jablonkagroup/rise_ai_scientists huggingface dataset:
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, 10191 DOI: 10.1039/D3CP90093B 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 ; Library science ; Physics ; Chemistry ; Computer security ; Psychology Chemical and Physical Properties of Materials ; Advanced Physical and Chemical Molecular Interactions ; Machine Learning in Materials Science
Authors: Christina Humer | Rachel Nicholls | Henry Heberle | Moritz Heckmann | Michael Pühringer | Thomas Wolf | Maximilian Lübbesmeyer | Julian Heinrich | Julius Hillenbrand | Giulio Volpin | Marc Streit
Source: ChemRxiv (preprint, 2023-12-21)
Field: Materials Science — Materials Chemistry

CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space Chemical reaction optimization (RO) is an iterative process that results in large and high-dimensional datasets. Current tools only allow for limited analysis and understanding of parameter spaces, making it hard for scientists to review or follow changes throughout the process. With the recent emergence of using artificial intelligence (AI) models to aid RO, another level of complexity was added. It is critical to assess the quality of a model’s prediction and understand its decision to aid human-AI collaboration and trust calibration. To that regard, we propose CIME4R—an open-source interactive web application for analyzing RO data and AI predictions. CIME4R supports users in (i) comprehending a reaction parameter space, (ii) investigating how the RO process developed over iterations, (iii) identifying critical factors of a reaction, and (iv) understanding model predictions. This aids users in making informed decisions during the RO process and helps them review an RO process in retrospect, especially in the realm of AI-guided RO. CIME4R aids decision-making through the interaction between humans and AI by combining the strengths of expert experience and high computational precision. We developed and tested CIME4R together with domain experts and verified its usefulness with three case studies. With CIME4R the experts were able to produce valuable insights from past RO campaigns and make informed decisions on which experiments to perform next. We believe that CIME4R is the beginning of an open-source community project that improves the workflow of scientists working in the reaction optimization domain. Workflow ; Computer science ; Process (computing) ; Iterative and incremental development ; Domain (mathematical analysis) ; Space (punctuation) ; Quality (philosophy) ; Artificial intelligence ; Data science ; Management science ; Machine learning ; Software engineering ; Mathematics ; Engineering ; Database Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Scientific Computing and Data Management
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, 13213 DOI: 10.1039/D3CP90108D 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: Chao Xu | Emily Mazeau | Richard H. West
Source: ChemRxiv (preprint, 2023-12-21)
Field: Materials Science — Materials Chemistry

Implementing the Blowers-Masel Approximation to Scale Activation Energy Based on Reaction Enthalpy in Mean-field Micro-kinetic Modeling for Catalytic Methane Partial Oxidation Mean-field micro-kinetic modeling is a powerful tool for catalyst design and the simulation of catalytic processes. The reaction enthalpies in a micro-kinetic model often need to be adjusted when changing species’ binding energies to model differ- ent catalysts, when performing thermodynamic sensitivity analyses, and when fitting experimental data. When altering reaction enthalpies, the activation energies should also be reasonably altered, to ensure realistic reaction rates. The Blowers-Masel ap- proximation (BMA) relates the reaction barrier to the reaction enthalpy. Unlike the Brønsted-Evans-Polani (BEP) relationship, the BMA requires less data because only one parameter, the intrinsic activation energy, needs to be determined. We validate this novel application of BMA relations to model surface reactions by comparing against density functional theory (DFT) data taken from literature. By incorporating the BMA rate description into the open-source Cantera software we enable a new work- flow, demonstrated herein, allowing rapid screening of catalysts using linear scaling relationships (LSRs) and BMA kinetics within the process simulation software. For demonstration purposes, a catalyst screening for catalytic methane partial oxidation (CMPO) on 81 hypothetical metals is conducted. We compare the results with and without BMA-corrected rates. The heat maps of various descriptors (e.g. CH4 conver- sion, syngas yield) show that using BMA rates instead of Arrhenius rates (with constant activation energies) changes which metals are most active. Heat maps of sensitivity analyses can help identify which reactions or species are most influential in shaping the descriptor map patterns. Our findings indicate that while using BMA-adjusted rates didn't markedly affect the most sensitive reactions, it did change the most influential species. Activation energy ; Arrhenius equation ; Catalysis ; Thermodynamics ; Kinetic energy ; Enthalpy ; Chemistry ; Reaction rate constant ; Methane ; Reaction rate ; Yield (engineering) ; Physical chemistry ; Order of reaction ; Kinetics ; Physics ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Electrocatalysts for Energy Conversion
Authors: Hiroyuki Matsuda | Kiyofumi Kurihara | Katsumi Tochigi
Source: JOURNAL OF CHEMICAL ENGINEERING OF JAPAN (article, 2023-11-29)
Field: Materials Science — Materials Chemistry

Evaluation of Solid–Liquid Equilibria for Ternary Pharmaceutical Compound + Water + Cyclodextrin or Its Derivative Systems with Wilson and Modified Chrastil Models The solid-liquid equilibria (SLE) of ternary mixtures of pharmaceutical compound water solid cosolvent cyclodextrin (CD) were calculated using the Wilson equation as the activity coefficient model, to evaluate the cosolvency of CD for poorly water-soluble pharmaceutical compounds. The pharmaceutical compounds were etodolac and famotidine. The cosolvents were CD and its derivatives, i.e., a-CD, b-CD, 2-HP-b-CD, 2-HE-b-CD, and M-b-CD. A simple group contribution method was constructed to predict the enthalpy of fusion of the CDs, which is needed to calculate the SLE of the system containing CD. The binary interaction parameters in the Wilson equation K ij were determined from solubility data for the pharmaceutical compounds and CDs in pure water and from experimental ternary data. The calculated solubilities were compared with those obtained using the modified Chrastil model. The proposed method gave almost the same calculation accuracies to the modified Chrastil model using fewer fitting parameters. Chemistry ; Ternary operation ; Solubility ; Cyclodextrin ; Thermodynamics ; Chromatography ; Physical chemistry Crystallization and Solubility Studies ; Analytical Chemistry and Chromatography ; Drug Solubulity and Delivery Systems
Authors: Niklas Dobberstein | Astrid Maaß | Jan Hamaekers
Source: arXiv (Cornell University) (preprint, 2023-11-24)
Field: Materials Science — Materials Chemistry

LLamol: A Dynamic Multi-Conditional Generative Transformer for De Novo Molecular Design Generative models have demonstrated substantial promise in Natural Language Processing (NLP) and have found application in designing molecules, as seen in General Pretrained Transformer (GPT) models. In our efforts to develop such a tool for exploring the organic chemical space in search of potentially electro-active compounds, we present "LLamol", a single novel generative transformer model based on the LLama 2 architecture, which was trained on a 13M superset of organic compounds drawn from diverse public sources. To allow for a maximum flexibility in usage and robustness in view of potentially incomplete data, we introduce "Stochastic Context Learning" as a new training procedure. We demonstrate that the resulting model adeptly handles single- and multi-conditional organic molecule generation with up to four conditions, yet more are possible. The model generates valid molecular structures in SMILES notation while flexibly incorporating three numerical and/or one token sequence into the generative process, just as requested. The generated compounds are very satisfactory in all scenarios tested. In detail, we showcase the model's capability to utilize token sequences for conditioning, either individually or in combination with numerical properties, making LLamol a potent tool for de novo molecule design, easily expandable with new properties. Generative grammar ; Computer science ; Transformer ; Security token ; Notation ; Artificial intelligence ; Generative model ; Robustness (evolution) ; Machine learning ; Natural language processing ; Theoretical computer science ; Engineering ; Chemistry ; Mathematics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Software Engineering Research
Authors: Linfeng Yu | Jianhua Xu | Chen Shen | Hongbin Zhang | Xiong Zheng | Huiming Wang | Zhenzhen Qin | Guangzhao Qin
Source: arXiv (Cornell University) (preprint, 2023-09-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Janus-graphene: a two-dimensional half-auxetic carbon allotropes with non-chemical Janus configuration The asymmetric properties of Janus two-dimensional materials commonly depend on chemical effects, such as different atoms, elements, material types, etc. Herein, based on carbon gene recombination strategy, we identify an intrinsic non-chemical Janus configuration in a novel purely sp$^2$ hybridized carbon monolayer, named as Janus-graphene. With the carbon gene of tetragonal, hexagonal, and octagonal rings, the spontaneous unilateral growth of carbon atoms drives the non-chemical Janus configuration in Janus-graphene, which is totally different from the chemical effect in common Janus materials such as MoSSe. A structure-independent half-auxetic behavior is mapped in Janus-graphene that the structure maintains expansion whether stretched or compressed, which lies in the key role of $p_z$ orbital. The unprecedented half-auxeticity in Janus-graphene extends intrinsic auxeticity into pure sp$^2$ hybrid carbon configurations. With the unique half-auxeticity emerged in the non-chemical Janus configuration, Janus-graphene enriches the functional carbon family as a promising candidate for micro/nanoelectronic device applications. Janus ; Graphene ; Materials science ; Carbon fibers ; Nanotechnology ; Janus particles ; Tetragonal crystal system ; Auxetics ; Chemical physics ; Monolayer ; Crystallography ; Composite material ; Chemistry ; Crystal structure ; Composite number Supercapacitor Materials and Fabrication ; Pickering emulsions and particle stabilization
Authors: Marten Ademmer | Po‐Hua Su | Lukas Dodell | Jakob Asenbauer | Markus Osenberg | André Hilger | Jeng‐Kuei Chang | Ingo Manke | Matthias Neumann | Volker Schmidt | Dominic Bresser
Source: arXiv (Cornell University) (preprint, 2023-06-21)
Field: Materials Science — Polymers and Plastics

Unveiling the impact of crosslinking redox-active polymers on their electrochemical behavior by 3D imaging and statistical microstructure analysis Polymer-based batteries offer potentially higher power densities and a smaller ecological footprint compared to state-of-the-art lithium-ion batteries comprising inorganic active materials. However, in order to benefit from this potential advantages, further research to find suitable material compositions is required. In the present paper, we compare two different electrode composites of poly(2,2,6,6-tetramethylpiperidinyloxy-4-ylmethacrylate) (PTMA) and CMK-8, one produced with and one without crosslinking the PTMA. The influence of both approaches on the corresponding electrodes is comparatively investigated using electrochemical measurements and statistical 3D microstructure analysis based on synchrotron X-ray tomography. A particular focus is put on the local heterogeneity in the coating and how the crosslinking influences the interaction between PTMA and CMK-8. It is shown that crosslinked PTMA--compared to its non-crosslinked counterpart--exhibits a more heterogeneous microstructure and, furthermore, leads to better surface coverage of CMK-8, larger pores and shorter transportation pathways through the latter. These changes improve the electrochemical properties of the electrode. Microstructure ; Electrochemistry ; Electrode ; Polymer ; Materials science ; Coating ; Lithium (medication) ; Redox ; Synchrotron ; Chemical engineering ; Nanotechnology ; Composite material ; Chemistry ; Metallurgy ; Physical chemistry ; Optics ; Physics Conducting polymers and applications ; Advancements in Battery Materials ; Supercapacitor Materials and Fabrication
Authors: Wang Yiqing | Shihua Zhong
Source: Research Square (preprint, 2023-11-21)
Field: Materials Science — Materials Chemistry

Fabrication of weakly basic-functionalized poly (Styrene Co-Maleic Anhydride) hyper-cross-linked resins for the efficient adsorption organic acid Abstract Herein, four hyper-cross-linked amide resins (DMDs) were synthesized by suspension polymerization and amination reaction. In the process of suspension polymerization, divinylbenzene (DVB) and maleic anhydride (MAH) with different feed ratios generated resins (DMHs) with different pore structures. After N, N'-dimethyl-1,3-propanediamine (DMAPA) chemical functionalization of DMH, the weak base exchange capacity of the product resins significantly increased, with the values of 1.01 mmol/g (DMD1), 1.15 mmol/g (DMD2), 1.22 mmol/g (DMD3), and 1.34 mmol/g (DMD4). Salicylic acid (SA), benzoic acid (BA), gallic acid (GA), and phenol (PHE) were utilized as the adsorbates to investigate batch adsorption. At 288 K, the maximum capacity ( q max ) of SA, BA, and GA on the DMD4 were 181.7 mg/g, 143.8 mg/g, and 145.2 mg/g, respectively. The adsorption of BA and GA attained the equilibrium within 100 min, and the kinetic data can be described by the pseudo-second-order (PSO) rate model. This universal synthetic method is of great importance for the fabrication of some other functionalized hyper-cross-linked polymers, and this strategy was universal for the weakly basic functionalization of some other resins. Divinylbenzene ; Maleic anhydride ; Benzoic acid ; Adsorption ; Suspension polymerization ; Surface modification ; Polymer chemistry ; Amination ; Styrene ; Copolymer ; Amide ; Chemistry ; Chemical modification ; Polymer ; Desorption ; Maleic acid ; Materials science ; Organic chemistry ; Catalysis Covalent Organic Framework Applications ; Adsorption and biosorption for pollutant removal ; Chemical Synthesis and Characterization
Authors: Jiao Huang | Qianli Xing | Jinglong Ji | Bo Yang
Source: arXiv (Cornell University) (preprint, 2023-12-03)
Field: Materials Science — Materials Chemistry

PerCNet: Periodic Complete Representation for Crystal Graphs Crystal material representation is the foundation of crystal material research. Existing works consider crystal molecules as graph data with different representation methods and leverage the advantages of techniques in graph learning. A reasonable crystal representation method should capture the local and global information. However, existing methods only consider the local information of crystal molecules by modeling the bond distance and bond angle of first-order neighbors of atoms, which leads to the issue that different crystals will have the same representation. To solve this many-to-one issue, we consider the global information by further considering dihedral angles, which can guarantee that the proposed representation corresponds one-to-one with the crystal material. We first propose a periodic complete representation and calculation algorithm for infinite extended crystal materials. A theoretical proof for the representation that satisfies the periodic completeness is provided. Based on the proposed representation, we then propose a network for predicting crystal material properties, PerCNet, with a specially designed message passing mechanism. Extensive experiments are conducted on two real-world material benchmark datasets. The PerCNet achieves the best performance among baseline methods in terms of MAE. In addition, our results demonstrate the importance of the periodic scheme and completeness for crystal representation learning. Crystal (programming language) ; Representation (politics) ; Completeness (order theory) ; Graph ; Leverage (statistics) ; Dihedral angle ; Theoretical computer science ; Computer science ; Benchmark (surveying) ; Algorithm ; Mathematics ; Molecule ; Artificial intelligence ; Physics ; Mathematical analysis Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Graph Neural Networks
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, 20765 DOI: 10.1039/D3CP90167J 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 ; Attribution ; Chromatin structure remodeling (RSC) complex ; Computer science ; Library science ; Chemistry ; Psychology ; Computer security ; Social psychology Luminescence Properties of Advanced Materials ; Quantum Dots Synthesis And Properties ; Catalytic Processes in Materials Science
Authors: Yiming Zhang | Yongjia Xu | Qing Huang | Shiyu Du | Mian Li | Youbing Li | Zeyu Mao | Qi Han
Source: arXiv (Cornell University) (preprint, 2023-07-18)
Field: Materials Science — Materials Chemistry

Structure maps for MAX phases formability revisited The extraordinary chemical diversity of MAX phases raises the question of how many and which novel ones are yet to be discovered. The conventional schemes rely either on executions of well designed experiments or elaborately crafted calculations; both of which have been key tactics within the past several decades that have yielded many of important new materials we are studying and using today. However, these approaches are expensive despite the emergence of high throughput automations or evolution of high speed computers. In this work, we have revisited the in prior proposed light duty strategy, i.e. structure mapping, for describing the genomic conditions under which one MAX phase could form; that allow us to make successful formability and non formability separation of MAX phases with a fidelity of 95.5%. Our results suggest that the proposed coordinates, and further the developed structure maps, are able to offer a useful initial guiding principles for systematic screenings of potential MAX phases and provide untapped opportunities for their structure prediction and materials design. Formability ; Computer science ; Fidelity ; Key (lock) ; Theoretical computer science ; Algorithm ; Materials science MXene and MAX Phase Materials ; Advanced biosensing and bioanalysis techniques ; Dendrimers and Hyperbranched Polymers
Authors: Marko D. Radovanović | Ignjat P. Filipović | Maja B. Djukić | M. S. Ristić | Matija Zlatar | Zoran D. Matović
Source:  (article, 2023-01-01)
Field: Chemistry — Organic Chemistry

Relativistic DFT calculation and their effect on the accuracy of results This study explores the significance of density functional theory (DFT) calculations with relativistic effects for two ethylenediaminetetraacetate (edta) type complexes: trans(O5)-[M(eddadp)]- (M = Rh3+, Co3+). Relativistic effects affect the electronic structure of a molecule and, thus, its chemical and spectroscopic properties. With the use of scalar relativistic corrections (SR-ZORA), as implemented in the ADF package, with the B3LYP functional, the TZP basis set and the COSMO solvation model, structural analyses show improved predictions for the geometries of both complexes. In the case of the Rh3+ complex, the differences in metal-ligand bond lengths with and without the relativistic effects were small. In the case of the Co3+ complex, the changes in metal-ligand bond lengths due to the relativistic effects were slightly more pronounced. Compared to experimental values, excitation energies are better when including relativistic corrections, especially for the Rh3+ complex. These results indicate the importance of relativistic DFT calculations for heavy element compounds. Relativistic quantum chemistry ; Density functional theory ; Solvation ; Scalar (mathematics) ; Bond length ; Molecule ; Metal ; Chemistry ; Ligand (biochemistry) ; Computational chemistry ; Physics ; Atomic physics ; Quantum mechanics ; Geometry ; Mathematics Free Radicals and Antioxidants ; Metal complexes synthesis and properties ; Advanced Chemical Physics Studies
Authors: Donald C. Salvador
Source: International Journal of Advanced Research in Science Communication and Technology (article, 2023-07-30)
Field: Materials Science — Materials Chemistry

Corrosion Resistance of Welded Structures: Materials Selection and Coating Solutions This study addresses the critical concern of corrosion resistance within welded structures by exploring the dynamic interplay between distinct materials and coatings. Through a meticulous examination of stainless steel, aluminum, and titanium specimens treated with varying coating types, the research illuminates the intricate relationship connecting corrosion behavior and the collaborative effects of materials and coatings. The outcomes underscore the pivotal significance of custom-tailored materials selection and appropriate coating solutions in elevating corrosion resistance. Particularly noteworthy is the exceptional corrosion resistance observed in titanium specimens coated with advanced composite solutions, alongside the augmented performance of stainless steel specimens with the same treatment. However, the susceptibility of aluminum specimens to corrosion is evident, with some mitigation offered by advanced composite coatings. These revelations furnish tangible direction for sectors such as construction, manufacturing, and infrastructure development, aiding in the formulation of resilient welded structures equipped to surmount corrosive challenges. By advancing the comprehension of corrosion resistance mechanisms, this research contributes to the perpetual advancement of engineering solutions, safeguarding the enduring integrity and dependability of pivotal infrastructure Corrosion ; Materials science ; Coating ; Metallurgy ; Welding ; Composite material Corrosion Behavior and Inhibition ; Material Selection and Properties ; Welding Techniques and Residual Stresses