jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rongbin Li | Qian Huang | Hongde Xia | Hongliang Zhao | Fengqin Liu | Shaojun Zhang
Source: Fuel (article, 2024-08-16)
Field: Materials Science — Materials Chemistry

Insight into mechanisms behind complex reactions by high-dimensional vectorized dynamic analysis Computer science ; Chemistry ; Parallel computing Machine Learning in Materials Science ; Chemical Thermodynamics and Molecular Structure
Authors: Li Li | Zongyue Dong | Xiangyu Kong | Yan Ma | Kehao Yang | Na Xue | Hua Yuan | Xiaolin Qi | Chunhua Han | Kai Zhang
Source: Separation Science Plus (article, 2024-11-24)
Field: Chemistry — Spectroscopy

Isolation, Synthesis, and Identification of Process‐Related Impurities From Morinidazole ABSTRACT Morinidazole belongs to the category of third‐generation nitroimidazole antibacterial drugs. In the course of morinidazole production, the mother liquor from the recrystallization process was subjected to analysis for the identification and detection of eight process‐related impurities through high‐performance liquid chromatography (HPLC). The eight impurities ( Imp‐A , Imp‐B , Imp‐C , Imp‐D , Imp‐E , Imp‐F , Imp‐G , and Imp‐H ) included three new impurities ( Imp‐A , Imp‐B , and Imp‐C ) that were previously unreported and one potential genotoxic impurity ( Imp‐H ). Purity separation from the recrystallization mother liquor was carried out using preparative HPLC. To characterize these eight process‐related impurities, high‐resolution mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy were utilized, followed by direct synthesis. The retention times of the impurities were confirmed through co‐injection via HPLC. Additionally, Imp‐B , Imp‐C , and Imp‐G were detected in commercial morinidazole products. A detailed discussion was conducted on the possible pathways leading to the formation of these impurities. Furthermore, the toxicities of these compounds were predicted using ADMET/PK property prediction software based on artificial intelligence algorithm—ADMET Predictor. These results will provide technical support for the quality control of morinidazole. Impurity ; High-performance liquid chromatography ; Recrystallization (geology) ; Chemistry ; Chromatography ; Nuclear magnetic resonance spectroscopy ; Stereochemistry ; Organic chemistry ; Biology Analytical Chemistry and Chromatography ; Protein purification and stability ; Antibiotics Pharmacokinetics and Efficacy
Authors: Gayathri Saranathan | Ayana Ghosh | Martin Foltín | Annmary Justine Koomthanam | Aalap Tripathy | Maxim Ziatdinov | Suparna Bhattacharya | Kevin M. Roccapriore | Paolo Faraboschi
Source:  (article, 2024-11-17)
Field: Materials Science — Surfaces, Coatings and Films

Active Learning Surrogates for Integrating Electron Microscopy and Computational Insights from Simulations in Autonomous Experiments Artificial Intelligence (AI) combined with simulations and experiments has great potential to accelerate scientific discovery across technology and pharmaceuticals. However, the gap between simulations and experiments is challenging due to disparities in time and scale, making it difficult to estimate properties like energy and electronic states from experiments, and to provide feedback based on theoretical insights.Our research addresses the challenge by developing unique deep kernel based surrogate models that learns from microscopic images, mapping structural features to energy differences from defect formation. We start with full-training using simulated images to determine optimal settings, establishing a baseline for active learning. Using these settings from the baseline, active learning is trained, and predicts structures along simulation trajectories based on uncertainty and energetic stability, thus reducing data requirements, simulation time and computational costs. The results demonstrate that the model achieves a low average error margin of approximately 0.03 meV, indicating good performance. To enhance feature extraction and reconstruction capabilities, we developed an autoencoder-decoder as additional surrogate to create latent space to capture essential features, enabling precise comparisons between simulations and experiments. The results from this model achieved a reconstruction loss of around 0.2 and accurately reconstructed molecular structures.Overall, this work advances the steering of experiments through computational simulations by employing a surrogate models that actively predicts the trajectories of structural evolution, achieving time-to-solution comparable to experimental measurements. Computer science ; Electron microscope ; Microscopy ; Artificial intelligence ; Human–computer interaction ; Materials science ; Nanotechnology ; Physics ; Optics Electron and X-Ray Spectroscopy Techniques ; Machine Learning in Materials Science ; Advanced Materials Characterization Techniques
Authors: Akihiro Nakanishi | Yukinori Koyama | Takayuki Nakanishi | Shiro Funahashi | Hisanori Yamane | Kohsei Takahashi | Naoto Hirosaki | Hidekazu Ikeno | Takashi Takeda
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Discovery of Narrow-Band Emitting Phosphor Na5al3f14:Eu2+ Using Local Structure Similarity Phosphor ; Similarity (geometry) ; Materials science ; Computer science ; Optoelectronics ; Artificial intelligence ; Image (mathematics) Luminescence Properties of Advanced Materials ; Solid-state spectroscopy and crystallography ; Radiation Detection and Scintillator Technologies
Authors: Vesselin K. Krastev | Matteo Baldelli | Lorenzo Bartolucci | Stefano Cordiner | Giacomo Falcucci | Vincenzo Mulone
Source: Journal of Physics Conference Series (article, 2024-11-01)
Field: Materials Science — Materials Chemistry

Identification of synthetic parameters for the thermal characterization of Phase Change Materials in MH-PCM hydrogen storage systems Abstract The present work adopts a multidimensional CFD methodology to investigate the thermal coupling between Phase Change Materials coupled and intermetallic Metal Hydrides, for hydrogen storage and delivery. In contrast to the currently available literature on this topic, the focus here is shifted from specific application-oriented modeling towards the systematic identification of a minimum set of parameters to highlight eventual similarity patterns among different PCM families. To achieve this goal, a representative cylindrical-type MH-PCM system model has been defined for a discharge-mode configuration, taking into account engineering-related constraints like the optimal hydrogen pressure delivery and hydrogen massflow control. The results obtained are expected to significantly improve design practices based on standard CFD methods, as well as to pave the way for the derivation of fast and accurate data-driven model surrogates for real-time modeling applications. Phase-change material ; Hydrogen storage ; Thermal energy storage ; Characterization (materials science) ; Materials science ; Phase change ; Identification (biology) ; Thermal ; Process engineering ; Thermodynamics ; Nanotechnology ; Composite material ; Engineering ; Engineering physics ; Physics Hydrogen Storage and Materials ; Phase Change Materials Research ; Advanced Battery Materials and Technologies
Authors: R. Bretin | Philippe Bocher
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Neighborhood and Surface Effects on Polycrystal Stress Field Extreme Values: An Analysis by Means of Cellular Automaton Cellular automaton ; Field (mathematics) ; Stress field ; Stress (linguistics) ; Surface (topology) ; Statistical physics ; Mathematics ; Physics ; Geometry ; Finite element method ; Pure mathematics ; Algorithm ; Thermodynamics Quasicrystal Structures and Properties ; Cellular Automata and Applications ; Aluminum Alloy Microstructure Properties
Authors: Niranjan Sitapure | Joseph Sang‐Il Kwon
Source:  (article, 2024-07-10)
Field: Materials Science — Materials Chemistry

Integrating Machine Learning in Process Control with LSTMc: A Case Study in Batch Crystallization Over the past three decades, the primary methods for managing complex chemical processes have predominantly relied on PI/PID controllers and model predictive controllers (MPCs). Despite their advancements, both approaches have limitations. PI/PID controllers require specific tuning for each scenario, while MPCs are computationally intensive. To address these challenges, we introduce the LSTM-controller (LSTMc), which is a model-independent, data-driven framework that leverages the robust time-series prediction capabilities of LSTM networks. The LSTMc predicts future control inputs by analyzing the evolution of the system's state and error dynamics, taking into account both the current and previous time steps. Our experiments, particularly in dextrose batch crystallization, have demonstrated the effectiveness of this approach. Impressively, the LSTMc achieves a set-point deviation of less than 2% in 10+ case studies we tested. These results position the LSTMc as a promising alternative for process control, as it adeptly adapts to changing process conditions and set-points, and offers efficient computation for optimal control inputs. Crystallization ; Process (computing) ; Computer science ; Process control ; Control (management) ; Process engineering ; Artificial intelligence ; Engineering ; Chemical engineering ; Programming language Crystallization and Solubility Studies ; Advanced Control Systems Optimization ; Fault Detection and Control Systems
Authors: Leo Segre | Shai Avidan
Source: arXiv (Cornell University) (preprint, 2024-12-17)
Field: Materials Science — Surfaces, Coatings and Films

Optimize the Unseen -- Fast NeRF Cleanup with Free Space Prior Neural Radiance Fields (NeRF) have advanced photorealistic novel view synthesis, but their reliance on photometric reconstruction introduces artifacts, commonly known as "floaters". These artifacts degrade novel view quality, especially in areas unseen by the training cameras. We present a fast, post-hoc NeRF cleanup method that eliminates such artifacts by enforcing our Free Space Prior, effectively minimizing floaters without disrupting the NeRF's representation of observed regions. Unlike existing approaches that rely on either Maximum Likelihood (ML) estimation to fit the data or a complex, local data-driven prior, our method adopts a Maximum-a-Posteriori (MAP) approach, selecting the optimal model parameters under a simple global prior assumption that unseen regions should remain empty. This enables our method to clean artifacts in both seen and unseen areas, enhancing novel view quality even in challenging scene regions. Our method is comparable with existing NeRF cleanup models while being 2.5x faster in inference time, requires no additional memory beyond the original NeRF, and achieves cleanup training in less than 30 seconds. Our code will be made publically available. Space (punctuation) ; Free space ; Computer science ; Computer vision ; Artificial intelligence ; Physics ; Optics ; Operating system Electron and X-Ray Spectroscopy Techniques ; Advancements in Photolithography Techniques ; Ion-surface interactions and analysis
Authors: Ana De Leon | Matthew Wadsworth | Okunzuwa Austine Ekuase | Tripp Lappalainen | Zipporah Harlan | O. Arda Vanli | Rebekah Sweat
Source: Composite Interfaces (article, 2024-07-04)
Field: Materials Science — Polymers and Plastics

Hygrothermal effect and statistical analysis of the interfacial performance of nano and microscale polymer composites Hygrothermal exposure significantly impacts polymer composite (PMC) performance, affecting various industries. This study evaluated the short-term hygrothermal effects on PMCs by examining interfacial shear strength (IFSS), water uptake, glass transition temperature (Tg), and morphology. Data-driven techniques minimized experimental time while analyzing multiple factors. Specimens were immersed in water at 25°C and 70°C for 3, 7, and 14 days. The IFSS between carbon nanotube yarns and carbon fiber with epoxy (EPON™ 862) was measured before and after exposure. Statistical analysis indicated that fiber type significantly influenced IFSS, while time had a marginal effect and temperature had no impact. The IFSS decreased by 4.14% for CF/epoxy and 14.9% for CNT/epoxy. Water uptake analysis revealed weight gains of 0.465% and 1.566% for epoxy after 14 days at 25°C and 70°C, respectively. Morphological studies showed moisture penetration between 7 and 14 days. Thermomechanical analysis (TMA) indicated that pristine epoxy expanded by 0.318% of its original height. After 14 days, the Tg of epoxy decreased by 6.4% at 25°C and 9.7% at 70°C. Dynamic mechanical analysis (DMA) on dried epoxy samples showed similar Tg but varied tan delta curves due to plasticization. Short-term hygrothermal evaluation revealed degradation in interface quality and viscoelastic properties. Materials science ; Microscale chemistry ; Composite material ; Nano- ; Polymer ; Composite number ; Statistical analysis Polymer Nanocomposites and Properties ; Polymer crystallization and properties ; Fiber-reinforced polymer composites
Authors: Pengcheng Wu | M. Shengrui Wang | Tao Chen | Lei Xing | Xiaobo Zou | Haoran Li
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Chemistry — Analytical Chemistry

A Knowledge-Informed Spectral Variable Interval Identification and Combination Based On the Hierarchical Clustering for Robust and Interpretable Analysis Hierarchical clustering ; Identification (biology) ; Variable (mathematics) ; Cluster analysis ; Artificial intelligence ; Computer science ; Spectral clustering ; Data mining ; Mathematics ; Pattern recognition (psychology) ; Biology Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Advanced Statistical Methods and Models
Authors: Chuandong Li | Xinhai Yu | Wei Yu | Bo Li | Shan‐Tung Tu
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Multiobjective Optimization of a Novel Hybrid Triply Periodic Minimal Surface Structural Catalyst and Reactors for On-Board Methanol Steam Reforming Steam reforming ; Methanol ; Catalysis ; Materials science ; Chemical engineering ; Process engineering ; Chemistry ; Engineering ; Organic chemistry ; Hydrogen production Catalytic Processes in Materials Science ; Catalysis and Hydrodesulfurization Studies ; Catalysts for Methane Reforming
Authors: Guilong Xiao | Jianxi Huang | Xuecao Li | Shuangxi Miao | J. P. Zheng | Qing‐Yu Liu | Jianjian Song | Kaiqi Du | Haixiang Guan | Quandi Niu | Wei Su | Anne Gobin
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Enhanced Corn Mapping with Height-Spectral Gaussian Mixture Modeling Mixture model ; Gaussian ; Mathematics ; Environmental science ; Statistics ; Physics Spectroscopy and Chemometric Analyses
Authors: John E. Sader | Alfredo Gomez | Adam P. Neumann | Alexander R. Nunn | M. L. Roukes
Source: arXiv (Cornell University) (preprint, 2024-06-18)
Field: Chemistry — Spectroscopy

Data-driven fingerprint nanomechanical mass spectrometry Fingerprint analysis is a ubiquitous tool for pattern recognition with applications spanning from geolocation and DNA analysis to facial recognition and forensic identification. Central to its utility is the ability to provide accurate identification without an a priori mathematical model for the pattern. We report a data-driven fingerprint approach for nanoelectromechanical systems mass spectrometry (NEMS-MS) that enables mass measurements of particles and molecules using complex, uncharacterized nanoelectromechanical devices of arbitrary specification. NEMS-MS is based on the frequency shifts of the NEMS vibrational modes induced by analyte adsorption. The sequence of frequency shifts constitutes a fingerprint of this adsorption, which is directly amenable to pattern matching. Two current requirements of NEMS-based mass spectrometry are: (1) a priori knowledge or measurement of the device mode-shapes, and (2) a mode-shape-based model that connects the induced modal frequency shifts to mass adsorption. This may not be possible for advanced NEMS with three-dimensional mode-shapes and nanometer-sized features. The advance reported here eliminates this impediment, thereby allowing device designs of arbitrary specification and size to be employed. This enables the use of advanced NEMS devices with complex vibrational modes, which offer unprecedented prospects for attaining the ultimate detection limits of nanoelectromechanical mass spectrometry. Mass spectrometry ; Fingerprint (computing) ; Chemistry ; Computational biology ; Computer science ; Chromatography ; Artificial intelligence ; Biology Mass Spectrometry Techniques and Applications
Authors: A. Toncelli
Source:  (article, 2024-11-26)
Field: Materials Science — Materials Chemistry

Abstract of the 4th International Online Conference on Crystals The 4th International Online Conference on Crystals (IOCC 2024), Part of the International Electronic Conference on Crystals series, was held online from 18 to 20 September 2024. This is a new and improved initiative based on the experience from the first, second, and third International Electronic Conference on Crystals. The fourth conference was organized around seven topics and related themes: Liquid Crystals, Crystal Engineering, Inorganic Crystalline Materials, Organic Crystalline Materials, Hybrid and Composite Crystalline Materials, Materials for Energy Applications, and Crystalline Metals and Alloys. The scope of this online conference is to bring together well-known worldwide experts who are currently working on Crystals to provide an online forum for presenting and discussing new results. The present report will start by providing an overview of the keynote speeches and the main axes around which the communication sessions revolve before moving on to more detailed abstracts, presenting each of the topics presented during the IOCC 2024 conference. Computer science X-ray Diffraction in Crystallography ; ZnO doping and properties ; Solid-state spectroscopy and crystallography
Authors: Armel Sèna ADJAGBONI
Source: International Journal of Pharmaceutical Physico-chemical and Nutritional Analysis (article, 2024-10-05)
Field: Chemistry — Analytical Chemistry

dentification of artemether-lumefantrine combination drugs using mid-infrared spectroscopy and chemometric tools The high circulation of substandard and/or falsified medicines is a major public health problem worldwide, particularly in low-resource countries. This work was carried out with the aim of combating this scourge using mid-infrared spectroscopy. The study focused on combination therapies based on artemether-lumefantrine and involved the construction and validation of a model for rapid detection of falsifications of artemether-lumefantrine. Other antimalarial drugs were also used to assess the specificity of the models constructed. A total of 46 samples were analyzed, all collected in Benin, from pharmacies in Departmental Hospital Centres and private pharmacies. The spectra recorded in the range from 4000 to 650 cm-1 were preprocessed then a principal component analysis was applied to break down and visualize the data, and to highlight groupings or trends. This enabled to observe the differences and similarities between the spectra of artemether/lumefantrine, and to assess the differentiating factors from other antimalarial molecules. Also, a data-driven soft independent modelling of class analogy (DD-SIMCA) model was built to evaluate its ability to authenticate artemether-lumefantrine samples. The other antimalarial drugs were used to test model specificity. Built DD-SIMCA model allowed a clear identification of artemether-lumefantrine (sensitivity 100%) and a good discrimination of other antimalarials (specificity 98%). Keywords: Quality control, construction, validation, DD-SIMCA. Artemether ; Artemether/lumefantrine ; Lumefantrine ; Infrared spectroscopy ; Chemometrics ; Spectroscopy ; Chemistry ; Medicine ; Chromatography ; Malaria ; Artemisinin ; Plasmodium falciparum ; Physics ; Organic chemistry Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies
Authors: Anna Hartmann | Vakayil Praveen | Minireviews | C Pelicano | M Antonietti | M Zhang | W Choi | M Kim | J Choi | X Zang | Y Ren | H Chen | V Tsukruk | J Peng | Y Liu | D Kim | Z Lin | Y Jiang | S Li | Y Fan | Z Tang | C Wan | R Li | J Wang | D.-G Cheng | F Chen | L Xu | M Gao | Y Kang | M Eguchi | Y Yamauchi | Y Yi | Y Xing | H Wang | Z Zeng | Z Sun | H Lin | K Yang | H Ma | R Ren | L Xiao | W Jiang | Y Xie | G Wang | J Lu | L Zhuang | E Halabi | I Gessner | J.-J Kim | R Jana | H Peterson | J Spitzberg | R Weissleder | P Electrosynthesis | C Lin | E Wong | J Jarvo | Q Wu | D Liu | B Jiao | Q Tian | X Wu | H Chang | S Chu | Q Jiang | T Yang | W Zhang | J Zhang | X Fan | F Cui | L Chen ; Chemistry | * Shao | S.-L Hu | T Zheng | W Trinh | H Zhou | Y Wang | C Zong | C.-L Li | ; Chen | L Stolz | C De Moraes | A Jones | H Eagleton | * Nelson | ; Mirica | R Kasuya | S Oketani | H Matsuda | F Sato | A Ishiwari | I Saeki | M Hisaki | J Kumar Bisai | L osiewicz | G Sotorrios | A Nichol | M Dominey | S Cowley
Source: Angewandte Chemie International Edition (article, 2024-06-03)
Field: Chemistry — Organic Chemistry

Graphical Abstract: Angew. Chem. Int. Ed. 24/2024 <em>Angewandte Chemie International Edition</em> is one of the prime chemistry journals in the world, publishing research articles, highlights, communications and reviews across all areas of chemistry. INT ; Chemistry ; Materials science ; Computer science ; Programming language Cyclopropane Reaction Mechanisms ; Axial and Atropisomeric Chirality Synthesis ; Organic Chemistry Cycloaddition Reactions
Authors: Yichao Tao | Chenggui Wang | Huanlong Qin
Source: Indian Journal of Pharmaceutical Sciences (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Application of Piezoelectric Catalytic Materials in Tumor Therapy Cancer is a major global health issue, the 3rd most common and 2nd deadliest among cancers. Its progression usually includes the stage from polyp formation to adenocarcinoma, influenced by factors such as age, genetic susceptibility, and environmental conditions such as diet and lifestyle. Typical therapy approaches encompass chemotherapy, surgery and radiation, with chemotherapy being crucial for disease recurrence and spread due to associated risks. Recent advancements in treatments include molecular-targeted and immunotherapy, but challenges such as drug resistance and low response rates continue to exist. Latest research has illuminated how dietary habits and gut microorganisms impact colorectal cancer treatment, revealing that the makeup of gut microbiota is key to the effectiveness of chemotherapy and immunotherapy treatments. The piezoelectric effect, especially the mechanical stress induced by ultrasonic waves shows considerable potential in generating reactive oxygen species for treating cancer. Piezoelectricity ; Catalysis ; Materials science ; Composite material ; Chemistry ; Organic chemistry Dendrimers and Hyperbranched Polymers ; Advanced Computing and Algorithms