jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jim Boelrijk | Stef R.A. Molenaar | Tijmen S. Bos | Tina A. Dahlseid | Bernd Ensing | Dwight R. Stoll | Patrick Forré | Bob W.J. Pirok
Source: ChemRxiv (preprint, 2024-02-19)
Field: Chemistry — Spectroscopy

Enhancing LC×LC separations through Multi-Task Bayesian Optimization Method development in comprehensive two-dimensional liquid chromatography (LC×LC) is a challenging process. The interdependencies between the two dimensions and the possibility of incorporating complex gradient profiles, such as multi-segmented gradients or shifting gradients, make trial-and-error method development time-consuming and highly dependent on user experience. Retention modeling and Bayesian optimization (BO) have been proposed as solutions to mitigate these issues. However, both approaches have their strengths and weaknesses. On one hand, retention modeling depends on effective peak tracking and accurate retention time and width predictions, becoming increasingly challenging for complex samples and advanced gradient assemblies. On the other hand, Bayesian optimization may require many experiments when dealing with many adjustable parameters, as in LC×LC. Therefore, in this work, we investigate the use of multi-task Bayesian optimization (MTBO), a method that can combine information from both retention modeling and experimental measurements. The algorithm was first tested and compared with BO using a synthetic retention modeling test case, where it was shown that MTBO finds better optima with fewer method-development iterations than conventional BO. Next, the algorithm was tested on the optimization of a method for a pesticide sample and we found that the algorithm was able to improve upon the initial scanning experiments. Multi-task Bayesian optimization is a promising technique in situations where modeling retention is challenging, and the high number of adjustable parameters and/or limited optimization budget makes traditional Bayesian optimization impractical. Bayesian optimization ; Task (project management) ; Computer science ; Bayesian probability ; Process (computing) ; Sample (material) ; Artificial intelligence ; Machine learning ; Engineering ; Chemistry Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Spectroscopy and Chemometric Analyses
Authors: Abel Jansma
Source: arXiv (Cornell University) (preprint, 2024-04-17)
Field: Chemistry — Organic Chemistry

A Mereological Approach to Higher-Order Structure in Complex Systems: from Macro to Micro with Möbius Relating macroscopic observables to microscopic interactions is a central challenge in the study of complex systems. While current approaches often focus on pairwise interactions, a complete understanding requires going beyond these to capture the full range of possible interactions. We present a unified mathematical formalism, based on the Möbius inversion theorem, that reveals how different decompositions of a system into parts lead to different, but equally valid, microscopic theories. By providing an exact bridge between microscopic and macroscopic descriptions, this framework demonstrates that many existing notions of interaction, from epistasis in genetics and many-body couplings in physics, to synergy in game theory and artificial intelligence, naturally and uniquely arise from particular choices of system decomposition, or mereology. By revealing the common mathematical structure underlying seemingly disparate phenomena, our work highlights how the choice of decomposition fundamentally determines the nature of the resulting interactions. We discuss how this unifying perspective can facilitate the transfer of insights across domains, guide the selection of appropriate system decompositions, and enable the search for new notions of interaction. To illustrate the latter in practice, we decompose the Kullback-Leibler divergence, and show that our method correctly identifies which variables are responsible for the divergence. In addition, we use Rota's Galois connection theorem to describe coarse-grainings of mereologies, and efficiently derive the renormalised couplings of a 1D Ising model. Our results suggest that the Möbius inversion theorem provides a powerful and practical lens for understanding the emergence of complex behaviour from the interplay of microscopic parts, with applications across a wide range of disciplines. Carving ; Order (exchange) ; Computer science ; Engineering ; Business ; Mechanical engineering Chemical Thermodynamics and Molecular Structure ; History and advancements in chemistry
Authors: Jayashree S. Kshirsagar | Wilson B. Chandane | Dipak P. Hiwarale | Nitin M. Naik | Kailas D. Sonawane | Gajanan Rashinkar | Rajashri Salunkhe | Sunita Shirke
Source: Asian Journal of Chemistry (article, 2024-11-30)
Field: Chemistry — Organic Chemistry

Novel Triazolo[4,3-a]pyrazines as Potential MmpL3 Inhibitors: Design, Synthesis, Antitubercular Evaluation and Molecular Docking Studies A series of biologically active novel triazolo[4,3-a]pyrazines (5a-f) were synthesized and characterized by spectroscopic techniques. The synthesized compounds 5a-f were evaluated for their in vitro anti-tubercular (anti-TB) activity against drug-sensitive Mtb H37Rv (ATCC 27294) strain as well as two drug-resistant Mtb strains viz. Mtb H37Rv ATCC 35822 (INH-resistant) and Mtb H37Rv ATCC 35837 (ETH-resistant). The synthesized compounds 5a-f displayed good to moderate anti-TB activity against drug-sensitive, INH-resistant and ETH-resistant Mtb H37Rv strains. Among all the compounds tested, compound 5c was found to be significantly potent. It inhibited the growth of drug-sensitive, INH-resistant and ETH-resistant Mtb H37Rv strains with MIC values 0.59 ± 0.11 µM, 20.83 ± 0.67 µM and 15.37 ± 0.14 µM, respectively. Moreover, compounds 5a-f were also tested for their cytotoxic efficacy against the mammalian Vero cell line at a maximum concentration of 50 µM. Molecular docking experiments of compounds 5a-f with the mycobacterial membrane protein large 3 (MmpL3) were performed to justify the biological activity and provide insight into the possible mechanism of action and binding mode of compounds. In silico predictions were used to validate compound toxicity descriptors, drug scores and drug-likeness properties. Chemistry ; Docking (animal) ; Stereochemistry ; Combinatorial chemistry ; Computational chemistry Click Chemistry and Applications ; Monoclonal and Polyclonal Antibodies Research ; Synthesis and biological activity
Authors: Thomas Plé
Source: arXiv (Cornell University) (preprint, 2024-05-02)
Field: Materials Science — Materials Chemistry

FeNNol paper training examples Inputs and outputs for the training examples of section VI of the FeNNol paper https://arxiv.org/abs/2405.01491 Computer science ; Python (programming language) ; Modular design ; Force field (fiction) ; Artificial neural network ; Graphics processing unit ; Computational science ; Field (mathematics) ; Graphics ; Artificial intelligence ; Computer architecture ; Parallel computing ; Computer graphics (images) ; Programming language Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Topic Modeling
Authors: Theodore Maranets | Yan Wang
Source: arXiv (Cornell University) (preprint, 2024-12-19)
Field: Materials Science — Materials Chemistry

How phonon coherence develops and contributes to heat conduction in periodic and aperiodic superlattices This work investigates the impact of device length on thermal conductivity in periodic and aperiodic superlattices (SLs). While it is well known that thermal conductivity in aperiodic SLs exhibits a weaker dependence on device length compared to periodic SLs, existing literature attributes this behavior to the scattering of coherent phonons by aperiodically arranged interfaces. Through atomistic wave-packet simulations, we show that coherent phonons in aperiodic SLs have spatial extensions limited to a certain number of SL layers, which prevents transmission if the extension is shorter than the device length. Specifically, the disordered interface spacing in aperiodic SLs causes coherent phonons to behave as non-propagative vibrational modes, resulting in diffuse energy transmission. In periodic SLs, however, coherent phonons can propagate across the entire structure, enabling high transmission. The difference between ballistic transport in periodic SLs and diffuse transport in aperiodic SLs is captured in the length-dependence of phonon transmission. These findings provide new insights into phonon coherence and its implications for heat conduction in superlattices, with potential applications in the thermal design of nanostructures. Aperiodic graph ; Superlattice ; Condensed matter physics ; Thermal conduction ; Coherence (philosophical gambling strategy) ; Phonon ; Physics ; Materials science ; Quantum mechanics ; Mathematics ; Combinatorics Thermal properties of materials ; Aerogels and thermal insulation ; Quasicrystal Structures and Properties
Authors: Jialin Wu
Source: arXiv (Cornell University) (preprint, 2024-08-15)
Field: Materials Science — Ceramics and Composites

Discovery and Application of the Two-Electron Quantum Theory of Glass States The glass state problem stems from the failure described in terms of one-electron theory or atoms (molecules) as independent particles. In 2005, de Gennes proposed that the way to explain the glass transition in simple terms was to construct the cluster model of molecules in contact with all existing glass models and to refine the picture of the mean-field hard-sphere molecules (HSMs) in contact with each other. In the process of refining this picture, we discovered the two-electron quantum theory derived from the second solution of de Gennes n = 0, where the clustered contact of the two HSMs along the z-axis is the sequential emergence of the 16 z-direction interface excited quantum states of their coupled electron pair, the two HSMs suddenly overlap by 0.27% to form a magic-interface two-dimensional vector. The two coupled electron orbitals synchronously escaped the two HSMs 16 times, tangent to the magic interface 16 times, and 16 parallel repulsive electron pairs with an interval of 5.9987°, which is a clustered boson interaction between the two HSMs. This is the common origin of boson peaks in the glass state and electron pairing in the high-temperature superconductivity. Therefore, the collective behavior of electrons in the two-electron theory can unify the glass transition and the high-temperature superconducting transition. This paper is not only a complete theoretical statement on glass transition, but also a new interpretation of the theory of high-temperature superconductivity, which provides a new theoretical perspective in the search for room-temperature superconducting materials. Electron ; Quantum ; Theoretical physics ; Quantum mechanics ; Physics Glass properties and applications
Authors: Samson Olaitan Jeje | Tawanda Marazani | Japheth Obiko | Mxolisi Brendon Shongwe
Source: MATEC Web of Conferences (review, 2024-01-01)
Field: Materials Science — Materials Chemistry

A review on enhancing near-α Ti alloys: Exploring sintering additives in conjunction with CP-Ti This review explores sintering additives' vital role in near-alpha titanium alloy production from commercially pure titanium, meeting demand for lightweight, high-strength materials. It emphasizes understanding the nuanced relationship between additives to optimize microstructures and enhance alloy performance. Beginning with the significance of near-alpha titanium alloys, it discusses the properties of commercially pure titanium and its limitations in high-performance applications. The review details the sintering process's crucial role, including its impact on resulting properties. Additionally, it examines various sintering additives, their roles in alloying, and their effects on microstructure and mechanical properties. Discussions on challenges, trends, future prospects, and existing literature augment the analysis. Conjunction (astronomy) ; Sintering ; Materials science ; Metallurgy ; Physics Titanium Alloys Microstructure and Properties ; Intermetallics and Advanced Alloy Properties ; Advanced materials and composites
Authors: Maciej Pilch | Dawid Kiesiewicz | Bartosz Oksiuta | Joanna Ortyl
Source: Chemical and Process Engineering New Frontiers (article, 2024-12-10)
Field: Chemistry — Organic Chemistry

Chemical engineering aspects in the design and construction of a new type of multimaterial 3D printer using photopolymerization and electrodeposition processes 3D printing has recently been experiencing a period of extremely rapid development. This is due to the fact that researchers as well as the industry recognize the many advantages of 3D printing. The dynamic development of this field brings about the advancement of new technologies, leading to the search for new photocurable resin formulations that enable efficient 3D printing in various environments. The development of an appropriate photocurable resin for 3D printing in the aqueous environment of electroplating baths is a crucial aspect in designing new devices for multi-material 3D printing that utilize coupled processes of electrodeposition and photopolymerization. Therefore, this article analyzes the effect of different environments on the kinetics of the photopolymerization process of photo-curable compositions dedicated to 3D printing. The study was carried out in four different environments: argon, water, saturated copper (II) sulfate solution and saturated copper (II) sulfate solution acidified with monomolar sulfuric (VI) acid. The work used techniques such as Fluorescent Probe Technique, photorheology, rheology and Raman spectroscopy to investigate the course of the photopolymerization process. The results of the experiments showed that the environment has a significant effect on the degree of conversion of monomers and on the rate of the photopolymerization process itself. Photopolymer ; 3D printing ; Materials science ; Aqueous solution ; Chemical engineering ; Nanotechnology ; Monomer ; Polymer ; Chemistry ; Composite material ; Organic chemistry ; Engineering Photopolymerization techniques and applications ; Additive Manufacturing and 3D Printing Technologies
Authors: Ri He | Hua Wang | Fenglin Deng | Yuxiang Gao | Binwen Zhang | Yubai Shi | Run-Wei Li | Zhicheng Zhong
Source: arXiv (Cornell University) (preprint, 2024-08-01)
Field: Materials Science — Materials Chemistry

Sliding Flexoelectricity in Two-Dimensional van der Waals Systems Two-dimensional sliding ferroelectrics, with their unique stacking degrees of freedom, offer a different approach to manipulate polarization by interlayer sliding. Bending sliding ferroelectrics inevitably leads to interlayer sliding motion, thus altering stacking orders and polarization properties. Here, by using machine-learning force field, we investigate the effects of bending deformation on geometries, stackings, energies, and polarizations in sliding ferroelectric bilayer h-BN and 3R-MoS2. We predict that bent ferroelectric bilayer forms irreversible kinks instead of arc when the bending angle exceeds a critical value. We demonstrate that the kinks originate from the competition between bending energy and interlayer van der Waals energy. The kink contains a ferroelectric domain wall that reverses the polarization, effectively inducing a flexoelectric effect. We term this phenomenon "sliding flexoelectricity" to distinguish it from conventional strain-gradient-induced flexoelectricity. Flexoelectricity ; van der Waals force ; Physics ; Hamaker constant ; Classical mechanics ; Condensed matter physics ; Van der Waals radius ; Quantum mechanics ; Liquid crystal Nonlocal and gradient elasticity in micro/nano structures ; Mechanical and Optical Resonators ; Force Microscopy Techniques and Applications
Authors: Keelan Brydon | Arpan Laha | Abirami Kalathy | Majid Pahlevani
Source: Electronics (article, 2024-11-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Novel Parameter Estimation Scheme for Supercapacitors As reliance on sustainable energy grows, the demand for efficient, high-performance energy storage systems becomes increasingly critical, especially in uninterruptible power supplies (UPS), where reliability and fast transitions are essential. Supercapacitors, with their high power density and rapid charging capabilities, are emerging as strong alternatives to lithium-ion batteries in UPS systems. This paper presents a novel real-time estimation technique for monitoring supercapacitor parameters within a UPS, focusing on the dynamic behavior of these parameters and their evolution over the system’s lifecycle. The proposed estimator demonstrates exceptional accuracy, achieving less than 1% error within 120 ms of startup and nearly zero error thereafter. The estimator’s performance remains robust even as supercapacitor parameters change due to aging effects over the lifespan. The UPS system features a modular design, enabling scalability to accommodate higher power requirements or longer backup durations and adaptability to various supercapacitor types. Experimental results highlight the system’s robustness in both charging and backup modes, emphasizing the potential of supercapacitors as key components in future UPS systems. Scheme (mathematics) ; Supercapacitor ; Estimation ; Computer science ; Control theory (sociology) ; Electronic engineering ; Mathematics ; Engineering ; Capacitance ; Physics ; Artificial intelligence ; Mathematical analysis ; Systems engineering Supercapacitor Materials and Fabrication ; Advanced Battery Technologies Research ; Electric and Hybrid Vehicle Technologies
Authors: J.M. de Bruin-Hoegée | R. Corzo | P.D. Zoon | P. Vergeer | J. Schoorl | M.J. van der Schans | D. Noort | A.C. van Asten
Source: TNO Repository (article, 2024-01-01)
Field: Chemistry — Spectroscopy

Evaluating the strength of evidence of elemental profiling of polymers with LA-ICP-MS Polymer ; Profiling (computer programming) ; Compatibility (geochemistry) ; Nanoparticle Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development ; Advanced Proteomics Techniques and Applications
Authors: Daniel Uzcátegui-Contreras | Antônio José Teixeira Guerra | Sebastián Niklitschek | A. Delgado
Source: arXiv (Cornell University) (preprint, 2024-10-15)
Field: Materials Science — Materials Chemistry

Machine Learning approach to reconstruct Density Matrices from Quantum Marginals In this work, we propose a machine learning-based approach to address a specific aspect of the Quantum Marginal Problem: reconstructing a global density matrix compatible with a given set of quantum marginals. Our method integrates a quantum marginal imposition technique with convolutional denoising autoencoders. The loss function is carefully designed to enforce essential physical constraints, including Hermiticity, positivity, and normalization. Through extensive numerical simulations, we demonstrate the effectiveness of our approach, achieving high success rates and accuracy. Furthermore, we show that, in many cases, our model offers a faster alternative to state-of-the-art semidefinite programming solvers without compromising solution quality. These results highlight the potential of machine learning techniques for solving complex problems in quantum mechanics. Quantum ; Density matrix ; Artificial intelligence ; Computer science ; Machine learning ; Mathematics ; Physics ; Quantum mechanics Machine Learning in Materials Science ; Neural Networks and Applications
Authors: Mikhail Khrisanfov | Dmitriy D. Matyushin | А. С. Самохин
Source: ChemRxiv (preprint, 2024-12-24)
Field: Chemistry — Spectroscopy

Finding Potentially Erroneous Entries in METLIN SMRT Background: METLIN SMRT is a widely-used dataset of retention times for high-performance liquid chromatography (HPLC). Besides direct application it is used for training models aimed at predicting retention times in HPLC. Although there are quite a number of articles featuring METLIN SMRT, the pipelines used for filtering from errors are either simplistic or nonexistent. Two more datasets of HPLC retention times - RepoRT and MCMRT - have emerged recently. RepoRT maintainers used a 10-fold cross-validation strategy with gradient boosting models to validate retention times in the database. MCMRT maintainers suggested a projection method for transferring retention times from one chromatographic method to another, but there is no information about applying the method for data validation. Therefore, a reliable method for filtering potentially erroneous entries is still required. Results: An approach to filter potentially erroneous entries, as suggested in our earlier work for a database of gas chromatography retention indexes, was repurposed for METLIN SMRT using five predictive models (GNN, CNN, FCFP, FCD, and CatBoost). The retention times were predicted for the whole dataset using a 5-fold cross-validation strategy. Entries with retention times differing significantly from the predictions (bottom 5%) were flagged with a “yellow card”. This procedure was repeated for each model, leading to obtaining a group containing 1544 entries (about 2% of the dataset) with 5 “yellow cards”. These entries were considered potentially erroneous, as anomalous behavior was observed in the analyzed trends (with the increasing number of “yellow cards”) for both the size of each group and the standard deviation of the predictions. Significance: The previously proposed filtering approach was expanded to a retention time database, enabling finding potentially erroneous entries in METLIN SMRT. This work demonstrates the viability of the approach and its potential to improve the quality of other large-scale chromatography-related databases both for machine learning and experimental use. Retention time ; Computer science ; Data retention ; Artificial intelligence ; Chromatography ; Data mining ; Chemistry Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies ; Computational Drug Discovery Methods
Source: Chemistry International (article, 2024-07-01)
Field: Chemistry — Organic Chemistry

Franziska Schoenebeck is the Thieme-IUPAC Prize Winner 2024 Abstract We are delighted to announce that the 2024 Thieme–IUPAC Prize has been awarded to Franziska Schoenebeck of RWTH Aachen University. Professor Schoenebeck becomes the 16th recipient of the prize and joins a distinguished group of scientists whose research has had a major impact on the field of synthetic organic chemistry. The prize, which is awarded every two years and includes an award of € 5000, will be presented to Schoenebeck at the ICOS-24 conference before her Thieme–IUPAC lecture. Chemical nomenclature ; Joins ; Library science ; Polymer science ; Chemistry ; Engineering ; Art ; Computer science ; Organic chemistry Inorganic and Organometallic Chemistry ; History and advancements in chemistry ; Chemistry and Chemical Engineering