jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sujeet Kumar Thakur | Raviteja Seera | Tayur N. Guru Row | S. V. Eswaran
Source: International Journal of Polymer Science (article, 2023-10-12)
Field: Chemistry — Inorganic Chemistry

Base-Catalyzed Polymerization of a Substituted Methylenebicyclo[3.3.1]nonane Lignite humic acid on reaction with formaldehyde and aqueous alkali led to a polybicyclo[3.3.1]nonane. This was characterized spectroscopically using mass spectrometry, FT-IR, powder X-ray diffraction, TEM, and NMR studies (1H-NMR, CP-MAS-SS-NMR) which though challenging were useful for confirming the structure of the BCN polymer. The product showed an envelope peak in its MALDI-MS spectrum, based on which <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mover accent="true"> <a:mrow> <a:mi>M</a:mi> </a:mrow> <a:mo>̅</a:mo> </a:mover> <a:msub> <a:mrow/> <a:mrow> <a:mtext>n</a:mtext> </a:mrow> </a:msub> </a:math> , <d:math xmlns:d="http://www.w3.org/1998/Math/MathML" id="M2"> <d:mover accent="true"> <d:mrow> <d:mi>M</d:mi> </d:mrow> <d:mo>̅</d:mo> </d:mover> <d:msub> <d:mrow/> <d:mrow> <d:mtext>w</d:mtext> </d:mrow> </d:msub> </d:math> , and polydispersity index have been calculated. Based on the NMR spectrum of intermediate, the presence of the N-formyl group has been shown in it. The new polymer could be useful in agriculture in water-deficient areas. Most papers on humic acids include only broad and general information like elemental analysis (occasionally TEM, SEM, TGA, DSC, etc.). Very complicated structures have been proposed by scientists earlier. Only in very recent years, it has been recognized that these are relatively small molecules which masquerade as supramolecular structures. It is pointed out that most papers do not put down the structure of the compound and provide no concrete proof for proposing such structures. The novelty of our work is that we have characterized the precise molecular weights based on mass spectrometry and NMR spectroscopy along with a well-defined structure. This is not the case in most other publications. Dispersity ; Nonane ; Homonuclear molecule ; Polymerization ; Materials science ; Aqueous solution ; Molecule ; Polymer science ; Polymer ; Crystallography ; Chemistry ; Polymer chemistry ; Organic chemistry Radioactive element chemistry and processing ; Lanthanide and Transition Metal Complexes ; Pesticide and Herbicide Environmental Studies
Authors: Md. Nasim | Anter El‐Azab | X. Zhang | Yexiang Xue
Source: arXiv (Cornell University) (preprint, 2023-09-13)
Field: Materials Science — Materials Chemistry

End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning The availability of tera-byte scale experiment data calls for AI driven approaches which automatically discover scientific models from data. Nonetheless, significant challenges present in AI-driven scientific discovery: (i) The annotation of large scale datasets requires fundamental re-thinking in developing scalable crowdsourcing tools. (ii) The learning of scientific models from data calls for innovations beyond black-box neural nets. (iii) Novel visualization and diagnosis tools are needed for the collaboration of experimental and theoretical physicists, and computer scientists. We present Phase-Field-Lab platform for end-to-end phase field model discovery, which automatically discovers phase field physics models from experiment data, integrating experimentation, crowdsourcing, simulation and learning. Phase-Field-Lab combines (i) a streamlined annotation tool which reduces the annotation time (by ~50-75%), while increasing annotation accuracy compared to baseline; (ii) an end-to-end neural model which automatically learns phase field models from data by embedding phase field simulation and existing domain knowledge into learning; and (iii) novel interfaces and visualizations to integrate our platform into the scientific discovery cycle of domain scientists. Our platform is deployed in the analysis of nano-structure evolution in materials under extreme conditions (high temperature and irradiation). Our approach reveals new properties of nano-void defects, which otherwise cannot be detected via manual analysis. Crowdsourcing ; Computer science ; Field (mathematics) ; Annotation ; Scalability ; Data science ; Visualization ; Scientific discovery ; Artificial intelligence ; Deep learning ; Machine learning ; World Wide Web Machine Learning in Materials Science
Authors: Gu-Wen Chen | Liang Xu | Yaoming Li | Zhi‐Pan Liu | Shengcai Zhu
Source: arXiv (Cornell University) (preprint, 2023-11-15)
Field: Materials Science — Materials Chemistry

Strength-dependent Transition of Graphite Under Shock Condition Resolved by First Principles The shock strength dependent formation of diamond represents one of the most intriguing questions in graphite research. Using ab initio DFT-trained carbon GNN model, we observe a strength-dependent graphite transition under shock. The poor sliding caused by scarce sliding time under high-strength shock forms hexagonal diamond with an orientation of (001)G//(100)HD+[010]G//[010]HD; under low-strength shock, cubic diamond forms after enough sliding time, unveiling the strength-dependent graphite transition. We provide computational evidence of the strength-dependent graphite transition from first principles, clarifying the long-term shock-induced hexagonal formation and structural strength-dependent trend source. Graphite ; Diamond ; Shock (circulatory) ; Materials science ; Ab initio ; Hexagonal crystal system ; Carbon fibers ; Composite material ; Condensed matter physics ; Crystallography ; Composite number ; Chemistry ; Physics ; Medicine Diamond and Carbon-based Materials Research ; High-pressure geophysics and materials ; Ion-surface interactions and analysis
Authors: M. A. Gavryushina | А. И. Маршаков | V. E. Ignatenko
Source: Corrosion material protection and research methods (article, 2023-12-30)
Field: Materials Science — Materials Chemistry

Forecast of the rate of underground corrosion of steel pipelines. Review The task of estimating the probable corrosion rate of underground steel pipelines has long been facing engineers and scientists and is still relevant. This review examines the factors influencing the formation and development of corrosion defects of underground pipelines, and various methods for predicting corrosion of pipelines. Models of various types (deterministic, probabilistic and created using machine learning) are shown and the criteria of their applicability are analyzed. Corrosion ; Pipeline transport ; Environmental science ; Forensic engineering ; Metallurgy ; Petroleum engineering ; Engineering ; Materials science ; Environmental engineering Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Industrial Engineering and Technologies
Authors: Jitendra More | Rakesh Vitthal Patil -
Source: International Journal For Multidisciplinary Research (article, 2023-09-22)
Field: Chemistry — Inorganic Chemistry

Emerging Trends in Metal-Organic Frameworks for Gas Separation and Storage This research paper explores the rapidly evolving landscape of Metal-Organic Frameworks (MOFs) in the context of gas separation and storage. In an era characterized by growing energy demands and environmental concerns, the efficient and sustainable management of gases such as carbon dioxide, methane, and hydrogen is of paramount importance. MOFs, with their tunable structures and exceptional surface areas, have emerged as promising candidates to address these challenges. The introduction provides an overview of the critical role MOFs play in revolutionizing gas separation and storage technologies. By synthesizing an extensive body of literature, the literature review outlines the historical context, highlighting the steady progression of MOFs from theoretical constructs to practical applications. It underscores knowledge gaps and highlights emerging trends, setting the stage for this research. The methods section details the experimental approaches employed, encompassing MOF synthesis, characterization techniques, and comprehensive testing methodologies. The results section presents compelling data demonstrating the performance of various MOFs in gas separation and storage scenarios. These results reveal the remarkable adsorption capacities and selectivity of MOFs, providing insights into their practicality. The discussion delves into the implications of these findings, illuminating how MOFs can redefine the landscape of gas separation and storage. Recognizing limitations and challenges, we propose potential research directions and applications. In conclusion, this paper underscores the transformative potential of MOFs in addressing pressing global issues related to energy and the environment. By offering efficient and sustainable solutions for gas separation and storage, MOFs can pave the way for a cleaner and more sustainable future. Metal-organic framework ; Context (archaeology) ; Nanotechnology ; Gas separation ; Transformative learning ; Sustainability ; Computer science ; Biochemical engineering ; Risk analysis (engineering) ; Adsorption ; Materials science ; Business ; Engineering ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Enhanced Oil Recovery Techniques
Authors: Zahra Al-Timimi | Zeina J. Tammemi
Source: Journal of Sustainable Materials Processing and Management (article, 2023-05-07)
Field: Materials Science — Polymers and Plastics

Analyzing the Heat Transfer Rate of Nanostructures of Poly (Methyl Methacrylate) / Al2O3 Utilizing Molecular Dynamics Simulations The main methods for preventing fires are physical, chemical, or a combination of the two. One of the main thermophysical characteristics that connect the chemical structure is thermal diffusivity. The relationship between heat transport as well as heat resistance has been thoroughly established in the literature. Heat transmission can also be connected to various fire-retardant characteristics, like maximal heat release or time to ignite, which rank among the most crucial factors in defining the potential fire danger of a specific material. The thermal stability, as well as fire-retardant qualities of polymers, are enhanced by metal oxides. In the present investigation, simulations of molecular dynamics constructed using the single atom approach was used to examine the consequence of Al2O3nanoparticles on thermal transfer of isotactic polymethyl methacrylate. Capacity, density, and thermal transfer were studied in the 300-700 K range to examine the heat transfer rate of poly (methyl methacrylate) besides poly (methyl methacrylate)/Al2O3nanocomposite. It is possible to calculate heat capacity using fluctuating characteristics. Conductivity was calculated through a non-equilibrium modeling simulation using Fourier's law. The thermal diffusivity of the poly (methyl methacrylate) with the thermal conductivity is increased by over ten times by the alumina nanoparticles, which also enhances the Tg by around 10 K The results show that the Al2O3nanoparticles increase a transition temperature of glass; conductivity, in addition diffusivity of the poly (methyl methacrylate) while decreasing the heat capacity. Thermal diffusivity ; Materials science ; Thermal conductivity ; Heat capacity ; Methyl methacrylate ; Glass transition ; Molecular dynamics ; Methacrylate ; Heat transfer ; Polymer ; Poly(methyl methacrylate) ; Chemical engineering ; Thermodynamics ; Polymer chemistry ; Composite material ; Chemistry ; Computational chemistry ; Monomer Flame retardant materials and properties ; Fire dynamics and safety research ; Polymer Nanocomposites and Properties
Authors: M Karplus | W Miller | E Neher | H Schwarz | J Simons | G Somorjai | R Zare | B Albinsson | H Kondoh | J Zhang | C Adamo | M Devries | C Diaz | S George | D Ghosh | K Holmberg | G Meijer | G Patwari | M Rodgers | S Sampath | M Suhm | A Troisi | Jason Greenwood | Ian Williams | Antoine Comby | Dominique Descamps | phane Ste | Emmanuel Petit | Morgan Valzer | Laurent Wloch | Pouyse | Ste phane Quideau | Jana Bockova | Cornelia Meinert | Vale rie Blanchet | Baptiste Fabre | Yann Mairesse | Alex Mort | Fan Xie | Arsh Hazrah | Yunjie Xu | Johal Ruiz | Josephine Loricco | Laurent Soule | Marta Castell | Axelle Gre lard | Brice Kauffmann | Erick Dufourc | Bruno Deme | Florence Popowycz | Judith Peters | Kazuki Kato | Masami Hara | Nobuyoshi Koga | P Abramov | O Ivankov | A Mostert | K Motovilov ; Alexandar | L Hansen | Rafael Bru | ; Abena | A Williams | Robert Emmett | Mark Roberts | Dino Costa | Gianpietro Malescio | Chang Bo | Runjin Wu | Florian Shijia | ; Pabst | L Brittany | Dina Bonnett | Sheyfer | Jacy Pubudu ; Cristian Celis-Barros | Travis Conrad | Jeffrey Grimes | Brian Mclachlan | Andrew Rotermund | Stephen Cook | Mezyk | Ghods Parisa | ; Ghasemabadi | J Graham | Maria Bodwell | Travis Demireva | Qun Fridgen ; Wang | Zhimin Zhang | Xiaofang Wu | Kai Li | Yuzhi Zhang | Jianzhong Song | Lili Fan | * Chuan-Kui Lin | * Wang | Zhongjie Wang
Source: Physical Chemistry Chemical Physics (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Contents list Permissions Request permissions Contents list Phys. Chem. Chem. Phys., 2023, 25, 16163 DOI: 10.1039/D3CP90131A This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given. Read more about how to correctly acknowledge RSC content. Acknowledgement ; Chromatin structure remodeling (RSC) complex ; Attribution ; Computer science ; Physics ; Library science ; Chemistry ; Computer security ; Psychology ; Social psychology Luminescence Properties of Advanced Materials ; Quantum Dots Synthesis And Properties ; Advanced Photocatalysis Techniques
Authors: Chun Wang | Han Jiao | Yinbo Yang | Lihong Wei | Ping Na
Source: Research Square (preprint, 2023-01-19)
Field: Chemistry — Inorganic Chemistry

Reaction route, mechanism, and procedure of the photoredox of U(Ⅵ) and Sb(Ⅲ) using a Fe 3 O 4 /TiO 2 /g-C 3 N 4 heterojunction nano- photocatalyst under visible sunlight Abstract Magnetic Fe 3 O 4 /TiO 2 /g-C 3 N 4 , as a stable and recyclable ternary two-layer heterojunction nano-photocatalyst, has been synthesized to integrate the merits of each which can remove U(Ⅵ) and Sb(Ⅲ) through responding to almost full-wave band of visible of sunlight. Meanwhile through the combination of actual tests (free radical trapping tests), characterization (XRD, FT-IR, Raman, XPS, EXAFS and EPR) and theoretical calculations structure optimization, band structures, TDOS, electrostatic potential, charge density difference and Bader charge analysis) revealed reaction route, catalytic mechanism and reaction procedure of this photocatalytic reaction. It was found that the adsorption process took place between TiO 2 / g-C 3 N 4 heterostructure in the form of (C 3 )–N–U(Ⅵ)–O 2c –Ti and N…Sb(Ⅲ)–O 2c –Ti where N (g-C3N4) and O (TiO 2) played decisive roles. The built-in electric field and electronic structure motivated TiO 2 and g-C 3 N 4 to accumulate a large amount of e - to reduce U(Ⅵ) and h + to oxidize Sb(Ⅲ) respectively, and completed the light-induced redox reaction by making full use of the e - , • OH and O 2 • ⁻ produced by photoexcited carriers which were difficult to recombine, finally, heterojunction complexes of (C 3 )–N–U(Ⅳ)–O 2c –Ti, C=N–U(Ⅳ)–O 2c –Ti and N…Sb(Ⅴ)–O 2c –Ti were formed. Moreover, the two-way effect of O 2 • ⁻ proved that the redox of U(Ⅵ) and Sb(Ⅲ) had a coupling relationship. In addition, Fe 3 O 4 /TiO 2 /g-C 3 N 4 prevented the damage of Fe 3 O 4 's photodissolution to its structure while Fe 3 O 4 provided a new and interrelated path for the redox of U(Ⅵ) and Sb(Ⅲ). Photocatalysis ; Heterojunction ; X-ray photoelectron spectroscopy ; Materials science ; Redox ; Ternary operation ; Visible spectrum ; Raman spectroscopy ; Catalysis ; Band gap ; Electron paramagnetic resonance ; Reaction mechanism ; Adsorption ; Photochemistry ; Physical chemistry ; Chemistry ; Optoelectronics ; Physics ; Nuclear magnetic resonance ; Optics ; Organic chemistry Radioactive element chemistry and processing ; Advanced Photocatalysis Techniques ; Nuclear materials and radiation effects
Authors: Tai Min | Tao Li | Yongyi Wu | Guoliang Yu | Shengxian Li | Yifeng Ren | Yadong Liu | Jiarui Liu | Hao Feng | Yu Deng | Mingxing Chen | Zhenyu Zhang
Source: Research Square (preprint, 2023-11-09)
Field: Materials Science — Materials Chemistry

Realization of sextuple polarization states and interstate switching in antiferroelectric CuInP2S6 Antiferroelectricity ; Realization (probability) ; Polarization (electrochemistry) ; Physics ; Chemistry ; Mathematics ; Quantum mechanics ; Ferroelectricity Solid-state spectroscopy and crystallography ; 2D Materials and Applications ; Advanced Condensed Matter Physics
Authors: Hagen Muenkler | Hubert Misztela | Michal Pikusa | Marwin Segler | Nadine Schneider | Krzysztof Maziarz
Source: arXiv (Cornell University) (preprint, 2023-05-04)
Field: Materials Science — Materials Chemistry

Are VAEs Bad at Reconstructing Molecular Graphs? Many contemporary generative models of molecules are variational auto-encoders of molecular graphs. One term in their training loss pertains to reconstructing the input, yet reconstruction capabilities of state-of-the-art models have not yet been thoroughly compared on a large and chemically diverse dataset. In this work, we show that when several state-of-the-art generative models are evaluated under the same conditions, their reconstruction accuracy is surprisingly low, worse than what was previously reported on seemingly harder datasets. However, we show that improving reconstruction does not directly lead to better sampling or optimization performance. Failed reconstructions from the MoLeR model are usually similar to the inputs, assembling the same motifs in a different way, and possess similar chemical properties such as solubility. Finally, we show that the input molecule and its failed reconstruction are usually mapped by the different encoders to statistically distinguishable posterior distributions, hinting that posterior collapse may not fully explain why VAEs are bad at reconstructing molecular graphs. Computer science ; Generative grammar ; Encoder ; Artificial intelligence ; Sampling (signal processing) ; Generative model ; Machine learning ; Algorithm ; Term (time) ; Theoretical computer science ; Pattern recognition (psychology) ; Computer vision ; Physics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Kat Nykiel | Alejandro Strachan
Source: arXiv (Cornell University) (preprint, 2023-07-26)
Field: Materials Science — Materials Chemistry

High-Throughput Density Functional Theory Screening of Double Transition Metal MXene Precursors MXenes are an emerging class of 2D materials of interest in applications ranging from energy storage to electromagnetic shielding. MXenes are synthesized by selective etching of layered bulk MAX phases into sheets of 2D MXenes. Their chemical tunability has been significantly expanded with the successful synthesis of double transition metal MXenes. While knowledge of the structure and energetics of double transition metal MAX phases is critical to designing and optimizing new MXenes, only a small subset of these materials been explored. We present a comprehensive dataset of key properties of MAX phases obtained using density functional theory within the generalized gradient approximation exchange-correlation functionals. Energetics and structure of 8,712 MAX phases have been calculated and stored in a queryable, open database hosted at nanoHUB. MXenes ; Density functional theory ; MAX phases ; Materials science ; Transition metal ; Energetics ; Chemical physics ; Electromagnetic shielding ; Throughput ; Nanotechnology ; Computational chemistry ; Chemistry ; Computer science ; Physics ; Thermodynamics ; Carbide MXene and MAX Phase Materials ; 2D Materials and Applications ; Graphene research and applications
Authors: Antonio Carnevali | M. Rosa Palacín | Clare P. Grey | Alejandro A. Franco
Source: ChemRxiv (preprint, 2023-10-17)
Field: Materials Science — Materials Chemistry

VOLTA: a tool for battery screening bridging the gap between virtual electrode materials and practical applications We present a battery screening Python pipeline, VOLTA. It allows for a novel battery active material explorative workflow, prioritizing the cell level performance indicators, such as cell capacity and voltage profile. This is achieved by the construction of a starting dataset of both observed and virtual active materials from the Materials Project, the implementation of the physics-based ARTISTIC project pipeline for the assessment of practical electrode properties like porosity and thickness, and the coupling of the electrodes into virtual cells, whose figures of merit are calculated, like voltage and capacity. The screening can be conducted by applying filters to these cell-level properties, achieving an indirect selection of the most suitable active materials. The approach is validated through comparison to current commercial battery technology, and we demonstrate that VOLTA is able to identify promising electrode materials for high energy batteries, like the well-known LiCoO2, LiNiO2 and graphite. We also illustrate a case-study, where the pipeline is used to identify suitable low-voltage, realistic virtual batteries obtained by combining entries of the Materials Project battery database (a battery revealing type of task). Pipeline (software) ; Computer science ; Battery (electricity) ; Electrode ; Bridging (networking) ; Workflow ; Voltage ; Materials science ; Electrical engineering ; Engineering ; Chemistry ; Database ; Physics ; Operating system Machine Learning in Materials Science ; Advancements in Battery Materials ; Advanced Battery Technologies Research
Authors: Shinya Akatsuka | M. Sakano | Takao A. Yamamoto | Takuya Nomoto | Ryotaro Arita | Ryogo Murata | T. Sasagawa | Kenji Watanabe | T. Taniguchi | Miho Kitamura | Koji Horiba | K. Sugawara | S. Souma | T. Sato | Hiroshi Kumigashira | Keisuke Shinokita | Hao Wang | Kazunari Matsuda | Satoru Masubuchi | T. Machida | K. Ishizaka
Source: arXiv (Cornell University) (preprint, 2023-09-27)
Field: Materials Science — Materials Chemistry

180$^\circ$-twisted bilayer ReSe$_2$ as an artificial noncentrosymmetric semiconductor We have fabricated a 180$^\circ$-twisted bilayer ReSe$_2$ by stacking two centrosymmetric monolayer ReSe$_2$ flakes in opposite directions, which is expected to lose spatial inversion symmetry. By the second harmonic generation and angle-resolved photoemission spectroscopy, we successfully observed spatial inversion symmetry breaking and emergent band dispersions. The band calculation shows the finite lifting of spin degeneracy (~50 meV) distinct from natural monolayer and bilayer ReSe$_2$. Our results demonstrate that the spin-momentum locked state, which leads to spintronic functions and Berry-curvature-related phenomena, can be realized even with the stacking of centrosymmetric monolayers. Point reflection ; Condensed matter physics ; Monolayer ; Berry connection and curvature ; Bilayer ; Curvature ; Stacking ; Physics ; Spintronics ; Semiconductor ; Materials science ; Chemistry ; Quantum mechanics ; Nanotechnology ; Ferromagnetism ; Geometry ; Nuclear magnetic resonance ; Geometric phase 2D Materials and Applications ; Machine Learning in Materials Science