyurethane In this work, we pioneered the preparation of diamond-containing flexible electrodes using 3D printing technology. The herein developed procedure involves a unique integration of boron-doped diamond (BDD) microparticles and multi-walled carbon nanotubes (CNTs) within a flexible polymer, thermoplastic polyurethane (TPU). Initially, the process for the preparation of homogeneous filaments with optimal printability was addressed, leading to the development of two TPU/CNT/BDD composite electrodes with different CNT:BDD weight ratios (1:1 and 1:2), which were benchmarked against a TPU/CNT electrode. Scanning electron microscopy revealed a uniform distribution of conductive fillers within the composite materials with no signs of clustering or aggregation. Notably, increasing the proportion of BDD particles led to a 10-fold improvement in conductivity, from 0.12 S m<sup>-1</sup> for TPU/CNT to 1.2 S m<sup>-1</sup> for TPU/CNT/BDD (1:2). Cyclic voltammetry of the inorganic redox markers, [Ru(NH<sub>3</sub>)<sub>6</sub>]<sup>3+/2+</sup> and [Fe(CN)<sub>6</sub>]<sup>3-/4-</sup>, also revealed a reduction in peak-to-peak separation (Δ<i>E</i> <sub>p</sub>) with a higher BDD content, indicating enhanced electron transfer kinetics. This was further confirmed by the highest apparent heterogeneous electron transfer rate constants (<i>k</i> <sup>0</sup> <sub>app</sub>) of 1 × 10<sup>-3</sup> cm s<sup>-1</sup> obtained for both markers for the TPU/CNT/BDD (1:2) electrode. Additionally, the functionality of the flexible TPU/CNT/BDD electrodes was successfully validated by the electrochemical detection of dopamine, a complex organic molecule, at millimolar concentrations by using differential pulse voltammetry. This proof-of-concept may accelerate development of highly desirable diamond-based flexible devices with customizable geometries and dimensions and pave the way for various applications where flexibility is mandated, such as neuroscience, biomedical fields, health, and food monitoring. Thermoplastic polyurethane ; Materials science ; Electrode ; Carbon nanotube ; Cyclic voltammetry ; Diamond ; Polyurethane ; Graphene ; Glassy carbon ; Chemical engineering ; Scanning electron microscope ; Composite number ; Composite material ; Nanotechnology ; Electrochemistry ; Chemistry ; Elastomer Conducting polymers and applications ; Electrochemical sensors and biosensors ; Neuroscience and Neural Engineering
Authors: Valeria Ventorino | Fatima Ezzahra Chouyia | Ida Romano | Mauro Mori | Olimpia Pepe
Source: Applied Microbiology and Biotechnology (article, 2024-09-13)
Field: Materials Science — Polymers and Plastics

Water retting process with hemp pre-treatment: effect on the enzymatic activities and microbial populations dynamic Proper retting process of hemp stems, in which efficient separation of cellulose fiber from the rest of the stem is promoted by indigenous microorganisms able to degrade pectin, is essential for fiber production and quality. This research aimed to investigate the effect of a pre-treatment dew retting in field of hemp stalks on the pectinolytic enzymatic activity and microbiota dynamic during lab-scale water retting process. A strong increase in the pectinase activity as well as in the aerobic and anaerobic pectinolytic concentration was observed from 14 to 21 days, especially using hemp stalks that were not subjected to a pre-retting treatment on field (WRF0 0.690 ± 0.05 U/mL). Results revealed that the microbial diversity significantly varied over time during the water retting and the development of microbiota characterizing the water retting of hemp stalks of different biosystems used in this study was affected by pre-treatment conditions in the field and water retting process and by an interaction between the two methods. Although at the beginning of the experiment a high biodiversity was recorded in all biosystems, the water retting led to a selection of microbial populations in function of the time of pre-treatment in field, especially in bacterial populations. The use of hemp stems did not subject to a field pre-treatment seems to help the development of a homogeneous and specific pectinolytic microbiota with a higher enzymatic activity in respect to samples exposed to uncontrolled environmental conditions for 10, 20, or 30 days before the water retting process. KEY POINTS: • Microbial diversity significantly varied over time during water retting. • Water retting microbiota was affected by dew pre-treatment in the field. • Retting of no pretreated hemp allows the development of specific microbiota with high enzymatic activity. Retting ; Pectinase ; Biology ; Microorganism ; Pulp and paper industry ; Horticulture ; Botany ; Food science ; Biotechnology ; Agronomy ; Bacteria ; Enzyme ; Biochemistry Natural Fiber Reinforced Composites ; Advanced Cellulose Research Studies ; Bamboo properties and applications