jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nguyễn Đức Thuận | Hoang Manh Cuong | Nguyen Hoang Nam | Nguyễn Thị Lan Hương | Hoang Si Hong
Source: RSC Advances (article, 2024-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Morphological analysis of Pd/C nanoparticles using SEM imaging and advanced deep learning In this study, we present a comprehensive approach for the morphological analysis of palladium on carbon (Pd/C) nanoparticles utilizing scanning electron microscopy (SEM) imaging and advanced deep learning techniques. A deep learning detection model based on an attention mechanism was implemented to accurately identify and delineate small nanoparticles within unlabeled SEM images. Following detection, a graph-based network was employed to analyze the structural characteristics of the nanoparticles, while density-based spatial clustering of applications with noise was utilized to cluster the detected nanoparticles, identifying meaningful patterns and distributions. Our results demonstrate the efficacy of the proposed model in detecting nanoparticles with high precision and reliability. Furthermore, the clustering analysis reveals significant insights into the morphological distribution and structural organization of Pd/C nanoparticles, contributing to the understanding of their properties and potential applications. Scanning electron microscope ; Nanoparticle ; Materials science ; Palladium ; Nanotechnology ; Chemical engineering ; Chemistry ; Catalysis ; Composite material ; Engineering ; Organic chemistry Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Machine Learning in Materials Science
Authors: Zhuoying Zhu | Junsoo Park | Hrushikesh Sahasrabuddhe | Alex M. Ganose | Rees Chang | John W. Lawson | Anubhav Jain
Source: npj Computational Materials (article, 2024-11-14)
Field: Materials Science — Materials Chemistry

A high-throughput framework for lattice dynamics Abstract We develop an automated high-throughput workflow for calculating lattice dynamical properties from first principles including those dictated by anharmonicity. The pipeline automatically computes interatomic force constants (IFCs) up to 4th order from perturbed training supercells, and uses the IFCs to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free energy and entropy. It performs phonon renormalization for dynamically unstable compounds to obtain real effective phonon spectra at finite temperatures and calculates the associated free energy corrections. The methods and parameters are chosen to balance computational efficiency and result accuracy, assessed through convergence testing and comparisons with experimental measurements. Deployment of this workflow at a large scale would facilitate materials discovery efforts toward functionalities including thermoelectrics, contact materials, ferroelectrics, aerospace components, as well as general phase diagram construction. Anharmonicity ; Workflow ; Thermoelectric materials ; Statistical physics ; Phonon ; Computer science ; Renormalization ; Computational science ; Lattice (music) ; Thermal conductivity ; Materials science ; Physics ; Condensed matter physics ; Thermodynamics ; Quantum mechanics Machine Learning in Materials Science ; Thermal properties of materials ; Advanced Thermoelectric Materials and Devices
Authors: Kedir Seid Mohammed | Minaleshewa Atlabachew | Biniyam Abdu | Ali Ahmed Desalew
Source: Scientific Reports (article, 2024-12-30)
Field: Materials Science — Biomaterials

A nanocellulose from sugarcane bagasse as a template for nickel oxide nanoparticles for removal of organic dyes from aqueous solution The aquatic ecosystem is negatively impacted by organic dye contamination, which is now one of the factors leading to environmental pollution. The present investigation involved the synthesis of nanocellulose (NC) and nanocellulose modified with NiO (NC/NiO) composite using acid hydrolysis and a one-step precipitation technique for NC and NiO, respectively. Malachite green (MG) dye was catalytically removed from an aqueous solution using the two products, which were mechanically homogenized. The produced materials were examined using different characterization techniques, like FTIR, BET, Uv-vis, XRD, SEM-EDX, and TGA. The characterization findings showed the homogeneous distribution of NiO on the NC. With MG dye serving as the model dye, an experiment was conducted to determine the catalyst's catalytic removal ability. The catalytic degradation experiments validated the significance of NiO and the high catalytic activities of the synthesized NC/NiO composite toward the breakdown of MG dye. The kinetic study of catalytic malachite green (MG) dye removal is well-described by the pseudo-first-order kinetic model. After five reuse cycles, high removal efficiency was noted, demonstrating the composite's remarkable stability and reusability. As a result, it was determined that the NC/NiO composite was a suitable catalyst for the degradation of a dye (MG) from the aqueous solution in the presence of H<sub>2</sub>O<sub>2</sub>, with an apparent rate constant, kapp, greater than 0.519 min<sup>-1</sup> and a catalytic efficiency of material by 10 mg catalyst was higher than 99% within 11 min at 48℃. Nanocellulose ; Bagasse ; Aqueous solution ; Nickel oxide ; Nickel ; Nanoparticle ; Materials science ; Chemical engineering ; Nanotechnology ; Chemistry ; Nuclear chemistry ; Cellulose ; Pulp and paper industry ; Organic chemistry ; Metallurgy Advanced Cellulose Research Studies ; Nanomaterials for catalytic reactions
Authors: Sarah Elhajj | Samer Gozem
Source: Journal of Chemical Theory and Computation (article, 2024-07-06)
Field: Chemistry — Organic Chemistry

First and Second Reductions in an Aprotic Solvent: Comparing Computational and Experimental One-Electron Reduction Potentials for 345 Quinones Using reference reduction potentials of quinones recently measured relative to the saturated calomel electrode (SCE) in N,N-dimethylformamide (DMF), we benchmark absolute one-electron reduction potentials computed for 345 Q/Q<sup>•-</sup> and 265 Q<sup>•-</sup>/Q<sup>2-</sup> half-reactions using adiabatic electron affinities computed with density functional theory and solvation energies computed with four continuum solvation models: IEF-PCM, C-PCM, COSMO, and SM12. Regression analyses indicate a strong linear correlation between experimental and absolute computed Q/Q<sup>•-</sup> reduction potentials with Pearson's correlation coefficient (<i>r</i>) between 0.95 and 0.96 and the mean absolute error (MAE) relative to the linear fit between 83.29 and 89.51 mV for different solvation methods when the slope of the regression is constrained to 1. The same analysis for Q<sup>•-</sup>/Q<sup>2-</sup> gave a linear regression with <i>r</i> between 0.74 and 0.90 and MAE between 95.87 and 144.53 mV, respectively. The y-intercept values obtained from the linear regressions are in good agreement with the range of absolute reduction potentials reported in the literature for the SCE but reveal several sources of systematic error. The y-intercepts from Q<sup>•-</sup>/Q<sup>2-</sup> calculations are lower than those from Q/Q<sup>•-</sup> by around 320-410 mV for IEF-PCM, C-PCM, and SM12 compared to 210 mV for COSMO. Systematic errors also arise between molecules having different ring sizes (benzoquinones, naphthoquinones, and anthraquinones) and different substituents (titratable vs nontitratable). SCF convergence issues were found to be a source of random error that was slightly reduced by directly optimizing the solute structure in the continuum solvent reaction field. While SM12 MAEs were lower than those of the other solvation models for Q/Q<sup>•-</sup>, SM12 had larger MAEs for Q<sup>•-</sup>/Q<sup>2-</sup> pointing to a larger error when describing multiply charged anions in DMF. Altogether, the results highlight the advantages of, and further need for, testing computational methods using a large experimental data set that is not skewed (e.g., having more titratable than nontitratable substituents on different parent groups or vice versa) to help further distinguish between sources of random and systematic errors in the calculations. Solvation ; Chemistry ; Linear regression ; Approximation error ; Thermodynamics ; Computational chemistry ; Analytical Chemistry (journal) ; Mathematics ; Molecule ; Statistics ; Physics ; Organic chemistry Free Radicals and Antioxidants ; Electrochemical Analysis and Applications ; Photochemistry and Electron Transfer Studies
Authors: Micheal Arockiaraj | J. Celin Fiona | Jessie Abraham | Sandi Klavžar | K. Balasubramanian
Source: Heliyon (article, 2024-01-21)
Field: Materials Science — Biomaterials

Guanidinium and hydrogen carbonate rosette layers: Distance and degree topological indices, Szeged-type indices, entropies, and NMR spectral patterns Supramolecular chemistry explores non-covalent interactions between molecules, and it has facilitated the design of functional materials and understanding of molecular self-assembly processes. We investigate a captivating class of supramolecular structures, the guanidinium and hydrogen carbonate rosette layers. These rosette layers are composed of guanidinium cations and carbonate anions, exhibiting intricate hydrogen-bonding networks that lead to their unique structural properties. Topological and entropy indices unveil the connectivity and complexity of the structures, providing valuable insights for diverse applications. We have developed the cut method technique to deconstruct the guanidinium and hydrogen carbonate rosette layers into smaller components and obtain the distance, Szeged-type and entropy measures. Subsequently, we conducted a comparative analysis between topological indices and entropies which contributes to a deeper understanding of the structural complexity of these intriguing supramolecular systems. We have derived the degree based topological indices and entropies of the underlying rosette layers. Furthermore, our computations reveal several isentropic structures associated with degree and entropy indices. We have employed distance vector sequence-based graph theoretical techniques in conjunction with symmetry-based combinatorial methods to enumerate and construct the various NMR spectral patterns which are demonstrated to contrast the isomers and networks of the rosettes. Supramolecular chemistry ; Hydrogen bond ; Rosette (schizont appearance) ; Entropy (arrow of time) ; Topology (electrical circuits) ; Chemistry ; Molecule ; Chemical physics ; Crystallography ; Materials science ; Mathematics ; Physics ; Combinatorics ; Thermodynamics ; Biology ; Organic chemistry Supramolecular Self-Assembly in Materials ; Computational Drug Discovery Methods ; Graph theory and applications
Authors: Bita Baghai | Sepideh Ketabi
Source: RSC Advances (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Hydrogen storage efficiency of Fe doped carbon nanotubes: molecular simulation study Given that adsorption is widely regarded as a favorable technique for hydrogen storage, it is appropriate to pursue the development of suitable adsorbent materials for industrial storage. This study aimed to assess the potential of Fe-doped carbon nanotubes (FeCNT) as a remarkable material for hydrogen storage. The structures of pure and Fe-doped CNTs were optimized based on quantum mechanical calculations using density functional theory (DFT) with the Perdew-Burke-Ernzerhof (PBE) method. To gain a comprehensive understanding of the adsorption behavior, Monte Carlo simulation was employed to investigate the adsorption of hydrogen molecules on FeCNT. The study specifically examined the impact of temperature, pressure, and hydrogen mole percentage on the adsorption capacity of FeCNT. The findings indicated that the uptake of hydrogen increased as the pressure increased, and when the pressure exceeded 5 MPa, FeCNT reached a state of near saturation. At room temperature and pressures of 1 and 5 MPa, the hydrogen capacities of FeCNT were determined to be 1.53 and 6.92 wt%, respectively. The radial distribution function diagrams confirmed the formation of a one-layer adsorption phase at pressures below 5 MPa. A comparison of the temperature dependence of hydrogen adsorption between FeCNT and pure CNT confirmed the effectiveness of Fe doping in hydrogen storage up to room temperature. FeCNT exhibited a greater reduction in initial hydrogen capacity at temperatures above room temperature. To evaluate the safety of the system, the use of N<sub>2</sub> as a dilution agent was investigated by examining the hydrogen uptake of FeCNT from pure and H<sub>2</sub>/N<sub>2</sub> mixtures at 300 K. The results showed that the addition of N<sub>2</sub> to the environment had no significant effect on FeCNT hydrogen storage at pressures below 4 MPa. Furthermore, the study of H<sub>2</sub> selectivity from the H<sub>2</sub>/N<sub>2</sub> mixture indicated that FeCNT demonstrated a preference for adsorbing H<sub>2</sub> over a wide range of bulk mole fractions at pressures of 4 and 5 MPa, suggesting that these pressures could be considered optimal. Under these conditions, Fe doping can offer an efficient and selective adsorption surface for hydrogen storage. Adsorption ; Hydrogen storage ; Carbon nanotube ; Hydrogen ; Doping ; Chemical engineering ; Materials science ; Carbon fibers ; Hydrogen molecule ; Cryo-adsorption ; Nanotechnology ; Chemistry ; Composite material ; Organic chemistry ; Optoelectronics Hydrogen Storage and Materials ; Ammonia Synthesis and Nitrogen Reduction ; Graphene research and applications
Authors: Manuel A. Treto‐Suárez | Yoan Hidalgo‐Rosa | Mario Saavedra‐Torres | Bryan D. Koivisto | Karel Mena Ulecia | Dayán Páez-Hernández | Ximena Zárate | Eduardo Schott
Source: Dalton Transactions (article, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Tunable optical properties of isoreticular UiO-67 MOFs for photocatalysis: a theoretical study A theoretical study of the reported photocatalytic systems based on Zr-based MOF (UiO-67) with biphenyl-4,4'-dicarboxylic acid (bpdc) and 2,2'-bipyridine-5,5'-dicarboxylic acid (bpydc) as linkers was performed. Quantum chemical calculations were carried out to understand the optical properties of the materials and to facilitate the rational design of new UiO-67 derivatives with potentially improved features as photocatalysts under ambient conditions. Hence, the effect of the structural modifications on the optical properties was studied considering different designs based on the nature of the linkers: in 1 only the bpdc linker was considered, or the mixture 1 : 1 between bpdc and bpydc linkers (labeled as 1A). Also, substituents R, -NH<sub>2</sub>, and -SH, were included in the 1A MOF only over the bpdc linker (labeled as 1A-bpdc-R) and on both bpdc and bpydc linkers (labeled as 1A-R). Thus a family of six isoreticular UiO-67 derivatives was theoretically characterized using Density Functional Theory (DFT) calculations on the ground singlet (S<sub>0</sub>) and first excited states (singlet and triplet) using Time-Dependent Density Functional Theory (TD-DFT), multiconfigurational post-Hartree-Fock method <i>via</i> Complete Active Space Self-Consistent Field (CASSCF). In addition, the use of periodic DFT calculations suggest that the energy transfer (ET) channel between bpdc and bpydc linkers might generate more luminescence quenching of 1A when compare to 1. Besides, the results suggest that the 1A-R (R: -SH and NH<sub>2</sub>) can be used under ambient conditions; however, the ET exhibited by 1A, cannot take place in the same magnitude in these systems. These ET can favor the photocatalytic reduction of a potential metal ion, that can coordinate with the bpydc ligand, <i>via</i> LMCT transition. Consequently, the MOF might be photocatalytically active against molecules of interest (such as H<sub>2</sub>, N<sub>2</sub>, CO<sub>2</sub>, among others) with photo-reduced metal ions. These theoretical results serve as a useful tool to guide experimental efforts in the design of new photocatalytic MOF-based systems. Photocatalysis ; Substituent ; Chemistry ; Nanotechnology ; Materials science ; Catalysis ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Gas Sensing Nanomaterials and Sensors ; Advanced Photocatalysis Techniques
Authors: Karina Hemmer | Hanna L. B. Boström | Simon Krause | Bettina V. Lotsch | Roland A. Fischer
Source: Communications Materials (article, 2024-12-10)
Field: Chemistry — Inorganic Chemistry

Strategies to achieve reproducible synthesis of phase-pure Zr-porphyrin metal-organic frameworks Porphyrin-based metal-organic frameworks (MOFs) are gaining traction for various applications due to their sorption, optoelectronic and catalytic properties. MOFs with Zr-based nodes constitute a particularly robust and versatile class of MOFs in which incorporation of metals into the porphyrin core allows further tuning of their physico-chemical properties. However, significant challenges regarding the phase-pure synthesis of Zr-porphyrin MOFs have slowed down progress in the field. Synthetic challenges in targeted phase formation originate from the densely populated phase space, due to energetically similar framework topologies accessible from the same building blocks, but also from the lack of detailed synthetic information. This Perspective discusses different synthetic approaches and detailed synthesis investigations to gain a deeper understanding while providing strategies towards suitable conditions to access phase-pure Zr-porphyrin MOFs. Transparent data reporting and holistic consideration of synthetic factors may allow for better control of these aspects. This is crucial for the establishment of structure–property relationships in such materials and will facilitate the realisation of their application potential. Synthesizing phase-pure zirconium-porphyrin metal-organic frameworks is challenging. This Perspective discusses different synthetic approaches and investigations to guide conditions to achieve phase-pure zirconium-porphyrin metal-organic frameworks. Metal-organic framework ; Porphyrin ; Materials science ; Phase (matter) ; Zirconium ; Nanotechnology ; Chemical engineering ; Chemistry ; Photochemistry ; Metallurgy ; Organic chemistry ; Engineering ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Membrane Separation and Gas Transport
Authors: Christian Tantardini | Hayk Zakaryan | Zhongkang Han | Tariq Altalhi | Sergey V. Levchenko | Alexander G. Kvashnin | Boris I. Yakobson
Source: Journal of Computational Science (article, 2024-08-06)
Field: Materials Science — Materials Chemistry

Material hardness descriptor derived by symbolic regression Hardness is a materials’ property with implications in several industrial fields, including oil and gas, manufacturing, and others. However, the relationship between this macroscale property and atomic (i.e., microscale) properties is unknown and in the last decade several models have unsuccessfully tried to correlate them in a wide range of chemical space. The understanding of such relationship is of fundamental importance for discovery of harder materials with specific characteristics to be employed in a wide range of fields. In this work, we have found a physical descriptor for Vickers hardness using a symbolic-regression artificial-intelligence approach based on compressed sensing. SISSO (Sure Independence Screening plus Sparsifying Operator) is an artificial-intelligence algorithm used for discovering simple and interpretable predictive models. It performs feature selection from up to billions of candidates obtained from several primary features by applying a set of mathematical operators. In our work the primary features are obtained from atomistic simulations for 61 materials. The resulting sparse SISSO model accurately describes the target property (i.e., experimental values of hardness) with minimal complexity. We have considered the experimental values of hardness for binary, ternary, and quaternary transition-metal borides, carbides, nitrides, carbonitrides, carboborides, and boronitrides. The found descriptor is a non-linear function of the microscopic properties, with the most significant contribution being from a combination of Voigt-averaged bulk modulus, Poisson’s ratio, and Reuss-averaged shear modulus. Results of high-throughput screening of 635 candidate materials using the found descriptor suggest the enhancement of material’s hardness through mixing with harder yet metastable structures (e.g., metastable VN, TaN, ReN2, Cr3N4, and ZrB6 all exhibit high hardness). Ternary operation ; Materials science ; Probabilistic logic ; Property (philosophy) ; Bulk modulus ; Vickers hardness test ; Binary number ; Computer science ; Statistical physics ; Mathematics ; Artificial intelligence ; Microstructure ; Composite material ; Physics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Boron and Carbon Nanomaterials Research
Authors: David Moss
Source: arXiv (Cornell University) (preprint, 2024-06-16)
Field: Materials Science — Materials Chemistry

Large and layer dependent nonlinear optical absorption of MXene 2D thin films As a rapidly expanding family of two dimensional (2D) materials, MXenes have recently gained considerable attention due to their appealing properties. Here, by developing a solution based coating method that enables transfer free and layer by layer film coating, we investigate the layer dependent nonlinear optical absorption of Ti3C2Tx films, an important member of the MXene family. By using the Zscan technique, we characterize the nonlinear absorption of the prepared MXene films consisting of different numbers of monolayers. The results show that there is a strong and layer dependent nonlinear absorption behavior, transitioning from revisable saturable absorption (RSA) to saturable absorption (SA) as the layer number increases from 5 to 30. Notably, the nonlinear absorption coefficient beta varies significantly within this range, changing from 7.13 x 100 cm/GW to -2.69 100 cm/GW. We also characterize the power dependent nonlinear absorption of the MXene films at various incident laser intensities, and a decreasing trend in beta is observed for increasing laser intensity. These results reveal the intriguing layer dependent nonlinear optical properties of 2D MXene films, highlighting their versatility and potential for implementing high-performance nonlinear photonic devices. Nonlinear optical ; Materials science ; Layer (electronics) ; Absorption (acoustics) ; Nonlinear system ; Optoelectronics ; Thin film ; Layer by layer ; Optics ; Nanotechnology ; Composite material ; Physics 2D Materials and Applications ; Plasmonic and Surface Plasmon Research ; Nonlinear Optical Materials Studies