jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shijie Yu | Yue Jiang | Lejian Yu | Huimeng Wang | Liting Pan | Jian Zhang | Yunmao Zhang | Xu Hou
Source: National Science Review (review, 2024-11-23)
Field: Materials Science — Surfaces, Coatings and Films

Liquid–solid composites with confined interface behaviors In the evolving landscape of materials science, the journey from traditional composite materials to liquid-solid composites has marked a significant shift. Composite materials, typically solid state, have long been the cornerstone of many applications due to their structural stability and mechanical properties. However, the emergence of liquid-solid composites has introduced a new paradigm, leveraging the dynamic composite interfaces and fluidic nature of liquids. Recent years have witnessed the rapid development of liquid-solid composites, distinguishing themselves by their defect-free, molecularly smooth surfaces and adaptive features. In this review, we introduce liquid-based confined interface materials, which represent a cutting-edge advancement, integrating confined liquids within solid frameworks at mesoscopic scales. Characterized by their confined competitive multiphase interfacial interactions, these materials offer practical functionalities like anti-fouling, multiphase flow control and drag reduction. We summarize the development of the materials, and showcase important applications based on the controllable motions of confined liquids and solid frameworks. We also discuss their design and preparation and address future challenges and outlooks, such as artificial intelligence, in advancing functionalities. Materials science ; Composite material ; Interface (matter) ; Solid surface ; Chemistry ; Chemical physics ; Wetting Surface Modification and Superhydrophobicity ; Pickering emulsions and particle stabilization ; Nanomaterials and Printing Technologies
Authors: Lamyaa Osama | Hala T. Handal | Sara A. M. El‐Sayed | Emad M. Elzayat | Mostafa Mabrouk
Source: Nanomaterials (article, 2024-06-24)
Field: Materials Science — Materials Chemistry

Fabrication and Optimisation of Alumina Nanoporous Membranes for Drug Delivery Applications: A Comparative Study Neurodegenerative disorders cause most physical and mental disabilities, and therefore require effective treatment. The blood-brain barrier (BBB) prevents drug molecules from crossing from the blood to the brain, making brain drug delivery difficult. Implantable devices could provide sustained and regulated medication to solve this problem. Two electrolytes (0.3 M oxalic acid and 0.3 M sulphuric acid) were used to anodise Al<sub>2</sub>O<sub>3</sub> nanoporous membranes, followed by a third anodisation in concentrated H<sub>2</sub>SO<sub>4</sub> to separate the through-hole membranes from the aluminium substrate. FTIR, AFM, and SEM/EDX were used to characterise the membranes' structure and morphology. The effects of the anodisation time and electrolyte type on the AAO layer pore density, diameter, interpore distance, and thickness were examined. As a model drug for neurodegenerative disorders, donepezil hydrochloride (DHC) was loaded onto thin alumina nanoporous membranes. The DHC release profiles were characterised at two concentrations using a UV-Vis spectrophotometer. Oxalic acid membranes demonstrated an average pore diameter of 39.6-32.5 nm, which was two times larger than sulphuric acid membranes (22.6-19.7 nm). After increasing the anodisation time from 3 to 5 h, all of the membranes showed a reduction in pore diameter that was stable regardless of the electrolyte type or period. Drug release from oxalic acid-fabricated membranes was controlled and sustained for over 2 weeks. Thus, nanoporous membranes as implantable drug delivery systems could improve neurodegenerative disease treatment. Membrane ; Nanoporous ; Oxalic acid ; Materials science ; Drug delivery ; Electrolyte ; Chemical engineering ; Nanotechnology ; Chemistry ; Inorganic chemistry ; Electrode ; Biochemistry Anodic Oxide Films and Nanostructures ; Nanoporous metals and alloys ; Conducting polymers and applications
Authors: Peng Wang | Huanchun Wu | Xiangbing Liu | Chaoliang Xu
Source: Crystals (article, 2024-09-27)
Field: Materials Science — Metals and Alloys

Machine Learning-Assisted Prediction of Stress Corrosion Crack Growth Rate in Stainless Steel Stainless-steel is extensively utilized in the key structural components of the main equipment in the nuclear island of pressurized water reactor nuclear power plants. The operational experience of nuclear power plants demonstrates that stress corrosion is one of the significant factors influencing the long-term safe operation of stainless steel in the high-temperature water of pressurized water reactor nuclear power plants. This study is based on the stress corrosion crack growth rate data of 316SS and 304SS stainless steel in the simulated primary water environment of pressurized water reactor nuclear power plants. Data mining and modeling were conducted using multiple machine learning algorithms, including Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and Gaussian Process Regression (GPR), and the Sharpley Additive explanation (SHAP) method was employed to analyze the interpretability of the model. The results indicate that the stress corrosion crack growth rate prediction model based on XGBoost outperforms other models in all assessment indicators. Compared with empirical equations, XGBoost exhibits high flexibility and excellent data-driven learning capabilities. In the test set, 90% of the prediction errors are within the range of experimental values, with the maximum error multiple being 2.5, which significantly improves the prediction accuracy. Moreover, the distribution of SHAP values is consistent with the theoretical study of the stress corrosion behavior of stainless-steel, effectively reflecting the impact of cold working, temperature, and stress intensity factor on the stress corrosion crack growth rate, thereby proving the reliability of the model’s prediction results. The achievements of this study hold significant reference value and application prospects for the prediction of the stress corrosion behavior of stainless-steel in a high-temperature and high-pressure water environment of pressurized water reactor nuclear power plants. Corrosion ; Materials science ; Stress (linguistics) ; Metallurgy Hydrogen embrittlement and corrosion behaviors in metals ; Non-Destructive Testing Techniques ; Fatigue and fracture mechanics
Authors: Suyi Dai | Min Liang | Haijun Cheng | Chang Yu | Weiguang Li | Fang Lai | Li Ma | Xiongmin Liu
Source: BMC Chemistry (article, 2024-04-29)
Field: Materials Science — Materials Chemistry

Thermal decomposition characteristics of BHT and its peroxide (BHTOOH) 2,6-Di-tert-butyl-4-methylphenol (BHT) is an excellent antioxidant that is easily oxidized to 2,6-di-tert-butyl-4-hydroperoxyl-4-methyl-2,5-cyclohexadienone (BHTOOH). For the safety of BHT production and usage, it is meaningful to study the thermal stability and decomposition properties of BHT and BHTOOH. In this paper, the thermal decomposition properties of BHT and BHTOOH were compared by the mini closed pressure vessel test (MCPVT) and differential scanning calorimetry (DSC). Their kinetics of thermal decomposition were studied using thermogravimetric analysis (TGA). The thermal decomposition products of BHT and BHTOOH were analyzed by gas chromatography-mass spectrometry (GC-MS). The results show that there was no significant change in temperature pressure when BHT was warmed up under a nitrogen atmosphere, indicating that BHT was stable within 400 K. The thermal decomposition reaction of BHTOOH was rapid with an initial reaction temperature of 375.2 K. The initial exothermic temperature (T<sub>i</sub>) and heat release (Q<sub>DSC</sub>) of DSC were 384.9 K and 865.0 J g<sup>-1</sup>, respectively. The apparent activation energies (E<sub>a</sub>) for the thermal decomposition reactions of BHT and BHTOOH calculated by the Kissinger method were 151.8 kJ mol<sup>-1</sup> and 66.07 kJ mol<sup>-1</sup>, respectively. The main decomposition products of BHT were isobutene and 2-tert-butyl-4-methylphenol. The thermal decomposition products of BHTOOH included BHT, 2,6-di-tert-butyl-4-ethylphenol, 3,5-di-tert-butyl-4-hydroxybenzaldehyde, 4,4'-(1,2-ethanediyl) bis [2,6-bis (1,1-dimethylethyl) phenol, etc. Based on the thermal decomposition behavior and products, the reaction pathway has been described. These results indicate that BHT is a potential thermal hazard during production, storage and application. For the safety of the chemical industry, the oxidation of BHT should be avoided. Thermal decomposition ; Thermogravimetric analysis ; Decomposition ; Chemistry ; Differential scanning calorimetry ; Thermal stability ; Hydroperoxyl ; Kinetics ; Nuclear chemistry ; Organic chemistry ; Radical ; Thermodynamics Thermal and Kinetic Analysis ; Polymer crystallization and properties ; Polymer Science and PVC
Authors: Sarah L. Walden | Purushottam Poudel | Chengjun Zou | Katsuya Tanaka | Pallabi Paul | Adriana Szeghalmi | Thomas Siefke | Thomas Pertsch | Felix H. Schacher | Isabelle Staude
Source: ACS Nano (article, 2024-01-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Two-Color Spatially Resolved Tuning of Polymer-Coated Metasurfaces For the realization of truly reconfigurable metasurface technologies, dynamic spatial tuning of the metasurface resonance is required. Here we report the use of organic photoswitches as a means for the light-induced spatial tuning of metasurface resonances. Coating of a dielectric metasurface, hosting high-quality-factor resonances, with a spiropyran (SPA)-containing polymer enabled dynamic resonance tuning up to 4 times the resonance full-width at half-maximum with arbitrary spatial precision. A major benefit of employing photoswitches is the broad toolbox of chromophores available and the unique optical properties of each. In particular, SPA and azobenzene (AZO) photoswitches can both be switched with UV light but exhibit opposite refractive index changes. When applied to the metasurface, SPA induced a red shift in the metasurface resonance with a figure of merit of 97 RIU<sup>-1</sup>, while AZO caused a blue shift in the resonance with an even greater sensitivity of 100 RIU<sup>-1</sup>. Critically, SPA and AZO can be individually recovered with red and blue light, respectively. To exploit this advantage, we coated a dielectric metasurface with spatially offset SPA- and AZO-containing polymers to demonstrate wavelength-dependent, spatially resolved control over the metasurface resonance tuning. Materials science ; Resonance (particle physics) ; Optoelectronics ; Figure of merit ; Dielectric ; Refractive index ; Optics ; Azobenzene ; Wavelength ; Polymer ; Physics Metamaterials and Metasurfaces Applications ; Polydiacetylene-based materials and applications ; Advanced Antenna and Metasurface Technologies
Authors: Nikola Koutná | Lars Hultman | P.H. Mayrhofer | Davide G. Sangiovanni
Source: Materials & Design (preprint, 2024-04-26)
Field: Materials Science — Materials Chemistry

Phase stability and mechanical property trends for MAB phases by high-throughput ab initio calculations MAB phases (MABs) are atomically-thin laminates of ceramic/metallic-like layers, having made a breakthrough in the development of 2D materials. Though offering a vast chemical and phase space, relatively few MABs have been synthesised. To guide experiments, we perform high-throughput ab initio screening of MABs that combine group 4–7 transition metals (M); Al, Si, Ga, Ge, or In (A); and boron (B) focusing on their phase stability trends and mechanical properties. Considering the 1:1:1, 2:1:1, 2:1:2, 3:1:2, 3:1:3, and 3:1:4 M:A:B ratios and 10 phase prototypes, synthesisability of a single-phase compound for each elemental combination is estimated through formation energy spectra of competing dynamically stable MABs. Based on the volumetric proximity of energetically-close phases, we identify systems in which volume-changing deformations may facilitate transformation toughening. Subsequently, chemistry- and phase-structure-related trends in the elastic stiffness and ductility are predicted using elastic-constants-based descriptors. The analysis of directional Cauchy pressures and Young's moduli allows comparing mechanical response parallel and normal to M–B/A layers. The suggested promising MABs include Nb3AlB4, Cr2SiB2, Mn2SiB2 or the already synthesised MoAlB. Materials science ; Ductility (Earth science) ; Ab initio ; Phase (matter) ; Ceramic ; Stiffness ; Ab initio quantum chemistry methods ; Thermodynamics ; Crystallography ; Composite material ; Chemistry ; Physics ; Organic chemistry MXene and MAX Phase Materials ; Advanced ceramic materials synthesis ; Boron and Carbon Nanomaterials Research
Authors: Xiangyu Zhang | Junyi Hu | Huiyu Liu | Tu Sun | Zidi Wang | Yingbo Zhao | Yue‐Biao Zhang | Ping Huai | Yanhang Ma | Shan Jiang
Source: Journal of the American Chemical Society (article, 2024-12-02)
Field: Materials Science — Materials Chemistry

Determining Covalent Organic Framework Structures Using Electron Crystallography and Computational Intelligence The structural characterization of new materials often poses immense challenges, especially when obtaining single-crystal structures is difficult, which is a common difficulty with covalent organic frameworks (COFs). Despite this, understanding the atomic structure is crucial as it provides insights into the arrangement and connectivity of organic building blocks, offering the opportunity to establish the correlation of structure-function relationships and unravel material properties. In this study, we present an approach for determining the structures of COFs, an integration of electron crystallography and computational intelligence (COF+). By applying established chemistry knowledge and employing particle swarm optimization (PSO) for trial structure generation, we overcome existing limitations, thus paving the way for advancements in COF structural determination. We have successfully implemented this technique on four representative COFs, each with unique characteristics. These examples underline the accuracy and efficacy of our approach in addressing the challenges tied to COF structural determination. Furthermore, our approach has revealed new structure candidates with different topologies or interpenetrations that are chemically feasible. This discovery demonstrates the capability of our algorithm in constructing trial COF structures without being influenced by topological factors. Our new approach to COF structure determination represents a significant advancement in the field and opens new avenues for exploring the properties and applications of COF materials. Chemistry ; Crystal structure prediction ; Particle swarm optimization ; Nanotechnology ; Function (biology) ; Crystal structure ; Biochemical engineering ; Computer science ; Machine learning ; Materials science ; Engineering ; Crystallography Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Luminescence and Fluorescent Materials
Authors: Srinivasan Mahendran | Jesús Carrete | Andreas Isacsson | Georg K. H. Madsen | Paul Erhart
Source: The Journal of Physical Chemistry C (article, 2024-01-18)
Field: Materials Science — Materials Chemistry

Quantitative Predictions of the Thermal Conductivity in Transition Metal Dichalcogenides: Impact of Point Defects in MoS<sub>2</sub> and WS<sub>2</sub> Monolayers Transition metal dichalcogenides are investigated for various applications at the nanoscale because of their unique combination of properties and dimensionality. For many of the anticipated applications, heat conduction plays an important role. At the same time, these materials often contain relatively large amounts of point defects. Here, we provide a systematic analysis of the impact of intrinsic and selected extrinsic defects on the lattice thermal conductivity of MoS<sub>2</sub> and WS<sub>2</sub> monolayers. We combine Boltzmann transport theory and Green's function-based <b>T</b>-matrix approach for the calculation of scattering rates. The force constants for the defect configurations are obtained from density functional theory calculations via a regression approach, which allows us to sample a rather large number of defects at a moderate computational cost and to systematically enforce both the translational and rotational acoustic sum rules. The calculated lattice thermal conductivity is in quantitative agreement with the experimental data for heat transport and defect concentrations for both MoS<sub>2</sub> and WS<sub>2</sub>. Crucially, this demonstrates that the strong deviation from a 1/<i>T</i> temperature dependence of the lattice thermal conductivity observed experimentally can be fully explained by the presence of point defects. We furthermore predict the scattering strengths of the intrinsic defects to decrease in the sequence V<sub>Mo</sub> ≈ V<sub>2S</sub><sup>=</sup> > V<sub>2S</sub><sup>⊥</sup> > V<sub>S</sub> > S<sub>ad</sub> in both materials, while the scattering rates for the extrinsic (adatom) defects decrease with increasing mass such that Li<sub>ad</sub> > Na<sub>ad</sub> > K<sub>ad</sub>. Compared with earlier work, we find that both intrinsic and extrinsic adatoms are relatively weak scatterers. We attribute this difference to the treatment of the translational and rotational acoustic sum rules, which, if not enforced, can lead to spurious contributions in the zero-frequency limit. Monolayer ; Transition metal ; Thermal conductivity ; Materials science ; Conductivity ; Nanotechnology ; Chemistry ; Physical chemistry ; Composite material 2D Materials and Applications ; Machine Learning in Materials Science ; MXene and MAX Phase Materials
Authors: Taichi Kurita | Keiji Numata
Source: Physical Chemistry Chemical Physics (review, 2024-01-01)
Field: Materials Science — Biomaterials

The structural and functional impacts of rationally designed cyclic peptides on self-assembly-mediated functionality Compared with their linear counterparts, cyclic peptides, characterized by their unique topologies, offer superior stability and enhanced functionality. In this review article, the rational design of cyclic peptide primary structures and their significant influence on self-assembly processes and functional capabilities are comprehensively reviewed. We emphasize how strategically modifying amino acid sequences and ring sizes critically dictate the formation and properties of peptide nanotubes (PNTs) and complex assemblies, such as rotaxanes. Adjusting the number of amino acid residues and side chains allows researchers to tailor the diameter, surface properties, and functions of PNTs precisely. In addition, we discuss the complex host-guest chemistry of cyclic peptides and their ability to form rotaxanes, highlighting their potential in the development of mechanically interlocked structures with novel functionalities. Moreover, the critical role of computational methods for accurately predicting the solution structures of cyclic peptides is also highlighted, as it enables the design of novel peptides with tailored properties for a range of applications. These insights set the stage for groundbreaking advances in nanotechnology, drug delivery, and materials science, driven by the strategic design of cyclic peptide primary structures. Cyclic peptide ; Self-assembly ; Peptide ; Chemistry ; Nanotechnology ; Materials science ; Biochemistry Supramolecular Self-Assembly in Materials ; Chemical Synthesis and Analysis ; Supramolecular Chemistry and Complexes
Authors: Chun-I Wang | J. Charlie Maier | Nicholas E. Jackson
Source: Chemical Science (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Accessing the electronic structure of liquid crystalline semiconductors with bottom-up electronic coarse-graining Understanding the relationship between multiscale morphology and electronic structure is a grand challenge for semiconducting soft materials. Computational studies aimed at characterizing these relationships require the complex integration of quantum-chemical (QC) calculations, all-atom and coarse-grained (CG) molecular dynamics simulations, and back-mapping approaches. However, these methods pose substantial computational challenges that limit their application to the requisite length scales of soft material morphologies. Here, we demonstrate the bottom-up electronic coarse-graining (ECG) of morphology-dependent electronic structure in the liquid-crystal-forming semiconductor, 2-(4-methoxyphenyl)-7-octyl-benzothienobenzothiophene (BTBT). ECG is applied to construct density functional theory (DFT)-accurate valence band Hamiltonians of the isotropic and smectic liquid crystal (LC) phases using only the CG representation of BTBT. By bypassing the atomistic resolution and its prohibitive computational costs, ECG enables the first calculations of the morphology dependence of the electronic structure of charge carriers across LC phases at the ∼20 nm length scale, with robust statistical sampling. Kinetic Monte Carlo (kMC) simulations reveal a strong morphology dependence on zero-field charge mobility among different LC phases as well as the presence of two-molecule charge carriers that act as traps and hinder charge transport. We leverage these results to further evaluate the feasibility of developing mesoscopic, field-based ECG models in future works. The fully CG approach to electronic property predictions in LC semiconductors opens a new computational direction for designing electronic processes in soft materials at their characteristic length scales. Granularity ; Semiconductor ; Materials science ; Electronic structure ; Top-down and bottom-up design ; Nanotechnology ; Chemical physics ; Computer science ; Optoelectronics ; Chemistry ; Computational chemistry Liquid Crystal Research Advancements ; Quantum Dots Synthesis And Properties ; Block Copolymer Self-Assembly