jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Siti Norhasanah Sanimu | Hwa‐Young Yang | Jeevan Kandel | Ye‐Chong Moon | Gangasagar Sharma Gaudel | Seung‐Ju Yu | Yong Ju Kim | Sejung Kim | Bong‐Hyun Jun | Won‐Yeop Rho
Source:  (preprint, 2023-04-30)
Field: Materials Science — Polymers and Plastics

Machine Learning-Assisted Fabrication of PCBM-Perovskite Solar Cells with Nanopatterned TiO2 Layer To unlock the full potential of PSCs, machine learning (ML) was implemented in this research to predict the best combination of mesoporous-titanium dioxide (mp-TiO) and weight percentage (wt%) of phenyl-C-butyric acid methyl ester (PCBM), along with the current density ( J ), open-circuit voltage ( V ), fill factor ( ff ) and energy conversion efficiency (ECE). Then, the combination that yielded the highest predicted ECE was selected as a reference to fabricate PCBM-PSCs with nanopatterned TiO layer. Subsequently, the PCBM-PSCs with nanopatterned TiO layers were fabricated and characterized to further understand the dual effects of nanopatterning depth and wt% of PCBM on PSCs. Experimentally, the highest ECE of 17.336% is achieved at 127 nm nanopatterning depth and 0.10 wt% of PCBM, where the J , V and ff are 22.877 mA/cm, 0.963 V and 0.787, respectively. The measured J , V , ff and ECE values show consistencies with the ML prediction. Hence, these findings not only revealed the potential of ML to be used as a preliminary investigation to navigate the research of PSCs, but also highlighted that nanopatterning depth has a significant impact on J , and the incorporation of PCBM on perovskite layer influenced the V and ff , which further boosted the performance of PSCs. Materials science ; Mesoporous material ; Perovskite (structure) ; Layer (electronics) ; Energy conversion efficiency ; Titanium dioxide ; Fabrication ; Nanotechnology ; Current density ; Chemical engineering ; Optoelectronics ; Catalysis ; Composite material ; Chemistry ; Organic chemistry Conducting polymers and applications ; Perovskite Materials and Applications
Authors: Qian-Ze Zhu | Chrisy Xiyu Du | Ella M. King | Michael P. Brenner
Source: arXiv (Cornell University) (preprint, 2023-12-14)
Field: Materials Science — Materials Chemistry

Proofreading mechanism for colloidal self-assembly Designing components that can robustly self-assemble into structures with biological complexity is a grand challenge for material science. Proofreading and error correction is required to improve assembly yield beyond equilibrium limits, using energy to avoid kinetic traps in the energy landscape. Here we introduce an explicit two staged proofreading scheme for patchy particle colloidal assemblies that substantially improves assembly yield and robustness. The first stage implements local rules whereby particles increase their binding strengths when they detect a local environment corresponding to a desired target. The second stage corrects remaining errors, adding a reverse pathway inspired by kinetic proofreading. The scheme shows significant yield improvements, eliminating kinetic traps, giving a much broader temperature range with high yield. Additionally, the scheme is robust against quenched disorder in the components. Our findings illuminate a pathway for advancing programmable design of synthetic living materials, potentially fostering the synthesis of novel biological materials and functional behaviors. Proofreading ; Robustness (evolution) ; Kinetic energy ; Computer science ; Biological system ; Yield (engineering) ; Nanotechnology ; Energy landscape ; Range (aeronautics) ; Scheme (mathematics) ; Synthetic biology ; Materials science ; Chemistry ; Mathematics ; Physics ; Biology Pickering emulsions and particle stabilization ; Micro and Nano Robotics ; Modular Robots and Swarm Intelligence
Authors: TARAKA RAMESH G. | Y. Rajendra Prasad
Source: International Journal of Applied Pharmaceutics (article, 2023-05-07)
Field: Chemistry — Analytical Chemistry

THE DEVELOPMENT AND VALIDATION OF A FAST STABILITY INDICATING RP-HPLC METHOD FOR QUANTIFICATION OF LUMEFANTRINE AND ITS ORGANIC IMPURITIES USING CENTRAL COMPOSITE EXPERIMENTAL DESIGN Objective: The objective of the present study was to develop and validate a stability indicating RP-HPLC method for Lumefantrine (LF) and its organic impurities using a central composite design (CCD). Methods: A specific, simple quality control friendly isocratic elution method using reverse phase HPLC was developed for quantification of Lumefantrine (LF) and its organic impurities at a wavelength of 265 nm. The chromatographic separation was achieved on the column of Thermo Hypersil ODS C18 (150x4.6 mm, 3µ) with a buffer containing 0.1percent formic acid and acetonitrile 10:90 v/v as a mobile phase with a flow rate of 1.6 ml/min at 35 °C with a run time of 10 min. Based on the preliminary trials, CCD was employed to check the effect of independent variables such as Acetonitrile ratio (A), Flow rate (B), and Column oven temperature (C). While resolution between Lumefantrine (LF) and Impurity-A (X1), Impurity-A and Impurity-B (X2), and Plate count of Lumefantrine (LF) (X3) were considered as dependent variables and statistical evaluation performed by using design expert software. The optimized conditions were validated as per ICH guidelines. Results: The retention time of LF and its organic impurities were 1.9 min, 3.0, 4.5, and 6.4 min, respectively. Design space was established and desirability was found. LOD and LOQ for the Lumefantrine (LF) and its impurities were established with respect to test concentration. The plotted calibration curves were linear with a regression coefficient of R2&gt;0.99, indicating that the linearity was within the limit. As a part of method validation, the parameters like Specificity with forced degradation, Linearity, Precision, Accuracy, Ruggedness, and Robustness were determined and the results were found to be within the allowable limits. Conclusion: The method developed and validated was found to be suitable for routine analysis and to be used for the measurement of Lumefantrine and its impurities. Since there is no stability indicating the RP-HPLC method with design space was reported in the literature, there is a need to develop quantitative methods under different conditions to achieve improvement in specificity and selectivity. Impurity ; Acetonitrile ; Chromatography ; Lumefantrine ; Formic acid ; Central composite design ; High-performance liquid chromatography ; Chemistry ; Calibration curve ; Analytical Chemistry (journal) ; Materials science ; Detection limit ; Response surface methodology ; Organic chemistry Analytical Methods in Pharmaceuticals ; Drug-Induced Hepatotoxicity and Protection ; Analytical Chemistry and Chromatography
Authors: Jessica Schnorr
Source:  (article, 2023-11-23)
Field: Chemistry — Analytical Chemistry

Automation of follicular measurements during ovarian stimulation using a convolutional neural network Background:The study aims to investigate the clinical use and measurement accuracy of the Cycle Clarity convolutional neural network follicle identi cation platform in ovarian simulations compared to SonoAVC and manual measurements by ultrasonographers. Methods:This was a prospective cohort study conducted in a private reproductive endocrinology and infertility clinic.The study involved 157 ovarian ultrasound examinations from 66 women undergoing ovarian stimulations for infertility treatment.Follicular ultrasound measurements were performed manually by ultrasonographers, SonoAVC, and the Cycle Clarity convolutional neural network.The primary endpoint was the median size (mm) of ovarian follicles in Cycle Clarity compared to SonoAVC and ultrasonographer measurements.A key secondary endpoint was the number of ovarian follicles greater than or equal to 10mm in size in Cycle Clarity compared to SonoAVC and ultrasonographer.Results: Sixty-six participants were enrolled, and 152 ovarian ultrasound examinations were performed on 114 unique ovaries as some patients were ultrasound on more than one visit.The ultrasonographer detected 815 follicles greater than or equal to 10mm in size with an average diameter of 14.55mm.Cycle Clarity without post-image proceeding detected 740 follicles with an average diameter of 14.87mm, a di erence of 2.2%.71 ovaries were imaged by both SonoAVCTM and Cycle Clarity.The median size (mm) of ovaries compared to the gold standard human read reduces the bias of Cycle Clarity by 2.69mm (95% CI: 1.97, 3.41), which indicates superiority and not just non-inferiority compared to SonoAVCTM.Ultrasound examinations were signi cantly faster with Cycle Clarity, including post-image analysis of 81.96 seconds compared to the ultrasonographer 706.79 seconds with an overall savings of 608 seconds per patient. Conclusion:Cycle Clarity image analysis produced measurements equivalent to human measurements and superior to SonoAVC with signi cant time savings for the patient and clinical team. Convolutional neural network ; Automation ; Stimulation ; Follicular phase ; Computer science ; Artificial intelligence ; Medicine ; Internal medicine ; Engineering ; Mechanical engineering Spectroscopy and Chemometric Analyses ; Non-Invasive Vital Sign Monitoring
Authors: Zuzana Murčínková | Jozef Živčák | Dominik Sabol
Source: Materials (article, 2023-04-24)
Field: Materials Science — General Materials Science

Torsional Vibrations in the Resonance of High-Speed Rotor Bearings Reduced by Dynamic Properties of Carbon Fiber Polymer Composites The present study deals with the harmful torsional resonance vibrations of textile rotor bearings, the amplitudes of which are reduced mainly by the use of high-capacity damping materials, characterized by an internal hierarchical structure and macroshape, added into the machine mechanical system. The additional materials are polymer matrix composites reinforced either by carbon nanofibers or carbon chopped microfibers and either aramid or carbon continuous fibers. The macroshape is based on a honeycomb with internal cavities. Torsional vibrations arise in mechanical systems as a result of fluctuations in the low-level pressing load of the flat belt driving the rotor-bearing pin and the changing of kinematic conditions within it, which, in the resonance area, leads to cage slip and unwanted impulsive torsional vibrations. Moreover, this occurs during high-frequency performance at around 2100 Hz, i.e., 126,000 min<sup>-1</sup>. The condition, before the redesign, was characterized by significantly reduced textile rotor-bearing life due to significant impulse torsional vibrations in the resonance area. The study showed a significant reduction in average and maximum torsional amplitudes in the resonance area by 33% and 43%, respectively. Furthermore, the paper provides visualization of the propagation of a stress wave at the microscale obtained by the explicit finite element method to show the dispersion of the wave and the fibers as one of the sources of high damping. Materials science ; Composite material ; Vibration ; Rotor (electric) ; Fiber ; Carbon fiber reinforced polymer ; Polymer ; Resonance (particle physics) ; Torsional vibration ; Bearing (navigation) ; Composite number ; Mechanical engineering ; Acoustics ; Computer science ; Engineering Material Properties and Applications ; Elasticity and Wave Propagation ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry
Authors: Jingjing Huang | An Staes | Francis Impens | Vadim Demichev | Frank Van Breusegem | Kris Gevaert | Patrick J. Willems
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-07-24)
Field: Chemistry — Spectroscopy

CysQuant: simultaneous quantification of cysteine oxidation and protein abundance using data dependent or independent acquisition mass spectrometry Abstract Protein cysteinyl thiols are susceptible to reduction-oxidation reactions that can influence protein function. Accurate quantification of cysteine oxidation is therefore crucial for decoding protein redox regulation. Here, we present CysQuant, a novel approach for simultaneous quantification of cysteine oxidation degrees and protein abundancies. CysQuant involves light/heavy iodoacetamide isotopologues for differential labeling of reduced and reversibly oxidized cysteines analyzed by data-dependent acquisition (DDA) or data-independent acquisition mass spectrometry (DIA-MS). Using plexDIA with in silico predicted spectral libraries, we quantified an average of 18% cysteine oxidation in Arabidopsis thaliana by DIA-MS, including a subset of highly oxidized cysteines forming disulfide bridges in AlphaFold2 predicted structures. Applying CysQuant to Arabidopsis seedlings exposed to excessive light, we successfully quantified the well-established increased reduction of Calvin-Benson cycle enzymes and discovered yet uncharacterized redox-sensitive disulfides in chloroplastic enzymes. Overall, CysQuant is a highly versatile tool for assessing the cysteine modification status that can be widely applied across various mass spectrometry platforms and organisms. Cysteine ; Chemistry ; Iodoacetamide ; Mass spectrometry ; Proteomics ; Redox ; Arabidopsis ; Biochemistry ; Enzyme ; Chromatography ; Organic chemistry Mass Spectrometry Techniques and Applications ; Redox biology and oxidative stress ; Advanced Proteomics Techniques and Applications
Authors: Mariana Pop | Ioana-Monica Sas-Boca | Dan Frunză | Florin Popa | Adriana Neag
Source: Preprints.org (preprint, 2023-10-17)
Field: Materials Science — Materials Chemistry

Aspects Regarding the Influence of Hot Deformation on the Mechanical and Structural Properties of 42CrMo4 Steel The aim of the paper is to analyze the experimental results of the influence of elevated temperatures and strain rate on the mechanical and structural properties of steel 42CrMo4. The experiments were based on uniaxial tension and compression tests at high temperatures between 700 &amp;deg;C and 1000 &amp;deg;C and strain rates range 0.0018 - 0.1 s-1. The influence of temperature and strain rate on yield stress, strain to fracture, hardness, structural changes, and fracture characteristics were analyzed. Due to the dynamic recrystallization phenomenon present during the hot tensile tests, an increase in the flow stress is observed at the beginning of the deformation, after which it decreases until the fracture. By increasing the deformation temperature from 700 &amp;deg;C to 1000 &amp;deg;C, the tensile stress decreases significantly for all strain rates. The increase in the strain rate leads to the increase in the tensile stress. In compression tests by increasing the strain rate, the true strain is slightly increasing, but this depends on the temperature. The non-uniformity of deformations obtained at different values of the strain rate and temperature were also analyzed. Analysis by scanning electron microscopy showed the ductile behavior of the material. The degree of damage of the material caused by the presence of cavities increases by increasing the deformation temperature. For all the presented deformation conditions, the presence of the fracture through the ductile fracture mechanism was produced by the localized of necking and the coalescence of microvoids. By increasing the deformation temperature and reducing the strain rate, the fracture behavior of 42CrMo4 steel can be improved. Necking ; Materials science ; Strain rate ; Composite material ; Flow stress ; Ultimate tensile strength ; Deformation (meteorology) ; Slow strain rate testing ; Coalescence (physics) ; Fracture (geology) ; Compression (physics) ; Stress (linguistics) High-Velocity Impact and Material Behavior ; Metallurgy and Material Forming ; Metal Alloys Wear and Properties
Authors: Hiroaki Kusunose | Rikuto Oiwa | Satoru Hayami
Source: arXiv (Cornell University) (preprint, 2023-03-20)
Field: Materials Science — Materials Chemistry

Symmetry-adapted modeling for molecules and crystals We have developed a symmetry-adapted modeling procedure for molecules and crystals. By using the completeness of multipoles to express spatial and time-reversal parity-specific anisotropic distributions, we can generate systematically the complete symmetry-adapted multipole basis set to describe any of electronic degrees of freedom in isolated cluster systems and periodic crystals. The symmetry-adapted modeling is then achieved by expressing the Hamiltonian in terms of the linear combination of these bases belonging to the identity irreducible representation, and the model parameters (linear coefficients) in the Hamiltonian can be determined so as to reproduce the electronic structures given by the density-functional computation. We demonstrate our method for the modeling of graphene, and emphasize usefulness of the symmetry-adapted basis to analyze and predict physical phenomena and spontaneous symmetry breaking in a phase transition. The present method is complementary to de-facto standard Wannier tight-binding modeling, and it provides us with a fundamental basis to develop a symmetry-based analysis for materials science. Hamiltonian (control theory) ; Symmetry operation ; Multipole expansion ; Basis (linear algebra) ; Symmetry (geometry) ; Theoretical physics ; Irreducible representation ; Discrete symmetry ; Physics ; Basis set ; Wannier function ; Quantum mechanics ; Statistical physics ; Mathematics ; Molecule ; Homogeneous space ; Geometry Graphene research and applications ; Chemical and Physical Properties of Materials ; Advanced Chemical Physics Studies
Authors: Nivedita Singh | Faiz M. Khan | Lakshmi Bala | Julio Vera | Olaf Wolkenhauer | Brigitte M. Pützer | Stella Logotheti | Shailendra K. Gupta
Source: Preprints.org (preprint, 2023-06-12)
Field: Chemistry — Organic Chemistry

Logic-Based Modeling and Drug Repurposing for the Prediction of Novel Therapeutic Targets and Combination Regimens against E2F1-Driven Melanoma Progression Skin melanoma presents increasing prevalence and poor outcomes. Progression to aggressive stages is characterized by overexpression of the transcription factor E2F1 and activation of downstream prometastatic gene regulatory networks (GRNs). Appropriate therapeutic manipulation of the E2F1-governed GRNs holds the potential to prevent metastasis however, these networks entail complex feedback and feedforward regulatory motifs among various regulatory layers, which make it difficult to identify druggable components. To this end, computational approaches such as mathematical modeling and virtual screening are important tools to unveil the dynamics of these signaling networks and identify critical components that could be further explored as therapeutic targets. Herein, we integrated a well-established E2F1-mediated epithelial-mesenchymal transition (EMT) map with transcriptomics data from E2F1-expressing melanoma cells to reconstruct a core regulatory network underlying aggressive melanoma. Using logic-based in silico perturbation experiments of a core regulatory network, we identified that simultaneous perturbation of Protein kinase B (AKT1) and oncoprotein murine double minute 2 (MDM2) drastically reduces EMT in melanoma. Using the structures of the two protein signatures, virtual screening strategies were performed with the FDA-approved drug library. Thus, by combining drug repurposing and computer-aided drug design techniques, followed by molecular dynamics simulation analysis identified two potent drugs (Cialis and Finasteride) that can efficiently inhibit AKT1 and MDM2 protein signatures respectively, and with better therapeutic properties. We proposed that these two drugs could be considered for the development of therapeutic strategies for the management of aggressive melanoma. E2F1 ; Melanoma ; Drug repositioning ; Virtual screening ; Computational biology ; Druggability ; Computer science ; Cancer research ; In silico ; Drug discovery ; Transcription factor ; Drug ; Biology ; Bioinformatics ; Gene ; Pharmacology Click Chemistry and Applications ; Protein Degradation and Inhibitors ; Gene Regulatory Network Analysis
Authors: Sai Gokul Subraveti | Zukui Li | Vinay Prasad | Arvind Rajendran
Source: ChemRxiv (preprint, 2023-03-19)
Field: Chemistry — Spectroscopy

Can a computer “learn” non-linear chromatography?: Experimental validation of physics-based deep neural networks for the simulation of chromatographic processes This article presents the capabilities of machine learning in addressing the challenges related to the accurate description of adsorption equilibria in the design of chromatographic processes. Our previously developed physics-based artificial neural network framework for adsorption and chromatography emulation (PANACHE) approach is extended to simulate the dynamics of chromatographic columns without using adsorption isotherms. The incorporation of underlying conservation laws in the form of a physics-constrained loss function during training enables PANACHE models to infer the complex dynamics of chromatographic columns, even without the knowledge of adsorption isotherms. The isotherm-agnostic abilities of PANACHE models are tested by considering two binary systems with complex adsorption equilibria: 1) mixed Langmuir M1-type binary system, and 2) Tröger's base enantiomers on Chiralpak AD that show inflection in the isotherm. For each case study, unique feed-forward deep neural networks with an input layer, five hidden layers, and an output layer are trained for two solute components using the elution data either from simulations or experiments. The results show that PANACHE models are successful in predicting the dynamics of binary solute mixtures in chromatographic columns even in the absence of adsorption isotherms, with prediction errors in the order of 10^-2 in the measure of relative L2-norm, for most of the cases. The ability of PANACHE models to infer the adsorption isotherms is also demonstrated. Adsorption ; Elution ; Binary number ; Artificial neural network ; Langmuir adsorption model ; Chromatography ; Materials science ; Chemistry ; Computer science ; Artificial intelligence ; Mathematics ; Physical chemistry Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Microfluidic and Capillary Electrophoresis Applications