jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Turgay Coşkun | Erdal Çetkin
Source: Research on Engineering Structures and Materials (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Vascularized mini cooling channels to achieve temperature uniformity: Battery thermal management and electronic cooling Here we propose to use of distinct vascularized plates to be used in the applications of battery thermal management and electronic cooling. The temperatures of battery cells increase during charge and discharge; and elevated temperature values in them accelerated degradation and even may trigger battery fire because of the thermal runaway. Therefore, thermal management system is a necessity for battery packs to increase the battery performance and diminish the risk factors in the electric vehicles. Generally, high amount of heat is released in the high capacity (>15 Ah) cells in short time interval under fast charge/discharge conditions; thus, thermal management of the battery system can be achieved with liquid cooling in that situation. A silicon heater system which represents the thermal behavior of a battery cell is manufactured based on the literature and it is used in experiments. Such a method has not proposed up to now in the literature, so the study may be creating a new experimental procedure for future studies without the risk of battery fire/degradation to uncover even extreme conditions experimentally. Electronic cooling is also in prime importance due to enhanced computing requirement of current systems, and vascularized plates can solve the hot spot problems occurring with decreased energy consumption. According to the results, the cooling capacity of the vascularized plates are calculated as 20W, and a battery cell can be kept within its optimal operating temperature range when the heat loads up to 30W. Also, the temperature uniformity along the surface of mimic of the battery is satisfied by vascularized plates. Thermal management of electronic devices and systems ; Battery (electricity) ; Materials science ; Active cooling ; Computer cooling ; Thermal ; Air cooling ; Water cooling ; Electrical engineering ; Nuclear engineering ; Mechanical engineering ; Engineering physics ; Engineering ; Thermodynamics ; Physics Catalytic Processes in Materials Science ; Advanced Battery Technologies Research ; Electric and Hybrid Vehicle Technologies
Authors: Josef Kehrein | Ekinsu Gürsöz | Robert Luxenhofer | Alex Bunker
Source: ChemRxiv (preprint, 2023-01-04)
Field: Chemistry — Organic Chemistry

Unravel the tangle: atomistic insight into ultrahigh curcumin-loaded poly(2-oxazoline) and poly(2-oxazine)-based micelles Amphiphilic ABA-triblock copolymers, comprised of poly(2-oxazoline) and poly(2-oxazine) blocks, can solubilize poorly water-soluble molecules; they form micelles with exceptionally high drug loading. In previous work, experimental studies have shown that even minor structural changes can have a significant impact on the maximum loading capacity for several different drugs. In an effort to shed light on the molecular interactions underlying the structure-property-relationships we performed all-atom molecular dynamics simulations on a selection of curcumin-loaded polymer micelles that have been experimentally characterized in detail. We investigated polymer-drug interactions in different micelle compositions, i.e. different drug loadings as well as variation of polymer structures of the inner hydrophobic core and the outer hydrophilic shell. Interestingly, the system with the highest experimental loading capacity also showed the highest amount of drug molecules encapsulated by the hydrophobic core in silico. Furthermore, in systems with a lower loading capacity the outer A blocks showed a greater extent of entanglement with the inner B blocks. Our results from hydrogen bond analyses corroborate the hypotheses of previous experimental studies: poly(2-butyl-2-oxazoline) B blocks, found experimentally to have a reduced loading capacity for curcumin in comparision to poly(2-propyl-2-oxazine), established fewer but longer-lasting hydrogen bonds. This possibly results from the additional methylene group in the backbone of poly(2-propyl-2-oxazine) to allow for different sidechain conformations around the hydrophobic cargo, compared to poly(2-butyl-2-oxazoline). This was further investigated by an unsupervised clustering of monomers within smaller model systems mimicking the different micelle compartments. In addition, an exchange of the hydrophilic poly(2-methyl-2-oxazoline) A blocks with the slightly more hydrophobic poly(2-ethyl-2-oxazoline) leads to a higher percentage of A blocks interacting with hydrophobic drugs and a reduced hydration of the corona; this suggests an impairment of micelle solubility or colloidal stability. This study demonstrates how all-atom molecular dynamics simulations can help in dissecting the effects of small structural changes in poly(2-oxazoline)-based micelles; we argue that it will pave the way for a more rational a priori design based approach to the development of drug delivery systems in the future. Micelle ; Oxazoline ; Polymer ; Hydrogen bond ; Amphiphile ; Methylene ; Molecule ; Copolymer ; Molecular dynamics ; Materials science ; Hydrophobic effect ; Chemistry ; Polymer chemistry ; Chemical engineering ; Organic chemistry ; Computational chemistry ; Aqueous solution Surfactants and Colloidal Systems ; biodegradable polymer synthesis and properties ; Advanced Polymer Synthesis and Characterization
Authors: Shun Muroga | Satoshi Yamazaki | Koji Michishio | Hideaki Nakajima | Takahiro Morimoto | Nagayasu Oshima | Kazufumi Kobashi | Toshiya Okazaki
Source: arXiv (Cornell University) (preprint, 2023-11-27)
Field: Materials Science — Materials Chemistry

Tabular Two-Dimensional Correlation Analysis for Multifaceted Characterization Data We propose tabular two-dimensional correlation analysis for extracting features from multifaceted characterization data, essential for understanding material properties. This method visualizes similarities and phase lags in structural parameter changes through heatmaps, combining hierarchical clustering and asynchronous correlations. We applied the proposed method to datasets of carbon nanotube (CNTs) films annealed at various temperatures and revealed the complexity of their hierarchical structures, which include elements like voids, bundles, and amorphous carbon. Our analysis addresses the challenge of attempting to understand the sequence of structural changes, especially in multifaceted characterization data where 11 structural parameters derived from 8 characterization methods interact with complex behavior. The results show how phase lags (asynchronous changes from stimuli) and parameter similarities can illuminate the sequence of structural changes in materials, providing insights into phenomena like the removal of amorphous carbon and graphitization in annealed CNTs. This approach is beneficial even with limited data and holds promise for a wide range of material analyses, demonstrating its potential in elucidating complex material behaviors and properties. Characterization (materials science) ; Amorphous solid ; Asynchronous communication ; Cluster analysis ; Computer science ; Biological system ; Sequence (biology) ; Materials science ; Carbon nanotube ; Nanotechnology ; Statistical physics ; Artificial intelligence ; Chemistry ; Physics ; Crystallography Machine Learning in Materials Science ; Neural Networks and Applications
Authors: Yuyan Ni | Shikun Feng | Wei‐Ying Ma | Zhi-Ming Ma | Yanyan Lan
Source: arXiv (Cornell University) (preprint, 2023-11-03)
Field: Materials Science — Materials Chemistry

Sliced Denoising: A Physics-Informed Molecular Pre-Training Method While molecular pre-training has shown great potential in enhancing drug discovery, the lack of a solid physical interpretation in current methods raises concerns about whether the learned representation truly captures the underlying explanatory factors in observed data, ultimately resulting in limited generalization and robustness. Although denoising methods offer a physical interpretation, their accuracy is often compromised by ad-hoc noise design, leading to inaccurate learned force fields. To address this limitation, this paper proposes a new method for molecular pre-training, called sliced denoising (SliDe), which is based on the classical mechanical intramolecular potential theory. SliDe utilizes a novel noise strategy that perturbs bond lengths, angles, and torsion angles to achieve better sampling over conformations. Additionally, it introduces a random slicing approach that circumvents the computationally expensive calculation of the Jacobian matrix, which is otherwise essential for estimating the force field. By aligning with physical principles, SliDe shows a 42\% improvement in the accuracy of estimated force fields compared to current state-of-the-art denoising methods, and thus outperforms traditional baselines on various molecular property prediction tasks. Jacobian matrix and determinant ; Computer science ; Noise reduction ; Force field (fiction) ; Robustness (evolution) ; Noise (video) ; Artificial intelligence ; Algorithm ; Machine learning ; Mathematics ; Applied mathematics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Melanie Voigt | Jean-Michel Dluziak | Nils Wellen | Victoria Langerbein | Martin Jaeger
Source: Research Square (preprint, 2023-11-02)
Field: Chemistry — Analytical Chemistry

Photoinduced and electrochemical induced degradation of the 4th EU watchlist compound venlafaxine Venlafaxine ; Degradation (telecommunications) ; Electrochemistry ; Materials science ; Chemistry ; Photochemistry ; Computer science ; Medicine ; Internal medicine ; Electrode ; Physical chemistry ; Telecommunications Analytical chemistry methods development ; Atmospheric chemistry and aerosols ; Radioactive element chemistry and processing
Authors: Rivaldo Azis Siregar | Ajeng Wulansari | Rifdian Indrianto Sudjoko
Source: Proceeding of International Conference of Advance Transportation Engineering and Applied Social Science (article, 2023-11-08)
Field: Materials Science — Materials Chemistry

EFFECT OF PERCENTAGE OF RESIN AND CATALYST OF FIBERGLASS FIBER COMPOSITES, WITH FIBER ORIENTATION DIRECTIONS (0°,45°), (45°,90°) AND (0°,90°) ONTENSILE AND IMPACT STRENGTHS In the world of aviation industry the use of composite materials began to be widely developed, one of the most frequentlyused composite materials in the industrial world is composite material with fillers in the form of Fiberglass. Currently,fiber-reinforced composite materials are widely used engineering materials because of their specific strength and stiffness which are far above engineering materials in general, so that their properties can be designed close to the needs. The research conducted used WR 200 Fiberglass with fiber direction orientation treatment (0°, 45°), (45°, 90°), (0°, 90°), with 1%, 1.5%, 2% catalyst. The manufacture of composite workpieces/specimens using the hand lay-up methodwith glass molds measuring 22 cm × 17 cm × 0.4 cm and 10 cm × 5 cm × 1 cm. Based on the tensile and impact tests carried out on the WR 200 fiberglass composite, the tensile test obtained the results with the treatment of fiber direction orientation 45 °, 90 ° with 1% catalyst composition getting the highest tensile strength value of 56.87 N / mm2. The treatment of 0°,90° fiber direction orientation with 2% catalyst composition got the lowest tensile strength value of 38.15 N/mm2. In the impact test, the results obtained with the 45°,90° fiber direction orientation treatment with 1% catalyst composition obtained the highest Fracture Stress value of 9.687 Joules and the highest Tenacity Price value of 0.121 Joules/mm2. The 0°,90 fiber direction orientation treatment with 2% catalyst composition got the lowest fracturestress value of 3,935 Joules and the lowest ductility price value of 0.049 Joules/mm2. Ultimate tensile strength ; Materials science ; Composite material ; Fiber ; Composite number ; Tenacity (mineralogy) ; Tensile testing Material Selection and Properties ; Geotechnical and construction materials studies ; Mechanical Engineering and Vibrations Research
Authors: Gaurab Rimal | R. Comès
Source: arXiv (Cornell University) (preprint, 2023-10-21)
Field: Materials Science — Materials Chemistry

Advances in Complex Oxide Quantum Materials Through New Approaches to Molecular Beam Epitaxy Molecular beam epitaxy (MBE), a workhorse of the semiconductor industry, has progressed rapidly in the last few decades in the development of novel materials. Recent developments in condensed matter and materials physics have seen the rise of many novel quantum materials that require ultra-clean and high-quality samples for fundamental studies and applications. Novel oxide-based quantum materials synthesized using MBE have advanced the development of the field and materials. In this review, we discuss the recent progress in new MBE techniques that have enabled synthesis of complex oxides that exhibit "quantum" phenomena, including superconductivity and topological electronic states. We show how these techniques have produced breakthroughs in the synthesis of 4d and 5d oxide films and heterostructures that are of particular interest as quantum materials. These new techniques in MBE offer a bright future for the synthesis of ultra-high quality oxide quantum materials. Molecular beam epitaxy ; Heterojunction ; Nanotechnology ; Materials science ; Quantum ; Engineering physics ; Oxide ; Quantum well ; Optoelectronics ; Epitaxy ; Physics ; Quantum mechanics Electronic and Structural Properties of Oxides ; Catalysis and Oxidation Reactions ; Catalytic Processes in Materials Science
Authors: Modather F. Hussein | Ibrahim Althobaiti | Hamud A. Altaleb | Yasser abubaker | Azzah Elenazi | Nadia Taha Ahmed | Rania B. Bakr
Source: Egyptian Journal of Chemistry (article, 2023-08-11)
Field: Chemistry — Organic Chemistry

Novel Indene-[1,3,4]Oxadiazine hybrids: Design, construction, molecular docking, QSAR, ADME study and anticancer potential In an attempt to improve and develop biologically potential anticancer agents, synthesis of new anticancer agents are in progress. This study focused on the synthesis of novel compounds and examined the anticancer potentials of lung cancer cell line (A549), breast cancer cell line (MCF-7) and liver cancer cell line (HepG2) using MTT assay. Molecular docking and ADME studies were performed for the anticancer compounds. A novel set of indeno[2,1-e][1,3,4]oxadiazinone 2a-f was designed and constructed via a reaction of ninhydrin, hydrazine hydrate and the appropriate isothiocyanate. The anticancer impact of the newly prepared compounds 2a-f was assessed in vitro against A549, MCF-7 and HepG2 cell lines. The cyclohexylmethylaminoindenooxadiazinone derivative 2f was the most active candidate towards A549 and HepG2 with IC50 (64.88 and 39.18 µg/ml), respectively. A molecular docking study was done within EGFR active site to predict the binding mode of the novel compounds. Both compounds 2b and 2f recorded high binding energy scores with the excellent fitting with the active site. ADME study results displayed compounds 2b and 2f registered positive values showing good drug-likeness behavior. Multiple linear regression analysis was used to construct consistent QSAR models based on quantum mechanics-derived chemical descriptors. The experimental anticancer activity data correlated well with the expected one. Hence, it is possible to speculate that the novel compound 2f could be considered n anticancer lead compound. Quantitative structure–activity relationship ; ADME ; Docking (animal) ; Chemistry ; Computational biology ; Stereochemistry ; Biology ; Medicine ; Biochemistry Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and Biological Evaluation ; Synthesis and biological activity
Authors: Thiruvenkadam Gowrani | Anitha Nilavan | Shree Nithiya | Gurmeet Singh | Hashem Abdulhameed Al | S. Rajendran
Source: Zastita materijala (article, 2023-03-15)
Field: Materials Science — Materials Chemistry

Electrochemical studies on the corrosion resistance of Gold 18K and thermo active alloy in artificial sweat in presence of sodium chloride Corrosion resistance of thermo active alloy and Gold 18K alloy immersed in artificial sweat in the absence and presence of 100 ppm of NaCl has been investigated by polarization study and AC impedance spectra. It is observed that corrosion resistance of thermo active alloy and also Gold 18K alloy immersed in artificial sweat in the presence of 100 ppm of NaCl increases. Hence it is concluded that people wearing ornaments made of these two alloys need not worry about the excess of sodium chloride in their sweat. When thermo active alloy is immersed in artificial sweat in the presence of 100 ppm of NaCl, linear polarization resistance value increases from 1760283 Ohm cm2 to 9506106 Ohm cm2 ; corrosion current decreases from 1.845x10-8 to 4.008x10-9 A/cm2 ; charge transfer resistance value increases from 4884 Ohmcm2 to 12210 Ohm cm2 ; impedance value increases from 4.367 to 4.8; double layer capacitance decreases from 1.0442 x10 -9 to 4.1769x10-10 F/cm2 , and phase angle increases from 48.1 to 66.34°. When Gold 18K alloy is immersed in artificial sweat in the presence of 100 ppm of NaCl, linear polarization resistance value increases from 1079199 Ohmcm2 to 2385141 Ohm cm2 ; corrosion current decreases from 4.036x10-8 to 0.1966 x 10 -8A/cm2 ; charge transfer resistance increases from 4291 Ohm cm2 to 48880 Ohm cm2 ; impedance value increases from 4.652 to 5.114; double layer capacitance decreases from 1.189 x10-9 to 1.0434 x10-10 F/cm2 , and phase angle increases from 61 to 88. Corrosion ; Alloy ; Materials science ; Capacitance ; Ohm ; Metallurgy ; Polarization (electrochemistry) ; Chloride ; Dielectric spectroscopy ; Analytical Chemistry (journal) ; Composite material ; Chemistry ; Electrochemistry ; Electrode ; Electrical engineering ; Chromatography Corrosion Behavior and Inhibition ; Smart Materials for Construction ; Gas Sensing Nanomaterials and Sensors
Authors: Sandeep Kumar | Hossein Tahmasbi | Kushal Ramakrishna | Mani Lokamani | Svetoslav Nikolov | Julien Tranchida | Mitchell Wood | Attila Cangi
Source: arXiv (Cornell University) (preprint, 2023-04-19)
Field: Materials Science — Materials Chemistry

Transferable Interatomic Potentials for Aluminum from Ambient Conditions to Warm Dense Matter We present a study on the transport and materials properties of aluminum spanning from ambient to warm dense matter conditions using a machine-learned interatomic potential (ML-IAP). Prior research has utilized ML-IAPs to simulate phenomena in warm dense matter, but these potentials have often been calibrated for a narrow range of temperature and pressures. In contrast, we train a single ML-IAP over a wide range of temperatures, using density functional theory molecular dynamics (DFT-MD) data. Our approach overcomes computational limitations of DFT-MD simulations, enabling us to study transport and materials properties of matter at higher temperatures and longer time scales. We demonstrate the ML-IAP transferability across a wide range of temperatures using molecular-dynamics (MD) by examining the thermal conductivity, diffusion coefficient, viscosity, sound velocity, and ion-ion structure factor of aluminum up to about 60,000 K, where we find good agreement with previous theoretical data. Molecular dynamics ; Warm dense matter ; Density functional theory ; Diffusion ; Transferability ; Range (aeronautics) ; Ion ; Thermal conductivity ; Viscosity ; Interatomic potential ; Aluminium ; Materials science ; Atmospheric temperature range ; Chemistry ; Chemical physics ; Thermodynamics ; Computational chemistry ; Physics ; Composite material ; Computer science Machine Learning in Materials Science ; Thermal properties of materials ; Material Dynamics and Properties
Authors: Kiran R. Kharat | Raveendran Pottathil
Source: Research Square (preprint, 2023-06-05)
Field: Materials Science — Biomaterials

Selective binding and induction of death in leukemia cells by Biodegradable magnetized iron nanodiscs Abstract Leukemia is a blood malignancy with a rate of new cases of 14.1 per 100,000 adults per year. Leukemic cells seek a way to escape from the cytotoxic effects of chemotherapy drugs, leading to treatment failure. In this paper, we demonstrated the separation of circulating leukaemia cells using an antibody-conjugated iron oxide nanodisc (MND-Ab) under a low magnetic field gradient. Biodegradable magnetic nanodiscs were prepared by using iron oxide, BSA and the antibody IPO-M6, which is an anti-HL-60 antibody. Atomic force microscope studies show that the nano-discs were sprayed uniformly with an average size of 22+/-2.1 nm. The efficiency of cell capture was monitored with Prussian blue staining and fluorescence microscopy. A bar magnet was placed near the plate at 2 mm distance from the centre of the plate. The labelled cells were gathered near the magnet after 2 minutes. When the MND-Ab-HL60 cells were exposed to magnetic oscillations (5 min) 10 htz, 90 Guass), 92–94% of the cells were found apoptotic or dead in treated HL60 cells compared to the untreated control. HL60 ; Chemistry ; Fluorescence microscope ; Antibody ; Biophysics ; Materials science ; Fluorescence ; Apoptosis ; Biology ; Immunology ; Biochemistry Nanoparticle-Based Drug Delivery ; Microfluidic and Bio-sensing Technologies ; Characterization and Applications of Magnetic Nanoparticles
Authors: Yoshihiro Osakabe | Akinori Asahara
Source: arXiv (Cornell University) (preprint, 2023-02-06)
Field: Materials Science — Materials Chemistry

Proposing Novel Extrapolative Compounds by Nested Variational Autoencoders Materials informatics (MI), which uses artificial intelligence and data analysis techniques to improve the efficiency of materials development, is attracting increasing interest from industry. One of its main applications is the rapid development of new high-performance compounds. Recently, several deep generative models have been proposed to suggest candidate compounds that are expected to satisfy the desired performance. However, they usually have the problem of requiring a large amount of experimental datasets for training to achieve sufficient accuracy. In actual cases, it is often possible to accumulate only about 1000 experimental data at most. Therefore, the authors proposed a deep generative model with nested two variational autoencoders (VAEs). The outer VAE learns the structural features of compounds using large-scale public data, while the inner VAE learns the relationship between the latent variables of the outer VAE and the properties from small-scale experimental data. To generate high performance compounds beyond the range of the training data, the authors also proposed a loss function that amplifies the correlation between a component of latent variables of the inner VAE and material properties. The results indicated that this loss function contributes to improve the probability of generating high-performance candidates. Furthermore, as a result of verification test with an actual customer in chemical industry, it was confirmed that the proposed method is effective in reducing the number of experiments to $1/4$ compared to a conventional method. Computer science ; Generative grammar ; Generative model ; Function (biology) ; Artificial intelligence ; Range (aeronautics) ; Component (thermodynamics) ; Machine learning ; Test data ; Deep learning ; Scale (ratio) ; Latent variable ; Pattern recognition (psychology) ; Data mining ; Engineering Machine Learning in Materials Science ; Computational Drug Discovery Methods