jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anne Zenner | Johannes Steinmetzer | Nico Ueberschaar | Martin Freesmeyer | Wolfgang Weigand | Julia Greiser
Source: Royal Society Open Science (article, 2024-07-01)
Field: Chemistry — Organic Chemistry

The synthesis of <i>N</i> ,1,4-tri(alkoxy-hydroxybenzyl)-1,4-diazepane-amines: investigations on reaction characteristics and mechanism 1,4-Diazepane-6-amine (DAZA) can be alkylated with three 2-hydroxybenzyl pendant arms, resulting in hexadentate chelators suitable for coordination of radiometals like <sup>68</sup>Ga. These chelators, <i>N</i>,1,4-tri(alkoxy-2-hydroxybenzyl)-DAZA, can be produced via a one-pot synthesis, with the first step being a carbonyl amine condensation of DAZA with two respective 4-alkoxy-2-hydroxybenzaldehydes, followed by reductive amination with sodium borohydride. While the first step of this reaction is predictable, the subsequent reductive amination can result in either mono-, di- or tri(alkoxy-hydroxybenzyl)-DAZA compounds. Seeking to identify dependencies that might allow a specific reaction control towards the formation of either of the three possible products, and particularly towards the favoured trialkylated DAZA compounds, a variety of synthesis trials were performed. Additionally, computational methods were employed to evaluate the underlying reaction mechanism. Synthesis trials verified that the trialkylated DAZA compounds are formed via direct reductive amination of the dialkylated DAZA compounds. Subsequently, a synthetic method was established, leading to an increase in the percentage of the trialkylated DAZA compounds, which allowed the successful isolation of those hexadentate chelators. Additionally, an alternative pathway proceeding via aminal C-N bond insertion of an attacking third carbonyl moiety was evaluated by means of quantum chemical calculations but so far remains entirely hypothetical. Alkoxy group ; Mechanism (biology) ; Reaction mechanism ; Chemistry ; Combinatorial chemistry ; Stereochemistry ; Physics ; Organic chemistry ; Catalysis Chemical Reaction Mechanisms ; Chemical Synthesis and Analysis ; DNA and Nucleic Acid Chemistry
Authors: Georgios Samourgkanidis | Theodora Kyratsi
Source: Preprints.org (preprint, 2024-01-12)
Field: Materials Science — Materials Chemistry

Influence of Laser Treatment on the Thermoelectric Properties of Bismuth Antimony Telluride Material In this study, the effect of laser processing (LP) on the thermoelectric (TE) properties of bismuth antimony telluride (BST) alloy pellets is investigated. The stoichiometric alloy used is Bi0.4Sb1.6Te3.0, which was prepared by mechanical alloying techniques (MA) and hot pressed (HP) into pellets under optimal pressing and temperature conditions. An innovative approach to HP was also developed to enhance the yield of BST samples per HP process while maintaining the TE profiles of the samples within a variance of less than 1%. The LP process was executed by employing a metal 3D printer, with a thorough analysis of beam parameters. Notably, the laser power (P) was held constant at 25 W, along with a fixed hatching distance (HD) of 50 μm, while the parameter adjusted was the laser&amp;#039;s scanning speed (SS), which spanned from [600 - 1800] mm/s in increments of 200 mm/s. Examination via scanning electron microscopy (SEM) revealed two material states: melted and sintered. The melted state formed the surface crust of &amp;quot;canyon&amp;quot; patterns that were held on the surface of the samples, and which both size and quantity were altered with changes in SS. For thermoelectric characterization, two distinct shapes of LP samples were produced: rectangular (for electrical properties) and disk (for thermal properties). The results demonstrated that the electrical properties are profoundly influenced by SS, with the electrical conductivity peak at SS value of 1600 mm/s, while the Seebeck coefficient reaches a minimum at the same value. Consequently, within the temperature range of interest, a notable 12% increase in electrical conductivity and a 9% decrease in the Seebeck coefficient were observed compared to the non-LP material state. Overall, the ZT value experience an 6.9% decline within the same temperature interval. Materials science ; Bismuth telluride ; Seebeck coefficient ; Thermoelectric effect ; Scanning electron microscope ; Alloy ; Laser ; Electrical resistivity and conductivity ; Thermoelectric materials ; Laser power scaling ; Analytical Chemistry (journal) ; Thermocouple ; Thermal conductivity ; Metallurgy ; Composite material ; Optics ; Thermodynamics ; Electrical engineering ; Chemistry Advanced Thermoelectric Materials and Devices ; Thermography and Photoacoustic Techniques ; Chalcogenide Semiconductor Thin Films
Authors: Bioru Okumura | Eriko Yamaguchi | Naoko Komura | Taku Ohtomi | S. Kawano | Hiroshi Katagiri | Hiromune Ando | Masato Ikeda
Source: ChemRxiv (preprint, 2024-01-18)
Field: Materials Science — Biomaterials

Photodegradable glyco-microfibers fabricated by the self-assembly of cellobiose derivatives bearing nitrobenzyl groups Stimuli-responsive materials constructed via the self-assembly of small biomolecules are attracting increasing attention because of their biocompatibility, sustainability, and variety of (bio)applications. Nevertheless, the research on oligosaccharide-based molecular designs for such stimuli-responsive materials (or stimuli-responsive glyco-materials) is limited, partly due to the intrinsic structural diversity of oligosaccharides and the difficulty associated with their selective chemical syntheses. Herein, we report the construction of photodegradable glyco-microfibers by the self-assembly of cellobiose derivatives bearing nitrobenzyl groups. The atomic-scale, self-assembled architecture of the photodegradable glyco-microfibers is unveiled and compared with those of pristine cellobiose and cellulose polymorphs in previous reports. Microfiber ; Cellobiose ; Chemistry ; Nanotechnology ; Biocompatibility ; Self-assembly ; Biomolecule ; Materials science ; Cellulose ; Organic chemistry ; Cellulase biodegradable polymer synthesis and properties ; Supramolecular Self-Assembly in Materials
Authors: Ximena Lopez‐Lorenzo | Ganapathy Ranjani | Per‐Olof Syrén
Source: ChemBioChem (article, 2024-07-22)
Field: Materials Science — Biomaterials

Conformational Selection in Enzyme‐Catalyzed Depolymerization of Bio‐based Polyesters Enzymatic degradation of polymers holds promise for advancing towards a bio-based economy. However, the bulky nature of polymers presents challenges in accessibility for biocatalysts, hindering depolymerization reactions. Beyond the impact of crystallinity, polymer chains can reside in different conformations affecting binding efficiency to the enzyme active site. We previously showed that the gauche and trans chain conformers associated with crystalline and amorphous regions of the synthetic polyethylene terephthalate (PET) display different affinity to PETase, thus affecting the depolymerization rate. However, structural-function relationships for biopolymers remain poorly understood in biocatalysis. In this study, we explored the biodegradation of previously synthesized bio-polyesters made from a rigid bicyclic chiral terpene-based diol and copolymerized with various renewable diesters. Herein, four of those polyesters spanning from semi-aromatic to aliphatic were subjected to enzymatic degradations in concert with induced-fit docking (IFD) analyses. The monomer yield following enzymatic depolymerization by IsPETase S238 A, Dura and LCC ranged from 2 % to 17 % without any further pre-treatment step. The degradation efficiency was found to correlate with the extent of matched substrate and enzyme conformations revealed by IFD, regardless of the actual reaction temperature employed. Our findings demonstrate the importance of conformational selection in enzymatic depolymerization of biopolymers. A straight or twisted conformation of the polymer chain is crucial in biocatalytic degradation by showing different affinities to enzyme ground-state conformers. This work highlights the importance of considering the conformational match between the polymer and the enzyme to optimize the biocatalytic degradation efficiency of biopolymers, providing valuable insights for the development of sustainable bioprocesses. Depolymerization ; Polyester ; Polymer ; Chemistry ; Biocatalysis ; Conformational isomerism ; Organic chemistry ; Materials science ; Catalysis ; Reaction mechanism ; Molecule biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Polymer crystallization and properties
Authors: Masha Sosonkina | Gabriel Mateescu | Peng Xu | Tosaporn Sattasathuchana | Buu Q. Pham | Mark S. Gordon | Sarom S. Leang
Source: Concurrency and Computation Practice and Experience (article, 2024-08-06)
Field: Chemistry — Inorganic Chemistry

Runtime performance of a GAMESS quantum chemistry application offloaded to GPUs Summary Computational chemistry is at the forefront of solving urgent societal problems, such as polymer upcycling and carbon capture. The complexity of modeling these processes at appropriate length and time scales is mainly manifested in the number and types of chemical species involved in the reactions and may require models of several thousand atoms and large basis sets to accurately capture the chemical complexity and heterogeneity in the physical and chemical processes. The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) has a wide array of methods that can efficiently and accurately treat complex chemical systems. In this work, we have used the GAMESS Effective Fragment Molecule Orbital (EFMO) method for electronic structure calculation of a challenging mesoporous silica nanoparticle (MSN) model surrounded by about 4700 water molecules to investigate the strong scaling and GPU offloading on hybrid CPU‐GPU nodes. Experiments were performed on the Perlmutter platform at the National Energy Research Scientific Computing Center. Good strong scaling and load balancing have been observed on up to 88 hybrid nodes for different settings of the execution parameters for the calculation considered here. When GPUs are oversubscribed by offloading work from multiple CPU processes, using the NVIDIA multi‐process service (MPS) has consistently reduced time to solution and energy consumed. Additionally, for some configuration parameter settings, oversubscription with MPS improved performance by up to 5.8% over the case without oversubscription. Computer science ; Scaling ; Computational science ; Scalability ; Quantum chemical ; Distributed computing ; Molecule ; Chemistry ; Database Zeolite Catalysis and Synthesis ; Machine Learning in Materials Science ; Catalysis and Oxidation Reactions
Authors: Yang Shi | Lixiang Wang | Lingling Li | Feng Chen | Yue Cao
Source: ChemistryOpen (review, 2024-12-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Innovative Progress of LSPR‐Based Dark‐Field Scattering Spectral Imaging in the Biomedical Assay at the Single‐Particle Level The growing demand for detection and sensing in the biomedical field is placing higher demands on technology. In clinical testing, it is expected to be able to realize both rapid large-field imaging and analysis of single particles (or single molecules or single cells), and it is expected to be able to grasp both the unique individuality of single particles in time and space during the complex reaction process, as well as the regular correlation between single particles in the same population distribution. Supported and promoted by the theory of localized surface plasmon resonance (LSPR), dark-field microscopy, as a single-particle optical imaging technique with a very high signal-to-noise ratio, provides a powerful new means to address the above clinical detection needs. This review will focus on the innovative applications of dark-field microscopy in biomedical-related assays in the past five years, introducing the basic principles and listing the impressing works. We also summarize how dark-field microscopy has been combined with other techniques, including surface-enhanced Raman scattering, fluorescence, colorimetry, electrochemistry, etc., to witness the joint progress and promotion of detection methods in the future. It also provides an outlook on the current challenges and future trends in this field. Nanotechnology ; Dark field microscopy ; Microscopy ; Field (mathematics) ; Population ; Computer science ; Materials science ; Optics ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Biosensors and Analytical Detection ; Plasmonic and Surface Plasmon Research
Authors: 敏正 山崎 | Xinyang Hu | Hualin Bi
Source: Journal of Baltic Science Education (article, 2024-12-25)
Field: Chemistry — Physical and Theoretical Chemistry

USING BAYESIAN NETWORKS FOR COGNITIVE DIAGNOSIS ASSESSMENT OF UPPER-SECONDARY SCHOOL STUDENTS UNDERSTANDING IN REDOX REACTION The redox reaction is a core concept of upper-secondary school chemistry curriculum. Accurate diagnosis of students’ conceptual understanding of the redox reaction from a cognitive structure perspective is critical for enhancing their understanding of chemical concepts. This study utilized Bayesian networks to investigate the cognitive structures of Chinese students regarding the redox reaction. A total of 409 upper-secondary school students participated, with 227 in 11th grade and 182 in 12th grade. Seven cognitive attributes related to the redox reaction were identified, and their hierarchical relationships were mapped. The research process of cognitive diagnosis assessment of redox reaction based on Bayesian network was developed. The results indicated that Bayesian networks can effectively assess students’ cognitive structures of the redox reaction. Key attributes identified in students’ cognitive structures were "electron transfer", "oxidation reaction / reduction reaction" and "oxidability / reducibility". Furthermore, a comparison of the cognitive structures between 11th and 12th graders showed that 12th graders had a more advanced understanding with fewer conceptual gaps, while 11th graders demonstrated less developed cognitive pathways, which may be attributed to a lack of deep conceptual understanding. Keywords: Bayesian network, cognitive diagnostic assessment, redox reaction, cognitive structure Cognition ; Redox ; Bayesian probability ; Bayesian network ; Computer science ; Psychology ; Artificial intelligence ; Chemistry ; Neuroscience Various Chemistry Research Topics ; Chemical Safety and Risk Management ; Science Education and Pedagogy
Authors: Hyun-Kyu Hwang | Seong‐Jong Kim
Source: npj Materials Degradation (article, 2024-11-30)
Field: Materials Science — Metals and Alloys

Effects of electropolishing and plasma ion nitriding on UNS S31603 corrosion in ship scrubber water Marine scrubbers use seawater as washing water and are damaged by sulfur oxides and chlorides during desulfurization. Therefore, surface treatments to enhance corrosion and pitting resistance of scrubber materials must be investigated. This investigation conducts cyclic potentiodynamic polarization experiments to analyze the effects of electropolishing and plasma ion nitiriding of UNS S31603 in washing water. The corrosion current density (0.186 μA cm-2) of electropolishing is significantly lower than mechanical polishing (1.125 μA cm-2), but plasma ion nitriding is higher (18.995 μA cm-2). Electropolishing forms a uniform and dense passivation film, increasing corrosion resistance, whereas plasma ion nitriding reduces corrosion resistance due to CrN formation. All specimens present local corrosion. Electropolishing reduces the maximum damage depth by 110.13 μm and increases pitting potential by 0.32 V compared to mechanical polishing. Plasma ion nitriding reduces maximum damage depth by 46.59 μm due to suppression of local acidification during hydrolysis. Electropolishing ; Nitriding ; Corrosion ; Scrubber ; Plasma ; Metallurgy ; Ion ; Materials science ; Chemistry ; Engineering ; Layer (electronics) ; Waste management ; Physics ; Composite material ; Nuclear physics Hydrogen embrittlement and corrosion behaviors in metals ; Metal and Thin Film Mechanics ; Corrosion Behavior and Inhibition
Authors: Sumair Ahmed Soomro | Muhammad Irfan Jahanger | Maaz Ullah Khan | Yanchun Zhou | Shuai Fu | Detian Wan | Yiwang Bao | Qingguo Feng | Chunfeng Hu
Source: International Journal of Applied Ceramic Technology (article, 2024-06-12)
Field: Materials Science — Materials Chemistry

Enhanced properties of multi‐element soluted (Nb <sub>0.8</sub> Ti <sub>0.05</sub> Zr <sub>0.05</sub> Mo <sub>0.05</sub> M <sub>0.05</sub> ) <sub>4</sub> AlC <sub>3</sub> (M = Hf, Ta) ceramics Abstract Recently multielements solid solution has shown significant improvement to the mechanical properties of parent MAX phases. Therefore, in this work, five elements with different radii were incorporated to check the effect on properties of MAX phases. (Nb 0.8 Ti 0.05 Zr 0.05 Mo 0.05 Hf 0.05 ) 4 AlC 3 (MAX Hf ) and (Nb 0.8 Ti 0.05 Zr 0.05 Mo 0.05 Ta 0.05 ) 4 AlC 3 (MAX Ta ) ceramics were successfully synthesized using the spark plasma sintering technique. The microstructure and elemental map analysis results further confirmed that the five transition metals were successfully solid soluted at the M‐sites of the hexagonal M 4 AlC 3 unit cell. The mean elemental compositions for M‐site elements were achieved as Nb 0.85 Ti 0.052 Zr 0.035 Mo 0.027 Hf 0.036 and Nb 0.847 Ti 0.051 Zr 0.043 Mo 0.025 Ta 0.033 for MAX Hf and MAX Ta ceramics, respectively. The electrical and thermal conductivities of multielement solid solution MAX phases were decreased compared to pure Nb 4 AlC 3 . However, Mechanical properties were significantly increased with the solid solution of five transition metals. The fracture toughness, flexural strength, compressive strength and Vickers hardness (10 N) of MAX Hf and MAX Ta ceramics were achieved as 8.87 MPa m 1/2 , 448 MPa, 867 MPa, 6.5 GPa and 10.36 MPa m 1/2 , 557 MPa, 1039 MPa, 8.2 GPa, respectively. The enhanced mechanical properties suggest the effectiveness of the solid solution strengthening effect and provide new opportunities to further tailor the mechanical properties of the MAX phase ceramics. Materials science ; Spark plasma sintering ; MAX phases ; Microstructure ; Vickers hardness test ; Ceramic ; Flexural strength ; Solid solution ; Fracture toughness ; Analytical Chemistry (journal) ; Hexagonal crystal system ; Composite material ; Metallurgy ; Crystallography MXene and MAX Phase Materials ; Aluminum Alloys Composites Properties ; Advanced ceramic materials synthesis
Source: Letters in Applied NanoBioScience (article, 2024-03-30)
Field: Materials Science — Materials Chemistry

Utilization of Eastern Nigerian Propolis Extract for Synthesis of Corrosion Inhibitive Silver Nanoparticles on Carbon Steel in Acidic Medium The high cost of production and potentially harmful effects of inorganic corrosion inhibitors on the ecosystem necessitated the search for a low-cost, efficient, and environmentally friendly alternative. Due to their high surface-to-volume ratio and capacity to create self-assembled films on metal surfaces, benign nanoparticles present a good alternative. In this study, Eastern Nigerian propolis extracts were utilized to synthesize silver nanoparticles and were characterized spectroscopically. The composites were then tested for corrosion-inhibitive potentials in HCl solution. The characteristic surface plasmon resonance (SPR) absorption bands were obtained at around 420 nm. The XRD results showed that the resultant crystalline silver nanoparticles of Eastern Nigerian Propolis Extract (ENPE-AgNPs) has FCC structure, with a mean nanoparticle size of 5.067 ± 1.465. The STEM image revealed several oval structures that were densely filled with AgNPs, which appeared as white spots, with patterns that appeared homogeneous. In the presence of 1000 ppm ENPE-AgNPs, the results showed high inhibition efficiency of 98.23 and 91.34 % for EIS and gravimetric technique, respectively. Also, the thermodynamic and adsorption characteristics of ENPE-AgNPs on CS in HCl solution were calculated. It was discovered that the ENPE-AgNPs performed well as an inhibitor of CS corrosion in HCl. Propolis ; Corrosion ; Carbon steel ; Carbon fibers ; Nanoparticle ; Chemistry ; Metallurgy ; Silver nanoparticle ; Nuclear chemistry ; Materials science ; Nanotechnology ; Food science ; Composite material ; Composite number Nanoparticles: synthesis and applications ; Plant-Derived Bioactive Compounds ; Lubricants and Their Additives
Authors: Abdou Khadir Dia | Axel Gambou Bosca | Nadia Ghazzali
Source: International Journal of Corrosion (article, 2024-04-24)
Field: Materials Science — Materials Chemistry

Walk-Through Corrosion Assessment of Slurry Pipeline Using Machine Learning The study of pipeline corrosion is crucial to prevent economic losses, environmental degradation, and worker safety. In this study, several machine learning methods such as recursive feature elimination (RFE), principal component analysis (PCA), gradient boosting method (GBM), support vector machine (SVM), random forest (RF), K-nearest neighbors (KNN), and multilayer perceptron (MLP) were used to estimate the thickness loss of a slurry pipeline subjected to erosion corrosion. These different machine learning models were applied to the raw data (the set of variables), to the variables selected by RFE, and to the variables selected by PCA (principal components), and a comparative analysis was carried out to find out the influence of the selection and transformation of the data on the performance of the models. The results show that the models perform better on the variables selected by RFE and that the best models are RF, SVM, and GBM with an average RMSE of 0.017. By modifying the hyperparameters, the SVM model becomes the best model with an RMSE of 0.011 and an <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"><a:mi>R</a:mi></a:math> -squared of 0.83. Support vector machine ; Principal component analysis ; Random forest ; Gradient boosting ; Artificial intelligence ; Mean squared error ; Multilayer perceptron ; Machine learning ; Pipeline (software) ; Hyperparameter ; Perceptron ; Computer science ; Feature selection ; Pattern recognition (psychology) ; Engineering ; Mathematics ; Artificial neural network ; Statistics Material Properties and Failure Mechanisms ; Non-Destructive Testing Techniques ; Erosion and Abrasive Machining