jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Alireza Aghajamali | Amir Karton
Source: Structural Chemistry (article, 2022-01-22)
Field: Chemistry — Organic Chemistry

Superior performance of the machine-learning GAP force field for fullerene structures Fullerene ; Force field (fiction) ; Chemistry ; Density functional theory ; Field (mathematics) ; Gaussian ; Root mean square ; Computational chemistry ; Band gap ; Nanotechnology ; Statistical physics ; Condensed matter physics ; Materials science ; Physics ; Mathematics ; Quantum mechanics Fullerene Chemistry and Applications ; Machine Learning in Materials Science ; Carbon Nanotubes in Composites
Authors: Jingjing Rao | Zhen Fan | Qicheng Huang | Yongjian Luo | Xingmin Zhang | Haizhong Guo | Xiaobing Yan | Guo Tian | Deyang Chen | Zhipeng Hou | Minghui Qin | Min Zeng | Xubing Lu | Guofu Zhou | Xingsen Gao | Jun‐Ming Liu
Source: Journal of Advanced Dielectrics (article, 2022-05-12)
Field: Materials Science — Materials Chemistry

Experimental search for high-performance ferroelectric tunnel junctions guided by machine learning Ferroelectric tunnel junction (FTJ) has attracted considerable attention for its potential applications in nonvolatile memory and neuromorphic computing. However, the experimental exploration of FTJs with high ON/OFF ratios is a challenging task due to the vast search space comprising of ferroelectric and electrode materials, fabrication methods and conditions and so on. Here, machine learning (ML) is demonstrated to be an effective tool to guide the experimental search of FTJs with high ON/OFF ratios. A dataset consisting of 152 FTJ samples with nine features and one target attribute (i.e., ON/OFF ratio) is established for ML modeling. Among various ML models, the gradient boosting classification model achieves the highest prediction accuracy. Combining the feature importance analysis based on this model with the association rule mining, it is extracted that the utilizations of {graphene/graphite (Gra) (top), LaNiO 3 (LNO) (bottom)} and {Gra (top), Ca[Formula: see text]Ce[Formula: see text]MnO 3 (CCMO) (bottom)} electrode pairs are likely to result in high ON/OFF ratios in FTJs. Moreover, two previously unexplored FTJs: Gra/BaTiO 3 (BTO)/LNO and Gra/BTO/CCMO, are predicted to achieve ON/OFF ratios higher than 1000. Guided by the ML predictions, the Gra/BTO/LNO and Gra/BTO/CCMO FTJs are experimentally fabricated, which unsurprisingly exhibit [Formula: see text]1000 ON/OFF ratios ([Formula: see text]8540 and [Formula: see text]7890, respectively). This study demonstrates a new paradigm of developing high-performance FTJs by using ML. Neuromorphic engineering ; Ferroelectricity ; Materials science ; Artificial intelligence ; Boosting (machine learning) ; Computer science ; Electrode ; Graphene ; Fabrication ; Machine learning ; Nanotechnology ; Algorithm ; Optoelectronics ; Physics ; Artificial neural network ; Dielectric Ferroelectric and Piezoelectric Materials ; Ferroelectric and Negative Capacitance Devices ; Advanced Memory and Neural Computing
Authors: Sushree Jagriti Sahoo | Xin Jing | Phanish Suryanarayana | Andrew J. Medford
Source: The Journal of Physical Chemistry C (article, 2022-01-25)
Field: Materials Science — Materials Chemistry

Ab-Initio Investigation of Finite Size Effects in Rutile Titania Nanoparticles with Semilocal and Nonlocal Density Functionals In this work, we employ hybrid and generalized gradient approximation (GGA) level density functional theory (DFT) calculations to investigate the convergence of surface properties and the electronic gap of rutile titania (TiO2) nanoparticles with particle size. The surface energies and electronic gaps are calculated for cuboidal particles with minimum dimension ranging from 3.7 Å (24 atoms) to 10.3 Å (384 atoms) using a highly parallel real-space DFT code to enable hybrid-level DFT calculations of larger nanoparticles than are typically practical. We deconvolute the geometric and electronic finite size effects in surface energy and evaluate the influence of defects on the electronic gap and density of states (DOS). The electronic finite size effects in surface energy vanish when the minimum length scale of the nanoparticles becomes greater than 10 Å. We show that this length scale is consistent with a computationally efficient numerical analysis of the characteristic length scale of electronic interactions. The surface energy of nanoparticles having a minimum dimension beyond this characteristic length can be approximated using slab calculations that account for the geometric defects. In contrast, the finite size effects on the electronic gap and DOS are highly dependent on the shape and size of these particles. The DOS for cuboidal particles and more realistic particles constructed using the Wulff algorithm reveal that defect states within the electronic gap play a key role in determining the eigenvalue distribution of nanoparticles and the electronic gap does not converge to the bulk limit for the particle sizes investigated. Density functional theory ; Materials science ; Band gap ; Electronic structure ; Hybrid functional ; Ab initio ; Nanoparticle ; Condensed matter physics ; Molecular physics ; Local-density approximation ; Physics ; Nanotechnology ; Quantum mechanics Quantum Dots Synthesis And Properties ; Copper-based nanomaterials and applications ; Chalcogenide Semiconductor Thin Films
Authors: Aditya Sundar | Jianguo Yu | Liang Qi | Mahmut Nedim Cinbiz
Source: International Journal of Hydrogen Energy (article, 2022-08-12)
Field: Materials Science — Materials Chemistry

High temperature stability and transport characteristics of hydrogen in alumina via multiscale computation Thermal diffusivity ; Density functional theory ; Diffusion ; Amorphous solid ; Hydrogen ; Thermodynamics ; Materials science ; Band gap ; Chemistry ; Computational chemistry ; Crystallography ; Physics Machine Learning in Materials Science ; Nuclear Materials and Properties ; Advanced ceramic materials synthesis
Authors: Yan Li | Chao Shi | Lin Li | Guoju Yang | Junyan Li | Jun Xu | Qinfen Gu | Xingxing Wang | Ji Han | Tianjun Zhang | Yi Li | Jihong Yu
Source: National Science Review (article, 2022-05-10)
Field: Chemistry — Inorganic Chemistry

Unraveling templated-regulated distribution of isolated SiO4 tetrahedra in silicoaluminophosphate zeolites with high-throughput computations Silicoaluminophosphate (SAPO) zeolites are well-known catalytic materials because of the mild acidity originating from the isolated SiO<sub>4</sub> tetrahedra in their frameworks. Regulating the distribution of isolated SiO<sub>4</sub> tetrahedra in SAPO zeolites is formidably challenging because SiO<sub>4</sub> tetrahedra tend to agglomerate to form Si islands and the isolated SiO<sub>4</sub> tetrahedra are difficult to determine using conventional characterization techniques. Here we synthesized Si-island-free SAPO-35 zeolites by using <i>N</i>-methylpiperidine as a new template, which exhibited excellent thermal stability compared to conventional SAPO-35 zeolites and a substantially improved methanol-to-olefins catalytic lifetime even comparable to that of commercial SAPO-34 zeolites. More strikingly, with the aid of high-throughput computations on 44 697 structure models combined with various state-of-the-art characterization techniques, for the first time, we reveal that the host-guest interactions between template molecules and SAPO frameworks determine the specific distributions of isolated SiO<sub>4</sub> tetrahedra, which are responsible for the improvement in the chemical properties of zeolites. Our work provides an insight into the template-based regulation of isolated SiO<sub>4</sub> tetrahedra in SAPO zeolites, which opens a new avenue in the discovery of promising zeolite catalysts with optimal SiO<sub>4</sub> distribution. Tetrahedron ; Throughput ; Computation ; Materials science ; Parallel computing ; Chemical engineering ; Chemistry ; Computer science ; Crystallography ; Engineering ; Algorithm ; Operating system Zeolite Catalysis and Synthesis ; Mesoporous Materials and Catalysis ; Catalysis and Oxidation Reactions
Authors: Matthew S. Johnson | Xiaorui Dong | Alon Grinberg Dana | Yunsie Chung | David Farina | Ryan J. Gillis | Mengjie Liu | Nathan W. Yee | Katrín Blöndal | Emily Mazeau | Colin A. Grambow | A. Mark Payne | Kevin Spiekermann | Hao‐Wei Pang | C. Franklin Goldsmith | Richard H. West | William H. Green
Source: ChemRxiv (preprint, 2022-07-22)
Field: Materials Science — Materials Chemistry

The RMG Database for Chemical Property Prediction The RMG-database for chemical property prediction is presented. The RMG-database consists of curated datasets and estimators for accurately predicting parameters necessary for constructing a wide variety of chemical kinetic mechanisms, including thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG-database contains 45 libraries of thermochemical parameters with a combined 4564 entries, a group additivity scheme with nine types of corrections including radical, polycyclic and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural net trained using transfer learning from a set of >130,000 DFT calculations to 10,000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabled values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation the database contains 92 libraries of kinetic parameters containing a combined 21,000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG-database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction and by providing information to check other kinetic parameters against. Thermochemistry ; Estimator ; Additive function ; Computer science ; Database ; Chemistry ; Chemical nomenclature ; Python (programming language) ; Solvation ; Thermodynamics ; Mathematics ; Solvent ; Physical chemistry ; Physics ; Organic chemistry ; Statistics Machine Learning in Materials Science ; Chemistry and Chemical Engineering ; Free Radicals and Antioxidants
Authors: Paulo De Carvalho Gomes | Mike Hardy | Yazmin K. Tagger | Jonathan James Stanley Rickard | Paula M. Mendes | Pola Goldberg Oppenheimer
Source: The Journal of Physical Chemistry C (article, 2022-08-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optimization of Nanosubstrates toward Molecularly Surface-Functionalized Raman Spectroscopy Diagnostic advancements require continuous developments of reliable analytical sensors, which can simultaneously fulfill many criteria, including high sensitivity and specificity for a broad range of target analytes. Incorporating the highly sensitive attributes of surface-enhanced Raman spectroscopy (SERS) combined with highly specific analyte recognition capabilities via molecular surface functionalization could address major challenges in molecular diagnostics and analytical spectroscopy fields. Herein, we have established a controllable molecular surface functionalization process for a series of textured gold surfaces. To create the molecularly surface-functionalized SERS platforms, self-assembled benzyl-terminated and benzoboroxole-terminated monolayers were used to compare which thicknesses and root-mean-square (RMS) roughness of planar gold produced the most sensitive and specific surfaces. Optimal functionalization was identified at 80 ± 8 nm thickness and 7.2 ± 1.0 nm RMS. These exhibited a considerably higher SERS signal (70-fold) and improved sensitivity for polysaccharides when analyzed using principal component analysis (PCA) and self-organizing maps (SOM). These findings lay the procedure for establishing the optimal substrate specifications as an essential prerequisite for future studies aiming at developing the feasibility of molecular imprinting for SERS diagnostic applications and the subsequent delivery of advanced, highly selective, and sensitive sensing devices and analytical platforms. Surface modification ; Materials science ; Raman spectroscopy ; Surface-enhanced Raman spectroscopy ; Nanotechnology ; Analyte ; Monolayer ; Raman scattering ; Chemical engineering ; Chemistry ; Optics ; Chromatography Gold and Silver Nanoparticles Synthesis and Applications ; Biosensors and Analytical Detection ; Advanced biosensing and bioanalysis techniques
Authors: Marcin Wysokowski | Krzysztof Nowacki | Filip Jaworski | Michał Niemczak | Przemysław Bartczak | Mariusz Sandomierski | Adam Piasecki | Maciej Galiński | Teofil Jesionowski
Source: Scientific Reports (article, 2022-05-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ionic liquid-assisted synthesis of chitin–ethylene glycol hydrogels as electrolyte membranes for sustainable electrochemical capacitors A novel chitin-ethylene glycol hybrid gel was prepared as a hydrogel electrolyte for electrical double-layer capacitors (EDLCs) using 1-butyl-3-methylimidazolium acetate [Bmim][Ac] as a chitin solvent. Examination of the morphology and topography of the chitin-EG membrane showed a homogeneous and smooth surface, while the thickness of the membrane obtained was 27 µm. The electrochemical performance of the chitin-EG hydrogel electrolyte was investigated by cyclic voltammetry and galvanostatic charge/discharge measurements. The specific capacitance value of the EDLC with chitin-EG hydrogel electrolyte was found to be 109 F g<sup>-1</sup> in a potential range from 0 to 0.8 V. The tested hydrogel material was electrochemically stable and did not decompose even after 10,000 GCD cycles. Additionally, the EDLC test cell with chitin-EG hydrogel as electrolyte exhibited superior capacitance retention after 10,000 charge/discharge cycles compared with a commercial glass fiber membrane. Electrolyte ; Ethylene glycol ; Ionic liquid ; Materials science ; Membrane ; Cyclic voltammetry ; Chemical engineering ; Electrochemistry ; Chitin ; Self-healing hydrogels ; Solvent ; Capacitance ; Electric double-layer capacitor ; Chitosan ; Polymer chemistry ; Chemistry ; Electrode ; Organic chemistry ; Biochemistry Supercapacitor Materials and Fabrication ; Advanced Sensor and Energy Harvesting Materials ; Conducting polymers and applications
Authors: Yaohui Xu | Zhao Ding
Source: Materials (article, 2022-07-27)
Field: Materials Science — Materials Chemistry

Oxidation-Induced and Hydrothermal-Assisted Template-Free Synthesis of Mesoporous CeO2 for Adsorption of Acid Orange 7 Hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>), an accessible and eco-friendly oxidant, was employed for the template-free hydrothermal synthesis of mesoporous CeO<sub>2</sub> based on a cerium carbonate precursor (Ce<sub>2</sub>(CO<sub>3</sub>)<sub>3</sub>•<i>x</i>H<sub>2</sub>O). Its microstructure and physicochemical properties were characterized by XRD, TEM and N<sub>2</sub> sorption techniques. The formation of the CeO<sub>2</sub> phase with a porous structure was strongly dependent on the presence of H<sub>2</sub>O<sub>2</sub>, while the values of the BET surface area, pore diameter and pore volume of CeO<sub>2</sub> were generally related to the amount of H<sub>2</sub>O<sub>2</sub> in the template-free hydrothermal synthesis. The BET surface area and pore volume of the mesoporous CeO<sub>2</sub> synthesized hydrothermally at 180 °C with 10 mL H<sub>2</sub>O<sub>2</sub> were 112.8 m<sup>2</sup>/g and 0.1436 cm<sup>3</sup>/g, respectively. The adsorption process had basically finished within 30 min, and the maximum adsorption efficiency within 30 min was 99.8% for the mesoporous CeO<sub>2</sub> synthesized hydrothermally at 140 °C with 10 mL, when the initial AO7 concentration was 120 mg/L without pH preadjustment. The experimental data of AO7 adsorption were analyzed using the Langmuir and Freundlich isotherm modes. Moreover, the mesoporous CeO<sub>2</sub> synthesized at 140 °C with 10 mL H<sub>2</sub>O<sub>2</sub> was regenerated in successive adsorption-desorption cycles eight times without significant loss in adsorption capacity, suggesting that the as-synthesized mesoporous CeO<sub>2</sub> in this work was suitable as an adsorbent for the efficient adsorption of AO7 dye from an aqueous solution. Mesoporous material ; Adsorption ; Aqueous solution ; BET theory ; Materials science ; Sorption ; Specific surface area ; Freundlich equation ; Hydrothermal circulation ; Cerium ; Mesoporous silica ; Hydrothermal synthesis ; Hydrogen peroxide ; Langmuir ; Arsenate ; Chemical engineering ; Nuclear chemistry ; Langmuir adsorption model ; Desorption ; Inorganic chemistry ; Chemistry ; Organic chemistry ; Catalysis ; Arsenic Catalytic Processes in Materials Science ; Adsorption and biosorption for pollutant removal ; Nanomaterials for catalytic reactions
Authors: Austin M. Mroz | Audrey M. Davenport | Jasper Sterling | Joshua D. Davis | Christopher H. Hendon
Source: Chemical Science (article, 2022-01-01)
Field: Chemistry — Electrochemistry

An electric field-based approach for quantifying effective volumes and radii of chemically affected space Chemical shape and size play a critical role in chemistry. The van der Waals (vdW) radius, a familiar manifold used to quantify size by assuming overlapping spheres, provides rapid estimates of size in atoms, molecules, and materials. However, the vdW method may be too rigid to describe highly polarized systems and chemical species that stray from spherical atomistic environments. To deal with these exotic chemistries, numerous alternate methods based on electron density have been presented. While each boasts inherent generality, all define the size of a chemical system, in one way or another, by its electron density. Herein, we revisit the longstanding problem of assessing sizes of atoms and molecules, instead through examination of the local electric field produced by them. While conceptually different than nuclei-centered methods like that of van der Waals, the field assesses <i>chemically affected volumes</i>. This approach implicitly accounts for long-range fields in highly polar systems and predicts that cations should affect more space than neutral counterparts. Electric field ; Space (punctuation) ; Field (mathematics) ; Chemistry ; Chemical physics ; Physics ; Aerospace engineering ; Nanotechnology ; Biological system ; Materials science ; Computer science ; Engineering ; Mathematics ; Biology ; Quantum mechanics ; Pure mathematics Electrochemical Analysis and Applications ; Advanced Chemical Sensor Technologies ; Gas Sensing Nanomaterials and Sensors
Authors: Tingwei Li | Peng‐Hu Du | Ling Bai | Qiang Sun | Puru Jena
Source: Physical Review Applied (article, 2022-12-22)
Field: Materials Science — Materials Chemistry

Thermoelectric Figure of Merit of a Superatomic Crystal <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mi>Re</mml:mi><mml:mn>6</mml:mn></mml:msub><mml:msub><mml:mi>Se</mml:mi><mml:mn>8</mml:mn></mml:msub><mml:msub><mml:mrow><mml:mrow><mml:mi mathvariant="normal">I</mml:mi></mml:mrow></mml:mrow><mml:mn>2</mml:mn></mml:msub></mml:math> Monolayer Superatomic materials are newly emerging candidates for high-performance thermoelectric (TE) devices due to their intrinsic ultralow thermal conductivities. However, the low TE power factor becomes a huge obstacle to reaching the required dimensionless figure of merit (ZT) values for practical applications. Here, motivated by the recently synthesized superatomic ${\mathrm{Re}}_{6}{\mathrm{Se}}_{8}{\mathrm{I}}_{2}$ monolayer [He et al. J. Am. Chem. Soc. 144, 74 (2022)], we study its superior TE properties by using density functional theory combined with phonon Boltzmann transport theory and deep potential molecular dynamics. We show that the large mass and anharmonic $\mathrm{Re}---\mathrm{I}$ bonds introduce strong phonon scattering and result in a low lattice thermal conductivity of 1.20 W m${}^{\ensuremath{-}1}$ K${}^{\ensuremath{-}1}$ at 300 K, while the strong and harmonic $\mathrm{Re}---\mathrm{Se}$ network ensures a high TE power factor of 4344 \textmu{}W m${}^{\ensuremath{-}1}$ K${}^{\ensuremath{-}2}$ in the b direction for n-type doping. This is an order of magnitude higher than those of other cluster-based materials. Owing to the low thermal conductivity and high TE power factor, ${\mathrm{Re}}_{6}{\mathrm{Se}}_{8}{\mathrm{I}}_{2}$ exhibits higher ZT values of 1.20 (500 K) and 1.43 (900 K) with n-type doping along the b direction compared with other cluster-based TE materials reported so far. Anharmonicity ; Thermal conductivity ; Figure of merit ; Condensed matter physics ; Phonon scattering ; Type (biology) ; Dimensionless quantity ; Materials science ; Physics ; Thermoelectric materials ; Phonon ; Thermodynamics ; Optics Advanced Thermoelectric Materials and Devices ; 2D Materials and Applications ; Thermal properties of materials
Authors: Ricardo Navar | Giulia Tarantino | Owain T. Beynon | Daniele Padovan | Luca Botti | Emma K. Gibson | Peter P. Wells | Alun Owens | Simon A. Kondrat | Andrew J. Logsdail | Ceri Hammond
Source: Journal of Materials Chemistry A (article, 2022-01-01)
Field: Chemistry — Inorganic Chemistry

Tracking the solid-state incorporation of Sn into the framework of dealuminated zeolite beta, and consequences for catalyst design In situ spectroscopy, kinetic studies and computational simulations are combined to study the synthesis of Sn-Beta by solid state incorporation, revealing which parameters influence successful preparation of the catalyst. Zeolite ; Catalysis ; BETA (programming language) ; Solid-state ; Chemical engineering ; Chemistry ; Materials science ; Physical chemistry ; Computer science ; Organic chemistry ; Engineering Zeolite Catalysis and Synthesis ; Catalysis for Biomass Conversion ; Catalytic Processes in Materials Science