jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Onur Boyar | Yanheng Gu | Yuji Tanaka | Shunsuke Tonogai | Tomoya Itakura | Ichiro Takeuchi
Source: arXiv (Cornell University) (preprint, 2024-05-28)
Field: Materials Science — Materials Chemistry

Crystal-LSBO: Automated Design of De Novo Crystals with Latent Space Bayesian Optimization Generative modeling of crystal structures is significantly challenged by the complexity of input data, which constrains the ability of these models to explore and discover novel crystals. This complexity often confines de novo design methodologies to merely small perturbations of known crystals and hampers the effective application of advanced optimization techniques. One such optimization technique, Latent Space Bayesian Optimization (LSBO) has demonstrated promising results in uncovering novel objects across various domains, especially when combined with Variational Autoencoders (VAEs). Recognizing LSBO's potential and the critical need for innovative crystal discovery, we introduce Crystal-LSBO, a de novo design framework for crystals specifically tailored to enhance explorability within LSBO frameworks. Crystal-LSBO employs multiple VAEs, each dedicated to a distinct aspect of crystal structure: lattice, coordinates, and chemical elements, orchestrated by an integrative model that synthesizes these components into a cohesive output. This setup not only streamlines the learning process but also produces explorable latent spaces thanks to the decreased complexity of the learning task for each model, enabling LSBO approaches to operate. Our study pioneers the use of LSBO for de novo crystal design, demonstrating its efficacy through optimization tasks focused mainly on formation energy values. Our results highlight the effectiveness of our methodology, offering a new perspective for de novo crystal discovery. Bayesian optimization ; Bayesian probability ; Space (punctuation) ; Crystal (programming language) ; Computer science ; Materials science ; Crystallography ; Artificial intelligence ; Chemistry ; Programming language Machine Learning in Materials Science ; Drilling and Well Engineering ; Crystallization and Solubility Studies
Authors: Xiaofei Shao | Xiaobiao Liu | Xikui Ma
Source: Materials (article, 2024-11-13)
Field: Materials Science — Materials Chemistry

Two-Dimensional Pentagonal Materials with Parabolic Dispersion and High Carrier Mobility Materials with high carrier mobility, represented by graphene, have garnered significant interest. However, the zero band gap arising from linear dispersion cannot achieve an ideal on-off ratio in field-effect transistors (FETs), limiting practical applications in certain fields. In contrast, parabolic dispersion usually exhibits extremely high carrier mobility and an appropriate band gap. In this work, we predicted a planar pentagonal lattice composed entirely of pentagons (namely <i>penta</i>-MX<sub>2</sub> monolayer), where M = Ni, Pd and Pt, X = group V elements. Using first-principles calculations, we demonstrated a parabolic dispersion within this framework, which results in intriguing phenomena, such as a direct band gap (0.551-1.105 eV) and extraordinary high carrier mobility. For <i>penta</i>-MX<sub>2</sub> monolayer, the carrier mobility can attain ~1 × 10<sup>8</sup> cm<sup>2</sup> V<sup>-1</sup> s<sup>-1</sup> (PBE), surpassing those of black phosphorene, graphene and 2D hexagonal materials. This monolayer also displays anisotropic mechanical properties and significant absorption peaks in the ultraviolet spectrum. Remarkably, 2D <i>penta</i>-MX<sub>2</sub> monolayers are promising for successful experimental exfoliation, particularly when X is a nitrogen element, opening up new possibilities for designing two-dimensional semiconductor materials characterized by high carrier mobility. Phosphorene ; Materials science ; Electron mobility ; Monolayer ; Band gap ; Semiconductor ; Direct and indirect band gaps ; Graphene ; Anisotropy ; Condensed matter physics ; Dispersion (optics) ; Lattice (music) ; Optoelectronics ; Nanotechnology ; Optics ; Physics 2D Materials and Applications ; MXene and MAX Phase Materials ; Graphene research and applications
Authors: Vicenzo Frendyatha Adiprasetya | Muhamad Akrom | Gustina Alfa Trisnapradika
Source: Eksergi (article, 2024-03-23)
Field: Materials Science — Materials Chemistry

Investigasi Efisiensi Penghambatan Korosi Senyawa Quinoxaline Berbasis Machine Learning Korosi memberikan kekhawatiran serius bagi sektor industri dan akademik karena mempunyai dampak negatif yang signifikan terhadap sejumlah bidang, termasuk perekonomian, lingkungan, masyarakat, industri, keamanan, dan keselamatan. Saat ini, banyak peminat topik pengendalian kerusakan bahan berbasis molekul organik. Quinoxaline mempunyai potensi sebagai inhibitor korosi karena tidak beracun, mudah diproduksi, dan efektif dalam berbagai kondisi korosif. Mengeksplorasi kemungkinan kandidat penghambat korosi melalui penelitian eksperimental adalah proses yang memakan waktu dan sumber daya yang intensif. Dengan menggunakan pendekatan machine learning (ML) berdasarkan model quantitative structure-property relationship (QSPR), kami mengevaluasi beragam algoritma linier dan non-linier sebagai model prediktif nilai corrosion inhibition efficiency (CIE) dalam penelitian ini. Kami menemukan bahwa, untuk kumpulan data senyawa quinoxaline, model non-linier Gradient Boosting Regressor (GBR) mengungguli keseluruhan model linier dan non-linier, serta hasil dari literatur dalam hal kinerja prediksi berdasarkan metrik root mean squared error (RMSE), mean squared error (MSE), mean absolute deviation (MAD), mean absolute percentage error (MAPE) dan coefficient of determination (R2). Secara keseluruhan, penelitian kami memberikan sudut pandang baru tentang kapasitas model ML untuk memperkirakan kemampuan penghambatan korosi pada permukaan besi oleh senyawa organik quinoxaline. Quinoxaline ; Chemistry ; Computer science ; Programming language ; Organic chemistry Corrosion Behavior and Inhibition ; Machine Learning in Materials Science ; Material Selection and Properties
Authors: Małgorzata Łazarska | Janusz Musiał | Tomasz Tański | Zbigniew Ranachowski
Source: Materials (article, 2024-12-21)
Field: Materials Science — Materials Chemistry

Transformations in the Ti-6Al-4V Alloy Studied Using Dilatometry Supported by Acoustic Emission This paper presents the results of research on the kinetics of transformations in the two-phase (α + β) Ti-6Al-4V alloy. The transformation start and end temperatures during heating at different rates were determined using a dilatometer. A modified dilatometer was employed, equipped with an acoustic emission measurement apparatus and software enabling the assessment of sample dimensional changes during heating and cooling. The results were obtained in the form of dilatometric curves. Additionally, the occurrence of the transformation was confirmed by acoustic emission signals. In the study of the Ti-6Al-4V alloy, acoustic emission refers to the application of this non-destructive technique to monitor the alloy's behavior during thermal processes. As the temperature increased, regardless of the heating rate, the α→β transformation was observed to occur after exceeding 900 °C. Within the transformation range, acoustic emission signals were recorded. Moreover, it was found that the applied research methods enabled the identification of signal components originating from the transformation. The application of acoustic methods in the analysis of phase transformations opens new possibilities for their use in industry. Dilatometer ; Acoustic emission ; Materials science ; Alloy ; Transformation (genetics) ; Phase (matter) ; SIGNAL (programming language) ; Atmospheric temperature range ; Range (aeronautics) ; Thermal expansion ; Thermal ; Acoustics ; Metallurgy ; Composite material ; Thermodynamics ; Computer science ; Chemistry Titanium Alloys Microstructure and Properties ; Surface Treatment and Coatings ; Metal Alloys Wear and Properties
Authors: Samuel R. Zarcone | Zihan Zhang | Suhashini Handunneththige | Zhen Ni | Nattamai Bhuvanesh | Michael Nippe | Karsten Meyer | Michael B. Hall | John A. Gladysz
Source: Inorganic Chemistry (article, 2024-08-20)
Field: Chemistry — Inorganic Chemistry

A Caged Neutral 17-Valence-Electron Iron(I) Radical [Fe(CO)<sub>2</sub>(Cl)(P((CH<sub>2</sub>)<sub>10</sub>)<sub>3</sub>P)]<sup>•</sup>: Synthetic, Structural, Spectroscopic, Redox, and Computational Studies UV irradiation of yellow CH<sub>2</sub>Cl<sub>2</sub> solutions of <i>trans</i>-Fe(CO)<sub>3</sub>(P((CH<sub>2</sub>)<sub>10</sub>)<sub>3</sub>P) (<b>2a</b>) and PMe<sub>3</sub> (10 equiv) gives, in addition to the previously reported dibridgehead diphosphine P((CH<sub>2</sub>)<sub>10</sub>)<sub>3</sub>P (46%), a green paramagnetic complex that crystallography shows to be the trigonal-bipyramidal iron(I) radical <i>trans</i>-[Fe(CO)<sub>2</sub>(Cl)(P((CH<sub>2</sub>)<sub>10</sub>)<sub>3</sub>P)]<sup>•</sup> (<b>1a</b><sup>•</sup>; 31% after workup). This is a rare example of an isolable species of the formula [Fe(CO)<sub>4-<i>n</i></sub>(L)<sub><i>n</i></sub>(X)]<sup>•</sup> (<i>n</i> = 0-3, L = two-electron-donor ligand; X = one-electron-donor ligand). Analogous precursors with longer P(CH<sub>2</sub>)<sub><i>n</i></sub>P segments (<i>n</i> = 12, 14, 16, 18) give only the demetalated diphosphines, and a rationale is proposed. The magnetic susceptibility of <b>1a</b><sup>•</sup>, assayed by Evans' method and SQUID measurements, indicates a spin (<i>S</i>) of <sup>1</sup>/<sub>2</sub>. Cyclic voltammetry shows that <b>1a</b><sup>•</sup> undergoes a partially reversible one-electron oxidation, but no facile reduction. The UV-visible, EPR, and <sup>57</sup>Fe Mössbauer spectra are analyzed in detail. Complex <b>2a</b> is similarly studied, and, despite the extra valence electron, exhibits a comparable oxidation potential (Δ<i>E</i><sub>1/2</sub> ≤ 0.04 V). The crystal structure shows a cage conformation, solvation level, disorder motif, and unit cell parameters essentially identical to those of <b>1a</b><sup>•</sup>. DFT calculations provide much insight regarding the structural, redox, and spectroscopic properties. Chemistry ; Valence (chemistry) ; Electron ; Crystallography ; Nuclear physics Metal-Catalyzed Oxygenation Mechanisms ; Magnetism in coordination complexes ; Metal complexes synthesis and properties
Authors: Dwipa Ajiati | Dadan Sumiarsa | Meiny Faudah Amin | Dikdik Kurnia
Source: Journal of Advanced Pharmaceutical Technology amp Research (article, 2024-07-01)
Field: Chemistry — Organic Chemistry

Potential antioxidant and antiradical agents from Allium ascalonicum: Superoxide dismutase and density functional theory in silico studies Antioxidants are compounds that can inhibit excessive free radical reactions in the body. Excessive free radicals can cause system imbalances in the body which can trigger oxidative stress and cause serious illness. The limitations of antioxidants in the body can be overcome by consuming safe natural additional antioxidants that can be obtained from natural products. Isolating compounds of <i>Allium</i> <i>ascalonicum</i> leaves as antioxidant and antiradical agents in inhibiting excessive free radicals by <i>in vitro</i> and <i>in</i> <i>silico</i>. The extracted compounds were purified by column chromatography. The compounds obtained were then characterized using ultraviolet, infrared, NMR, and mass spectrometry. Determination of antioxidant activity was carried out by <i>in</i> <i>vitro</i> using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and the non-enzymatic superoxide dismutase (SOD) methods. The <i>in</i> <i>silico</i> study used the density functional theory (DFT) calculation method with global descriptive parameters (GDP), donor acceptor map (DAM), and frontier molecular orbitals (FMO) analysis. Three compounds have been isolated, of which compound <b>1</b> is a new compound. In the DPPH method, compound <b>1</b> has more strong antioxidant activity than others, as well as in the non-enzymatic SOD method. Whereas, in the DFT calculation shows that compound <b>1</b> has the best reactivity and stability between other compounds and was categorized as the best antiradical. Compound <b>1</b> has the highest antioxidant activity compared to the other compounds by <i>in</i> <i>vitro</i> both the DPPH and non-enzymatic SOD methods. <i>In</i> <i>silico,</i> compound 1 has the potential as the best antiradical. In silico ; Superoxide dismutase ; Antioxidant ; Superoxide ; Chemistry ; Allium ; Biochemistry ; Biology ; Botany ; Enzyme ; Gene Free Radicals and Antioxidants ; Garlic and Onion Studies ; Phytochemicals and Antioxidant Activities
Authors: Mohammed Mahdi Abed | Tariq M. Naife | Mervat Amin Abdel Kawi Ibrahim
Source: Iraqi Journal of Chemical and Petroleum Engineering (article, 2024-09-30)
Field: Chemistry — Analytical Chemistry

Advancing green technology: demulsifier preparation and evaluation for crude oil emulsion treatment using corn oil Globally, oil production has steadily increased which causes a rise in the coproduction of oil and water emulsions. These emulsions pose significant challenges in transportation and the oil refinery industry, causing high-pressure drops and corrosion problems due to chlorides in the water. Despite advancements in renewable energy, crude oil remains a primary energy source. The crude oil industry faces numerous challenges, including cost emulsion issues. This study developed a corn oil bio-demulsifier (MFK). A unique demulsifier was tested using FTIR, GC-MS, and TGA. Using the bottle test method, the produced demulsifier MFK was tested with Basrah oil and East Baghdad S1 oil. The emulsion-breaking processes have been studied under several factors, such as settling time, dosage, temperature, pH, water content, and mixing time after demulsifier addition. At 2000 ppm Basrah oil, water separation efficiency reached 75%. For East Baghdad S1 oil, the highest separation result was 43.3% at 4000ppm, after 5 h of settling time at 70°C, with a 30/70 water-to-oil ratio. When studying the pH, the best water separation rate was 86.5% at a pH of 10. The best water content was 92% when the water-to-oil ratio was 50/50, and the best demulsifier mixing time with the emulsion was 2 min with a separation rate of 74.5%. When mixing was increased, undesirable results occurred. This study demonstrated that biodemulsifiers may replace conventional biodemulsifiers in early units while reducing environmental and economic impacts with further study and development. Demulsifier ; Emulsion ; Crude oil ; Corn oil ; Environmental science ; Pulp and paper industry ; Chemistry ; Food science ; Petroleum engineering ; Engineering ; Organic chemistry Petroleum Processing and Analysis
Authors: Yumeng Yin | A. A. P. Trichet | Jiangrui Qian | Jason M. Smith
Source: The Journal of Physical Chemistry Letters (article, 2024-11-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Shape Measurement of Single Gold Nanorods in Water Using Open-Access Optical Microcavities Shape measurement of single nanoparticles in fluids is an outstanding challenge with applications in characterizing synthetic functional nanoparticles and in early warning detection of rod-shaped pathogens in water supplies. Here we introduce a novel technique to measure the aspect ratio of rod-shaped particles by analyzing changes in the polarization state of a laser beam transmitted through an optical microcavity through which the particle diffuses. The resolution in aspect ratio measurement is found to be around 1%. Our work opens the new possibility of in situ and single-particle shape measurement, which has promising applications in nanoparticle characterization, water monitoring, and beyond. Nanorod ; Materials science ; Optoelectronics ; Optics ; Nanotechnology ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Nanoparticle-Based Drug Delivery ; Advanced biosensing and bioanalysis techniques
Authors: Xiaoye Zhou | Yuqi Liu | Bing Tang | Junyuan Wang | Haikuan Dong | Xiao‐Ming Xiu | Shunda Chen | Zheyong Fan
Source: arXiv (Cornell University) (preprint, 2024-10-17)
Field: Materials Science — Materials Chemistry

Million-atom heat transport simulations of polycrystalline graphene approaching first-principles accuracy enabled by neuroevolution potential on desktop GPUs First-principles molecular dynamics simulations of heat transport in systems with large-scale structural features are challenging due to their high computational cost. Here, using polycrystalline graphene as a case study, we demonstrate the feasibility of simulating heat transport with near first-principles accuracy in systems containing over 1.4 million atoms, achievable even with consumer desktop GPUs. This is enabled by the highly efficient neuroevolution potential (NEP) approach, as implemented in the open-source GPUMD package. Leveraging the NEP model's accuracy and efficiency, we quantify the reduction in thermal conductivity of polycrystalline graphene due to grain boundaries with varying grain sizes, resolving contributions from in-plane and out-of-plane (flexural) phonon modes. Additionally, we find that grain boundaries can lead to finite thermal conductivity even under significant tensile strain, in contrast to the divergent behavior observed in pristine graphene under similar conditions, indicating that grain boundaries may play a crucial role in thermal transport in low-dimensional momentum-conserving systems. These findings could offer insights for interpreting experimental observations, given the widespread presence of both large-scale grain boundaries and external strains in real materials. The demonstrated ability to simulate millions of atoms with near-first-principles accuracy on consumer desktop GPUs using the NEP approach will help make large-scale high-fidelity atomistic simulations more accessible to the broader research community. Graphene ; Computer science ; Neuroevolution ; Atom (system on chip) ; Computational science ; Simulation ; Parallel computing ; Nanotechnology ; Materials science ; Artificial intelligence ; Artificial neural network Thermal properties of materials ; Machine Learning in Materials Science ; Fuel Cells and Related Materials
Authors: Stefan Hödl | Tal Kachman | Yoram Bachrach | Wilhelm T. S. Huck | William E. Robinson
Source: Digital Discovery (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

What can attribution methods show us about chemical language models? Language models trained on molecular string representations have shown strong performance in predictive and generative tasks. However, practical applications require not only making accurate predictions, but also explainability - the ability to explain the reasons and rationale behind the predictions. In this work, we explore explainability for a chemical language model by adapting a transformer-specific and a model-agnostic input attribution technique. We fine-tune a pretrained model to predict aqueous solubility, compare training and architecture variants, and evaluate visualizations of attributed relevance. The model-agnostic SHAP technique provides sensible attributions, highlighting the positive influence of individual electronegative atoms, but does not explain the model in terms of functional groups or explain how the model represents molecular strings internally to make predictions. In contrast, the adapted transformer-specific explainability technique produces sparse attributions, which cannot be directly attributed to functional groups relevant to solubility. Instead, the attributions are more characteristic of how the model maps molecular strings to its latent space, which seems to represent features relevant to molecular similarity rather than functional groups. These findings provide insight into the representations underpinning chemical language models, which we propose may be leveraged for the design of informative chemical spaces for training more accurate, advanced and explainable models. Attribution ; Work (physics) ; Solubility ; Computer science ; Natural language processing ; Biochemical engineering ; Chemistry ; Psychology ; Thermodynamics ; Social psychology ; Physical chemistry ; Engineering ; Physics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Text Analysis Techniques
Authors: Tayssir Hamieh
Source: Preprints.org (preprint, 2024-03-18)
Field: Chemistry — Spectroscopy

Effect of the Temperature on the Polar and Lewis Acid-Base properties of the Adsorption of PMMA on Silica by Inverse Gas Chromatography The temperature effect plays an important role for an accurate determination of the polar free energy, polar thermodynamic parameters, and enthalpic and entropic Lewis’s acid base properties of oxides, polymers and composites polymers/oxides. The adsorption of polymers on other solid surfaces is crucial in many industrial applications, coatings, paints, catalysis, colloids and adhesion processes. (1) Background: Inverse gas chromatography at infinite was used for the physico-chemical characterization of solid substrates by determining the thermodynamic parameters of adsorption of model organic solvents on solid surfaces such as polymers, metallic oxides, carbon fibers, pharmaceutical or 3D/4D printing substrates. (2) Methods: A new method based on the London dispersion equation was applied with a new parameter associating the deformation po-larizability and the harmonic mean of the ionization energies of solvent. More accurate values of the dispersive and polar interaction energies of the various organic solvents adsorbed on PMMA in bulk phase and PMMA/silica at different recovery fractions were obtained as well as the Lewis acid-base parameters and the transition temperatures of the different composites. (3) Results: This new methodology gave very interesting results on the behavior of PMMA adsorbed on silica. An important effect of the temperature and the recovery fraction on the various physicochemical and thermodynamic properties was highlighted. The variations of all interaction parameters showed the presence of three transition temperatures for the different PMMA adsorbed on silica with the various coverage rates with a shift of these temperatures for a recovery fraction of 31% (4) Con-clusions: An important variation of the polar enthalpy and entropy of adsorption, the Lewis ac-id-base parameters and the intermolecular separation distance as a function of the temperature and the recovery fraction of PMMA on silica. Inverse gas chromatography ; Adsorption ; Polar ; Inverse ; Lewis acids and bases ; Gas chromatography ; Base (topology) ; Chemistry ; Inverse temperature ; Chromatography ; Chemical polarity ; Chemical engineering ; Polymer chemistry ; Materials science ; Organic chemistry ; Thermodynamics ; Catalysis ; Molecule ; Mathematics ; Physics ; Geometry ; Engineering Adsorption, diffusion, and thermodynamic properties of materials ; Chemical Thermodynamics and Molecular Structure ; Catalytic Processes in Materials Science