jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Aji Alexander | Michele Reticcioli | Llorenç Albons | Jesús Redondo | Marco Corrias | Igor Píš | Zhichang Wang | Viktor Johánek | Josef Mysliveček | Cesare Franchini | Dominik Wrana | Martin Setvín
Source: ACS Applied Materials & Interfaces (article, 2024-12-10)
Field: Materials Science — Materials Chemistry

Atomic-Scale View at the Segregation of Alkali Metals toward the KTaO<sub>3</sub>(001) Perovskite Surface Perovskites exhibit outstanding performance in applications such as photocatalysis, electrochemistry, or photovoltaics, yet their practical use is hindered by the instability of these materials under operating conditions, specifically caused by the segregation of alkali cations toward the surface. The problem arises from the bulk strain related to different cation sizes, as well as the inherent electrostatic instability of perovskite surfaces. Here, we focus on atomistic details of the surface-driven process of interlayer switching of alkali atoms at the inorganic perovskite surface. We show that the (001) surface of KTaO<sub>3</sub> cleaved at room temperature contains equally populated TaO<sub>2</sub> and KO terminations, while the uncompensated polarity of these terminations promotes diffusion of KO from the subsurface toward the topmost surface layer at temperatures as low as 200 °C. This effect is directly probed at the atomic scale by Atomic Force Microscopy and the chemical properties of the resulting surfaces are investigated by the adsorption of CO and H<sub>2</sub>O. The experiments indicate that KO segregation is associated with the formation of K and O vacancies in the near-surface region, which is further supported by depth-dependent X-ray Photoelectron Spectroscopy measurements and Density Functional Theory calculations. Our study shows that the KO segregation influences the surface reactivity both toward CO and water, which was probed at the atomic scale. Materials science ; Alkali metal ; Perovskite (structure) ; Atomic units ; Scale (ratio) ; Surface (topology) ; Inorganic chemistry ; Chemical physics ; Mineralogy ; Chemical engineering ; Geometry ; Physics Electronic and Structural Properties of Oxides ; Magnetic and transport properties of perovskites and related materials ; Ferroelectric and Piezoelectric Materials
Authors: Shiyi Qin | Surajudeen Omolabake | Aminata Diaby | Jianping Li | Leonardo D. González | Christopher M. Holland | Ví­ctor M. Zavala | Shannon S. Stahl | Reid C. Van Lehn
Source: ACS Sustainable Chemistry & Engineering (article, 2024-12-13)
Field: Chemistry — Analytical Chemistry

Identifying Green Solvent Mixtures for Bioproduct Separation Using Bayesian Experimental Design Liquid–liquid extraction (LLE) is a widely used technique for the separation and purification of liquid-phase products with applications in various industries, including pharmaceuticals, petrochemicals, and renewable chemistry. A critical step in the design of an LLE process is the selection of appropriate solvents. This study presents a new methodology for identifying solvent mixtures for bioproduct separation using Bayesian experimental design (BED). Motivated by the need for environmentally friendly and effective separation methods, we address the challenge of selecting solvent systems that balance separation efficiency, selectivity, and environmental impact while also tackling the difficulty of separating multiple bioproducts using complex solvent systems. Our approach specifically seeks to predict product partition coefficients (log10 Kp values) as thermodynamic parameters underlying solvent selection. The iterative approach integrates Bayesian optimization with experimental measurements to guide solvent selection and leverages COSMO-RS simulations to enhance high-throughput experimentation. Using the design of solvent systems for the separation of lignin-derived aromatic products via centrifugal partition chromatography (CPC) as a case study, we show that within seven iterations/cycles of the methodology, we can identify new mixtures of green solvents that align with CPC design principles. These results demonstrate the efficacy of the BED framework in optimizing green solvent systems for complex separations, highlighting the potential of this method to advance the field of green chemistry and contribute to the development of sustainable industrial processes. Petrochemical ; Process engineering ; Biochemical engineering ; COSMO-RS ; Process design ; Green chemistry ; Solvent ; Bioproducts ; Separation process ; Environmentally friendly ; Extractive distillation ; Computer science ; Chemistry ; Biofuel ; Chromatography ; Organic chemistry ; Engineering ; Waste management Chromatography in Natural Products ; Analytical Chemistry and Chromatography ; Crystallization and Solubility Studies
Authors: Suleiman Mousa | Sean P. Rigby
Source: Materials (review, 2024-11-01)
Field: Materials Science — Materials Chemistry

Fractal Modelling of Heterogeneous Catalytic Materials and Processes This review considers the use of fractal concepts to improve the development, fabrication, and characterisation of catalytic materials and supports. First, the theory of fractals is discussed, as well as how it can be used to better describe often highly complex catalytic materials and enhance structural characterisation via a variety of different methods, including gas sorption, mercury porosimetry, NMR, and several imaging modalities. The review then surveys various synthesis and fabrication methods that can be used to create catalytic materials that are fractals or possess fractal character. It then goes on to consider how the fractal properties of catalysts affect their performance, especially their overall activity, selectivity for desired products, and resistance to deactivation. Finally, this review describes how the optimum fractal catalyst material for a given reaction system can be designed on a computer. Fractal ; Porosimetry ; Catalysis ; Materials science ; Fabrication ; Fractal analysis ; Sorption ; Selectivity ; Process engineering ; Fractal dimension ; Computer science ; Chemical engineering ; Nanotechnology ; Biological system ; Porosity ; Chemistry ; Porous medium ; Organic chemistry ; Mathematics ; Composite material ; Engineering ; Adsorption Pickering emulsions and particle stabilization ; Theoretical and Computational Physics ; Enhanced Oil Recovery Techniques
Authors: Wenye Xuan | Yuhao Liu | Shih‐Yuan Chen | Matthew S. Dyer | Hsin‐Yi Tiffany Chen
Source: Nano Letters (article, 2024-01-29)
Field: Materials Science — Materials Chemistry

Unveiling the Morphology of Carbon-Supported Ru Nanoparticles by Multiscale Modeling Simulating the behavior of metal nanoparticles on supports is crucial for boosting their catalytic performance and various nanotechnology applications; however, such simulations are limited by the conflicts between accuracy and efficiency. Herein, we introduce a multiscale modeling strategy to unveil the morphology of Ru supported on pristine and N-doped graphene. Our multiscale modeling started with the electronic structures of a supported Ru single atom, revealing the strong metal-support interaction around pyridinic nitrogen sites. To determine the stable configurations of Ru<sub>2-13</sub> clusters on three different graphene supports, global energy minimum searches were performed. The sintering of the global minimum Ru<sub>13</sub> clusters on supports was further simulated by ab initio molecular dynamics (AIMD). The AIMD data set was then collected for deep potential molecular dynamics to study the melting of Ru nanoparticles. This study presents comprehensive descriptions of carbon-supported Ru and develops modeling approaches that bridge different scales and can be applied to various supported nanoparticle systems. Graphene ; Nanoparticle ; Molecular dynamics ; Materials science ; Nanotechnology ; Multiscale modeling ; Carbon fibers ; Chemical physics ; Computational chemistry ; Chemistry ; Composite number Catalytic Processes in Materials Science ; nanoparticles nucleation surface interactions ; Chemical and Physical Properties of Materials
Authors: Kabiru Haruna | Othman Charles S. Al Hamouz | Tawfik A. Saleh
Source: Heliyon (article, 2024-09-19)
Field: Materials Science — Materials Chemistry

The corrosion inhibition performance of a diissocyanate-imidazole based organic compound during acid cleaning of MSF desalination plant Inorganic scale formation is a common issue in multi-stage flash (MSF) desalination plants, significantly impacting operational efficiency. To address this, acid cleaning is frequently employed, but it can lead to severe corrosion of alloy components if not properly controlled with corrosion inhibitors. This study investigates the effectiveness of toluene-2,4-diisocyanate-4-(1H-imidazole-ly) aniline (TDIA) as a corrosion inhibitor for 304L stainless steel in a simulated acid cleaning solution (1M HCl and 3.5 % NaCl). A range of tests, including electrochemical analysis, weight loss measurements, and surface characterization techniques such as AFM, EDS, and SEM, were used to assess the inhibitor's performance at temperatures of 25, 45, 65, and 90 °C. At a concentration of 50 ppm, TDIA achieved inhibition efficiencies of around 90% at 25 °C and above 80% at 90 °C, demonstrating effective protection across all temperatures studied. The adsorption behavior of TDIA followed the Langmuir adsorption model, and it acted as a mixed-type inhibitor by forming a protective layer on the metal surface, which prevents corrosive agents from accessing the steel. The dual-environment testing method, simulating conditions in desalination plants, offers valuable insights into the inhibitor's practical performance, enhancing the applicability of these findings to real-world industrial scenarios. Imidazole ; Desalination ; Corrosion ; Chemistry ; Organic compound ; Organic chemistry ; Nuclear chemistry ; Materials science ; Biochemistry ; Membrane Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Alessandro Mameli | Alessandro Kovtun | Derek Jones | Vasiliki Benekou | Vincenzo Palermo | Marco Bandini | Manuela Melucci
Source: Nanoscale Advances (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Covalent functionalization by using blue light activated radicals: on the reaction mechanisms of arylazo sulfone binding on graphene Covalent functionalization of graphene presents a pivotal strategy to enhance its surface properties and overcome inherent chemical inertness. While diazonium salts have been extensively utilized for this purpose, their limitations necessitate exploration of alternative approaches. Arylazo sulfones, such as diazonium salt derivatives serving as chromophores, offer a promising solution, enabling photochemical reactions under visible light. Here, we propose a novel method for rapid covalent photofunctionalization of chemical vapor deposition (CVD) graphene on copper substrates using arylazo sulfones. The generation of aryl radicals - chlorobenzene in this case - was achieved through blue light LED irradiation of 4-chlorophenylazo methyl sulfone solution in acetonitrile. Efficient surface covalent modification of graphene was verified by observing (i) the photogeneration of radicals with a decrease in the π-π* band absorbance and an increase in the n-π* of arylazosulfone solution by UV-Vis spectroscopy; (ii) an increase in C sp<sup>3</sup> defects on graphene from the Raman D band, the Auger C KLL signal and graphene C 1s X-ray photoelectron spectroscopy (XPS); and (iii) the presence of the chlorobenzene XPS Cl 2p signal. The aryl radical generation was enhanced by the copper substrate during irradiation, with a possible double path reaction mechanism. This approach highlights the versatility of arylazo sulfones in covalently patterning graphene surfaces, thus unlocking opportunities by overcoming the current approach consisting of the deposition of resist materials with successive cycles of lithography and electrochemistry. Radical ; Surface modification ; Covalent bond ; Graphene ; Chemistry ; Photochemistry ; Blue light ; Combinatorial chemistry ; Materials science ; Organic chemistry ; Nanotechnology ; Optoelectronics Carbon and Quantum Dots Applications ; Conducting polymers and applications ; Molecular Junctions and Nanostructures
Authors: Bart Klumpers | Emiel J. M. Hensen | Ivo A. W. Filot
Source: Journal of Chemical Theory and Computation (article, 2024-07-24)
Field: Materials Science — Materials Chemistry

Transferable, Living Data Sets for Predicting Global Minimum Energy Nanocluster Geometries Modeling of nanocluster geometries is essential for studying the dependence of catalytic activity on the available active sites. In heterogeneous catalysis, the interfacial interaction of the support with the metal can result in modification of the structural and electronic properties of the clusters. To tackle the study of a diverse array of cluster shapes, data-driven methodologies are essential to circumvent prohibitive computational costs. At their core, these methods require large data sets in order to achieve the necessary accuracy to drive structural exploration. Given the similarity in binding character of the transition metals, cluster shapes encountered for various systems show a large amount of overlap. This overlap has been utilized to construct a living data set which may be carried over across multiple studies. Iterative refinement of this data set provides a low-cost pathway for initialization of cluster studies. It is shown that utilization of transferable structural information can reduce model construction costs by more than 90%. The benefits of this approach are particularly notable for alloy systems, which possess significantly larger configurational spaces compared to the pure-phase counterparts. Computer science ; Initialization ; Cluster (spacecraft) ; Set (abstract data type) ; Construct (python library) ; Similarity (geometry) ; Data mining ; Artificial intelligence Machine Learning in Materials Science ; Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions
Authors: Qiang Zhu | Shinnosuke Hattori
Source: Digital Discovery (article, 2024-11-20)
Field: Materials Science — Materials Chemistry

Automated high-throughput organic crystal structure prediction <i>via</i> population-based sampling With advancements in computational molecular modeling and powerful structure search methods, it is now possible to systematically screen crystal structures for small organic molecules. Throughput ; Sampling (signal processing) ; Computer science ; Crystal structure prediction ; Population ; Artificial intelligence ; Data mining ; Pattern recognition (psychology) ; Crystal structure ; Chemistry ; Computer vision ; Crystallography ; Telecommunications ; Medicine Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: Alpár Ferencz Hatvani-Nagy | Viktória Hajdu | Ágnes Mária Ilosvai | Gábor Muránszky | Emőke Sikora | Ferenc Kristály | Lajos Daróczi | Béla Viskolcz | Béla Fiser | László Vanyorek
Source: Scientific Reports (article, 2024-02-20)
Field: Chemistry — Organic Chemistry

Bentonite as eco-friendly natural mineral support for Pd/CoFe2O4 catalyst applied in toluene diamine synthesis Toluene diamine (TDA) is a major raw material in the polyurethane industry and thus, its production is highly important. TDA is obtained through the catalytic hydrogenation of 2,4-dinitrotoluene (2,4-DNT). In this study a special hydrogenation catalyst has been developed by decomposition cobalt ferrite nanoparticles onto a natural clay-oxide nanocomposite (bentonite) surface using a microwave-assisted solvothermal method. The catalyst particles were examined by TEM and X-ray diffraction. The palladium immobilized on the bentonite crystal surface was identified using an XRD and HRTEM device. The obtained catalyst possesses the advantageous property of being easily separable due to its magnetizability on a natural mineral support largely available and obtained through low carbon- and energy footprint methods. The catalyst demonstrated outstanding performance with a 2,4-DNT conversion rate exceeding 99% along with high yields and selectivity towards 2,4-TDA and all of this achieved within a short reaction time. Furthermore, the developed catalyst exhibited excellent stability, attributed to the strong interaction between the catalytically active metal and its support. Even after four cycles of reuse, the catalytic activity remained unaffected and the Pd content of the catalyst did not change, which indicates that the palladium component remained firmly attached to the magnetic support's surface. Bentonite ; Toluene ; Catalysis ; Environmentally friendly ; Diamine ; Mineral ; Environmental science ; Chemistry ; Natural (archaeology) ; Environmental chemistry ; Chemical engineering ; Organic chemistry ; Geology ; Biology ; Engineering ; Ecology Nanomaterials for catalytic reactions ; Catalytic Processes in Materials Science ; Catalysis and Hydrodesulfurization Studies
Authors: Erni Salasia Fitri | Risfidian Mohadi | Neza Rahayu Palapa | Susila Arita Rachman | Aldes Lesbani
Source: Science & Technology Indonesia (article, 2024-01-22)
Field: Materials Science — Materials Chemistry

Selective Removal of Anionic and Cationic Dyes Using Magnetic Composites Water is one of the most basic human needs, and dyes are one of the sources of water pollution. Since adsorption has proven to be effective in removing contaminants, it is the most widely used technique. In this adsorption, a LDH Zn-Al /magnetic biochar composite was used for dye removal. Zn-Al LDH, magnetic biochar, and LDH Zn-Al/biochar magnetic composite were successfully synthesized, based on XRD and FTIR studies. XRD analysis of the Zn-Al LDH material shows diffractions of (003), (006), (101), (012), (015), (107), and (110) around the 2theta angle at 10.29°, 20.07°, 29.59°, 32.12°, 34.02°, 48.06°, and 60.16° which are characteristic of LDH materials. In magnetic biochar and LDH Zn-Al/magnet biochar composites diffraction (220), (311), (422) and (440) at 2theta around 24.9°, 35°, 63° and 68.4° in these materials indicate the characteristics of carbon-based materials from biochar. FTIR analysis showed the appearance of a vibration peak at 1404cm−1 indicating the presence of C H groups contained in biochar. The characteristic double-layer hydroxy (M-O) vibrations below 1000 cm−1 also indicated that the composite preparation process had been successful. The study’s results show that cationic dyes are more easily adsorbed than anionic dyes. Specifically, the LDH Zn-Al/Magnetic Biochar composite more extensively absorbs the cationic dye malachite green. Biochar ; Malachite green ; Cationic polymerization ; Adsorption ; Fourier transform infrared spectroscopy ; Composite number ; Chemistry ; Nuclear chemistry ; Materials science ; Composite material ; Chemical engineering ; Organic chemistry ; Pyrolysis Magnesium Oxide Properties and Applications ; Adsorption and biosorption for pollutant removal ; Recycling and utilization of industrial and municipal waste in materials production
Authors: Daniele Soccodato | Gabriele Penazzi | Alessandro Pecchia | Anh‐Luan Phan | Matthias Auf der Maur
Source: Machine Learning Science and Technology (article, 2024-04-29)
Field: Materials Science — Materials Chemistry

Machine learned environment-dependent corrections for a spds∗ empirical tight-binding basis Abstract Empirical tight-binding (ETB) methods have become a common choice to simulate electronic and transport properties for systems composed of thousands of atoms. However, their performance is profoundly dependent on the way the empirical parameters were fitted, and the found parametrizations often exhibit poor transferability. In order to mitigate some of the the criticalities of this method, we introduce a novel Δ-learning scheme, called MLΔTB. After being trained on a custom data set composed of ab-initio band structures, the framework is able to correlate the local atomistic environment to a correction on the on-site ETB parameters, for each atom in the system. The converged algorithm is applied to simulate the electronic properties of random GaAsSb alloys, and displays remarkable agreement both with experimental and ab-initio test data. Some noteworthy characteristics of MLΔTB include the ability to be trained on few instances, to be applied on 3D supercells of arbitrary size, to be rotationally invariant, and to predict physical properties that are not exhibited by the training set. Transferability ; Tight binding ; Ab initio ; Computer science ; Invariant (physics) ; Atom (system on chip) ; Set (abstract data type) ; Test set ; Scheme (mathematics) ; Algorithm ; Electronic structure ; Statistical physics ; Artificial intelligence ; Machine learning ; Physics ; Computational chemistry ; Chemistry ; Mathematics ; Quantum mechanics ; Parallel computing ; Mathematical analysis Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Surface and Thin Film Phenomena
Authors: Andreas Klein | Florian Leiss-Maier | Rahel Mühlhofer | Benedikt Boesen | Ghulam Mustafa | Hannah Kugler | Cathleen Zeymer
Source: ChemRxiv (preprint, 2024-02-29)
Field: Chemistry — Organic Chemistry

A de novo metalloenzyme for cerium photoredox catalysis Cerium photoredox catalysis has emerged as a powerful strategy to activate molecules under mild conditions. Radical intermediates are formed using visible light and simple complexes of the earth-abundant lanthanide. However, it remains a major challenge to achieve stereocontrol in these reactions. Here, we report an artificial photoenzyme enabling this chemistry inside a protein. We utilize a de novo designed protein scaffold that tightly binds lanthanide ions in its central cavity. Upon visible-light irradiation, the cerium-dependent enzyme catalyzes the radical C–C bond cleavage of 1,2-diols in aqueous solution. Protein engineering led to variants with improved photostability and initial stereoselectivity. The photoenzyme cleaves a range of aromatic and aliphatic substrates, including lignin surrogates. Surface display of the protein scaffold on E. coli facilitates whole-cell photobiocatalysis. Furthermore, we show that also natural lanthanide-binding proteins are suitable for this approach. Our study thus demonstrates a new-to-nature enzymatic photoredox activity with broad catalytic potential. Cerium ; Chemistry ; Lanthanide ; Photoredox catalysis ; Catalysis ; Aqueous solution ; Combinatorial chemistry ; Photochemistry ; Bond cleavage ; Enzyme catalysis ; Stereochemistry ; Organic chemistry ; Ion ; Photocatalysis Radical Photochemical Reactions ; Metalloenzymes and iron-sulfur proteins ; Metal-Catalyzed Oxygenation Mechanisms