jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Samantha L. Fossa | Brian P. Anton | Daniel W. Kneller | Laudine M. C. Petralia | Mehul B. Ganatra | Madison L. Boisvert | Saulius Vainauskas | Siu‐Hong Chan | Cornelis H. Hokke | Jeremy M. Foster | Christopher H. Taron
Source: Journal of Biological Chemistry (article, 2023-11-07)
Field: Chemistry — Organic Chemistry

A novel family of sugar-specific phosphodiesterases that remove zwitterionic modifications of GlcNAc 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 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. Phosphodiesterase ; Sugar ; Biochemistry ; Chemistry ; Enzyme Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Peptidase Inhibition and Analysis
Authors: Caihua Qiu | Feng Ding | Xiu He | Mengbo Wang
Source: Information Technology And Control (article, 2023-12-22)
Field: Chemistry — Analytical Chemistry

Apply Physical System Model and Computer Algorithm to Identify Osmanthus Fragrans Seed Vigor Based on Hyperspectral Imaging and Convolutional Neural Network This study explored the feasibility of using hyperspectral imaging technology and to identify Osmanthus fragrans seeds with different vigor under computer algorithm and physical system. Two varieties of Osmanthus seeds (JinQiGui and RiXiangGui) were artificially aged and then hyperspectral data were collected. Multivariate scattering correction (MSC) was used for spectral preprocessing. The selection of characteristic wavelength was realized by competitive adaptive reweighted sampling algorithm (CARS). The extreme learning machine (ELM) and k-nearest neighbor (KNN) were used to establish the spectral discriminant model, and convolutional neural network was used in the computer image discriminant model. The results show that the ability to recognize different vigor JQG was better than RXG. MSC preprocessing can not only make the data distribution more aggregated, but also effectively improve the accuracy of the model. MSC+CARS combined with discriminant model can be realized close to 100% recognition with fewer bands. Compared with machine learning model, image- depth learning model can get higher model accuracy for different vigor JQG and RXG without complex preprocessing. These results indicate that hyperspectral imaging technology can effectively distinguish different vigor of Osmanthus fragrans seeds based on computer technology and physical system, which is of great significance for future research. Hyperspectral imaging ; Preprocessor ; Osmanthus fragrans ; Artificial intelligence ; Convolutional neural network ; Computer science ; Pattern recognition (psychology) ; Discriminant ; Data pre-processing ; Imaging spectrometer ; Extreme learning machine ; Linear discriminant analysis ; Artificial neural network ; Machine learning ; Spectrometer Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Smart Agriculture and AI
Authors: Michael Widom | M. Mihalkovič
Source: Israel Journal of Chemistry (review, 2023-10-16)
Field: Materials Science — Materials Chemistry

Quasicrystal Structure Prediction: A Review Abstract Predicting quasicrystal structures is a multifaceted problem that can involve predicting a previously unknown phase, predicting the structure of an experimentally observed phase, or predicting the thermodynamic stability of a given structure. We survey the history and current state of these prediction efforts with a focus on methods that have improved our understanding of the structure and stability of known metallic quasicrystal phases. Advances in the structural modeling of quasicrystals, along with first principles total energy calculation and statistical mechanical methods that enable the calculation of quasicrystal thermodynamic stability, are illustrated by means of cited examples of recent work. Quasicrystal ; Stability (learning theory) ; Chemistry ; Statistical physics ; Work (physics) ; Phase (matter) ; Focus (optics) ; Thermodynamics ; Crystallography ; Physics ; Machine learning ; Computer science ; Optics Quasicrystal Structures and Properties ; X-ray Diffraction in Crystallography ; Crystallography and molecular interactions
Authors: Chih‐Hao Chang | Li-Hui Tsai | Yi-Chen Lee | Weicheng Yao | Jiang‐Jen Lin
Source: International Journal of Molecular Sciences (article, 2023-04-10)
Field: Materials Science — Materials Chemistry

Synergistic Effects of Silicate-Platelet Supporting Ag and ZnO, Offering High Antibacterial Activity and Low Cytotoxicity Silver nanoparticles (AgNPs) are remarkably able to eliminate microorganisms, but induce cytotoxicity in mammalian cells, and zinc oxide nanoparticles (ZnONPs) are considered to have a wide bactericidal effect with weak cytotoxicity. In this study, both zinc oxide nanoparticles and silver nanoparticles were co-synthesized on a nano-silicate platelet (NSP) to prepare a hybrid of AgNP/ZnONP/NSP. Ultraviolet-visible spectroscopy (UV-Vis), X-ray diffraction (XRD), and transmission electron microscopy (TEM) were used to characterize the formation of nanoparticles on the NSP. Synthesized ZnONP/NSP (ZnONP on NSP) was confirmed by the absorption peaks on UV-Vis and XRD. AgNP synthesized on ZnONP/NSP was also characterized by UV-Vis, and ZnONP/NSP showed no interference with synthesis. The images of TEM demonstrated that NSP provides physical support for the growth of nanoparticles and could prevent the inherent aggregation of ZnONP. In antibacterial tests, AgNP/ZnONP/NSP exhibited more efficacy against Staphylococcus aureus (<i>S. aureus</i>) than ZnONP/NSP (ZnONP was synthesized on NSP) and AgNP/NSP (AgNP was synthesized on NSP). In cell culture tests, 1/10/99 (weight ratio) of AgNP/ZnONP/NSP exhibited low cytotoxicity for mammalian cells (>100 ppm). Therefore, AgNP/ZnONP/NSP, containing both AgNP and ZnONP, with both strong antibacterial qualities and low cytotoxicity, showed potentially advantageous medical utilizations due to its antibacterial properties. Cytotoxicity ; Zinc ; Nuclear chemistry ; Nanoparticle ; Chemistry ; Biochemistry ; Materials science ; Nanotechnology ; In vitro ; Organic chemistry Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Gu‐Hyeok Kang | Myung-Soo Kim | Young-Bin Park
Source: Polymer Testing (article, 2023-07-01)
Field: Materials Science — Materials Chemistry

Improvement of electrical conductivity in glass bubble-carbon nanotube/polyamide 6 hybrid scale composite through novel mechanical forming and segregated network morphology The study suggests that GB-CNT/PA6 multiscale hybrid composite can be used to create a network structure with controllable electrical conductivity, making it a promising material for various practical applications. The paper introduces a new method for controlling electrical conductivity of composite materials by creating a segregated network morphology (SNM) using a glass bubble (GB)-carbon nanotube (CNT)/polyamide 6 (PA6) multiscale hybrid composite. Instead of relying solely on CNTs, the addition of GB allows for a more economical process by reducing the required CNT concentration to achieve the desired electrical conductivity. The paper also analyzes the effects of varying GB and CNT content on electrical conductivity based on percolation theory. The results demonstrate an 18.8 times increase in electrical conductivity with the SNM approach. The study proposes that this approach could be used to create composite materials with controllable electrical conductivity, making them suitable for various applications. Materials science ; Carbon nanotube ; Composite number ; Polyamide ; Percolation threshold ; Composite material ; Electrical resistivity and conductivity ; Conductivity ; Percolation (cognitive psychology) ; Percolation theory ; Bubble ; Nanotechnology ; Computer science ; Electrical engineering Carbon Nanotubes in Composites ; Thermal properties of materials ; Advanced Sensor and Energy Harvesting Materials
Authors: Alejandro Regalado-Méndez | Juliana Zavaleta-Avendaño | Ever Peralta-Reyes | Reyna Natividad
Source: Journal of Solid State Electrochemistry (article, 2023-04-11)
Field: Chemistry — Electrochemistry

Convex optimization for maximizing the degradation efficiency of chloroquine in a flow-by electrochemical reactor Anode ; Analytical Chemistry (journal) ; Materials science ; Electrochemistry ; Diamond ; Cathode ; Volumetric flow rate ; Degradation (telecommunications) ; Electrode ; Chemistry ; Thermodynamics ; Chromatography ; Physics ; Composite material ; Electrical engineering Electrochemical Analysis and Applications ; SARS-CoV-2 detection and testing ; Antibiotics Pharmacokinetics and Efficacy
Authors: Mehrdad Youzi | Mohammad Kianezhad | Mehran Vaezi | Hossein Nejat Pishkenari
Source: Physical Chemistry Chemical Physics (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Motion of nanovehicles on pristine and vacancy-defected silicene: implications for controlled surface motion Understanding the motion of surface-rolling nanomachines has attracted lots of attention in recent studies, due to their ability in carrying molecular payloads and nanomaterials on the surface. Controlling the surface motion of these nanovehicles is beneficial in the fabrication of nano-transportation systems. In the present study, molecular dynamics (MD) simulations alongside the potential energy analysis have been utilized to investigate the motion of C<sub>60</sub> and C<sub>60</sub>-based nanovehicles on the silicene monolayer. Nano-machine simulations are performed using molecular mechanic forcefield. Compared with graphene and hexagonal boron-nitride, the molecules experience a higher energy barrier on the silicene, which leads to a lower diffusion coefficient and higher activation energy of C<sub>60</sub> and nanomachines. Overcoming the maximum energy barrier against sliding motion is more probable at higher temperatures where the nanomachines receive higher thermal energy. After evaluating the motion of molecules around local vacancies, we introduce a nanoroad structure that can restrict surface motion. The motion of C<sub>60</sub> and nanovehicles over the surface is limited to the width of nanorods up to a certain temperature. To increase the controllability of the motion, a thermal gradient has been applied to the surface and the molecules move toward the lower temperature regions, where they find lower energy levels. Comparing the results of this study with other investigations regarding the surface motion of molecules on boron-nitride and graphene surfaces brings forth the idea of controlling the motion by silicene-based hybrid substrates, which can be further investigated. Silicene ; Nanotechnology ; Nanomaterials ; Motion (physics) ; Materials science ; Vacancy defect ; Surface (topology) ; Graphene ; Physics ; Condensed matter physics ; Classical mechanics Graphene research and applications ; Supramolecular Self-Assembly in Materials ; Molecular Junctions and Nanostructures
Authors: Bowen Shi | Jiajun Hong | Zhihua Wang | Zhenbo Chang | Feng Li
Source: Journal of Petroleum Exploration and Production Technology (article, 2023-11-02)
Field: Chemistry — Analytical Chemistry

Treatment of paraffin deposition behavior in gas-condensate wells with chemical inhibitors Abstract As deep gas-condensate reservoirs are explored, the problem of paraffin deposition is becoming more prominent. Therefore, this paper collects condensate samples from representative paraffin deposition gas-condensate wells and analyzes basic physical properties. The cold plate deposition device is employed to study paraffin deposition behavior under well conditions and to divide the critical regions for paraffin deposition in gas-condensate wells. The experimental apparatus, such as the crude oil dynamic paraffin deposition rate tester, is utilized to investigate the preventive effect of paraffin dispersants and paraffin crystal modifier. The results show that there is significant phase change behavior in gas-condensate wells and gas phase is dominant form, but there is also phase evolution. It can be identified from the experiments that paraffin deposition is mainly located in the 1000 ~ 1500 m region, and a paraffin deposition identification chart has been established. The maximum deposition rate could reach 15.50 mm/year, which matched the temperature and pressure conditions of 45 ℃ and 70 MPa. The preventive effect of paraffin crystal modifiers greatly exceeds that of paraffin dispersants, with paraffin prevention rates of 85–95% at the optimal concentrations of 0.25–0.50 wt.%. The dissolving paraffin rate can reach 0.0169 g/min. It decreases the paraffin appearance temperature approximately 40% and significantly changes the paraffin crystal morphology. Increased deposition surface area of the cold plate structural design describes the paraffin deposition. This diagram facilitates the reliable identification of paraffin deposition areas and the deposition rates in the wellbore during production. The optimum amounts of BZ and PI paraffin inhibitors are quantified. This study provides a comprehensive understanding of the paraffin deposition behavior, and scientific basis and guidance for the selection of paraffin inhibitors in gas-condensate wells. Deposition (geology) ; Dissolution ; Dispersant ; Materials science ; Chemical engineering ; Chemistry ; Geology ; Organic chemistry ; Dispersion (optics) Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: Abd El-Moneim A. Harb | Khairy Elsayed | A.E. Kabeel | Mahmoud Ahmed | Ahmed Abdo
Source: Journal of Thermal Analysis and Calorimetry (article, 2023-09-12)
Field: Materials Science — Materials Chemistry

Investigating the modified thermoelectric generator system performance Abstract It is essential to enhance the performance of the thermoelectric generator as lower efficiencies are obtained recently. This could be achieved by changing its dimensions in addition to copper strip thickness. The present study is performed to obtain the best dimensions of the P – N legs considering the interaction between all variables. To do this, a comprehensive TEG model is achieved in addition to utilizing the single-objective optimization technique. The main performance metrics, including electricity production and conversion efficiency, are assessed, and contrasted with the conventional TEG system since the simulation. The length of the legs and their cross-sectional area were shown to significantly affect power production. The thickness of the conducting plate, in contrast, barely matters. For instance, a P – N pair with legs that have a 2 mm 2 cross-sectional area generates 0.4 W and 1.3 W for temperature differences of 480 °C and 980 °C, respectively. Furthermore, the equivalent efficiencies are 4.41% and 6.73%, respectively. Using the genetic algorithm revealed that the ideal values for the leg cross section, leg length, and conducting plate thickness are 1.84 mm 2 , 0.5 mm, and 0.44 mm, respectively. Once compared to the conventional system, using the optimization method results in an improvement in power production and conversion efficiency of about 247% at a temperature differential of 980 °C. Thermoelectric generator ; Generator (circuit theory) ; Materials science ; Power (physics) ; Seebeck coefficient ; Thermoelectric effect ; Energy conversion efficiency ; Electricity generation ; Mathematics ; Composite material ; Analytical Chemistry (journal) ; Thermodynamics ; Optoelectronics ; Chemistry ; Thermal conductivity ; Physics Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies ; Thermal properties of materials
Authors: Aaron Bjarnason | Aniruddha Majumder
Source: Industrial & Engineering Chemistry Research (article, 2023-03-10)
Field: Materials Science — Materials Chemistry

A Novel Simulated Moving Plug Flow Crystallizer (SM-PFC) for Addressing the Encrustation Problem: Simulation-Based Studies on Cooling Crystallization The plug flow crystallizer (PFC) is a promising candidate in the move toward adoption of continuous manufacturing in the pharmaceutical industry. However, a major concern for the smooth running of PFCs is the encrustation or fouling which can result in blockage of the crystallizer or unplanned shutdown of the process. In order to address this problem, simulation studies are carried out to explore the feasibility of a novel simulated-moving PFC (SM-PFC) configuration that can run uninterrupted in the presence of heavy fouling without compromising the desired critical quality attributes of the product crystals. The key concept of the SM-PFC lies in the arrangement of the crystallizer segments where a fouled segment is isolated, while a clean segment is simultaneously brought online avoiding fouling-related issues and maintaining uninterrupted operation. The inlet and outlet ports are also changed appropriately so that the whole operation mimics the movement of the PFC. The simulation results suggest that the proposed PFC configuration could be a potential mitigating approach for the encrustation problem enabling continuous operation of the crystallizer in the presence of heavy fouling while maintaining the product specifications. Fouling ; Process engineering ; Process (computing) ; Crystallization ; Flow (mathematics) ; Spark plug ; Plug flow ; Computer science ; Environmental science ; Mechanical engineering ; Chemistry ; Engineering ; Chemical engineering ; Mechanics Crystallization and Solubility Studies ; Innovative Microfluidic and Catalytic Techniques Innovation ; Freezing and Crystallization Processes
Authors: Joseph Broomfield | Melpomeni Kalofonou | Sylvia Franklin | Sue M. Powell | Thomas Pataillot-Meakin | Nicolas Moser | Charlotte L. Bevan | Pantelis Georgiou
Source: PubMed (article, 2023-08-01)
Field: Chemistry — Spectroscopy

Handheld ISFET Lab-on-Chip detection of TMPRSS2-ERG and AR mRNA for prostate cancer prognostics. Ion-sensitive field-effect transistors (ISFETs) in combination with unmodified complementary metal oxide semiconductors present a point-of-care platform for clinical diagnostics and prognostics. This work illustrates the sensitive and specific detection of two circulating mRNA markers for prostate cancer, the androgen receptor and the TMPRSS2-ERG fusion using a target-specific loop-mediated isothermal amplification method. TMPRSS2-ERG and androgen receptor RNA were detected down to 3x10<sup>1</sup> and 5x10<sup>1</sup> copies respectively in under 30 minutes. Administration of these assays onto the ISFET Lab-on-chip device was successful and the specificity of each marker was corroborated with mRNA extracted from prostate cancer cell lines. Prostate cancer ; ISFET ; TMPRSS2 ; Messenger RNA ; Prognostics ; Loop-mediated isothermal amplification ; Androgen receptor ; Cancer research ; Prostate ; Cancer ; Medicine ; Materials science ; Computer science ; Field-effect transistor ; Internal medicine ; Transistor ; Chemistry ; Gene ; Engineering ; Electrical engineering ; Biochemistry Mass Spectrometry Techniques and Applications ; Advanced biosensing and bioanalysis techniques ; Advanced Proteomics Techniques and Applications
Authors: Tomasz Porȩba | Marcin Świątkowski | Giorgia Confalonieri
Source: CrystEngComm (article, 2023-01-01)
Field: Chemistry — Organic Chemistry

Melting pseudosymmetry and thermal expansion in 3-benzoylpropionic acid 3-Benzoylpropionic acid undergoes continuous transition associated with pseudosymmetry melting upon heating. The transition stems from a directional steric crowding, which refutes the recent premise of its colossal thermal expansion. Steric effects ; Thermal expansion ; Thermal ; Premise ; Melting temperature ; Chemistry ; Transition (genetics) ; Negative thermal expansion ; Crystallography ; Materials science ; Thermodynamics ; Physics ; Stereochemistry ; Composite material ; Philosophy Chemical Thermodynamics and Molecular Structure ; Crystallography and molecular interactions ; Thermodynamic properties of mixtures
Authors: Shusheng Xie | Leilei Gu | Jianping Guo
Source: Journal of Physics D Applied Physics (article, 2023-10-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Design of chiral plasmonic metamaterials based on interpretable deep learning Abstract Chiral plasmonic metamaterials can amplify chiral signals, resulting in circular dichroism (CD) responses that are several orders of magnitude far beyond those of nature. However, the design process of chiral plasmonic metamaterials based on conventional methods is time-consuming. In recent years, the combination of deep learning (DL) and nanophotonics have accelerated the design of nanophotonic devices. Here, we construct the fully connected neural network model for the forward prediction and inverse design of chiral plasmonic metamaterials structures and introduce the permutation importance approach to optimize the model and increase its interpretability. Our experimental results show that using the peak magnitude of CD and the corresponding wavelength instead of the entire spectrum as the output in the forward prediction improves the accuracy of the peak magnitude of CD prediction, avoids the introduction of auxiliary networks, and simplifies the network structure; the permutation importance analysis shows that the gold length of the resonator is the most critical structural parameter affecting the CD response. In the inverse design, the permutation importance method helps us to make feature selections for the input of the network. By reducing 251 inputs (the whole CD spectrum) to 4 inputs (the peak magnitude of CD and the corresponding wavelength), the network can still maintain a good prediction performance and decrease the training time of the network. Our proposed method can be extended not only to other DL models to study the CD response of chiral metamaterials but also to other areas where DL is combined with metamaterials to accelerate the system optimization and design process of nanophotonic devices. Metamaterial ; Plasmon ; Interpretability ; Nanophotonics ; Computer science ; Permutation (music) ; Inverse ; Deep learning ; Topology (electrical circuits) ; Algorithm ; Physics ; Materials science ; Optoelectronics ; Artificial intelligence ; Mathematics ; Geometry ; Acoustics Metamaterials and Metasurfaces Applications