jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: João M. J. M. Ravasco | João Felicidade | Maria V. Pinto | Fábio M. F. Santos | René Campos‐González | Jesús F. Arteaga | Manon Mehraz | Christelle Langevin | Adelaide Fernandes | Ha‐Chi Nguyen | David Y. W. Ng | Jaime A. S. Coelho | Uwe Pischel | Pedro M. P. Góis
Source: JACS Au (article, 2024-11-07)
Field: Materials Science — Materials Chemistry

Data-Driven Discovery of a New Fluorescent BASHY Dye for Bioimaging Fluorescent molecules play a crucial role in biomedicine by facilitating the visualization and tracking of biological processes with sensitivity and specificity. However, tailoring their structure to meet the demands of live cell and <i>in vivo</i> imaging presents a significant challenge due to the intricate interplay of factors governing their structural and photophysical properties. In this study, we explored the potential of using multivariate linear free-energy relationships (mLFER) to optimize a multicomponent fluorescent platform. We prepared a small library of 20 fluorescent boronic-acid-derived salicylidenehydrazone (BASHY) complexes using a versatile reaction protocol and characterized their chemical stability in water-containing media. The obtained data served as input for the development of an mLFER model, enabling the prediction of a new BASHY dye and unraveling previously unknown mechanisms governing the stability of this unique platform of fluorescent dyes. The optimized dye was successfully employed in live cell experiments and in zebrafish larvae. Fluorescence ; Computer science ; Nanotechnology ; Materials science ; Physics ; Optics Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Advanced biosensing and bioanalysis techniques
Authors: Lingji Zhang | Mengke Shi | Shuo Zhang | Feng Yue | Cairong Yang | Yang Meng | Wen Li | Cong Li | Mario Berrettoni | Silvia Zamponi | Yongpeng Ma | Hongzhong Zhang
Source: Catalysts (article, 2024-11-26)
Field: Materials Science — Materials Chemistry

Preparation of Bi2WO6/MXene(Ti3C2Tx) Composite Material and Its Photothermal Catalytic Reduction of CO2 in Air In response to growing concerns about the greenhouse effect, the direct conversion of atmospheric CO2 has become a pivotal research focus. This research utilizes hydrothermal synthesis to develop Bi2WO6/MXene(Ti3C2Tx), which efficiently reduces CO2 directly at the gas–solid interface through photothermal synergy, without requiring additional sacrificial agents or alkaline absorption solutions. The results indicate that the CO formation rate is about 216.9 μmol·g−1h−1. Notably, this system demonstrates exceptional selectivity for reducing CO2 to CO. The outstanding photothermal catalytic efficiency is attributed to the introduction of MXene, which serves as an efficient and economical co-catalyst. The integration of MXene improves the composite material’s specific surface area and pore structure, enhances its CO2 adsorption capacity, and results in the Bi2WO6/MXene hybrid having a shorter charge transfer distance and a larger interface contact area. This ensures superior charge transfer capabilities, ultimately leading to a significant enhancement in the catalytic efficiency of the composite. This study presents a straightforward and highly selective method for capturing and converting atmospheric CO2, offering fresh insights for developing efficient photothermal catalytic materials. Materials science ; Composite number ; Chemical engineering ; Composite material MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques ; 2D Materials and Applications
Authors: Veerupaksh Singla | Qiyuan Zhao | Brett M. Savoie
Source: Digital Discovery (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Machine learning of stability scores from kinetic data The absence of computational methods to predict stressor-specific degradation susceptibilities represents a significant and costly challenge to the introduction of new materials into applications. Stressor ; Stability (learning theory) ; Degradation (telecommunications) ; Computer science ; Kinetic energy ; Machine learning ; Artificial intelligence ; Psychology ; Clinical psychology ; Physics Machine Learning in Materials Science ; Thermal and Kinetic Analysis ; Computational Drug Discovery Methods
Authors: Min Zhou | Dingming Chen | Ying Liu | Haifeng Wang
Source: Nature Communications (article, 2024-10-09)
Field: Materials Science — Materials Chemistry

Stretching vibration driven adiabatic transfer kinetics for photoexcited hole transfer from semiconductor to adsorbate Interfacial hole transfer from a photoexcited semiconductor to surface adsorbates is pivotal for initiating solar-to-chemical energy conversion, yet the atomic-level transfer kinetics remains elusive. Using the methoxy/TiO<sub>2</sub>(110) system as an archetype, here we elucidate the hole transfer mechanism from hole-trapping lattice oxygen to the methoxy adsorbate at gas/solid and liquid/solid interfaces through molecular dynamics simulations and static minimum energy path calculations. Instead of direct nonadiabatic hopping, we uncover an adiabatic migration pathway adapted to local substrate relaxation, driven by a bond-stretching mechanism supported by stronger Ti-O stretching vibrations. Notably, this mechanism persists at the aqueous methoxy/TiO<sub>2</sub>(110) interface, albeit hindered by interfacial water and coadsorbates. Surprisingly, the hole transfer barriers across various photoexcited adsorbate/TiO<sub>2</sub> interfaces correlate more closely with the vertical excitation energies of the adsorbates rather than their redox potentials, indicating an early-type transition-state nature. These insights deepen our understanding of elementary hole transfer kinetics in surface photochemistry. Kinetics ; Semiconductor ; Adiabatic process ; Vibration ; Chemical physics ; Materials science ; Transfer (computing) ; Chemistry ; Physics ; Classical mechanics ; Thermodynamics ; Optoelectronics ; Computer science ; Quantum mechanics Electronic and Structural Properties of Oxides ; Semiconductor materials and devices ; Nanowire Synthesis and Applications
Authors: Mathieu Vidal | Maryam Sadeghiyan Dehaghani | Takeharu Yoshii | Keigo Wakabayashi | Ignacio Cameán | Mathias Barreau | Nolwenn Le Breton | Iann C. Gerber | Pascal Puech | A.K. Boudalis | Thomas Blon | Tobias Placke | Hirotomo Nishihara | Spyridon Zafeiratos | Philippe Serp
Source: The Journal of Physical Chemistry C (article, 2024-10-25)
Field: Materials Science — Materials Chemistry

Probing Prismatic/Basal Surfaces of Carbon Materials upon Graphitization by Gas Adsorption, TPD, and XPS The prismatic and basal plane surfaces of carbon materials dictate most of their anisotropic physicochemical properties. For many applications where interfacial interactions are key, high-temperature treatments are performed to achieve their graphitization. Such treatment changes edge and basal plane configuration, impacting the energetical behavior of the carbon surfaces, particularly for carbon nanomaterials, with consequences for their properties. Therefore, efforts should be devoted to probing the prismatic and basal plane surfaces of such materials to understand their surface properties for the development of high-performance carbon materials. Herein, we investigate the effect of high-temperature graphitization (3073 K) on the structural, textural, chemical, and magnetic properties of graphitic carbon nanomaterials presenting different prismatic/basal surfaces. The evolution of the prismatic/basal surfaces has been probed by nitrogen adsorption, temperature-programmed desorption, and X-ray photoelectron spectroscopy (XPS). Although these three techniques are in agreement for the starting materials, they diverge in the case of materials that have undergone thermal annealing. This is linked in particular to the formation of loops following the heat treatment, which are identified as belonging to the prismatic surface by XPS and modified the N2 adsorptive potentials. Formed small vacancies on closed loops and nonperfect closure of certain loops can contribute to the accumulation of very reactive defects at the loop level. The thermal annealing also has a pronounced influence on the magnetic properties of these materials. Interestingly, we show that a positive correlation exists between the spin density of the annealed graphitic carbons and their prismatic and basal surfaces. X-ray photoelectron spectroscopy ; Materials science ; Adsorption ; Annealing (glass) ; Nanomaterials ; Carbon fibers ; Nanotechnology ; Desorption ; Surface modification ; Chemical engineering ; Composite material ; Chemistry ; Composite number ; Organic chemistry Graphene research and applications ; Advancements in Battery Materials ; Carbon Nanotubes in Composites
Authors: Wei Wu | Mengshan Li | Wu Yan | Lixin Guan
Source: BMC Chemistry (article, 2024-01-30)
Field: Materials Science — Materials Chemistry

Cluster energy prediction based on multiple strategy fusion whale optimization algorithm and light gradient boosting machine The experimental results show that the most stable Au20 cluster structure is a regular tetrahedron with the lowest energy, displaying tight and uniform atom distribution, high geometric symmetry. Compared to other models, the MSFWOA-LightGBM model excels in accuracy and correlation, with MSE, RMSE, and R<sup>2</sup> values of 0.897, 0.947, and 0.879, respectively. Additionally, the MSFWOA-LightGBM model possesses outstanding scalability, offering valuable insights for material design, energy storage, sensing technology, and biomedical imaging, with the potential to drive research and development in these areas. Algorithm ; Computer science ; Cluster analysis ; Artificial intelligence ; Maxima and minima ; Boosting (machine learning) ; Machine learning ; Mathematics Machine Learning in Materials Science ; Nanocluster Synthesis and Applications ; Advanced Nanomaterials in Catalysis
Authors: Rebecca McGonigle | Jodie Glasgow | Catriona M. Houston | Iain Cameron | Christian Homann | Dominic J. Black | Róbert Pál | Lewis E. MacKenzie
Source: ChemRxiv (preprint, 2024-05-02)
Field: Materials Science — Materials Chemistry

Lessons learned in autoclave synthesis of upconversion nanoparticles: unreported variables and safety considerations Autoclaves – vessels for sustaining high temperatures and high pressures – are widely used across chemical and biological sciences, and are one of the more accessible pieces of equipment for synthesis of luminescent upconversion nanoparticles (UCNPs) amongst other nanomaterials. Yet, despite being crucial to nanomaterial synthesis, the details of autoclave reactors used are barely reported in the literature, leaving several key synthesis variables widely unreported, and thereby hampering the reproducibility of many synthesises. In this perspective, we discuss the safety considerations of autoclave reactors and note that autoclaves should only be used if they are (a) purchased from reputable suppliers/manufacturers and (b) have been certified compliant with relevant safety standards. Ultimately, using unsuitable autoclave equipment can pose a severe physical hazard and may breach legal workplace safety requirements. In addition, we highlight a number of parameters in autoclave synthesis that we suggest should be reported as standard in order to maximise the reproducibility of autoclave synthesis experiments. Subsequently, we discuss two case studies where a commercially available high-safety autoclave system was used to synthesise UCNPs. We also provide broader context for the physical and optical properties of UCNPs, their applications, and other UCNP synthesis methods. We hope that this perspective encourages users of autoclave synthesis, whether in nanomaterials or in broader contexts to: (a) adopt and report the use of high-safety autoclaves and (b) report the many experimental variables involved in autoclave use to enhance reproducibility and robustness of nanomaterial synthesis. Autoclave ; Nanomaterials ; Nanotechnology ; Materials science ; Computer science ; Metallurgy Luminescence Properties of Advanced Materials ; Radiation Detection and Scintillator Technologies ; Nuclear materials and radiation effects
Authors: Adrian Xiao Bin Yong | Tianyu Su | Elif Ertekin
Source: Digital Discovery (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Dismai-Bench: benchmarking and designing generative models using disordered materials and interfaces Dismai-Bench benchmarks generative models on datasets of large disordered materials and interfaces, through direct comparisons between training structures and generated structures. Generative grammar ; Computer science ; Interface (matter) ; Point cloud ; Discriminator ; Point (geometry) ; Deep learning ; Generative adversarial network ; Generative model ; Simple (philosophy) ; Artificial intelligence ; Geometry ; Mathematics Machine Learning in Materials Science ; Topic Modeling
Authors: Johannes Sandberg | Thomas Voigtmann | Émilie Devijver | N. Jakse
Source: Machine Learning Science and Technology (article, 2024-04-29)
Field: Materials Science — Materials Chemistry

Feature selection for high-dimensional neural network potentials with the adaptive group lasso Abstract Neural network potentials are a powerful tool for atomistic simulations, allowing to accurately reproduce ab initio potential energy surfaces with computational performance approaching classical force fields. A central component of such potentials is the transformation of atomic positions into a set of atomic features in a most efficient and informative way. In this work, a feature selection method is introduced for high dimensional neural network potentials, based on the adaptive group lasso (AGL) approach. It is shown that the use of an embedded method, taking into account the interplay between features and their action in the estimator, is necessary to optimize the number of features. The method’s efficiency is tested on three different monoatomic systems, including Lennard–Jones as a simple test case, Aluminium as a system characterized by predominantly radial interactions, and Boron as representative of a system with strongly directional components in the interactions. The AGL is compared with unsupervised filter methods and found to perform consistently better in reducing the number of features needed to reproduce the reference simulation data at a similar level of accuracy as the starting feature set. In particular, our results show the importance of taking into account model predictions in feature selection for interatomic potentials. Feature selection ; Lasso (programming language) ; Group (periodic table) ; Feature (linguistics) ; Selection (genetic algorithm) ; Artificial neural network ; Artificial intelligence ; Pattern recognition (psychology) ; Group selection ; Computer science ; Machine learning ; Chemistry Machine Learning in Materials Science ; Thermography and Photoacoustic Techniques ; Neural Networks and Applications
Authors: Souvik Mitra | Clara Zens | Stephan Kupfer | Diddo Diddens
Source: The Journal of Chemical Physics (article, 2024-12-03)
Field: Chemistry — Physical and Theoretical Chemistry

Toward robust electronic coupling predictions in redox-active TEMPO/TEMPO+ systems This research elucidates the intricate nature of electronic coupling in the redox-active (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO), commonly utilized in organic radical batteries. This study employs a combination of classical molecular dynamics and various electronic coupling calculation schemes. Within the context of the generalized Mulliken-Hush method, the electronic couplings are investigated via the complete active space self-consistent field approach, in combination with n-electron valence state perturbation theory, to provide an accurate description of both static and dynamic electron correlation as well as using (time-dependent) density functional theory simulations. Furthermore, the electronic communication between redox-active sites is studied using the cost-efficient density functional theory (DFT)-based frontier molecular orbital (FMO) approach. Our study reveals the dependence of the electronic coupling on the distance and the relative orientation of the redox pairs (TEMPO and TEMPO+). Apart from the expected exponential distance dependence, we found pronounced orientation dependence, with coupling values varying up to 0.2 eV, which is reflected by a substantial basis set dependency of the couplings, in particular at short distances. In addition, our study highlights the limitations of the DFT-based FMO method, in particular at short intermolecular distances between the redox-active sites, which may lead to a mixing of the involved molecular orbitals. This comparison will provide us with the most cost-accuracy-effective method for calculating electronic couplings in TEMPO-TEMPO+ systems. Density functional theory ; Chemistry ; Intermolecular force ; Valence (chemistry) ; Atomic orbital ; Molecular orbital ; Coupling (piping) ; Complete active space ; Electronic structure ; Chemical physics ; Hybrid functional ; Computational chemistry ; Electron ; Molecular physics ; Basis set ; Physics ; Quantum mechanics ; Molecule ; Materials science Photochemistry and Electron Transfer Studies ; Electrochemical Analysis and Applications ; Radical Photochemical Reactions
Authors: Xiangyang Meng | Zhiqiang Ding | Huan Gao | Zhe Ma | Li Pan | Bin Wang | Yue‐Sheng Li
Source: Molecules (article, 2024-05-06)
Field: Chemistry — Organic Chemistry

Chromium Catalysts for Selective Ethylene Oligomerization Featuring Binuclear PNP Ligands A series of novel binuclear PNP ligands based on the cyclohexyldiamine scaffold were synthesized for this study. The experimental results showed that positioning the two PNP sites at the para-positions of the cyclohexyl framework led to a significant enhancement in the catalytic activity for selective tri/tetramerization of ethylene. The PNP/Cr(acac)<sub>3</sub>/MAO(methylaluminoxane) catalytic system exhibited relatively high catalytic activity (up to 3887.7 kg·g<sup>-1</sup>·h<sup>-1</sup>) in selective ethylene oligomerization with a total selectivity of 84.5% for 1-hexene and 1-octene at 40 °C and 50 bar. The relationship between the ligand structure and ethylene oligomerization performance was further explored using density functional theory calculations. Methylaluminoxane ; Ethylene ; Catalysis ; Chemistry ; Selectivity ; Ligand (biochemistry) ; Chromium ; 1-Octene ; Density functional theory ; Stereochemistry ; Combinatorial chemistry ; Polymer chemistry ; Organic chemistry ; Computational chemistry ; Metallocene ; Receptor ; Biochemistry ; Polymer ; Polymerization Organometallic Complex Synthesis and Catalysis ; Synthetic Organic Chemistry Methods ; Catalytic Cross-Coupling Reactions
Authors: Maksim Kamarou | Hongbin Tan | Dmitry Moskovskikh | N. V. Kulinich | Xiaoling Ma | Feihua Yang | Evgenii V. Beletskii | Elena V. Alekseeva | Sergey Yudin | Valentin Romanovski
Source: Engineering Reports (article, 2024-11-18)
Field: Materials Science — Materials Chemistry

High Strength Anhydrite Cement Based on Lime Mud From Water Treatment Process: One Step Synthesis in Water Environment, Characterization and Technological Parameters ABSTRACT In the process of water treatment from surface water sources, lime mud as waste is formed. This waste contains CaO, Ca(OH) 2 , and CaCO 3 . The article proposes a comprehensive method for processing lime mud into high‐strength anhydrite cement. The method involves the interaction of lime mud with waste sulfuric acid from the production of polymer fibers using a structure‐controlled method in the (CaO·Ca(OH) 2 ·CaCO 3 )—H 2 SO 4 —H 2 O system at a temperature of 40°C. X‐ray diffraction analysis showed the presence of CaSO 4 and CaSO 4 ·0.62H 2 O phases with a purity of 99.8%. The structure‐controlled method makes it possible to control the formation and growth of calcium sulfate crystals of the required shape and size, due to which it is possible to obtain anhydrite cement with desired properties. Combined grinding of synthetic anhydrite with activator additives makes it possible to obtain anhydrite cement with a strength of up to 28.5 MPa. Anhydrite ; Lime ; Cement ; Characterization (materials science) ; Process (computing) ; Materials science ; Environmental science ; Metallurgy ; Gypsum ; Computer science ; Nanotechnology Ferroelectric and Piezoelectric Materials ; Magnesium Oxide Properties and Applications ; Pigment Synthesis and Properties
Authors: Xi Liu | Meng Gao | Yunlong Qin | Zhiqiang Xiong | Huizhen Zheng | Itamar Willner | Xiaoming Cai | Ruibin Li
Source: Angewandte Chemie (article, 2024-07-09)
Field: Materials Science — Materials Chemistry

Exploring Nanozymes for Organic Substrates: Building Nano‐organelles Abstract Since the discovery of the first peroxidase nanozyme (Fe 3 O 4 ), numerous nanomaterials have been reported to exhibit intrinsic enzyme‐like activity toward inorganic oxygen species, such as H 2 O 2 , oxygen, and O 2 − . However, the exploration of nanozymes targeting organic compounds holds transformative potential in the realm of industrial synthesis. This review provides a comprehensive overview of the diverse types of nanozymes that catalyze reactions involving organic substrates and discusses their catalytic mechanisms, structure‐activity relationships, and methodological paradigms for discovering new nanozymes. Additionally, we propose a forward‐looking perspective on designing nanozyme formulations to mimic subcellular organelles, such as chloroplasts, termed “nano‐organelles”. Finally, we analyze the challenges encountered in nanozyme synthesis, characterization, nano‐organelle construction and applications while suggesting directions to overcome these obstacles and enhance nanozyme research in the future. Through this review, our goal is to inspire further research efforts and catalyze advancements in the field of nanozymes, fostering new insights and opportunities in chemical synthesis. Nanotechnology ; Chemistry ; Biochemical engineering ; Organelle ; Materials science ; Biochemistry ; Engineering Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Nanoparticles: synthesis and applications
Authors: Fausto Díaz-Sánchez | Miguel A. García‐Castro | Patricia Amador | Jesús A. Arzola-Flores | Ximena Limón-Aguilar
Source: The Journal of Physical Chemistry A (article, 2024-03-06)
Field: Chemistry — Organic Chemistry

Experimental Determination of the Standard Enthalpy of Formation of Trimellitic Acid and Its Prediction by Supervised Learning The standard molar enthalpy of formation for trimellitic acid (TMAc) in the crystalline phase at 298.15 K, Δ<sub>f</sub><i>H</i><sub><i>m</i></sub>°(cr), was calculated experimentally from the enthalpy of combustion through combustion calorimetry experiments. Likewise, the standard molar enthalpy of sublimation was determined from the standard molar enthalpy of fusion and from the standard molar enthalpy of vaporization from differential scanning calorimetry and thermogravimetry, respectively. Subsequently, the standard molar enthalpies of formation in the gas-phase at 298.15 K, Δ<sub>f</sub><i>H</i><sub><i>m</i></sub>°(g), were calculated. The enthalpies of formation for TMAc, hemimellitic, and trimesic acids were predicted using multiple linear regression (MLR) with a nonreplacement evaluation technique. MLR was applied to the data set that allowed estimating these thermochemical properties with an <i>R</i><sup>2</sup> greater than 0.99. This model was used to compare the predicted and experimental results for benzene carboxylic acids. Enthalpy of atomization ; Enthalpy of vaporization ; Standard enthalpy of formation ; Enthalpy ; Chemistry ; Enthalpy of sublimation ; Enthalpy of fusion ; Standard enthalpy of reaction ; Calorimetry ; Sublimation (psychology) ; Thermodynamics ; Differential scanning calorimetry ; Physical chemistry Chemical Thermodynamics and Molecular Structure ; Thermal and Kinetic Analysis ; Phase Equilibria and Thermodynamics