jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Junyuan Bai | Xueyong Pang | Gaowu Qin
Source: arXiv (Cornell University) (preprint, 2023-09-09)
Field: Materials Science — Materials Chemistry

Decoding Complex Compositions in Topologically Close-Packed Nano-plates of Magnesium Alloys: A High-Throughput Route to Stable Precipitates Coherent topologically close-packed nanoplates in magnesium alloys can effectively improve strength and creep resistance.However, the formation mechanisms of several metastable TCP nanoplates remain unclear, and the traditional trial-and-error methods hinder the rapid discovery of novel TCP precipitate strengthened Mg alloys.By integrating the thermodynamic and kinetic conditions for TCP precipitation, we developed a two-step high-throughput screening strategy, identifying 43 previously unreported TCP nanoplates in a series of Mg alloys. These findings highlight the critical need for precise compositional characterization of nanoprecipitates and establish a theoretical framework for designing creep-resistant Mg alloys containing TCP nanoplates. Materials science ; Precipitation ; Magnesium ; Zirconium ; Nanoscopic scale ; Hexagonal crystal system ; Creep ; Metal ; Metallurgy ; Phase (matter) ; Crystallography ; Nanotechnology ; Chemistry Microstructure and mechanical properties ; Magnesium Alloys: Properties and Applications ; Advanced Materials Characterization Techniques
Authors: Filip Bosnić | Mile Šikić
Source: arXiv (Cornell University) (preprint, 2023-06-10)
Field: Materials Science — Materials Chemistry

Finding Hamiltonian cycles with graph neural networks We train a small message-passing graph neural network to predict Hamiltonian cycles on Erdős-Rényi random graphs in a critical regime. It outperforms existing hand-crafted heuristics after about 2.5 hours of training on a single GPU. Our findings encourage an alternative approach to solving computationally demanding (NP-hard) problems arising in practice. Instead of devising a heuristic by hand, one can train it end-to-end using a neural network. This has several advantages. Firstly, it is relatively quick and requires little problem-specific knowledge. Secondly, the network can adjust to the distribution of training samples, improving the performance on the most relevant problem instances. The model is trained using supervised learning on artificially created problem instances; this training procedure does not use an existing solver to produce the supervised signal. Finally, the model generalizes well to larger graph sizes and retains reasonable performance even on graphs eight times the original size. Heuristics ; Solver ; Computer science ; Artificial neural network ; Graph ; Random graph ; Artificial intelligence ; Heuristic ; Machine learning ; Theoretical computer science ; Algorithm ; Problem solver Machine Learning in Materials Science ; Advanced Graph Neural Networks ; Topic Modeling
Authors: Mingdi Yu | Yuchi Cui | Jingya Wang | Yiwen Chen | Zhigang Ding | Ying Tao | Javier LLorca | Xiaoqin Zeng
Source: arXiv (Cornell University) (preprint, 2023-01-28)
Field: Materials Science — Biomaterials

Critical resolved shear stresses for slip and twinning in Mg-Y-Ca alloys and their effect on the ductility The deformation mechanisms of an extruded Mg-5Y-0.08Ca (wt. %) alloy were analyzed by means of micropillar compression tests on single crystals along different orientations -- selected to activate specific deformation modes -- as well as slip trace analysis, transmission electron microscopy and transmission Kikuchi diffraction. The polycrystalline alloy presented a remarkable ductility in tension (~32%) and negligible differences in the yield strength between tension and compression. It was found that the presence of Y and Ca in solid solution led to a huge increase in the CRSS for basal slip (29 $\pm$ 5 MPa), pyramidal slip (203 $\pm$ 7 MPa) and tensile twin nucleation (above 148 MPa), while the CRSS for prismatic slip only increases up to 105 $\pm$ 4 MPa. The changes in the CRSS for slip and tensile twinning in Mg-Y-Ca alloys expectedly modify the dominant deformation mechanisms in polycrystals. In particular, tensile twinning is replaced by prismatic slip during compressive deformation along the a-axis. The reduction of twinning (which generally induces strong anisotropy in the plastic deformation in textured alloys), and the activation of prismatic slip (which provides an additional plastic deformation mechanism with limited hardening) were responsible for the large tensile ductility of the alloy. Crystal twinning ; Materials science ; Slip (aerodynamics) ; Ultimate tensile strength ; Deformation mechanism ; Composite material ; Alloy ; Plasticity ; Metallurgy ; Deformation (meteorology) ; Anisotropy ; Microstructure ; Optics ; Thermodynamics Magnesium Alloys: Properties and Applications ; Metal and Thin Film Mechanics ; Aluminum Alloys Composites Properties
Authors: Casey Bloomquist | Melisa Dogan | James C. Harris | Benjamin Herzog | William J. Tenn | Eray S. Aydil | Miguel A. Modestino
Source: ChemRxiv (preprint, 2023-11-01)
Field: Chemistry — Electrochemistry

Understanding the effects of forced and bubble-induced convection in transport-limited organic electrosynthesis Organic electrosynthesis offers a sustainable path to decarbonize the chemical industry by integrating renewable energy into chemical manufacturing. However, achieving the selectivity and energy efficiency required for industrial applications is challenging due to the inherent mass transport limitations. Convection can mitigate mass transport limitations, but its impact on organic electrochemical processes remains poorly understood. We investigate the interplay between mass transport and electrochemical reaction rates under convective flows in the context of the electrosynthesis of adiponitrile, one of the largest organic electrochemical processes in the industry. We use experiments and data-driven predictive models to demonstrate that forced liquid convection and bubble-induced convection produce near-identical mass transport conditions when the corresponding Sherwood numbers—the ratio of convective mass transport to diffusive mass transport—are equal. Moreover, we show that the Faradaic efficiency (i.e., the electrochemical selectivity) scales with the Sherwood number for a given current density and reactant concentration. This scalability enables performance to be predicted irrespective of the convection mode employed to enhance mass transport. Our results provide a deeper understanding of mass transport in organic electrosynthesis and offer guidelines to enable more sustainable chemical manufacturing practices. Electrosynthesis ; Mass transfer ; Damköhler numbers ; Context (archaeology) ; Chemistry ; Sherwood number ; Electrochemistry ; Forced convection ; Convection ; Transport phenomena ; Mass transport ; Mechanics ; Chemical engineering ; Chemical physics ; Process engineering ; Nusselt number ; Electrode ; Reynolds number ; Engineering physics ; Physics ; Chromatography ; Organic chemistry ; Physical chemistry Electrochemical Analysis and Applications ; Electrocatalysts for Energy Conversion ; CO2 Reduction Techniques and Catalysts
Authors: Dmytro Yaremchuk | Ostap Kalyuzhnyi | Jaroslav Ilnytskyi
Source: arXiv (Cornell University) (preprint, 2023-04-14)
Field: Materials Science — Surfaces, Coatings and Films

Modelling thermoresponsive polymer brush by mesoscale computer simulations We consider a functional surface comprising thermoresponsive polymer chains, the material that has found numerous technological and biomedical applications. However, to achieve the required time and length scales for computer modelling of such applications, one is compelled to use coarse-grained mesoscopic modelling approaches. The model used here is based on the previous work [Soto-Figueroa et al., Soft Matter, 8, 1871 (2012)], and it mimics the principal feature of the poly(N-iso-propylacrylamide) (PNIPAM), namely, the rapid change of its hydrophilicity at the lower critical solution temperature (LCST). For the case of an isolated chain, we discuss scaling properties of the radius of gyration, end-to-end distance, various distribution functions, and the density profile of monomers below and above the LCST. For the case of the model thermoresposive brush, we search for the optimum grafting density at which the change in the brush height, upon crossing the LCST, reaches its maximum value. The interpretation of the thermoresponse, in terms of the Alexander-de Gennes blobs and the level of solvation of polymer chains in a brush, is provided. Lower critical solution temperature ; Radius of gyration ; Mesoscopic physics ; Polymer ; Scaling ; Thermoresponsive polymers in chromatography ; Brush ; Materials science ; Chemical physics ; Solvation ; Work (physics) ; Soft matter ; Statistical physics ; Polymer chemistry ; Thermodynamics ; Physics ; Chemistry ; Copolymer ; Phase (matter) ; Physical chemistry ; Molecule ; Mathematics ; Composite material ; Condensed matter physics ; Colloid ; Geometry Polymer Surface Interaction Studies ; Hydrogels: synthesis, properties, applications ; Adhesion, Friction, and Surface Interactions
Authors: Yusuf Adamu | Tajudeen Kolawole Bello | Umar Shehu | Abdullahi Bello | Sagir Adamu | Muhammed Tijani Isa
Source: Research Square (preprint, 2023-05-30)
Field: Materials Science — Polymers and Plastics

Mechanical, Physical and Thermal Properties of Waste Polypropylene/Polystyrene/Natural Rubber (wPP/PS/NR) Blends Abstract Combining two or more polymers as a blend is necessary rather than synthesizing new ones for the balance of polymer properties for end-use applications. This work introduces a sustainable polymer blend (matrix) for high-impact applications, as the accessibility and cost of production of these high-impact polymers keep souring. This was achieved by designing an experiment using design expert v10.0 to account for the number of experimental runs and optimise the polymer blend. Mechanical, dynamic mechanical, and temperature effects were considered on the blended polymer. Sixteen (16) experimental runs were generated with blend ratio as the independent variable and Impact Strength (IS) and Tensile Strength (TS) as the responses. The optimal blend ratio was obtained for wPP, PP and NR as 23, 30 and 47 % respectively. While, the optimum conditions for maximum impact and tensile strengths from the D.E was 241.62 J/m and 118.04 MPa respectively, with a desirability of 0.973. While the validated values obtained were 248.9 J/m; with errors of 2.93 % and 120.14 MPa; with an error of 1.75 % respectively. Thermogravimetry analysis revealed a single peak degradation for sp17, sp18, and sp19 (control samples) while multiple degradation peaks were observed for the blends. It was believed to be a result of different times for degradation of the individual components forming the polymer blend. Also, the T d onset started around 300 o C and the T d offset was around 500 o C for all tested samples. While, the Dynamic Mechanical Analysis (DMA) showed that there was an improvement in the T g and damping factor for sp5 (109 o C, 0.171) as compared to sp17 and sp18 (81.1 o C, 0.089 and 104.3 o C, 0.061), but no improvement was recorded for storage and loss moduli. SEM micrographs showed a good surface morphology for the blend with optimal mechanical and thermal properties. The blend can be utilized for engineering applications, including matrices for body armour, helmets, car bumper, etc. Polypropylene ; Natural rubber ; Polystyrene ; Materials science ; Thermal ; Natural (archaeology) ; Composite material ; Polymer chemistry ; Polymer science ; Polymer ; Physics ; Thermodynamics ; Geology Natural Fiber Reinforced Composites ; Polymer crystallization and properties ; Polymer Nanocomposites and Properties
Authors: V. G. Deı̆buk
Source: Journal of Thermoelectricity (article, 2023-03-25)
Field: Materials Science — Materials Chemistry

Phase stability of thermoelectric ZnSb-SnTe thin films The article theoretically studies the phase stability of thin films of pseudobinary semiconductor alloys ZnSb–SnTe. The obtained T – x phase diagrams made it possible to predict the existence of a wide miscibility gap. Taking into account small internal stresses and the influence of the quartz substrate did not lead to significant changes in the phase diagram depending on the film thickness. It has been shown that spinodal decomposition processes caused by annealing at T = 225 °C in (ZnSb)1-х(SnTe)х alloys at x = 0.27 lead to microstructural evolution with the formation of precipitates of the SnSb metal phase. This fact is in good agreement with the experimental studies of the thin films considered and is the reason for the sharp increase in the power factor to 3383 μWm-1K-1 at 300 °C. The described recrystallization processes are the main mechanism for the high thermoelectric characteristics of this material. Bibl. 20, Fig. 3. Thermoelectric effect ; Materials science ; Thin film ; Thermoelectric materials ; Phase (matter) ; Condensed matter physics ; Engineering physics ; Nanotechnology ; Thermodynamics ; Chemistry ; Physics Advanced Thermoelectric Materials and Devices ; Advanced Semiconductor Detectors and Materials
Authors: Zi‐Kui Liu
Source: arXiv (Cornell University) (preprint, 2023-09-18)
Field: Materials Science — Materials Chemistry

Building Materials Genome from Ground-State Configuration to Engineering Advance Individual phases are commonly considered as the building blocks of materials. However, the accurate theoretical prediction of properties of individual phases remains elusive. The top-down approach by decoding genomic building blocks of individual phases from experimental observations is non-unique. The density functional theory (DFT), as the state-of-the-art solution of quantum mechanics, prescribes the existence of a ground-state configuration at zero K for a given system. It is self-evident that the ground-state configuration alone is insufficient to describe a phase at finite temperatures as symmetry-breaking non-ground-state configurations are excited statistically at temperatures above zero K. Our multi-scale entropy approach (recently terms as Zentropy theory) postulates that the entropy of a phase is composed of the sum of the entropy of each configuration weighted by its probability plus the configurational entropy among all configurations. Consequently, the partition function of each configuration in statistical mechanics needs to be evaluated by its free energy rather than total energy. The combination of the ground- and non-ground-state configurations represents the building blocks of materials and can quantitively predict free energy of individual phases with the free energies of ground- and non-ground-state configurations predicted from DFT, plus all properties derived from free energy of individual phases. Ground state ; Statistical physics ; Entropy (arrow of time) ; Principle of maximum entropy ; Excited state ; Statistical mechanics ; Physics ; Computer science ; Quantum mechanics ; Artificial intelligence Machine Learning in Materials Science
Authors: Antonette Albarracin
Source: SPAMAST Research Journal (article, 2023-01-30)
Field: Chemistry — Analytical Chemistry

Forecasting of Rice Crop Production Using a Recurrent Neural Network Rice holds immense significance in Filipinos' diets, is consumed nearly three times daily, and is a crucial dietary component. Using a recurrent neural network (RNN), this study seeks to develop and evaluate a web application for predicting rice crop production in Davao del Sur. The system enables the Davao del Sur agriculturist to anticipate rice crop production over the next four quarters. The model used in the system was designed to process and analyze sequential data, such as time series, by capturing and retaining long-term dependencies and patterns. The researcher used the rapid application development model for system development. It started with data preprocessing and prototyping, which involved close coordination with end users to collect their feedback for interface enhancements. The model's performance is evaluated using validation loss, training loss, mean squared error (MSE), and R-squared metrics. The model's parameters were fine-tuned by utilizing these metrics, resulting in an improved capability to learn from data and generate accurate forecasts. The web application offers administrators a login feature, providing them with data administration and reporting functionalities. In addition to accessing the forecasting information, users can generate reports to assist with decision-making. The model is trained and validated in testing, and the front-end's functionality is evaluated. The training results indicated the optimal model configuration; the optimal epoch for the model with a batch size of 16 is 200. Artificial neural network ; Production (economics) ; Crop production ; Crop ; Agricultural engineering ; Computer science ; Environmental science ; Agronomy ; Artificial intelligence ; Geography ; Engineering ; Agriculture ; Economics ; Biology Spectroscopy and Chemometric Analyses
Authors: Lesley Spencer | Jake Horder | Sejeong Kim | Milos Toth | Igor Aharonovich
Source: arXiv (Cornell University) (preprint, 2023-09-25)
Field: Materials Science — Materials Chemistry

Monolithic Integration of Single Quantum Emitters in hBN Bullseye Cavities The ability of hexagonal boron nitride to host quantum emitters in the form of deep-level color centers makes it an important material for quantum photonic applications. This work utilizes a monolithic circular Bragg grating device to enhance the collection of single photons with 436 nm wavelength emitted from quantum emitters in hexagonal boron nitride. We observe a 6- fold increase in collected intensity for a single photon emitter coupled to a device compared to an uncoupled emitter, and show exceptional spectral stability at cryogenic temperature. The devices were fabricated using a number of etching methods, beyond standard fluorine-based reactive ion etching, and the quantum emitters were created using a site-specific electron beam irradiation technique. Our work demonstrates the potential of monolithically-integrated systems for deterministically-placed quantum emitters using a variety of fabrication options. Optoelectronics ; Materials science ; Common emitter ; Etching (microfabrication) ; Fabrication ; Photonics ; Photon ; Reactive-ion etching ; Quantum dot ; Nitride ; Optics ; Nanotechnology ; Physics Diamond and Carbon-based Materials Research ; Advanced Fiber Laser Technologies ; Mechanical and Optical Resonators
Authors: Raphael M. Tromer | Isaac M. Félix | Luiz Felipe C. Pereira | M. G. E. da Luz | L. A. Ribeiro Junior | Douglas S. Galvão
Source: arXiv (Cornell University) (preprint, 2023-07-03)
Field: Materials Science — Materials Chemistry

Lattice Thermal Conductivity of 2D Nanomaterials: A Simple Semi-Empirical Approach Extracting reliable information on certain physical properties of materials, like thermal behavior, such as thermal transport, which can be very computationally demanding. Aiming to overcome such difficulties in the particular case of lattice thermal conductivity (LTC) of 2D nanomaterials, we propose a simple, fast, and accurate semi-empirical approach for its calculation.The approach is based on parameterized thermochemical equations and Arrhenius-like fitting procedures, thus avoiding molecular dynamics or \textit{ab initio} protocols, which frequently demand computationally expensive simulations. As proof of concept, we obtain the LTC of some prototypical physical systems, such as graphene (and other 2D carbon allotropes), hexagonal boron nitride (hBN), silicene, germanene, binary, and ternary BNC latices and two examples of the fullerene network family. Our values are in good agreement with other theoretical and experimental estimations, nonetheless being derived in a rather straightforward way, at a fraction of the computational cost. Silicene ; Thermal conductivity ; Ternary operation ; Materials science ; Parameterized complexity ; Graphene ; Ab initio ; Lattice (music) ; Nanomaterials ; Statistical physics ; Chalcogenide ; Binary number ; Nanotechnology ; Computer science ; Physics ; Algorithm ; Mathematics ; Quantum mechanics Thermal properties of materials ; Graphene research and applications ; Fullerene Chemistry and Applications
Authors: Tao Li | Chen Chen | Xingjian Xiao | Xin Ye | Jiacheng Sun | Jitao Ji | Rongtao Yu | Wange Song | Shining Zhu
Source: Research Square (preprint, 2023-07-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Neural network assisted high-spatial-resolution polarimetry with non-interleaved chiral metasurfaces Polarimetry ; Resolution (logic) ; Artificial neural network ; Materials science ; Computer science ; Optics ; Artificial intelligence ; Physics Metamaterials and Metasurfaces Applications ; Optical Polarization and Ellipsometry ; Photoreceptor and optogenetics research
Authors: Youkai Yu | Zhiqin Yuan | Chao Lu
Source:  (preprint, 2023-03-08)
Field: Materials Science — Materials Chemistry

Long-Lasting Chemiluminescence by Aggregation-Induced Emission Surfactant with Ultralow Critical Micelle Concentration The development of green and simple chemiluminescence (CL) systems with intensive and long-lasting emission is highly desirable in lighting and extension of their applications. In this study, it is found that the involvement of aggregation-induced emission (AIE) surfactant could greatly enhance the CL of luminol–H2O2–Co2+ system. The inserted hydrophobic tetraphenylethylene fluorophore in AIE is able to increase the hydrophobicity of alkyl chain and decrease the critical micelle concentration (CMC) of surfactant. The synergistic effect of micelle-improved enrichment and CL resonance energy transfer endows luminol–H2O2–Co2+ system intensive and long-lasting emission under neutral pH conditions (pH 7.4). The visible emission is still observed even after 60 min. Our study has opened a new avenue for exploring green and simple effective CL systems through AIE surfactant with unltralow CMC toward various applications in lighting, optical sensing, and photocatalysis, etc. Chemiluminescence ; Pulmonary surfactant ; Micelle ; Fluorophore ; Critical micelle concentration ; Photochemistry ; Chemistry ; Tetraphenylethylene ; Alkyl ; Luminol ; Aggregation-induced emission ; Chemical engineering ; Organic chemistry ; Fluorescence ; Aqueous solution ; Optics Luminescence and Fluorescent Materials ; Nanoplatforms for cancer theranostics ; Molecular Sensors and Ion Detection