jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Christian Mier Escurra | Armando Rodrigo Mor | Tianming Luo | Peter Vaessen
Source: International Journal of Electrical Power & Energy Systems (article, 2024-03-07)
Field: Materials Science — Materials Chemistry

Partial discharge and interference discrimination in gas-insulated systems using electric and magnetic sensors The correct identification of partial discharges (PDs) is instrumental for the maintenance plan in gas-insulated systems (GIS). However, onsite PD measurements are difficult, especially in HVDC systems, where partial discharges can be confused with interference. This paper proposes a method to discern PDs from interferences based on the GIS characteristic impedance. The characteristic impedance is measured using very-high frequency electric and magnetic sensors, and it is calculated using four approaches based on the PD charge magnitude, peak value, peak-to-peak value, and frequency spectrum. The method is first tested with a PD calibrator in a matched and open-circuited GIS testbench. Then, the identification of PDs and interference is tested in a full-scale GIS, where the measurements are subjected to pulse overlapping and noise. Five types of interferences and PDs are injected into the GIS in two positions and measured in multiple mounting holes. The results show that all four approaches can precisely calculate the characteristic impedance in a matched testbench. In the full-scale GIS, these approaches show more deviation, with the peak approach being the most accurate. A practical application of the method is demonstrated using a calibrator in the full-scale GIS. The proposed method contributes to a more reliable PD monitoring system for HVDC/AC GIS and allows better maintenance planning, reducing unnecessary costs, notably for offshore substations. Partial discharge ; Interference (communication) ; Electromagnetic interference ; Electric discharge ; Electric discharge in gases ; Electrical engineering ; Materials science ; Engineering ; Electronic engineering ; Acoustics ; Voltage ; Physics ; Electrode High voltage insulation and dielectric phenomena ; Plasma Diagnostics and Applications ; Magnetic Field Sensors Techniques
Authors: Z. L. Zhang | Mohamadreza Afrasiabi | Markus Bambach�
Source: Scientific Reports (article, 2024-05-18)
Field: Materials Science — Materials Chemistry

A meshless computational framework for studying cold spray additive manufacturing including large numbers of powder particles with diverse characteristics Cold spray (CS) has emerged as an appealing additive manufacturing (AM) technique for producing or repairing individual components or entire structures. Compared to fusion-based AM technologies, cold spray additive manufacturing (CSAM) offers distinct advantages in the fabrication of components, while avoiding some melting/solidification-related issues such as phase transformation and oxidation. It involves intricate processes that pose significant challenges for numerical modeling, particularly when simulating the entire process at a large scale. The smoothed particle hydrodynamics (SPH) method is highly suitable for handling large material deformations due to its Lagrangian and meshless nature. In this work, we develop an enhanced SPH method to conduct large-scale simulations of CSAM with different powder sizes, morphologies, and distributions. A modified material model has been incorporated to accurately capture the strain-rate hardening effects during the plastic stage. The computational scale is greatly improved by using a Message Passing Interface (MPI) based framework, enabling the simulation of approximately ten million SPH particles. To the authors' knowledge, this study marks the first attempt to numerically reproduce the entire process of CSAM with real powder sizes and distributions. Experimental data measured for a wide range of powder velocities are used to validate the simulation results and assess the prediction accuracy. Subsequently, we comparatively study the bonding mechanisms of powders with the same or different sizes, while also identifying a four-stage coating process. The effects of powder morphology on the bonding process are thoroughly investigated. A large-scale CSAM process is finally reproduced to demonstrate the capability of the present meshless scheme, and mechanisms of pore formation are analyzed, providing valuable insights for practical engineering applications. Gas dynamic cold spray ; Spray drying ; Computer science ; Materials science ; Process engineering ; Chemical engineering ; Nanotechnology ; Engineering High-Velocity Impact and Material Behavior ; Fluid Dynamics Simulations and Interactions ; Fluid Dynamics and Heat Transfer
Authors: Amali G. Guruge | Hesam Makki | Alessandro Troisi
Source: Journal of Materials Chemistry C (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Structural properties of conductive polymer blends interfaced with water: computational insights from PEDOT:PSS In various bioelectronic applications, conductive polymers come into contact with biological tissues, where water is the major component. In this study, we investigated the interface between the conductive polymer poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) and water, focusing on how the morphology of the PEDOT:PSS is altered by water permeation. We constructed well-equilibrated PEDOT:PSS-water systems in both PEDOT- and PSS-rich phases. Our findings show that water permeates into the polymer through a complex network of water channels, which exhibit a similar pore size distribution in both PEDOT- and PSS-rich phases, leading to similar water intake in these phases. Compared to the dry state of the polymer, water permeation leads to the formation of smaller, less ordered, and distantly located lamella crystallites, potentially resulting in reduced conductivity. Therefore, we argue that these structural changes from the dry state of the polymer to the wet state may be the origin of the significant conductivity reduction observed experimentally in PEDOT:PSS in water or PEDOT:PSS hydrogels. Materials science ; PEDOT:PSS ; Electrical conductor ; Conductive polymer ; Composite material ; Polymer ; Chemical engineering Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Analytical Chemistry and Sensors
Authors: Difei Leng | Qiuyan Fu | Y.J. Ge | Chenhao He | Yang Lv | Xiangguo Li
Source: Materials (article, 2024-03-01)
Field: Materials Science — Materials Chemistry

Effect of K+ Diffusion on Hydration of Magnesium Potassium Phosphate Cement with Different Mg/P Ratios: Experiments and Molecular Dynamics Simulation Calculations Magnesium potassium phosphate cement (MKPC) is formed on the basis of acid-base reaction between dead burnt MgO and KH<sub>2</sub>PO<sub>4</sub> in aqueous solution with K-struvite as the main cementitious phase. Due to the unique characteristics of these cements, they are suitable for special applications, especially the immobilization of radioactive metal cations and road repair projects at low temperature. However, there are few articles about the hydration mechanism of MKPC. In this study, the types, proportions and formation mechanism of MKPC crystalline phases under different magnesium to phosphorus (Mg/P) ratios were studied by means of AAS, ICP-OES, SEM, EDS and XRD refinement methods. Corresponding MD simulation works were used to explain the hydration mechanism. This study highlights the fact that crystalline phases distribution of MKPC could be adjusted and controlled by different Mg/P ratios for the design of the MKPC, and the key factor is the kinetic of K<sup>+</sup>. Magnesium ; Potassium ; Cement ; Molecular dynamics ; Magnesium phosphate ; Diffusion ; Materials science ; Potassium phosphate ; Phosphate ; Dynamics (music) ; Chemistry ; Chemical engineering ; Thermodynamics ; Metallurgy ; Organic chemistry ; Computational chemistry ; Psychology ; Physics Magnesium Oxide Properties and Applications ; Concrete and Cement Materials Research ; Ferroelectric and Piezoelectric Materials
Authors: Shavkat Mamatkulov | Jakub Polák | Jamoliddin Razzokov | Lukáš Tomaník | Petr Slavı́ček | Joachim Dzubiella | Matej Kanduč | Jan Heyda
Source: Journal of Chemical Theory and Computation (article, 2024-01-16)
Field: Materials Science — Materials Chemistry

Unveiling the Borohydride Ion through Force-Field Development The borohydride ion, BH<sub>4</sub><sup>-</sup>, is an essential reducing agent in many technological processes, yet its full understanding has been elusive, because of at least two significant challenges. One challenge arises from its marginal stability in aqueous solutions outside of basic pH conditions, which considerably limits the experimental thermodynamic data. The other challenge comes from its unique and atypical hydration shell, stemming from the negative excess charge on its hydrogen atoms, which complicates the accurate modeling in classical atomistic simulations. In this study, we combine experimental and computer simulation techniques to devise a classical force field for NaBH<sub>4</sub> and deepen our understanding of its characteristics. We report the first measurement of the ion's activity coefficient and extrapolate it to neutral pH conditions. Given the difficulties in directly measuring its solvation free energies, owing to its instability, we resort to quantum chemistry calculations. This combined strategy allows us to derive a set of nonpolarizable force-field parameters for the borohydride ion for classical molecular dynamics simulations. The derived force field simultaneously captures the solvation free energy, the hydration structure, as well as the activity coefficient of NaBH<sub>4</sub> salt across a broad concentration range. The obtained insights into the hydration shell of the BH<sub>4</sub><sup>-</sup> ion are crucial for accurately modeling and understanding its interactions with other molecules, ions, materials, and interfaces. Solvation ; Force field (fiction) ; Solvation shell ; Molecular dynamics ; Ion ; Borohydride ; Chemistry ; Chemical physics ; Aqueous solution ; Water model ; Molecule ; Field (mathematics) ; Computational chemistry ; Physics ; Physical chemistry ; Organic chemistry ; Quantum mechanics Hydrogen Storage and Materials ; Quantum, superfluid, helium dynamics ; Advanced Chemical Physics Studies
Authors: A. Jalalpour | J. Arghavani | R. Naghdabadi
Source: Continuum Mechanics and Thermodynamics (article, 2024-08-05)
Field: Materials Science — Polymers and Plastics

Thermo-oxidative aging of natural rubber: experimental study and a thermodynamically consistent mechanical-chemical-diffusion model Natural rubber ; Materials science ; Elastomer ; Curing (chemistry) ; Creep ; Composite material ; Diffusion ; Stress relaxation ; Ultimate tensile strength ; Thermodynamics Polymer Nanocomposites and Properties ; Polymer crystallization and properties ; Rheology and Fluid Dynamics Studies
Authors: Jieyu Lü | Zhengshuai Song | Qiyuan Zhao | Yuanqi Du | Yirui Cao | Haojun Jia | Chenru Duan
Source: ChemRxiv (preprint, 2024-10-24)
Field: Materials Science — Materials Chemistry

Generative Design of Functional Metal Complexes Utilizing the Internal Knowledge of Large Language Models The design of functional transition metal complexes (TMCs) is hindered by the combinatorial explosion of the search space spanned by various metals and ligands, necessitating efficient multi- objective optimization strategies. Traditional genetic algorithms (GAs) are frequently employed in this domain, utilizing random mutations and crossovers steered by explicit mathematical objective formulations to navigate the search space. The transfer and sharing of knowledge across different GA optimization tasks, however, remain challenging. Here, we introduce the integration of large language models (LLMs) into the evolutionary optimization framework (LLM-EO) for TMCs. LLM- EO significantly outperforms traditional GAs due to the intrinsic chemical knowledge embedded within LLMs, acquired during their extensive pretraining. Notably, without the need for supervised fine-tuning, LLMs can leverage the entirety of historical data amassed during the optimization processes, demonstrating superior performance compared to LLMs that are limited to the best TMCs identified in the evolutionary cycle. Specifically, LLM-EO identifies eight out of the top 20 TMCs with the largest HOMO-LUMO gaps by interrogating merely 200 candidates within a vast search space of 1.37 million TMCs. Through prompt engineering using natural language, LLM-EO introduces unparalleled flexibility in multi-objective optimizations, especially when guided by seasoned researchers, thereby circumventing the necessity for intricate mathematical formulations. As generative models, LLMs possess the capability to propose novel ligands and TMCs with unique chemical properties by amalgamating both internal knowledge and external chemistry data, thus combining the benefits of efficient optimization and molecular generation. With the increasing potential of LLMs, both in their capacity as pretrained foundational models and new strategies in post-training inference, we anticipate broad applications of LLM-based evolutionary optimization in the fields of chemistry and materials design. Generative grammar ; Computer science ; Natural language processing ; Linguistics ; Artificial intelligence ; Philosophy Machine Learning in Materials Science
Authors: Piyawanee Jariyasakoolroj | Busarin Chongcharoenyanon | Kiattichai Wadaugsorn
Source: Journal of Applied Polymer Science (article, 2024-02-21)
Field: Materials Science — Biomaterials

Kinetic migration of <scp>PBS</scp> and <scp>PBSA</scp> biopolymers prepared by cast film extrusion and biaxial stretching: A combined experimental and modeling approach Abstract The kinetic migration of poly(butylene succinate) (PBS) and poly(butylene succinate‐co‐adipate) (PBSA) biopolymers, prepared by cast film extrusion (thin film) and biaxial stretching (biaxially oriented [BO] film) techniques, were investigated based on experimental and mathematical modeling. MATLAB coding was used to fit the migration data to a diffusion model. BO films significantly reduced the migration rate compared with thin films, with reductions of 29% and 41% for BO‐PBS and BO‐PBSA, respectively, due to the increased degree of molecular crystallinity. Higher ethanol content increased the quantity of substance diffusing from plastic film. PBS and PBSA are more suitable for packaging hydrophilic foods than alcoholic beverages. PBS exhibited a lower migration rate than PBSA due to its more rigid polymer matrix. Remarkably, BO‐films exhibited 31% and 41% lower diffusion coefficients ( D ) compared with thin films, but significantly higher partition coefficients ( K P,F ) by 44% and 267% for BO‐PBS and BO‐PBSA, respectively. This suggests a stronger affinity of migrant for BO film matrix. However, at 70°C, PBSA films may be hydrolyzed with a high ethanol, resulting in an inadequate diffusion model. The diffusion–reaction concept should be implemented for a better fit. These findings provide valuable insights for selecting appropriate packaging materials and predicting migration under diverse conditions, ultimately promoting consumer safety. Crystallinity ; Materials science ; Extrusion ; Adipate ; Chemical engineering ; Diffusion ; Thin film ; Polymer ; Polybutylene succinate ; Polymer chemistry ; Composite material ; Nanotechnology ; Thermodynamics biodegradable polymer synthesis and properties ; Polymer crystallization and properties ; Nanocomposite Films for Food Packaging
Authors: Pallab Das | Pankaj Tiwari | Jong‐Min Lee
Source: Chemical Engineering Journal (article, 2024-04-06)
Field: Materials Science — Materials Chemistry

Multistep kinetic analysis of additive-enhanced plastic degradation Isothermal process ; Kinetic energy ; Degradation (telecommunications) ; Thermodynamics ; Activation energy ; Polymer ; Diffusion ; Kinetics ; Chemistry ; Biological system ; Materials science ; Chemical engineering ; Physical chemistry ; Computer science ; Physics ; Organic chemistry Thermal and Kinetic Analysis ; Energetic Materials and Combustion ; Thermochemical Biomass Conversion Processes
Authors: Weiqi Sun | Haohua Zhang | Qingjie He | Yazhou Wang | Jiaao Wu | Yiting Bu | Bin Li | Lixian Sun | Fen Xu | Yang Lu | Ting Yu | Zhi-Cheng Yang | Lu Geng
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Monolithic Nickel-Doped Molybdenum Nitride Improves Hydrogen Storage Properties of Mgh2 Materials science ; Molybdenum ; Doping ; Nitride ; Hydrogen storage ; Nickel ; Hydrogen ; Optoelectronics ; Nanotechnology ; Metallurgy ; Chemistry Hydrogen Storage and Materials ; MXene and MAX Phase Materials ; Superconductivity in MgB2 and Alloys
Authors: Yikai Liu | Tushar K. Ghosh | Guang Lin | Ming Chen
Source: The Journal of Physical Chemistry Letters (article, 2024-04-03)
Field: Materials Science — Materials Chemistry

Unbiasing Enhanced Sampling on a High-Dimensional Free Energy Surface with a Deep Generative Model Biased enhanced sampling methods that utilize collective variables (CVs) are powerful tools for sampling conformational ensembles. Due to their large intrinsic dimensions, efficiently generating conformational ensembles for complex systems requires enhanced sampling on high-dimensional free energy surfaces. While temperature-accelerated molecular dynamics (TAMD) can trivially adopt many CVs in a simulation, unbiasing the simulation to generate unbiased conformational ensembles requires accurate modeling of a high-dimensional CV probability distribution, which is challenging for traditional density estimation techniques. Here we propose an unbiasing method based on the score-based diffusion model, a deep generative learning method that excels in density estimation across complex data landscapes. We demonstrate that this unbiasing approach, tested on multiple TAMD simulations, significantly outperforms traditional unbiasing methods and can generate accurate unbiased conformational ensembles. With the proposed approach, TAMD can adopt CVs that focus on improving sampling efficiency and the proposed unbiasing method enables accurate evaluation of ensemble averages of important chemical features. Sampling (signal processing) ; Computer science ; Molecular dynamics ; Focus (optics) ; Generative model ; Artificial intelligence ; Importance sampling ; Deep learning ; Algorithm ; Generative grammar ; Machine learning ; Mathematics ; Monte Carlo method ; Statistics ; Chemistry ; Computational chemistry ; Physics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Complex Network Analysis Techniques
Authors: Yang Zhang | Qiancheng Ren | Jiayuan Fang | Jinglan Liu | Suhao Wang | Jizhou Song | Pei Zhao
Source: Physical review. B./Physical review. B (article, 2024-01-22)
Field: Materials Science — Materials Chemistry

Simultaneous measurement of in-plane and interfacial thermal conductivity of isotopically labeled bilayer graphene The thermal properties of bilayer graphene (BLG) play a crucial role in the advancement of its promising electronic devices. However, the measurement of thermal conductivity using current techniques faces obstacles due to the low temperature gradient both in plane and across the interface in the sample. Here we present an approach to simultaneously explore the in-plane and interfacial thermal conductivity of chemical vapor deposited AB-stacked BLG by utilizing an isotope labeling assisted Raman spectroscopic technique. By applying the modified heat diffusion model, we acquire the interfacial thermal conductivity of isotopically labeled AB-stacked BLG of $105\ifmmode\pm\else\textpm\fi{}3\phantom{\rule{0.16em}{0ex}}\mathrm{MW}/({\mathrm{m}}^{2}\phantom{\rule{0.16em}{0ex}}\mathrm{K})$, whereas we find the in-plane thermal conductivity of each layer is reduced compared with their monolayers. This technique demonstrates strong support for advancing the BLG thermal engineering research as well as a potential of extending to other two-dimensional systems. Thermal conductivity ; Bilayer graphene ; Materials science ; Graphene ; Bilayer ; Raman spectroscopy ; Monolayer ; Plane (geometry) ; Thermal ; Diffusion ; Condensed matter physics ; Analytical Chemistry (journal) ; Nanotechnology ; Thermodynamics ; Physics ; Chemistry ; Optics ; Composite material ; Membrane Graphene research and applications ; Thermal properties of materials ; Thermal Radiation and Cooling Technologies
Authors: Salem Jawad Alhamd | Mohammed Nsaif Abbas | Hassan Jameel Al-Fatlawy | Thekra Atta Ibrahim | Zaid Nsaif Abbas
Source: Karbala International Journal of Modern Science (article, 2024-05-09)
Field: Chemistry — Analytical Chemistry

Removal of phenol from oilfield produced water using non-conventional adsorbent medium by an eco-friendly approach Petroleum extraction generates substantial quantities of produced water, a challenge compounded by water scarcity in oil-producing regions, notably the Middle East. Leveraging produced water effectively, adhering to environmental standards, can offer a viable solution to the issue of water scarcity. This study explores the potential of mandarin peels as an available, cost-effective adsorbent for treating synthetic aqueous solution simulated to oil-field produced water, specifically targeting phenol, a dangerous pollutant. Employing a batch-mode adsorption unit, six operational factors—phenol concentration, acidity, agitation speed, contact time, adsorbent dose, and temperature—were investigated. Results revealed an inverse relationship between phenol removal and pH, concentration, and temperature, while direct correlations were observed with other variables. Mandarin peels exhibited notable phenol recovery, reaching a maximum efficiency of 74.43% at pH 1, 450 rpm agitation speed, 38 ppm initial concentration, 5 g dose, time of 180 minutes, and 20°C temperature. Isothermal and kinetic analyses favored the Langmuir and intra-particle diffusion models. Thermodynamically, the process proved exothermic, marked by low entropy, and spontaneous within the tested temperature range. Adhering to the zero residues level concept, exploring beneficial and safe disposal methods for contaminated residues led to investigating toxic mandarin peel residue as a rodenticide, displaying promising efficacy on laboratory albino rats. Consequently, this study proposes a sustainable approach, treating produced water laden with toxic pollutants using readily available agricultural waste while concurrently repurposing the toxic waste into an environmentally friendly material, aligning with the zero waste level concept. Phenol ; Environmentally friendly ; Adsorption ; Pulp and paper industry ; Chemistry ; Process engineering ; Chemical engineering ; Environmental science ; Waste management ; Petroleum engineering ; Organic chemistry ; Geology ; Engineering ; Biology ; Ecology Petroleum Processing and Analysis ; Extraction and Separation Processes ; Enhanced Oil Recovery Techniques