jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Donghyun Lee | Jungwook Choi
Source: Micro and Nano Systems Letters (article, 2023-12-14)
Field: Materials Science — Biomaterials

Unidirectional freeze casting of compressible metallic aerogel composed of freeze-dried cellulose nanofibers and silver nanowires Abstract Metallic aerogels have attracted tremendous interest because of their superior properties, such as low density, high electrical conductivity, and large specific surface area. However, extremely brittle connections in their 3D networks remain a challenge. In this study, compressible aerogels with microporous fiber-like structure consisting of freeze-dried cellulose nanofibers (CNFs) and silver nanowires (AgNWs) were fabricated by unidirectional freeze-casting process. To improve the robustness, elasticity, and deformability of the aerogel, freeze-dried microfiber-structured CNFs assembled with AgNWs were used. The freeze-dried CNF/AgNW-based aerogels exhibited a low density (8.51–13.5 mg/cm 3 ) and high porosity (up to 98.2%). Furthermore, these aerogels demonstrated impressive mechanical properties with high compressive strength (up to 4.85 kPa at 70% strain), elastic modulus (up to 16.3 kPa), and yield strength (up to 2 kPa). Additionally, the aerogels exhibited reversible deformability up to a 10% strain and maintained their durability over 200 cycles of compressive strain at 10%. The fabricated aerogels also showed a low electrical resistivity (&lt; 8.65 mΩ·m) in addition to robust and compressible mechanical properties. These aerogels are expected to be useful in a wide range of applications that require characteristics such as light weight, high compressive strength, high elasticity, and low electrical resistivity. Materials science ; Aerogel ; Composite material ; Nanofiber ; Compressive strength ; Porosity ; Electrical resistivity and conductivity ; Brittleness ; Nanowire ; Elastic modulus ; Nanotechnology Advanced Cellulose Research Studies ; Aerogels and thermal insulation ; Electrospun Nanofibers in Biomedical Applications
Authors: Nicholas Cucciniello | Alessandro R. Mazza | Pinku Roy | Sundar Kunwar | Di Zhang | Henry Y. Feng | Katrina Arsky | Aiping Chen | Q. X. Jia
Source: Materials (article, 2023-10-13)
Field: Materials Science — Materials Chemistry

Anisotropic Properties of Epitaxial Ferroelectric Lead-Free 0.5[Ba(Ti0.8Zr0.2)O3]-0.5(Ba0.7Ca0.3)TiO3 Films As the energy demand is expected to double over the next 30 years, there has been a major initiative towards advancing the technology of both energy harvesting and storage for renewable energy. In this work, we explore a subset class of dielectrics for energy storage since ferroelectrics offer a unique combination of characteristics needed for energy storage devices. We investigate ferroelectric lead-free 0.5[Ba(Ti<sub>0.8</sub>Zr<sub>0.2</sub>)O<sub>3</sub>]-0.5(Ba<sub>0.7</sub>Ca<sub>0.3</sub>)TiO<sub>3</sub> epitaxial thin films with different crystallographic orientations grown by pulsed laser deposition. We focus our attention on the influence of the crystallographic orientation on the microstructure, ferroelectric, and dielectric properties. Our results indicate an enhancement of the polarization and strong anisotropy in the dielectric response for the (001)-oriented film. The enhanced ferroelectric, energy storage, and dielectric properties of the (001)-oriented film is explained by the coexistence of orthorhombic-tetragonal phase, where the disordered local structure is in its free energy minimum. Materials science ; Ferroelectricity ; Dielectric ; Tetragonal crystal system ; Orthorhombic crystal system ; Pulsed laser deposition ; Anisotropy ; Polarization (electrochemistry) ; Thin film ; Optoelectronics ; Nanotechnology ; Crystallography ; Crystal structure ; Optics ; Chemistry Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Microwave Dielectric Ceramics Synthesis
Authors: Pouria Nourian | Collin D. Wick | Andrew J. Peters
Source: Smart Materials and Structures (article, 2023-09-17)
Field: Materials Science — Polymers and Plastics

Effect of crosslinking fraction, hardener functionality and topological quality on stress recovery of thermoset shape memory polymers: a coarse-grained molecular dynamics study Abstract We analyzed the effects of crosslinking fraction and number of functional sites per hardener molecule on the stress recovery and topology of thermoset shape memory polymers (TSMPs) via coarse-grained molecular dynamics simulations. After systematically varying the quality of the crosslinked network by manipulating the number of unique epoxies reacted with each hardener, we found that two fingerprints correlate well with stress recovery of TSMPs. These fingerprints are the fraction of epoxy molecules connected to two distinct hardener molecules, and the fraction of molecules that are part of the largest or main network in the system. Their product can be used as a topological score ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>topo</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> ) to quantify the topological feature of the network. When analyzing stress recovery as a function of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>topo</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , we found a strong correlation between <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>topo</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> and recovery stress. Moreover, we observed that while a higher crosslinking fraction did frequently lead to a higher stress recovery, many exceptions existed. High functionality hardeners tend to exhibit higher stress recovery at similar <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>topo</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> , especially at high (&gt;0.65) <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:msub> <mml:mi>S</mml:mi> <mml:mrow> <mml:mrow> <mml:mtext>topo</mml:mtext> </mml:mrow> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> . These results suggest that increasing the number of functional sites per hardener molecule combined with improving the topology of the network with a method such as semi batch monomer addition can lead to an improvement in the stress recovery of TSMPs. Algorithm ; Mole fraction ; Materials science ; Computer science ; Topology (electrical circuits) ; Physics ; Thermodynamics ; Mathematics Polymer composites and self-healing ; Advanced Polymer Synthesis and Characterization ; Photochromic and Fluorescence Chemistry
Authors: Dagmar Štellerová | Vladimı́r Lukeš | Martin Breza
Source: Molecules (article, 2023-03-25)
Field: Materials Science — Materials Chemistry

How Does Pseudo-Jahn-Teller Effect Induce the Photoprotective Potential of Curcumin? In this paper, the molecular and electronic structure of curcumin is studied. High-symmetric gas-phase tautomers and their deprotonated forms in various symmetry groups are identified. The stability of lower-symmetry structures was explained by using the Pseudo-Jahn-Teller (PJT) effect. This effect leads to stable structures of different symmetries for the neutral enol and keto forms. The presented analysis demonstrated the potential significance of the PJT effect, which may modulate the setting of electronic and vibrational (vibronic) energy levels upon photodynamic processes. The PJT effect may rationalize the photoprotection action and activity of naturally occurring symmetric dyes. Jahn–Teller effect ; Tautomer ; Chemistry ; Photoprotection ; Deprotonation ; Enol ; Curcumin ; Computational chemistry ; Electronic structure ; Symmetry (geometry) ; Photochemistry ; Stereochemistry ; Chemical physics ; Organic chemistry ; Catalysis Porphyrin and Phthalocyanine Chemistry ; Curcumin's Biomedical Applications ; Free Radicals and Antioxidants
Authors: Paolo Inaudi | Ornella Abollino | Monica Argenziano | Mery Malandrino | Caterina Guiot | Stefano Bertinetti | Laura Favilli | Agnese Giacomino
Source: Molecules (article, 2023-11-03)
Field: Chemistry — Electrochemistry

Advancements in Portable Voltammetry: A Promising Approach for Iron Speciation Analysis Iron, a crucial element in our environment, plays a vital role in numerous natural processes. Understanding the presence and concentration of iron in the environment is very important as it impacts various aspects of our planet's health. The on-site detection and speciation of iron are significant for several reasons. In this context, the present work aims to evaluate the applicability of voltammetry for the on-site determination of iron and its possible speciation using a portable voltammetric analyzer. Voltammetry offers the advantage of convenience and cost-effectiveness. For iron (III) determination, the modification of a glassy carbon electrode (GCE) with an antimony-bismuth film (SbBiFE) using the acetate buffer (pH = 4) as a supporting electrolyte was used. The technique adopted was Square Wave Adsoptive Cathodic Stripping Voltammetry (SW-AdCSV), and we used 1-(2-piridylazo)-2-naphthol (PAN) as the iron (III) ligand. Linearity, repeatability, detection limit, and accuracy were determined using synthetic solutions; then, a Standard Reference Material (SRM) of 1643f Trace Elements in Water (iron content: 93.44 ± 0.78 µg L<sup>-1</sup>) was used for validation measurements in the real matrix. the accuracy of this technique was found to be excellent since we obtained a recovery of 103.16%. The procedure was finally applied to real samples (tap, lake, and seawater), and the results obtained were compared via Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). The amount of iron found was 207.8 ± 6.6 µg L<sup>-1</sup> for tap water using voltammetry and 200.9 ± 1.5 µg L<sup>-1</sup> with ICP-OES. For lake water, 171.7 ± 3.8 µg L<sup>-1</sup>, 169.8 ± 4.1 µg L<sup>-1</sup>, and 187.5 ± 5.7 µg L<sup>-1</sup> were found using voltammetry in the lab both on-site and using ICP-OES, respectively. The results obtained demonstrate the excellent applicability of the proposed on-site voltammetric procedure for the determination of iron and its speciation in water. Voltammetry ; Cathodic stripping voltammetry ; Detection limit ; Tap water ; Anodic stripping voltammetry ; Analytical Chemistry (journal) ; Chemistry ; Supporting electrolyte ; Seawater ; Cyclic voltammetry ; Repeatability ; Context (archaeology) ; Electrolyte ; Electrochemistry ; Environmental chemistry ; Electrode ; Chromatography ; Environmental science Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; Water Quality and Pollution Assessment
Authors: Elena Gelžinytė | Simon Wengert | Tamás K. Stenczel | Hendrik H. Heenen | Karsten Reuter | Gábor Cśanyi | Noam Bernstein
Source: arXiv (Cornell University) (preprint, 2023-06-20)
Field: Materials Science — Materials Chemistry

wfl Python Toolkit for Creating Machine Learning Interatomic Potentials and Related Atomistic Simulation Workflows Predictive atomistic simulations are increasingly employed for data intensive high throughput studies that take advantage of constantly growing computational resources. To handle the sheer number of individual calculations that are needed in such studies, workflow management packages for atomistic simulations have been developed for a rapidly growing user base. These packages are predominantly designed to handle computationally heavy ab initio calculations, usually with a focus on data provenance and reproducibility. However, in related simulation communities, e.g. the developers of machine learning interatomic potentials (MLIPs), the computational requirements are somewhat different: the types, sizes, and numbers of computational tasks are more diverse, and therefore require additional ways of parallelization and local or remote execution for optimal efficiency. In this work, we present the atomistic simulation and MLIP fitting workflow management package wfl and Python remote execution package ExPyRe to meet these requirements. With wfl and ExPyRe, versatile Atomic Simulation Environment based workflows that perform diverse procedures can be written. This capability is based on a low-level developer-oriented framework, which can be utilized to construct high level functionality for user-friendly programs. Such high level capabilities to automate machine learning interatomic potential fitting procedures are already incorporated in wfl, which we use to showcase its capabilities in this work. We believe that wfl fills an important niche in several growing simulation communities and will aid the development of efficient custom computational tasks. Python (programming language) ; Workflow ; Computer science ; Interatomic potential ; Computational science ; Distributed computing ; Database ; Operating system ; Molecular dynamics Machine Learning in Materials Science ; Scientific Computing and Data Management ; Advanced Data Storage Technologies
Authors: Siheng Li | Keyang Liu | Jiří Klimeš | Ji Chen
Source: Physical Review Research (article, 2023-04-12)
Field: Materials Science — Materials Chemistry

Understanding the wetting of transition metal dichalcogenides from an <i>ab initio</i> perspective Transition metal dichalcogenides (TMDs) are a class of two-dimensional (2D) materials that have been widely studied for emerging electronic properties. In this paper, we use computational simulations to examine the water adsorption on TMDs systematically and the wetting property of tungsten diselenide ) specifically. We start with density functional theory (DFT) based random phase approximation (RPA), assessing the performance of exchange-correlation functionals and comparing water adsorption on various TMDs. We also perform ab initio molecular dynamics (AIMD) simulations on ${\mathrm{WSe}}_{2}$, from which we find that the distribution of interfacial water is sensitive to the exchange-correlation functional selected and a reasonable choice leads to a diffusive contact layer where water molecules prefer the ``flat'' configuration. Classical molecular dynamics (MD) simulations of water droplets on surfaces using appropriately parameterized water-surface interaction further confirm the dependence of water contact angle on the interaction and the interfacial water structure reproduced by different DFT functionals. Our study highlights the sensitivity of wetting to the water-substrate interaction and provides a starting point for a more accurate theoretical investigation of water-TMD interfaces. Wetting ; Transition metal ; Perspective (graphical) ; Ab initio ; Materials science ; Wetting transition ; Nanotechnology ; Chemistry ; Computer science ; Composite material ; Catalysis ; Organic chemistry 2D Materials and Applications ; Graphene research and applications ; Machine Learning in Materials Science
Authors: Jiaqian Li | Steven E. Kirberger | Yiao Wang | Huarui Cui | Carston R. Wagner | William C. K. Pomerantz
Source: Bioconjugate Chemistry (article, 2023-07-31)
Field: Materials Science — Materials Chemistry

Design of Highly Fluorinated Peptides for Cell-based <sup>19</sup>F NMR The design of imaging agents with high fluorine content is essential for overcoming the challenges associated with signal detection limits in <sup>19</sup>F MRI-based molecular imaging. In addition to perfluorocarbon and fluorinated polymers, fluorinated peptides offer an additional strategy for creating sequence-defined <sup>19</sup>F magnetic resonance imaging (MRI) imaging agents with a high fluorine signal. Our previously reported unstructured trifluoroacetyllysine-based peptides possessed good physiochemical properties and could be imaged at high magnetic field strength. However, the low detection limit motivated further improvements in the fluorine content of the peptides as well as removal of nonspecific cellular interactions. This research characterizes several new highly fluorinated synthetic peptides composed of highly fluorinated amino acids. <sup>19</sup>F NMR analysis of peptides <b>TB-1</b> and <b>TB-9</b> led to highly overlapping, intense fluorine resonances and acceptable aqueous solubility. Flow cytometry analysis and fluorescence microscopy further showed nonspecific binding could be removed in the case of <b>TB-9</b>. As a preliminary experiment toward developing molecular imaging agents, a fluorinated EGFR-targeting peptide (<b>KKK</b><sup><b>FF</b></sup><b>KK-</b><sup><b>β</b></sup><b>A-YHWYGYTPENVI</b>) and an EGFR-targeting protein complex E<sub>1</sub>-DD bioconjugated to <b>TB-9</b> were prepared. Both bioconjugates maintained good <sup>19</sup>F NMR performance in aqueous solution. While the E<sub>1</sub>-DD-based imaging agent will require further engineering, the success of cell-based <sup>19</sup>F NMR of the EGFR-targeting peptide in A431 cells supports the potential use of fluorinated peptides for molecular imaging. Chemistry ; Fluorine-19 NMR ; Peptide ; Fluorine ; Combinatorial chemistry ; Molecular imaging ; Fluorescence ; Aqueous solution ; Nuclear magnetic resonance spectroscopy ; Organic chemistry ; Biochemistry ; In vivo Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Medical Imaging Techniques and Applications
Authors: Bin Wang | Lili Li
Source: INMATEH Agricultural Engineering (article, 2023-12-06)
Field: Chemistry — Analytical Chemistry

DETECTION OF DEFECTS OF CERASUS HUMILIS FRUITS BASED ON HYPERSPECTRAL IMAGING AND CONVOLUTIONAL NEURAL NETWORKS In order to perform highly effective identification of external defects and increase the additional value of Cerasus Humilis fruits, this study used hyperspectral imaging technology to collect information on intact and defective Cerasus Humilis fruits. Based on the full transition spectrum, partial least squares discriminant analysis (PLS-DA) and back propagation neural networks (BPNN) were used to establish a discriminative model. The competitive adaptive reweighted sampling (CARS) was used to extract feature wavelengths, principal component analysis was used for data compression of single band images, BPNN and convolutional neural networks (CNN) were used for defect Cerasus Humilis fruits recognition of principal component images. The results showed that the overall detection accuracy of PLS-DA and BPNN models based on wavelength spectral information were 83.81% and 85.71%, respectively. BPNN was used to establish the calibration model based on the selected characteristic wavelengths by CARS, the accuracy rate was 90.47%. The classified accuracy of CNN model based on principal component images was 93.33%, which was obviously better than that of BPNN model at 83.81%. The research shows that the CNN model was successfully applied to the detection of Cerasus Humilis fruits defects using hyperspectral imaging. This study provides a theoretical basis for the development of fruit grading and sorting equipment. Hyperspectral imaging ; Artificial intelligence ; Pattern recognition (psychology) ; Principal component analysis ; Convolutional neural network ; Discriminative model ; Computer science ; Mathematics ; Linear discriminant analysis ; Artificial neural network Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Remote Sensing and Land Use
Authors: Minh-Quyet Ha | Duong‐Nguyen Nguyen | Viet-Cuong Nguyen | Hiori Kino | Yasunobu Ando | Takashi Miyake | Thierry Denœux | Van‐Nam Huynh | Hieu‐Chi Dam
Source: Journal of Applied Physics (article, 2023-02-06)
Field: Materials Science — Materials Chemistry

Evidence-based data mining method to reveal similarities between materials based on physical mechanisms Measuring the similarity between materials is essential for estimating their properties and revealing the associated physical mechanisms. However, current methods for measuring the similarity between materials rely on theoretically derived descriptors and parameters fitted from experimental or computational data, which are often insufficient and biased. Furthermore, outliers and data generated by multiple mechanisms are usually included in the dataset, making the data-driven approach challenging and mathematically complicated. To overcome such issues, we apply the Dempster–Shafer theory to develop an evidential regression-based similarity measurement (eRSM) method, which can rationally transform data into evidence. It then combines such evidence to conclude the similarities between materials, considering their physical properties. To evaluate the eRSM, we used two material datasets, including 3d transition metal–4f rare-earth binary and quaternary high-entropy alloys with target properties, Curie temperature, and magnetization. Based on the information obtained on the similarities between the materials, a clustering technique is applied to learn the cluster structures of the materials that facilitate the interpretation of the mechanism. The unsupervised learning experiments demonstrate that the obtained similarities are applicable to detect anomalies and appropriately identify groups of materials whose properties correlate differently with their compositions. Furthermore, significant improvements in the accuracies of the predictions for the Curie temperature and magnetization of the quaternary alloys are obtained by introducing the similarities, with the reduction in mean absolute errors of 36% and 18%, respectively. The results show that the eRSM can adequately measure the similarities and dissimilarities between materials in these datasets with respect to mechanisms of the target properties. Outlier ; Similarity (geometry) ; Cluster analysis ; Data mining ; Curie temperature ; Computer science ; Magnetization ; Entropy (arrow of time) ; Artificial intelligence ; Pattern recognition (psychology) ; Physics ; Thermodynamics ; Ferromagnetism ; Condensed matter physics Machine Learning in Materials Science ; Hydrogen embrittlement and corrosion behaviors in metals ; Computational Drug Discovery Methods
Authors: Miles Benardout | Adam Le Gresley | Amr El Shaer | Stephen P. Wren
Source: Preprints.org (preprint, 2023-08-29)
Field: Chemistry — Spectroscopy

Application of fSP3 towards Non-Systemic Drug Discovery Non-systemic oral drugs, which do not get absorbed through the gastrointestinal membrane, are an important group of compounds for targeting diseases residing within the gastrointestinal lumen. However, they require a set of design principles not sufficiently covered by traditional druglikeness metrics, such as Lipinski&amp;rsquo;s Rule of 5. These druglikeness metrics fail to accurately identify true negative outcomes; such is the requirement for novel cheminformatic based approaches for the discovery of non-systemic small molecules. One such example of these newer metrics is the fraction of SP3-hybridised carbon atoms (fSP3) which has shown promising application as an identifier of poor oral-bioavailability. Herein, we discuss the application of fSP3 in the drug discovery process in a number of case studies, including our own work discovering non-systemic fructose scavengers for the treatment of fructose malabsorption. Bioavailability ; Drug ; Drug discovery ; Pharmacology ; Chemistry ; Computer science ; Computational biology ; Medicine ; Biology ; Biochemistry Analytical Chemistry and Chromatography ; Diet and metabolism studies ; Diet, Metabolism, and Disease