jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Andreas Schmidt | Julia Rienmüller | Florian Weigend | Stefanie Dehnen
Source: Angewandte Chemie International Edition (article, 2024-10-08)
Field: Chemistry — Inorganic Chemistry

Affecting Charges and Structures of {Bi<sub>6</sub>} Architectures by 12‐Electron Transition Metal Fragments Molecules based on polyatomic bismuth substructures are currently attracting a lot of attention owing to this heavy and essentially non-toxic element's uncommon chemical and physical properties, which include unprecedented bonding properties. Hexaatomic {Bi<sub>6</sub>} substructures that underly more complex cluster structures were recently reported to adopt different structures or exhibit different structural details as a consequence of the charge of the {Bi<sub>6</sub>} unit. This leads to either crown-shaped cycles for a nominal Bi<sub>6</sub> <sup>6-</sup> or differently distorted trigonal prisms for compositions close to Bi<sub>6</sub> <sup>2-</sup>. It was predicted by quantum chemistry that Bi<sub>6</sub> <sup>4-</sup> should adopt a distinctly distorted boat-like shape, yet a corresponding compound has remained elusive. Here, we report a proof of this assumption by the synthesis of [K(crypt-222)]<sub>2</sub>[Bi<sub>6</sub>{Zn(hmds)}<sub>2</sub>] ⋅ 1.5THF (1), comprising a bimetallic [Bi<sub>6</sub>{Zn(hmds)}<sub>2</sub>]<sup>2-</sup> cluster that fulfills the prediction for the geometric and electronic structure of the missing link (crypt-222=4,7,13,16,21,24-hexaoxa-1,10-diazabicyclo-[8.8.8]hexa-cosane, hmds=hexamethyldisilazanid). A detailed quantum chemical study shows how the nature of Lewis-acidic transition metal complexes-in particular, 12-electron fragments-control and fine-tune the resulting {Bi<sub>6</sub>} architectures in accordance with the degree of electron-withdrawal from the polybismuthide core. Chemistry ; Bismuth ; Bimetallic strip ; Transition metal ; Crystallography ; Electron counting ; Cluster (spacecraft) ; Molecule ; Electron ; Chemical physics ; Nanotechnology ; Metal ; Materials science ; Physics ; Organic chemistry ; Computer science Synthesis and characterization of novel inorganic/organometallic compounds ; Inorganic Chemistry and Materials ; Inorganic Fluorides and Related Compounds
Authors: Massimiliano Lupo Pasini | Jong Youl Choi | Kshitij Mehta | Pei Zhang | David W. Rogers | Jonghyun Bae | Khaled Z. Ibrahim | Ashwin M. Aji | Karl W. Schulz | Jordà Polo | Prasanna Balaprakash
Source: arXiv (Cornell University) (preprint, 2024-06-12)
Field: Materials Science — Materials Chemistry

Scalable Training of Trustworthy and Energy-Efficient Predictive Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN We present our work on developing and training scalable, trustworthy, and energy-efficient predictive graph foundation models (GFMs) using HydraGNN, a multi-headed graph convolutional neural network architecture. HydraGNN expands the boundaries of graph neural network (GNN) computations in both training scale and data diversity. It abstracts over message passing algorithms, allowing both reproduction of and comparison across algorithmic innovations that define nearest-neighbor convolution in GNNs. This work discusses a series of optimizations that have allowed scaling up the GFMs training to tens of thousands of GPUs on datasets consisting of hundreds of millions of graphs. Our GFMs use multi-task learning (MTL) to simultaneously learn graph-level and node-level properties of atomistic structures, such as energy and atomic forces. Using over 154 million atomistic structures for training, we illustrate the performance of our approach along with the lessons learned on two state-of-the-art United States Department of Energy (US-DOE) supercomputers, namely the Perlmutter petascale system at the National Energy Research Scientific Computing Center and the Frontier exascale system at Oak Ridge Leadership Computing Facility. The HydraGNN architecture enables the GFM to achieve near-linear strong scaling performance using more than 2,000 GPUs on Perlmutter and 16,000 GPUs on Frontier. Foundation (evidence) ; Scalability ; Computer science ; Graph ; Artificial intelligence ; Theoretical computer science ; Geography ; Archaeology ; Database Machine Learning in Materials Science ; Fuel Cells and Related Materials
Authors: Nils Bäumer | Shiho Yamada | Soichiro Ogi | Shigehiro Yamaguchi
Source: ChemRxiv (preprint, 2024-11-06)
Field: Chemistry — Organic Chemistry

Interfacing Flexible Design and Social Self-Sorting Enables Comprehensive Control over Photophysical and Self-Assembly Properties of Supramolecular Polymers Supramolecular self-assembly offers an intriguing approach to construct microarchitectures, which combine properties of their molecular constituents with dynamic supramolecular features. Control over intermolecular interactions and their resulting properties can sometimes be achieved by targeted design. However, it is often unfeasible to transfer the insights gained from a specific supramolecular synthon to another chromophore without tedious synthetic work guided by trial and error. Herein we demonstrate how a flexible molecular design approach enables access to a diverse library of photophysical properties, which can be further diversified by social self-sorting strategies using a second supramolecular building block as a modulator. By intercalation into the supramolecular polymer the modulator can disrupt interchromophore interactions and modulate the ensembles emissive properties across the visible color space by simply adjusting the ratio between the two building blocks. Furthermore, by combining a chromophore appended synthon with a different morphology than the modulator the mesoscopic size distribution of the co-assemblies can be modified to resemble either of its constituents. Finally, the thermodynamic stability of the modulated polymers can be adjusted by varying the amount of solubilizing alkyl chains in the ensemble. Crucially, this peripheral stabilization approach does not affect the engineered photophysical or supramolecular properties. Our results demonstrate how flexible molecular design enriched by a supramolecular modulator can offer access to a wide variety of photophysical properties and enable unique fine-tuning of various supramolecular properties. Interfacing ; Supramolecular chemistry ; Sorting ; Self-assembly ; Computer science ; Nanotechnology ; Supramolecular polymers ; Control (management) ; Self organisation ; Materials science ; Computer hardware ; Engineering ; Chemistry ; Artificial intelligence Polydiacetylene-based materials and applications ; Supramolecular Self-Assembly in Materials ; Advanced Polymer Synthesis and Characterization
Authors: Ezzatollah Najafi | Mohammad Janghouri | Soma Majedi
Source: Journal of the Iranian Chemical Society (article, 2024-11-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The crystal structure and optical characteristics of two tin(IV) anthracene-9-carboxylate complexes and their use in OLEDs Anthracene ; Carboxylate ; Tin ; OLED ; Crystal structure ; Crystallography ; Materials science ; Chemistry ; Photochemistry ; Stereochemistry ; Nanotechnology ; Organic chemistry Magnetism in coordination complexes ; Organic Light-Emitting Diodes Research ; Lanthanide and Transition Metal Complexes
Authors: Puhong Yi | Yue Xu | Hanlin Liu | Yuhua Hao | Mengdan Liu | Zhi‐Qiang Liu | Ya‐Ping Xue | Liqun Jin | Yu‐Guo Zheng
Source: Process Biochemistry (article, 2024-12-25)
Field: Chemistry — Organic Chemistry

Efficient kinetic resolution of D,L-phosphinothricin using an aminotransferase-mediated cascade Cascade ; Kinetic resolution ; Resolution (logic) ; Chemistry ; Chromatography ; Biology ; Biochemistry ; Computer science ; Artificial intelligence Chemical Reaction Mechanisms ; Organophosphorus compounds synthesis ; DNA and Nucleic Acid Chemistry
Authors: Shuya Nakata | Y. Mori | Shigenori Tanaka
Source: ChemRxiv (preprint, 2024-07-11)
Field: Materials Science — Materials Chemistry

Navigating Ultra-Large Virtual Chemical Spaces with Product-of-Experts Chemical Language Models Ultra-large virtual chemical spaces have emerged as a valuable resource for drug discovery, providing access to billions of make-on-demand compounds with high synthetic success rates. Chemical language models can potentially accelerate the exploration of these vast spaces through direct compound generation. However, existing models are not designed to navigate specific virtual chemical spaces and often overlook synthetic accessibility. To address this gap, we introduce product-of-experts (PoE) chemical language models, a modular and scalable approach to navigating ultra-large virtual chemical spaces. This method allows for controlled compound generation within a desired chemical space by combining a prior model pre-trained on the target space with expert and anti-expert models fine-tuned using external property-specific datasets. We demonstrate that the PoE chemical language model can generate compounds with desirable properties, such as those that favorably dock to the dopamine receptor D2 (DRD2) and are predicted to cross the blood-brain barrier (BBB), while ensuring that the majority of generated compounds are present within the target chemical space. Our results highlight the potential of chemical language models for navigating ultra-large virtual chemical spaces, and we anticipate that this study will motivate further research in this direction. The source code and data are freely available at https://github.com/shuyana/poeclm/. Chemical space ; Computer science ; Scalability ; Space (punctuation) ; Modular design ; Property (philosophy) ; Resource (disambiguation) ; Product (mathematics) ; Drug discovery ; Data science ; Database ; Programming language ; Chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Cell Image Analysis Techniques
Authors: K Suraj | Mamta Devi | Jampala Pasyanthi | Kaushik Kunte | Gourav Shukla | Premkumar Murugesan | Ajay Mohan | Katchala Nanaji | Bulusu V. Sarada | Sudhanshu Sharma | Swati Sharma | Mithun Radhakrishna
Source: The Journal of Physical Chemistry C (article, 2024-10-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Influence of Electrode Pore Size and Electrolyte on Carbon Aerogel Supercapacitors: Insights from Experimental Studies and Molecular Simulations This study investigates the enhancement of supercapacitor energy density by exploring the role of carbon aerogel (CA) electrode pore size and aqueous electrolyte compositions by employing a combination of experimental techniques and molecular dynamics simulations. Supercapacitors, known for their rapid charge–discharge cycles and longer lifespans, face the challenge of lower energy density compared to lithium-ion batteries. To address this, recent state-of-the-art advancements have focused on optimizing electrode architecture, such as hierarchical porous carbon structures, and fine-tuning electrolyte compositions to maximize ion-transport efficiency and capacitance. Our research integrates these modern strategies by leveraging high-fidelity 3D modeling of carbon electrode pores at different quench rates to guide the synthesis of CA electrodes with precise pore size distributions. We assessed the performance of these optimized electrodes in supercapacitor systems using cutting-edge electrolytes, including 3 M aqueous KOH and 1 M Na2SO4, both recognized in current research for their high ionic conductivity and compatibility with porous carbon materials. Notably, the KOH-based system demonstrated superior specific capacitance, attributed to the increased surface area and enhanced ion accessibility of K+ and OH– ions within the optimized CA structure. The specific capacitance values measured experimentally for the KOH system at 1 A/g (119 F/g) showed a strong correlation with molecular dynamics simulation predictions (128 F/g), underscoring the accuracy and predictive power of modern computational techniques in electrode design. Supercapacitor ; Electrolyte ; Aerogel ; Materials science ; Electrode ; Carbon fibers ; Chemical engineering ; Nanotechnology ; Composite material ; Electrochemistry ; Chemistry ; Physical chemistry ; Engineering Supercapacitor Materials and Fabrication ; Aerogels and thermal insulation ; Mesoporous Materials and Catalysis
Authors: Bei Hu | Xue-Jing Luo | Senda Su | Shu‐Ying Luo | Chunjiang Li | R. Zhang | Fu‐Pei Liang | Kai Wang
Source: Crystal Growth & Design (article, 2024-12-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Asymmetric Binuclear Dysprosium Single-Molecule Magnets Synthesized from a Peripheral-Protected Nonequivalent Chelation Strategy As a kind of special binuclear dysprosium single-molecule magnet ({Dy2}-SMM), the asymmetric {Dy2}-SMMs feature two Dy centers that locate in distinct ligand fields. Such an asymmetric structure allows to locally modulate a special part of the magnet while maintaining original features of other parts, thus favoring more delicate and targeted tuning of the single-ion anisotropy of the Dy center and magnetic interactions between Dy centers. Yet, they are still rare due to the difficulty in synthesis. Herein, we report three asymmetric {Dy2}-SMMs, namely, [Dy2(tmsa)(MeOsa)(H2O)2] (NO3)2·CH3OH (1), [Dy2(tmsa)(sa)2(H2O)]NO3 (2), and [Dy2(tmsa)(Fsa)(H2O)2] (NO3)2·5H2O·CH3OH (3), where H3tmsa, HMeOsa, Hsa, and HFsa represent tris[(3-methoxysalicylidene)aminoethyl]amine, 3-methoxysalicylaldehyde, salicylaldehyde, and 3-fluorinesalicylaldehyde, respectively. They were prepared by a peripheral-protected nonequivalent chelating strategy, wherein a single tmsa3– ligand uses two distinct chelating pockets to encapsulate two Dy ions while providing peripheral protection. Significantly, salicylaldehyde-based auxiliary ligands bearing different substituents, including HMeOsa, Hsa, and HFsa, have fine-tuned the local ligand fields of the Dy ions successfully. 1–3 thus show different slow magnetic relaxation behaviors, with the highest efficient energy barriers (Ueff) of 79, 154, and 110 K, respectively. This work provides an efficient strategy for the achievement of new asymmetric {Dy2}-SMMs and the fine-tuning of the relaxation behavior of these special SMMs. Dysprosium ; Ligand (biochemistry) ; Chelation ; Single-molecule magnet ; Chemistry ; Crystallography ; Molecule ; Salicylaldehyde ; Ion ; Relaxation (psychology) ; Magnet ; Magnetization ; Inorganic chemistry ; Receptor ; Magnetic field ; Organic chemistry ; Physics Magnetism in coordination complexes ; Lanthanide and Transition Metal Complexes ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Meng‐Nan Liu | Ben Liang | Huiyong Chen | Chengyi Dai | Qun‐Xing Luo | Long Xu | Jianbo Zhang | Xiaoxun Ma | Qingqing Hao
Source: ACS Applied Nano Materials (article, 2024-03-22)
Field: Chemistry — Inorganic Chemistry

Nanoplatelet Mordenite Zeolite with a Controlled Aspect Ratio: Implications for the Alkylation of Benzene with Benzyl Alcohol Modulating the anisotropic growth rate of zeolites to tailor their physicochemical properties holds significant promise across various fields, such as catalysis and adsorption. However, achieving this objective using commercially available small molecules remains a fascinating yet challenging task in zeolite crystallization, particularly for zeolites with a strong growth orientation. Herein, we demonstrate the synthesis of well-faceted nanoplatelet mordenite (MOR) zeolite with a thickness of 80 nm along the (100) direction in a low alkaline gel system utilizing tetraethylammonium hydroxide (TEAOH) and hexamethylenimine (HMI) as dual templates. Time-resolved analysis of precursor evolution reveals the unique crystallization pathway of in situ crystal transformation induced by the exchange of structure-directing agents. The dissolved species maintain some “memory” of MCM-56 due to the strong interaction between the silanol groups and HMI, which inhibits the attachment of incoming building units to the MOR phase and benefits the formation of nanoplatelet MOR. A comprehensive investigation into key factors influencing nanoplatelet MOR zeolite formation demonstrated that metastable MCM-56 and the crystallization rate play pivotal roles. Moreover, fine-tuning the crystallization rate allows customization of the crystal size and aspect ratio for nanoplatelet MOR zeolite. The catalytic performance of the nanoplatelet MOR zeolite in the alkylation of benzene with benzyl alcohol is enhanced compared to its bulk counterpart. Mordenite ; Alkylation ; Zeolite ; Benzene ; Benzyl alcohol ; Alcohol ; Materials science ; Chemistry ; Organic chemistry ; Catalysis Zeolite Catalysis and Synthesis ; Mesoporous Materials and Catalysis ; Catalysis and Oxidation Reactions
Authors: Tomáš Halenkovič | Jan Gutwirth | Stanislav Šlang | Radwan Chahal | Abdelali Hammouti | Joël Charrier | Petr Němec | Virginie Nazabal
Source: EPJ Web of Conferences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Rapid thermal annealing of chalcogenide thin films for mid-infrared sensing and nonlinear photonics The influence of rapid thermal annealing (RTA) onto chalcogenide Ge-Sb-Se thin films is reported, focusing on changes in optical properties. These materials possess broad mid-infrared transparency covering the most critical absorption bands for (bio)chemical sensing and high third-order optical nonlinearities for potential applications in nonlinear photonics. The parameters of the RTA process within this study include the annealing temperature, heating rate, and the two sample processing methods – one by placing the sample inside the graphite susceptor and the other by simply laying the sample onto the silicon wafer. Selenide thin films were found to undergo a shift of the absorption edge upon the RTA, resulting in an optical bandgap energy increase (bleaching effect) and a notable refractive index decrease. As a result of structural relaxation, such changes show a great potential of RTA in fine-tuning of optical performance of chalcogenide thin films and planar chalcogenide waveguides. The authors acknowledge the IBAIA (101092723) Horizon Europe project, the ANR AQUAE (ANR-21-CE04-0011-04) project of the French National Research Agency (ANR), and project No. 22-05179S of the Czech Science Foundation (GAČR) for financial support. Chalcogenide ; Photonics ; Infrared ; Annealing (glass) ; Optoelectronics ; Chalcogenide glass ; Materials science ; Thermal ; Thin film ; Engineering physics ; Nanotechnology ; Optics ; Physics ; Composite material ; Meteorology Phase-change materials and chalcogenides ; Chalcogenide Semiconductor Thin Films ; Photonic and Optical Devices
Authors: Lily Jiaxin Wan | Hanchen Ye | Jinghua Wang | Manvi Jha | Deming Chen
Source:  (article, 2024-06-28)
Field: Materials Science — Materials Chemistry

An Iteratively-refined Dataset for High-Level Synthesis Functional Verification through LLM-Aided Bug Injection This paper explores the application of Large Language Models (LLMs) in the domain of High-Level Synthesis (HLS) for hardware design and verification, focusing on functional verification challenges. The scarcity of open-source HLS codebases, especially those containing bugs, poses a significant challenge, as LLMs require extensive datasets for efficient fine-tuning and evaluation. To tackle this, we introduce an innovative bug injection methodology working with a new dataset that we curated from a wide range of open-source HLS benchmark suites. This dataset features over 1,500 designs, with both the version injected with bugs and the corresponding bug-free version. Our bug injection method synergizes In-Context Learning (ICL) with Retrieval Augmented Generation (RAG), and Chain of Thought (CoT). This approach significantly boosts the dataset’s overall validity rate for single-bug injections. We demonstrate our solution quality using GPT-4 Turbo for injecting either logic bugs or non-ideal pragmas (compiler directives) into HLS designs. For logic bugs, we achieve an 84.8% ratio for valid injection attempts. Furthermore, our approach maintains an 88.0% dataset validity rate (the valid bug injection rate). In addition, we also evaluate the quality of HLS pragma injections (focusing on non-ideal pragmas), and achieve a 74.0% attempt and an 87.9% valid injection ratio. Compared to brute-force prompting, our strategy yields a 20.4% and a 54.0% validity improvement for the bug and non-ideal pragma injection, respectively. The Chrysalis dataset is accessible at https://github.com/UIUC-ChenLab/Chrysalis-HLS. Computer science ; Programming language ; Software engineering Machine Learning in Materials Science
Authors: Suchona Akter | Yong Li | Min‐Bum Kim | Md Omar Faruque | Zhonghua Peng | Praveen K. Thallapally | Mohammad R. Momeni
Source: Langmuir (article, 2024-11-14)
Field: Chemistry — Inorganic Chemistry

Fine-Tuning Microporosity of Crystalline Vanadomolybdate Frameworks for Selective Adsorptive Separation of Kr from Xe Selective adsorptive capture and separation of chemically inert krypton (Kr) and xenon (Xe) noble gases with very low ppmv concentrations in air and industrial off-gases constitute an important technological challenge. Here, using a synergistic combination of experiment and theory, the microporous crystalline vanadomolybdates (MoVO<sub><i>x</i></sub>) as highly selective Kr sorbents are studied in detail. By varying the Mo/V ratios, we show for the first time that their one-dimensional (1D) pores can be fine-tuned for the size-selective adsorption of Kr over the larger Xe with selectivities reaching >100. Using extensive electronic structure calculations and grand canonical Monte Carlo simulations, the competition between Kr uptake with CO<sub>2</sub> and N<sub>2</sub> was also investigated. As most materials reported so far are selective toward the larger, more polarizable Xe than Kr, this work constitutes an important step toward robust Kr-selective sorbent materials. This work highlights the potential use of porous crystalline transition metal oxides as energy-efficient and selective noble gas capture sorbents for industrial applications. Separation (statistics) ; Adsorption ; Chemical engineering ; Materials science ; Chemistry ; Physical chemistry ; Computer science Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Radioactive element chemistry and processing