jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Barry K. Lavine | Thomas M. Hancewicz
Source: Spectroscopy (article, 2023-11-01)
Field: Chemistry — Analytical Chemistry

Analysis of Infrared and Raman Imaging Data Using Alternating and Modified Alternating Least Squares Modified alternating least squares (MALS) outperforms alternating least squares (ALS) in the analysis of infrared and Raman image spectral data. MALS offers superior stability thanks to ridge regression and a substantial speed advantage due to the kernel nature of the algorithm, reducing computational overhead. MALS excels in resolving basis vectors even in low signal-to-noise, nearly collinear data, whereas ALS often falls short. For spectroscopic imaging, both MALS and other ALS methods rely on spatial resolution between sample components, as low spatial resolution leads to increased mixing of components. Spectroscopic imaging combines spectroscopy and digital imaging to extract chemical composition. Multivariate curve resolution (MCR)’s foundation in ALS regression makes it a vital tool for this analysis, enabling a comprehensive examination of complex spectroscopic images. This tutorial delves into the mathematical techniques necessary for extracting chemical insights from infrared and Raman spectroscopic images. While this discussion focuses on two-dimensional spatial data, the methodology can be extended to three-dimensional data. Raman spectroscopy ; Partial least squares regression ; Chemical imaging ; Image resolution ; Infrared ; Basis (linear algebra) ; Computer science ; Principal component analysis ; Kernel (algebra) ; Sample (material) ; Artificial intelligence ; Biological system ; Pattern recognition (psychology) ; Optics ; Chemistry ; Hyperspectral imaging ; Mathematics ; Physics ; Machine learning Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Yilan Lu
Source: Journal of Materials Processing and Design (article, 2023-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A simple and convenient preparation of flexible paper-Ag NPs substrate for surface enhanced Raman spectroscopy In recent years, flexible SERS substrates based on cellulosic materials have been widely investigated. In this study, paper was dissolved and dispersed in an alkaline solution, and Ag NPs were synthesised in situ on cleaned paper scraps, which were dried to form a complete paper SERS substrate. The whole preparation process is simple, the preparation time is short, and the Ag NPs are uniformly distributed inside and outside the paper, which can be arbitrarily cut and extracted by wiping the analyte surface, which is convenient for liquid sample detection. Most importantly, the substrate overcomes the problem of paper dissolution and damage due to immersion. The detection of 10<sup>-7</sup> M R6G was achieved with enhancement factor of 1.95 × 10<sup>5</sup>. The Raman activity was still present after 60 days of refrigerated storage. The reproducibility was good (RSD = 9.5 %). And now the substrate has been successfully used for the detection of ciprofloxacin in water, with the detection limits of 2.2 × 10<sup>-4</sup> M. Raman spectroscopy ; Substrate (aquarium) ; Surface-enhanced Raman spectroscopy ; Analyte ; Detection limit ; Reproducibility ; Dissolution ; Materials science ; Nanotechnology ; Analytical Chemistry (journal) ; Sample preparation ; Chemical engineering ; Chemistry ; Chromatography ; Raman scattering ; Optics ; Organic chemistry Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Identification and Quantification in Food
Authors: Samantha L. Fossa | Brian P. Anton | Daniel W. Kneller | Laudine M. C. Petralia | Madison L. Boisvert | Mehul B. Ganatra | Saulius Vainauskas | Siu‐Hong Chan | Cornelis H. Hokke | Jeremy M. Foster | Christopher H. Taron
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-06-02)
Field: Chemistry — Organic Chemistry

A novel family of sugar-specific phosphodiesterases that remove zwitterionic modifications of <i>N</i> -acetylglucosamine ABSTRACT The zwitterions phosphorylcholine (PC) and phosphoethanolamine (PE) are often found esterified to certain sugars in polysaccharides and glycoconjugates in a wide range of biological species. One such modification involves PC attachment to the 6-carbon of N -acetylglucosamine (GlcNAc-6-PC) in N-glycans and glycosphingolipids (GSLs) of parasitic nematodes, a modification that helps the parasite evade host immunity. Knowledge of enzymes involved in the synthesis and degradation of PC and PE modifications is limited. More detailed studies on such enzymes would contribute to a better understanding of the function of PC modifications and have potential application in the structural analysis of zwitterion-modified glycans. In this study, we used functional metagenomic screening to identify phosphodiesterases encoded in a human fecal DNA fosmid library that remove PC from GlcNAc-6-PC. A novel bacterial phosphodiesterase was identified and biochemically characterized. This enzyme (termed GlcNAc-PDase) shows remarkable substrate preference for GlcNAc-6-PC and GlcNAc-6-PE, with little or no activity on other zwitterion-modified hexoses. The identified GlcNAc-PDase protein sequence is a member of the large endonuclease/exonuclease/phosphatase (EEP) superfamily where it defines a distinct subfamily of related sequences of previously unknown function, mostly from Clostridium bacteria species. Finally, we demonstrate use of GlcNAc-PDase to confirm the presence of GlcNAc-6-PC in N-glycans and GSLs of the parasitic nematode Brugia malayi in a glycoanalytical workflow. Biochemistry ; Glycan ; Phosphorylcholine ; Phosphodiesterase ; Enzyme ; N-Acetylglucosamine ; Biology ; Exonuclease ; Glycobiology ; Glycosylation ; Glycoconjugate ; Microbiology ; Chemistry ; Glycoprotein Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Studies on Chitinases and Chitosanases
Authors: Siqi Wang | Tongqi Wen | Jian Han | David J. Srolovitz
Source: arXiv (Cornell University) (preprint, 2023-11-06)
Field: Materials Science — Materials Chemistry

Coherent and semicoherent $α$/$β$ interfaces in titanium: structure, thermodynamics, migration The $α/β$ interface is central to the microstructure and mechanical properties of titanium alloys. We investigate the structure, thermodynamics and migration of the coherent and semicoherent Ti $α/β$ interfaces as a function of temperature and misfit strain via molecular dynamics (MD) simulations, thermodynamic integration and an accurate, DFT-trained Deep Potential. The structure of an equilibrium semicoherent interface consists of an array of steps, an array of misfit dislocations, and coherent terraces. Analysis determines the dislocation and step (disconnection) array structure and habit plane. The MD simulations show the detailed interface morphology dictated by intersecting disconnection arrays. The steps are shown to facilitate $α/β$ interface migration, while the misfit dislocations lead to interface drag; the drag mechanism is different depending on the direction of interface migration. These results are used to predict the nature of $α$ phase nucleation on cooling through the $α$-$β$ phase transition. Nucleation ; Materials science ; Solvent drag ; Dislocation ; Disconnection ; Microstructure ; Drag ; Phase (matter) ; Titanium aluminide ; Titanium ; Molecular dynamics ; Thermodynamics ; Chemical physics ; Condensed matter physics ; Crystallography ; Physics ; Chemistry ; Composite material ; Computational chemistry ; Metallurgy ; Intermetallic Titanium Alloys Microstructure and Properties ; Nuclear Materials and Properties ; High Temperature Alloys and Creep
Authors: Martin Esmann | Stephen C. Wein | C. Antón
Source: arXiv (Cornell University) (preprint, 2023-12-14)
Field: Materials Science — Materials Chemistry

Solid-state single-photon sources: recent advances for novel quantum materials In this review, we describe the current landscape of emergent quantum materials for quantum photonic applications. We focus on three specific solid-state platforms: single emitters in monolayers of transition metal dichalcogenides, defects in hexagonal boron nitride, and colloidal quantum dots in perovskites. These platforms share a unique technological accessibility, enabling the rapid implementation of testbed quantum applications, all while being on the verge of becoming technologically mature enough for a first generation of real-world quantum applications. The review begins with a comprehensive overview of the current state-of-the-art for relevant single-photon sources in the solid-state, introducing the most important performance criteria and experimental characterization techniques along the way. We then benchmark progress for each of the three novel materials against more established (yet complex) platforms, highlighting performance, material-specific advantages, and giving an outlook on quantum applications. This review will thus provide the reader with a snapshot on latest developments in the fast-paced field of emergent single-photon sources in the solid-state, including all the required concepts and experiments relevant to this technology. Nanotechnology ; Photonics ; Quantum dot ; Quantum technology ; Photon ; Testbed ; Quantum ; Computer science ; Engineering physics ; Materials science ; Physics ; Optoelectronics ; Open quantum system ; Quantum mechanics 2D Materials and Applications ; Diamond and Carbon-based Materials Research ; Advanced Fiber Laser Technologies
Authors: Patnala Vanitha | Salla Gangi Reddy | Shashi Prabhakar | R. P. Singh | Venkateswarlu Annapureddy
Source: arXiv (Cornell University) (preprint, 2023-05-03)
Field: Chemistry — Analytical Chemistry

Analysing the Grain size and asymmetry of the particle distribution using auto-correlation technique Extracting the grain size from the microscopic images is a rigorous task involving much human expertise and manual effort. While calculating the grain size, we will be utilizing a finite number of particles which may lead to an uncertainty in the measurement. To avoid this difficulty, we utilize a simple mathematical tool, the auto-correlation function, to determine the grain size. The random particle distribution and the finite width Gaussian histogram of particle size has motivated us to utilize the auto-correlation function, which has been extensively studied for finding the size of random optical patterns. The finite width of the correlation function provides the grain size, and the difference in correlation length along two mutually independent directions provides information about the asymmetry present in the particle distribution, i.e., the deviation from a spherical shape. The results may find applications in material, pharmaceutical, chemical, and biological studies where extracting the grain size is essential. Asymmetry ; Particle-size distribution ; Histogram ; Particle size ; Statistical physics ; Gaussian ; Correlation ; Grain size ; Function (biology) ; Particle (ecology) ; Mathematics ; Correlation function (quantum field theory) ; Biological system ; Statistics ; Physics ; Computer science ; Materials science ; Artificial intelligence ; Geometry ; Chemistry ; Image (mathematics) Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Shruti Ringe | Shounak Kulkarni | Abhijeet Sutar | Suresh Kumar BV | A. Shenoy
Source: Preprints.org (preprint, 2023-11-10)
Field: Chemistry — Analytical Chemistry

Enhancing Tablet Dissolution Insights: A Comparative Study of Predictive ANN, PLS, and SVM Model With NIR Spectra The pharmaceutical industry is making significant strides in enhancing process comprehension through the development of concepts like Quality by Design (QbD) and Process Analytical Technology (PAT). This shift has moved from traditional offline testing methods to real-time estimation of product quality. The dissolution characteristics of pharmaceutical tablets play a crucial role in maximizing the release of medications and their bioavailability. One factor that can affect dissolution is the blending procedure. Inadequate mixing can lead to patches of concentrated active components or excipients within the tablet, resulting in inconsistent dissolution behavior. A study investigated the impact of blending time and speed on the dissolution behavior of Amlodipine tablets using near-infrared (NIR) spectroscopy and multivariate modeling. NIR spectra were collected for Amlodipine tablets produced under various blending conditions using a 2-level central composite design. Dissolving profiles were analyzed using a USP dissolution device. Multivariate analysis techniques, including principal component analysis (PCA), partial least squares (PLS), Support Vector Machine (SVM), and Artificial Neural Networks (ANN), were applied to the collected NIR spectra. The findings demonstrated that blending speed and time had a significant influence on the dissolving properties of Amlodipine tablets. Blending at faster speeds and for shorter durations resulted in excessive shear and insufficient mixing, ultimately reduced drug release. The multivariate models constructed using ANN outperformed SVM and PLS in predicting dissolution profiles based on NIR spectra. This research highlights the effectiveness of NIR spectroscopy and multivariate modeling in optimizing tablet dissolution. These advancements enable continuous manufacturing of high-quality pharmaceutical products. Dissolution ; Quality by Design ; Multivariate statistics ; Process analytical technology ; Amlodipine ; Near-infrared spectroscopy ; Dissolution testing ; Critical quality attributes ; Principal component analysis ; Materials science ; Partial least squares regression ; Computer science ; Process engineering ; Biological system ; Artificial intelligence ; Machine learning ; Chemistry ; Chemical engineering ; Engineering ; Particle size ; Bioprocess Spectroscopy and Chemometric Analyses ; Drug Solubulity and Delivery Systems ; Pharmaceutical Quality and Counterfeiting
Authors: Yukihiro Ozaki | Mika Ishigaki
Source: Spectroscopy (article, 2023-11-01)
Field: Chemistry — Analytical Chemistry

Frontiers of NIR Imaging After a brief introduction to the technique, this review will discuss the state-of-the-art NIR imaging instrumentation and its applications, including applications of an ordinary NIR imaging system to solvent diffusion into a polymer. Other imaging applications discussed include the use of a portable NIR imaging system in the pharmaceutical industry, high-speed and wide-area monitoring of polymers, and imaging for fish embryos development research. Also discussed is an imaging-type two-dimensional Fourier spectroscopy (ITFS) system and its application to medaka (Japanese rice fish, Oryzias latipes) egg development. Finally, general perspectives on NIR imaging will be provided. Oryzias ; Direct imaging ; Near-infrared spectroscopy ; Fish <Actinopterygii> ; Nanotechnology ; Computer science ; Materials science ; Biology ; Physics ; Optics ; Fishery Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Yinchun Hu | Limin Qu | Zhenyang Bao | Zhaoshuang Li | Renzhong Wei | Qin Huang | Yan Qing | Xingong Li | Yiqiang Wu
Source: Research Square (preprint, 2023-12-27)
Field: Chemistry — Organic Chemistry

An environmentally friendly multifunctional soy protein adhesive composed of rosin acid derivative inspired from organic-inorganic hybrid structure Abstract Soy protein adhesives have the advantages of low price and renewability but are limited by terrible bonding strength and poor water resistance, which restricts the practical application. Herein, inspired by the structure of mussels and organic-inorganic hybrid strengthening mechanism, a novel and bio-based soy protein adhesive (SPI-RA-CSA) based on rosin acid derivative and calcium sulfoaluminate was generated. According to the optimization of response surface methodology (RSM), the best proportion of adhesive SPI-RA6-CSA1 was chosen. The dry and wet shear strengths of SPI-RA6-CSA1 adhesive reached 1.52 and 1.35 MPa, respectively, which were 70% and 210% higher than original soy protein adhesive. Meanwhile, SPI-RA6-CSA1 adhesive showed excellent coating performance even if it was coated on wet wood veneer. In addition, SPI-RA6-CSA1 adhesive effectively inhibited the formation of mold and exhibited outstanding antimicrobial ability for Staphylococcus aureus ( S. aureus ) and Escherichia coli ( E. coli ) with antimicrobial rates of 87.36% and 85.73%, respectively. What’s more, SPI-RA6-CSA1 adhesive demonstrated prominent flame retardant properties reducing the harm of fire accidents. SPI-RA6-CSA1 adhesive also possessed the characteristics of low energy consumption and environmentally friendliness by Life Cycle Assessment (LCA). Therefore, this simple strategy provides workable guidance for the production of multifunctional and green soy protein adhesive. Adhesive ; Soy protein ; Environmentally friendly ; Rosin ; Materials science ; Composite material ; Pulp and paper industry ; Chemistry ; Chemical engineering ; Food science ; Organic chemistry ; Resin acid Antimicrobial agents and applications ; biodegradable polymer synthesis and properties ; Lignin and Wood Chemistry
Authors: Ramón L. Panadés‐Barrueta | Dorothea Golze
Source: arXiv (Cornell University) (preprint, 2023-05-25)
Field: Materials Science — Materials Chemistry

Accelerating core-level $GW$ calculations by combining the contour deformation approach with the analytic continuation of $W$ In recent years, the $GW$ method has emerged as a reliable tool for computing core-level binding energies. The contour deformation (CD) technique has been established as an efficient, scalable, and numerically stable approach to compute the $GW$ self-energy for deep core excitations. However, core-level $GW$ calculations with CD face the challenge of higher scaling with respect to system size $N$ compared to the conventional quartic scaling in valence state algorithms. In this work, we present the CD-WAC method (CD with $W$ Analytic Continuation), which reduces the scaling of CD applied to the inner shells from $O(N^5)$ to $O(N^4)$ by employing an analytic continuation of the screened Coulomb interaction $W$. Our proposed method retains the numerical accuracy of CD for the computationally challenging deep core case, yielding mean absolute errors $&lt;5$ meV for well-established benchmark sets, such as CORE65, for single-shot $GW$ calculations. More extensive testing for different $GW$ flavors prove the reliability of the method. We have confirmed the theoretical scaling by performing scaling experiments on large acene chains and amorphous carbon clusters, achieving speedups of up to 10x for structures of only 116 atoms. This improvement in computational efficiency paves the way for more accurate and efficient core-level $GW$ calculations on larger and more complex systems. Scaling ; Analytic continuation ; Coulomb ; Quartic function ; Physics ; Hamiltonian (control theory) ; Benchmark (surveying) ; Valence (chemistry) ; Statistical physics ; Algorithm ; Computational physics ; Mathematics ; Quantum mechanics ; Mathematical analysis ; Mathematical optimization ; Geometry ; Electron Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Electron and X-Ray Spectroscopy Techniques
Authors: Animesh Kundu
Source: International Journal of Chemical and Environmental Sciences (article, 2023-10-03)
Field: Chemistry — Inorganic Chemistry

Chemically Driven Water Oxidation Catalyzed by Ruthenium Complexes: An Overview Water oxidation is one of the vital parts of the natural and artificial photosynthesis. Moreover it plays an important role to convert solar energy to fuel. But the oxidation of water is a complicated task and required efficient catalysts to perform it artificially. In this review, a brief overview of homogeneous, ruthenium based molecular catalysts for the water oxidation reaction has been documented. This report will help to design and develop robust and efficient water oxidation catalysts artificially. Ruthenium ; Catalysis ; Artificial photosynthesis ; Homogeneous ; Catalytic oxidation ; Chemistry ; Redox ; Solar energy ; Combinatorial chemistry ; Computer science ; Environmental science ; Chemical engineering ; Organic chemistry ; Engineering Asymmetric Hydrogenation and Catalysis ; Electrocatalysts for Energy Conversion ; Environmental remediation with nanomaterials
Authors: Nuzul Wahyuning Diyah | Gita Miranda Warsito | Isnaeni Isnaeni | Shabrina Wahyu Hidayati
Source: Camellia. (article, 2023-12-31)
Field: Chemistry — Organic Chemistry

Antimicrobial Activity and Molecular Docking of Benzoyl-N,N’-dialkylurea against Target Proteins in Microbial Cells This research aims to evaluate the antimicrobial activity of benzoyl dialkylurea derivatives to meet the global need for new antibiotic lead compounds. Four compounds were tested in vitro against Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, and Candida albicans by broth dilution method using ciprofloxacin and nystatin as standards. Docking simulations were performed to target essential proteins including DNA gyrase, FabH, RNA polymerase in bacterial cells and DHFR in C. albicans. BDMU, BEU1, BEU2, BEU3 exhibited antibacterial activity while BEU1 and BEU2 showed weak antifungal activity against C. albicans. The BDMU, BEU2, BEU3 considered promising growth inhibition against P. aeruginosa. In silico molecular docking on DNA gyrase from P. aeruginosa (PDB. 6M1S) was proposed as a model for mechanism of action in bacterial cells. The monobenzoyl of dialkylurea containing urea functionality with chloro-substituent at position-2 and 4 on aromatic rings were potential as lead compound to generate new antibacterial agent. DNA gyrase ; Candida albicans ; Antimicrobial ; Bacillus subtilis ; Docking (animal) ; Chemistry ; Antibacterial activity ; Microbiology ; Escherichia coli ; Pseudomonas aeruginosa ; Staphylococcus aureus ; Biochemistry ; Bacteria ; Biology Synthesis and biological activity ; Organic Chemistry Cycloaddition Reactions ; Chemical Synthesis and Reactions
Authors: Hongming Wang | Huan-Yu Ku | Jie-Yien Lin | Hongbin Chen
Source: arXiv (Cornell University) (preprint, 2023-06-08)
Field: Materials Science — Materials Chemistry

Deep learning the hierarchy of steering measurement settings of qubit-pair states Quantum steering has attracted increasing research attention because of its fundamental importance, as well as its applications in quantum information science. Here we leverage the power of the deep learning model to infer the steerability of quantum states with specific numbers of measurement settings, which form a hierarchical structure. A computational protocol consisting of iterative tests is constructed to overcome the optimization, meanwhile, generating the necessary training data. According to the responses of the well-trained models to the different physics-driven features encoding the states to be recognized, we can numerically conclude that the most compact characterization of the Alice-to-Bob steerability is Alice's regularly aligned steering ellipsoid; whereas Bob's ellipsoid is irrelevant. We have also provided an explanation to this result with the one-way stochastic local operations and classical communication. Additionally, our approach is versatile in revealing further insights into the hierarchical structure of quantum steering and detecting the hidden steerability. Leverage (statistics) ; Qubit ; Computer science ; Hierarchy ; Quantum ; Ellipsoid ; Subspace topology ; Protocol (science) ; Topology (electrical circuits) ; Artificial intelligence ; Physics ; Quantum mechanics ; Engineering ; Electrical engineering Machine Learning in Materials Science ; Neural Networks and Reservoir Computing ; Quantum Computing Algorithms and Architecture