jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Huanrong Liang | Yuhang Ma | Huaxin Yi | Jiandong Yao
Source: Materials (review, 2023-11-27)
Field: Materials Science — Materials Chemistry

Emerging Schemes for Advancing 2D Material Photoconductive-Type Photodetectors By virtue of the widely tunable band structure, dangling-bond-free surface, gate electrostatic controllability, excellent flexibility, and high light transmittance, 2D layered materials have shown indisputable application prospects in the field of optoelectronic sensing. However, 2D materials commonly suffer from weak light absorption, limited carrier lifetime, and pronounced interfacial effects, which have led to the necessity for further improvement in the performance of 2D material photodetectors to make them fully competent for the numerous requirements of practical applications. In recent years, researchers have explored multifarious improvement methods for 2D material photodetectors from a variety of perspectives. To promote the further development and innovation of 2D material photodetectors, this review epitomizes the latest research progress in improving the performance of 2D material photodetectors, including improvement in crystalline quality, band engineering, interface passivation, light harvesting enhancement, channel depletion, channel shrinkage, and selective carrier trapping, with the focus on their underlying working mechanisms. In the end, the ongoing challenges in this burgeoning field are underscored, and potential strategies addressing them have been proposed. On the whole, this review sheds light on improving the performance of 2D material photodetectors in the upcoming future. Photodetector ; Materials science ; Optoelectronics ; Passivation ; Controllability ; Nanotechnology ; Engineering physics ; Engineering ; Layer (electronics) 2D Materials and Applications ; MXene and MAX Phase Materials ; Gas Sensing Nanomaterials and Sensors
Authors: Rania Farouq | Yehia Selim
Source: Journal of Polymers and the Environment (article, 2023-01-10)
Field: Chemistry — Organic Chemistry

Functionalized Polyethylene Glycol as a Catalyst for Esterification of Salicylic Acid Abstract In this work, two catalysts based on polyethylene glycol (PEG) containing sulfonic acid group and the −COOH group of citric acid (CA) were synthesized. Characterization of the −SO 3 H functionalized PEG and citric acid functionalized PEG has been carried out using FT–IR. The acidity of PEG–SO 3 H and PEG–CA has been explored to investigate their catalytic efficiency towards eco-friendly production of methyl salicylate via esterification of salicylic acid using methanol as a reactant as well as solvent. Methanol to acid molar ratios of 4:1, 6:1, 8:1, and 10:1 was applied. The sulfonated PEG is found to be a very active solid acid catalyst giving high yields (82%) under the optimized reaction conditions (10:1 M ratio of methanol to acid; reaction temperature, 65 °C; reaction time, 150 min with catalyst loading of 1.5%. In comparison with the catalytic activity of H 2 SO 4, PEG–SO 3 H, and PEG-CA; the PEG–SO 3 H surpassed the catalytic activity of both H 2 SO 4 and PEG–CA. The IEC of PEG–SO 3 H was 4 meq/g. And the maximum water uptake of PEG-SO 3 H was 8.25%. PEG ratio ; Citric acid ; Catalysis ; Polyethylene glycol ; Methanol ; Sulfonic acid ; Salicylic acid ; Nuclear chemistry ; Materials science ; PEG 400 ; Solvent ; Chemistry ; Organic chemistry ; Polymer chemistry ; Biochemistry Chemical Synthesis and Reactions ; Ionic liquids properties and applications ; Catalysis for Biomass Conversion
Authors: Tan-Lien Pham | Woon Ih Choi | Aamir Shafique | Hye Jung Kim | Mun‐Bo Shim | Kyoungmin Min | Won‐Joon Son | Inkook Jang | Dae Sin Kim | Mauro Boero | Carlo Massobrio | Guido Ori | Hyo Sug Lee | Young‐Han Shin
Source: Physical Review Applied (article, 2023-03-01)
Field: Materials Science — Materials Chemistry

Structural-Stability Study of Antiperovskite<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:mi>Na</mml:mi></mml:math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mi/><mml:mn>3</mml:mn></mml:msub></mml:math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:mrow><mml:mi mathvariant="normal">O</mml:mi><mml:mi>Cl</mml:mi></mml:mrow></mml:math>for<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:mi>Na</mml:mi></mml:math>-Rich Solid Electrolyte The structural phase transition of the high-symmetry cubic phase of antiperovskite $\mathrm{Na}$${}_{3}$$\mathrm{O}\mathrm{Cl}$ is investigated by computing the phonon band structures of 14 different polymorphs with distinct types of $\mathrm{O}\mathrm{Na}$${}_{6}$ octahedral tilting. The resulting $P$-$T$ phase diagram shows that, at high temperature and low pressure, the high-symmetry cubic structure with $Pm\overline{3}m$ symmetry is the most stable phase. At low temperature and high pressure, on the other hand, the monoclinic structure with $P{2}_{1}/m$ symmetry becomes the most stable phase. In between those two, there is a region in the phase diagram where the orthorhombic structure with $Bmmb$ symmetry is the most stable phase. To improve upon the quasiharmonic results, we do additional calculations in the framework of the self-consistent phonon (SCP) theory, including lattice anharmonicity by using cubic and quartic interatomic force constants (IFCs). This is particularly important for the high-symmetry cubic phase. We find that by decreasing the temperature, the frequency of the soft phonon at the $M$ and $R$ symmetry points gradually shifts to lower values. From these results, we can infer that a phase transition occurs around 166--195 K upon soft-mode condensation. Due to the proximity of the soft-mode frequencies at both symmetry points $R$ and $M$, we expect a cubic-to-orthorhombic phase transition to be realized via simultaneous condensation of the two octahedral tilting modes. Orthorhombic crystal system ; Phase diagram ; Phase transition ; Octahedron ; Antiperovskite ; Crystallography ; Physics ; Condensed matter physics ; Materials science ; Phase (matter) ; Crystal structure ; Chemistry ; Quantum mechanics ; Nanotechnology ; Nitride Thermal Expansion and Ionic Conductivity ; Advanced Battery Materials and Technologies ; Perovskite Materials and Applications
Authors: Wenxiang Xiao | Yinan Xiong | Yaoxin Li | Zhencheng Chen | Hua Li
Source: Sensors (article, 2023-03-09)
Field: Materials Science — Materials Chemistry

Non-Enzymatically Colorimetric Bilirubin Sensing Based on the Catalytic Structure Disruption of Gold Nanocages As an essential indicator of liver function, bilirubin is of great significance for clinical diagnosis. A non-enzymatic sensor has been established for sensitive bilirubin detection based on the bilirubin oxidation catalyzed by unlabeled gold nanocages (GNCs). GNCs with dual-localized surface plasmon resonance (LSPR) peaks were prepared by a one-pot method. One peak around 500 nm was ascribed to gold nanoparticles (AuNPs), and the other located in the near-infrared region was the typical peak of GNCs. The catalytic oxidation of bilirubin by GNCs was accompanied by the disruption of cage structure, releasing free AuNPs from the nanocage. This transformation changed the dual peak intensities in opposite trend, and made it possible to realize the colorimetric sensing of bilirubin in a ratiometric mode. The absorbance ratios showed good linearity to bilirubin concentrations in the range of 0.20~3.60 μmol/L with a detection limit of 39.35 nM (3σ, <i>n</i> = 3). The sensor exhibited excellent selectivity for bilirubin over other coexisting substances. Bilirubin in real human serum samples was detected with recoveries ranging from 94.5 to 102.6%. The method for bilirubin assay is simple, sensitive and without complex biolabeling. Nanocages ; Bilirubin ; Absorbance ; Detection limit ; Chemistry ; Catalysis ; Bilirubin oxidase ; Selectivity ; Surface plasmon resonance ; Linear range ; Nanoparticle ; Chromatography ; Nanotechnology ; Materials science ; Enzyme ; Organic chemistry Advanced Nanomaterials in Catalysis ; Neonatal Health and Biochemistry ; Advanced biosensing and bioanalysis techniques
Authors: Aditya Koneru | Henry Chan | Sukriti Manna | Troy D. Loeffler | Debdas Dhabal | Andressa A. Bertolazzo | Valeria Molinero | Subramanian K. R. S. Sankaranarayanan
Source: npj Computational Materials (article, 2023-07-18)
Field: Materials Science — Ceramics and Composites

Multi-reward reinforcement learning based development of inter-atomic potential models for silica Abstract Silica is an abundant and technologically attractive material. Due to the structural complexities of silica polymorphs coupled with subtle differences in Si–O bonding characteristics, the development of accurate models to predict the structure, energetics and properties of silica polymorphs remain challenging. Current models for silica range from computationally efficient Buckingham formalisms (BKS, CHIK, Soules) to reactive (ReaxFF) and more recent machine-learned potentials that are flexible but computationally costly. Here, we introduce an improved formalism and parameterization of BKS model via a multireward reinforcement learning (RL) using an experimental training dataset. Our model concurrently captures the structure, energetics, density, equation of state, and elastic constants of quartz (equilibrium) as well as 20 other metastable silica polymorphs. We also assess its ability in capturing amorphous properties and highlight the limitations of the BKS-type functional forms in simultaneously capturing crystal and amorphous properties. We demonstrate ways to improve model flexibility and introduce a flexible formalism, machine-learned ML-BKS, that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential (GAP) in capturing the experimental structure and properties of silica polymorphs and amorphous silica. Amorphous silica ; Metastability ; Rotation formalisms in three dimensions ; Amorphous solid ; Computer science ; Gaussian ; Materials science ; Statistical physics ; Computational chemistry ; Chemistry ; Mathematics ; Physics Glass properties and applications ; High-pressure geophysics and materials ; Material Dynamics and Properties
Authors: Kun Yang | Laigang Hu | Wenhao Wu | Min Hu | Ling Jiang | Daohui Lin | Jian Wu
Source: Research Square (preprint, 2023-11-07)
Field: Chemistry — Inorganic Chemistry

Double-walled Al-based MOF with large microporous specific surface area for trace benzene adsorption Microporous material ; Adsorption ; TRACE (psycholinguistics) ; Benzene ; Materials science ; Chemical engineering ; Surface (topology) ; Specific surface area ; Nanotechnology ; Chemistry ; Physical chemistry ; Organic chemistry ; Composite material ; Catalysis ; Geometry Metal-Organic Frameworks: Synthesis and Applications ; Gas Sensing Nanomaterials and Sensors ; Catalytic Processes in Materials Science
Authors: Daniele Polidoro | Daily Rodríguez‐Padrón | Alvise Perosa | Rafael Luque | Maurizio Selva
Source: Materials (article, 2023-01-06)
Field: Chemistry — Inorganic Chemistry

Chitin-Derived Nanocatalysts for Reductive Amination Reactions Chitin, the second most abundant biopolymer in the planet after cellulose, represents a renewable carbon and nitrogen source. A thrilling opportunity for the valorization of chitin is focused on the preparation of biomass-derived <i>N</i>-doped carbonaceous materials. In this contribution, chitin-derived <i>N</i>-doped carbons were successfully prepared and functionalized with palladium metal nanoparticles. The physicochemical properties of these nanocomposites were investigated following a multi-technique strategy and their catalytic activity in reductive amination reactions was explored. In particular, a biomass-derived platform molecule, namely furfural, was upgraded to valuable bi-cyclic compounds under continuous flow conditions. Chitin ; Reductive amination ; Nanomaterial-based catalyst ; Furfural ; Biopolymer ; Cellulose ; Biomass (ecology) ; Catalysis ; Amination ; Chemical engineering ; Nanocomposite ; Chemistry ; Materials science ; Carbon fibers ; Organic chemistry ; Nanotechnology ; Chitosan ; Composite material ; Polymer ; Composite number Asymmetric Hydrogenation and Catalysis ; Nanomaterials for catalytic reactions ; Carbon dioxide utilization in catalysis
Authors: Jonathan S. Van Buskirk | Joseph D. Kraus | Daniel C. Fredrickson
Source: Chemistry of Materials (article, 2023-04-28)
Field: Materials Science — Materials Chemistry

The Intermetallic Reactivity Database: Compiling Chemical Pressure and Electronic Metrics toward Materials Design and Discovery The advent of high-throughput density functional theory (DFT) calculations has supported the creation of large databases containing the quantitative output necessary for constructing theoretical phase diagrams and predicting physical properties. In this article, we present a complementary resource, the Intermetallic Reactivity Database (IRD), focused on the chemical bonding features of solid-state structures and indicators of potential structural transformations. Each IRD entry augments common features, such as band structures and density of states (DOS) distributions, with chemically motivated information including DFT-Chemical Pressure (CP) schemes and visualizable representations of the atomic charges. Together, these data types enable the rationalization and prediction of potential structural phenomena encountered in intermetallic chemistry, as we illustrate with four examples: the origins of the Y2Ni2Mg structure in terms of CP features of its parent structures, the anticipation of intergrowth phases from the net atomic CPs collected in Al-containing binary phases, the correlation between trends in the CP schemes of CaCu5-type phases and experimentally observed structural variations, and finally, the development of theoretical methodology with the testing of a streamlined method for generating DFT-CP schemes. Altogether, these examples highlight how the IRD supports the creation of models of structural chemistry that extend beyond the bounds of its entries. Intermetallic ; Computer science ; Density functional theory ; Database ; Reactivity (psychology) ; Materials science ; Chemistry ; Computational chemistry Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Rare-earth and actinide compounds
Authors: Mohamed Rabia | Asmaa M. Elsayed | Maha Abdallah Alnuwaiser
Source: Processes (article, 2023-08-07)
Field: Materials Science — Polymers and Plastics

Preparation and Characterization of Polyhedron Mn(III) Oxide/-β-Mn(IV) Oxide/Poly-o-chloroaniline Porous Nanocomposite for Electroanalytical Photon Detection Poly-o-chloroaniline (POCA) and Mn2O3/β-MnO2/POCA porous nanocomposite are both synthesized using oxidative polymerization, with K2S2O8 and KMnO4 as oxidants, respectively. The materials are characterized to confirm their optical, morphological, crystalline, chemical, and elemental properties. The nanocomposite exhibits superior optical properties compared to POCA. The promising optical characteristics make the nanocomposite an attractive candidate for light-sensing applications. Through electrical estimation, the nanocomposite photodetector displays the highest sensitivity between 340 and 440 nm, with Jph (current density) of 0.14 and 0.13 mA cm−2, correspondingly, and an estimated photon number of 7.461021 and 6.93 × 1021 photons/s, respectively. At 340 and 440 nm, the calculated photoresponsivity (R) values are 0.73 and 0.64 mA W−1, respectively, while the estimated detectivity (D) values are 1.64 × 108 and 1.45 × 108 Jones, respectively. These promising results indicate that the fabricated photodetector can soon potentially estimate light wavelengths and photon numbers in various industrial applications. Nanocomposite ; Materials science ; Photodetector ; Polymerization ; Oxide ; Analytical Chemistry (journal) ; Nanotechnology ; Optoelectronics ; Composite material ; Polymer ; Chemistry ; Organic chemistry ; Metallurgy Conducting polymers and applications ; Analytical Chemistry and Sensors ; Gas Sensing Nanomaterials and Sensors
Authors: Yinjie Jiang | Ying Wei | Fei Wu | Zhengxing Huang | Kun Kuang | Zhihua Wang
Source: Proceedings of the AAAI Conference on Artificial Intelligence (article, 2023-06-26)
Field: Materials Science — Materials Chemistry

Learning Chemical Rules of Retrosynthesis with Pre-training Retrosynthesis aided by artificial intelligence has been a very active and bourgeoning area of research, for its critical role in drug discovery as well as material science. Three categories of solutions, i.e., template-based, template-free, and semi-template methods, constitute mainstream solutions to this problem. In this paper, we focus on template-free methods which are known to be less bothered by the template generalization issue and the atom mapping challenge. Among several remaining problems regarding template-free methods, failing to conform to chemical rules is pronounced. To address the issue, we seek for a pre-training solution to empower the pre-trained model with chemical rules encoded. Concretely, we enforce the atom conservation rule via a molecule reconstruction pre-training task, and the reaction rule that dictates reaction centers via a reaction type guided contrastive pre-training task. In our empirical evaluation, the proposed pre-training solution substantially improves the single-step retrosynthesis accuracies in three downstream datasets. Retrosynthetic analysis ; Task (project management) ; Generalization ; Computer science ; Artificial intelligence ; Training (meteorology) ; Salient ; Focus (optics) ; Benchmarking ; Machine learning ; Natural language processing ; Engineering ; Mathematics ; Chemistry ; Systems engineering Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: Leire Villaescusa | Iker Hernández | Laura Azcune | Ainhoa Rudi | José M. Mercero | Aitor Landa | Mikel Oiarbide | Claudio Palomo
Source: The Journal of Organic Chemistry (article, 2023-01-11)
Field: Chemistry — Organic Chemistry

Rigidified Bis(sulfonyl)ethylenes as Effective Michael Acceptors for Asymmetric Catalysis: Application to the Enantioselective Synthesis of Quaternary Hydantoins The catalytic, enantio- and diastereoselective addition of hydantoin surrogates <b>II</b> to "rigidified" vinylidene bis(sulfone) reagents is developed, thus overcoming the inability of commonly employed β-substituted vinylic sulfones to react. Adducts are transformed in enantioenriched 5,5-disubstituted hydantoins through hydrolysis and reductive desulfonylation processes providing new structures for eventual bioassays. Density functional theory studies that rationalize the observed reactivity and stereoselectivity trends are also provided. Enantioselective synthesis ; Sulfonyl ; Sulfone ; Reactivity (psychology) ; Chemistry ; Adduct ; Stereoselectivity ; Hydantoin ; Michael reaction ; Reagent ; Combinatorial chemistry ; Catalysis ; Stereochemistry ; Organic chemistry Asymmetric Synthesis and Catalysis ; Chemical synthesis and alkaloids ; Organic and Inorganic Chemical Reactions
Authors: Vladimir Kondratyev | Marian Dryzhakov | Timur Gimadiev | Dmitriy Slutskiy
Source: Journal of Cheminformatics (article, 2023-02-02)
Field: Materials Science — Materials Chemistry

Generative model based on junction tree variational autoencoder for HOMO value prediction and molecular optimization In this work, we provide further development of the junction tree variational autoencoder (JT VAE) architecture in terms of implementation and application of the internal feature space of the model. Pretraining of JT VAE on a large dataset and further optimization with a regression model led to a latent space that can solve several tasks simultaneously: prediction, generation, and optimization. We use the ZINC database as a source of molecules for the JT VAE pretraining and the QM9 dataset with its HOMO values to show the application case. We evaluate our model on multiple tasks such as property (value) prediction, generation of new molecules with predefined properties, and structure modification toward the property. Across these tasks, our model shows improvements in generation and optimization tasks while preserving the precision of state-of-the-art models. Autoencoder ; Generative model ; Computer science ; Generative grammar ; Value (mathematics) ; Artificial intelligence ; Tree (set theory) ; Machine learning ; Deep learning ; Mathematics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Shiyan Zhu | Chengpeng Zhu | Deng Luo | Xiaoyong Zhang | Kechao Zhou
Source: Metals (article, 2023-01-28)
Field: Materials Science — Materials Chemistry

Development of a Low-Density and High-Strength Titanium Alloy Weight reduction is often considered the primary goal in the development of structure materials. A new Ti-8Al-1Cr-1V-0.5Fe-0.1Si (wt.%) alloy with a low-density and a high-strength was developed in this work. The microstructures and mechanical properties of the alloy were investigated in hot-rolled and solution-aging (STA) treatment conditions. The microstructures of the alloy in both states consist of the spherical αp phase, acicular αs phase, and a small amount of β phase. Attributed to such heterogeneous microstructures, the hot-rolled alloy exhibits an outstanding tensile strength of 1046.1 MPa, a total elongation of ~8.3%, and an impressive low density of 4.23 g/cm3. After heat treatment, the alloy also exhibits a similar strength and ductility. A detailed analysis of the deformation modes shows that the numerous dislocations slippages and deformation twinning in the αp phase are the main reasons for the high ductility, and the acicular αs phase provides the alloy with high strength after heat treatment. This newly developed alloy is a potential material for various structural applications. Acicular ; Materials science ; Alloy ; Microstructure ; Ductility (Earth science) ; Ultimate tensile strength ; Metallurgy ; Titanium alloy ; Deformation (meteorology) ; Phase (matter) ; Crystal twinning ; Elongation ; Composite material Titanium Alloys Microstructure and Properties ; Intermetallics and Advanced Alloy Properties ; Additive Manufacturing Materials and Processes
Authors: Hyun‐Kyung Kim | Aiping Yu | Magda Titirici | Céline Merlet | Yihua Gao | John Wang
Source: APL Materials (article, 2023-07-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Materials challenges for supercapacitors International audience Materials science ; Supercapacitor ; Nanotechnology ; Capacitance ; Electrode ; Physical chemistry Supercapacitor Materials and Fabrication ; Advanced Sensor and Energy Harvesting Materials ; Advanced battery technologies research