jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Antonio Lobosco | Claudia Lubrano | Daniela Rana | Viviana Rincón Montes | Simon Musall | Andreas Offenhäusser | Francesca Santoro
Source: Advanced Materials (article, 2024-10-14)
Field: Materials Science — Polymers and Plastics

Enzyme‐Mediated Organic Neurohybrid Synapses The development of organic artificial synapses that exhibit biomimicry features also may enable a more seamless integration of neuroelectronic devices in the nervous system, allowing artificial neuromodulation to be perceived as natural behavior by neuronal cells. Nevertheless, the capability to interact with both electroactive and non-electroactive neurotransmitters remains a challenge since state-of-the-art devices mainly rely on the oxidation of electroactive species. Here, the study proposes an organic artificial synapse engineered to enable interaction with non-electroactive species present in the central nervous system. By integrating a conductive polymeric film functionalized with platinum nanoparticles, the device can catalyze the oxidation of electroactive molecules (i.e., H<sub>2</sub>O<sub>2</sub>) resulting from neurotransmitter-specific enzymatic reactions following an enzymatic functionalization, therefore exhibiting neuromorphic functions driven by non-electroactive neurotransmitters. The creation of devices that can interact with or monitor these neurotransmitters can be seen as a significant step toward innovative technologies to expand the understanding of the mechanisms underlying neurological disorders and the development of novel, more effective treatments for them. Neuromorphic engineering ; Neuromodulation ; Nanotechnology ; Materials science ; Biomimetics ; Neurotransmitter ; Synapse ; Neuroscience ; Computer science ; Biology ; Artificial neural network ; Central nervous system ; Artificial intelligence Conducting polymers and applications ; Neuroscience and Neural Engineering ; Photoreceptor and optogenetics research
Authors: Lorenzo Veronico | Giuseppe Colafemmina | Luigi Gentile
Source: Colloids and Interfaces (article, 2024-01-04)
Field: Chemistry — Analytical Chemistry

Enhancing Oil-Uptake Efficiency with an Alkyl Polyglycoside–Dodecanol Formulation This study provides valuable insights into biobased surfactant systems, shedding light on their behavior and potential applications in cleaning and oil recovery processes. By combining the alkyl polyglycoside Triton® CG-110 with C12OH fatty alcohol, a promising strategy emerges, enhancing the efficiency of surfactant-based formulations. This innovative approach paves the way for sustainable solutions in diverse industrial applications. A rheological analysis of the formulations containing C12OH demonstrated a Newtonian-like behavior of up to 3.2 v/v% of Triton, while a viscoelastic response was observed in a system containing 6.4 v/v% of Triton. Self-diffusion nuclear magnetic resonance revealed the formation of larger aggregates with C12OH, diverging from the classical spherical micellar solution. Moreover, cleaning efficiency tests highlighted C12OH’s significant enhancement of the surfactant system’s oil-uptake capacity. This study identified the optimum formulation point, corresponding to the Winsor III microemulsion phase, in samples containing C12OH. This pivotal discovery showcases the potential of tailored surfactant blends, indicating a path toward greener and more effective industrial practices. Dodecanol ; Alkyl ; Business ; Chemistry ; Organic chemistry Petroleum Processing and Analysis ; Microbial bioremediation and biosurfactants ; Enhanced Oil Recovery Techniques
Authors: Yan Zhang | Fei Liu | Xiu Qin Li | Yan Gao | Kang Li | Qinghe Zhang
Source: Communications Chemistry (article, 2024-03-08)
Field: Chemistry — Spectroscopy

Generic and accurate prediction of retention times in liquid chromatography by post–projection calibration Retention time predictions from molecule structures in liquid chromatography (LC) are increasingly used in MS-based targeted and untargeted analyses, providing supplementary evidence for molecule annotation and reducing experimental measurements. Nevertheless, different LC setups (e.g., differences in gradient, column, and/or mobile phase) give rise to many prediction models that can only accurately predict retention times for a specific chromatographic method (CM). Here, a generic and accurate method is present to predict retention times across different CMs, by introducing the concept of post-projection calibration. This concept builds on the direct projections of retention times between different CMs and uses 35 external calibrants to eliminate the impact of LC setups on projection accuracy. Results showed that post-projection calibration consistently achieved a median projection error below 3.2% of the elution time. The ranking results of putative candidates reached similar levels among different CMs. This work opens up broad possibilities for coordinating retention times between different laboratories and developing extensive retention databases. Projection (relational algebra) ; Calibration ; Ranking (information retrieval) ; Retention time ; Chromatography ; Gradient elution ; Computer science ; Elution ; High-performance liquid chromatography ; Chemistry ; Analytical Chemistry (journal) ; Mathematics ; Artificial intelligence ; Statistics ; Algorithm Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies ; Computational Drug Discovery Methods
Authors: Dylan H. Ross | Harsh Bhotika | Xueyun Zheng | Richard Smith | Kristin Burnum-Johnson | Aivett Bilbao Pena
Source: PROTEOMICS (review, 2024-03-04)
Field: Chemistry — Spectroscopy

Computational tools and algorithms for ion mobility spectrometry‐mass spectrometry Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented. Ion-mobility spectrometry ; Mass spectrometry ; Metabolomics ; Proteomics ; Characterization (materials science) ; Computer science ; Instrumentation (computer programming) ; Identification (biology) ; Lipidomics ; Chemistry ; Nanotechnology ; Biochemical engineering ; Chromatography ; Materials science ; Engineering ; Biology Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies
Authors: Jayani Kalahe | Thiruvilla S. Mahadevan | Xiaonan Lu | John D. Vienna | Brian J. Riley | Jincheng Du
Source: Journal of Nuclear Materials (article, 2024-03-07)
Field: Materials Science — Ceramics and Composites

Insights on the structure and properties of sodium iron phosphate glasses from molecular dynamics simulations Chemistry ; Coordination number ; Redox ; Molecular dynamics ; Crystallography ; Sodium ; Bond length ; Phosphate glass ; Oxygen ; Phosphate ; Inorganic chemistry ; Crystal structure ; Computational chemistry ; Ion ; Organic chemistry Glass properties and applications ; Luminescence Properties of Advanced Materials ; Pigment Synthesis and Properties
Authors: Mashhood Zahid | Tomy Abuzairi
Source: Nanomaterials (article, 2024-07-31)
Field: Materials Science — Materials Chemistry

Sustainable Graphene Production: Flash Joule Heating Utilizing Pencil Graphite Precursors The production of graphene from cost-effective and readily available sources remains a significant challenge in materials science. This study investigates the potential of common pencil leads as precursors for graphene synthesis using the Flash Joule Heating (FJH) process. We examined 6H, 4B, and 14B pencil grades, representing different graphite-to-clay ratios, under varying voltages (0 V, 200 V, and 400 V) to elucidate the relationships among initial composition, applied voltage, and resulting graphene quality. Samples were characterized using Raman spectroscopy, electrical resistance measurements, and microscopic analysis. The results revealed grade-specific responses to applied voltages, with all samples showing decreased electrical resistance post-FJH treatment. Raman spectroscopy indicated significant structural changes, particularly in I<sub>D</sub>/I<sub>G</sub> and I<sub>2D</sub>/I<sub>G</sub> ratios, providing insights into defect density and layer stacking. Notably, the 14B pencil lead exhibited unique behavior at 400 V, with a decrease in the I<sub>D</sub>/I<sub>G</sub> ratio from 0.135 to 0.031 and an increase in crystallite size from 143 nm to 612 nm, suggesting potential in situ annealing effects. In contrast, harder grades (6H and 4B) showed increased defect density at higher voltages. This research contributes to the development of more efficient and environmentally friendly methods for graphene production, potentially opening new avenues for sustainable and scalable synthesis. Graphene ; Joule heating ; Materials science ; Flash (photography) ; Pencil (optics) ; Graphite ; Production (economics) ; Nanotechnology ; Engineering physics ; Optoelectronics ; Composite material ; Mechanical engineering ; Engineering ; Optics ; Physics Graphene research and applications ; Recycling and Waste Management Techniques ; Graphene and Nanomaterials Applications
Authors: Joel Davidsson | Mykyta Onizhuk | Christian Vorwerk | Giulia Galli
Source: Nature Communications (article, 2024-06-06)
Field: Materials Science — Materials Chemistry

Discovery of atomic clock-like spin defects in simple oxides from first principles Virtually noiseless due to the scarcity of spinful nuclei in the lattice, simple oxides hold promise as hosts of solid-state spin qubits. However, no suitable spin defect has yet been found in these systems. Using high-throughput first-principles calculations, we predict spin defects in calcium oxide with electronic properties remarkably similar to those of the NV center in diamond. These defects are charged complexes where a dopant atom - Sb, Bi, or I - occupies the volume vacated by adjacent cation and anion vacancies. The predicted zero phonon line shows that the Bi complex emits in the telecommunication range, and the computed many-body energy levels suggest a viable optical cycle required for qubit initialization. Notably, the high-spin nucleus of each dopant strongly couples to the electron spin, leading to many controllable quantum levels and the emergence of atomic clock-like transitions that are well protected from environmental noise. Specifically, the Hanh-echo coherence time increases beyond seconds at the clock-like transition in the defect with <sup>209</sup>Bi. Our results pave the way to designing quantum states with long coherence times in simple oxides, making them attractive platforms for quantum technologies. Qubit ; Physics ; Coherence (philosophical gambling strategy) ; Spin (aerodynamics) ; Quantum computer ; Condensed matter physics ; Quantum ; Atomic physics ; Chemical physics ; Quantum mechanics Electronic and Structural Properties of Oxides ; Diamond and Carbon-based Materials Research ; High-pressure geophysics and materials
Authors: Fan Zhang | Zhe Wang | Lixuan Liu | Anmin Nie | Yanxing Li | Yongji Gong | Wenguang Zhu | Chenggang Tao
Source: Nature Communications (article, 2024-01-24)
Field: Materials Science — Materials Chemistry

Atomic-scale manipulation of polar domain boundaries in monolayer ferroelectric In2Se3 Domain boundaries have been intensively investigated in bulk ferroelectric materials and two-dimensional materials. Many methods such as electrical, mechanical and optical approaches have been utilized to probe and manipulate domain boundaries. So far most research focuses on the initial and final states of domain boundaries before and after manipulation, while the microscopic understanding of the evolution of domain boundaries remains elusive. In this paper, we report controllable manipulation of the domain boundaries in two-dimensional ferroelectric In<sub>2</sub>Se<sub>3</sub> with atomic precision using scanning tunneling microscopy. We show that the movements of the domain boundaries can be driven by the electric field from a scanning tunneling microscope tip and proceed by the collective shifting of atoms at the domain boundaries. Our density functional theory calculations reveal the energy path and evolution of the domain boundary movement. The results provide deep insight into domain boundaries in two-dimensional ferroelectric materials and will inspire inventive applications of these materials. Domain (mathematical analysis) ; Ferroelectricity ; Scanning tunneling microscope ; Polar ; Materials science ; Boundary (topology) ; Electric field ; Atomic units ; Field (mathematics) ; Domain wall (magnetism) ; Condensed matter physics ; Microscopy ; Nanotechnology ; Chemical physics ; Physics ; Optoelectronics ; Optics ; Dielectric ; Magnetic field Ferroelectric and Piezoelectric Materials ; 2D Materials and Applications ; Electronic and Structural Properties of Oxides
Authors: Chuanming Sun | Guangning Wu | Guixiang Pan | Tingyu Zhang | Jiali Li | Shibo Jiao | Yong‐Chao Liu | Kui Chen | Kai Liu | Dongli Xin | Guoqiang Gao
Source: Sensors (article, 2024-04-22)
Field: Materials Science — Materials Chemistry

Convolutional Neural Network-Based Pattern Recognition of Partial Discharge in High-Speed Electric-Multiple-Unit Cable Termination Partial discharge detection is considered a crucial technique for evaluating insulation performance and identifying defect types in cable terminals of high-speed electric multiple units (EMUs). In this study, terminal samples exhibiting four typical defects were prepared from high-speed EMUs. A cable discharge testing system, utilizing high-frequency current sensing, was developed to collect discharge signals, and datasets corresponding to these defects were established. This study proposes the use of the convolutional neural network (CNN) for the classification of discharge signals associated with specific defects, comparing this method with two existing neural network (NN)-based classification models that employ the back-propagation NN and the radial basis function NN, respectively. The comparative results demonstrate that the CNN-based model excels in accurately identifying signals from various defect types in the cable terminals of high-speed EMUs, surpassing the two existing NN-based classification models. Partial discharge ; Convolutional neural network ; Artificial neural network ; Computer science ; Pattern recognition (psychology) ; Artificial intelligence ; Engineering ; Electronic engineering ; Voltage ; Electrical engineering High voltage insulation and dielectric phenomena ; Elevator Systems and Control ; Electrical Fault Detection and Protection
Authors: Yupeng Cao | Hui Lin | Tong Zong | Xiangbo Xu | Mingdong Li | Xia Bian | Zhiqiang Li
Source: Scientific Reports (article, 2024-12-30)
Field: Materials Science — Materials Chemistry

Strength characteristics and prediction model of solidified municipal sludge reinforced by dredged silt combined with sodium silicate and polyurethane The treatment and resource utilization of municipal sludge and dredged silt have been rendered urgent by the acceleration of urbanization and stricter environmental protection demands. An effective solution was developed to address the challenges of poor mechanical properties and the difficulty in directly using cement-based materials for municipal sludge treatment. The utilization of dredged silt with high water content served as the foundational skeleton material. Appropriate proportion (0.5:1.0) of sodium silicate, which accelerates cement hardening, and polyurethane, which facilitates chemical bond cooperation, was combined to form SP material, partially replacing cement. Unconfined compressive strength (UCS) tests were subsequently conducted on the solidified municipal sludge. These tests aimed to investigate the influence of the dredged silt mixing ratio, initial water content of dredged silt, and the SP mixing ratio on the strength of the solidified municipal sludge. Furthermore, a strength prediction model was established for solidified municipal sludge, taking into consideration the mixing ratios of dredged silt and SP. The research findings indicate that dredged silt can serve as a skeleton structure for solidified municipal sludge. The UCS of the solidified municipal sludge increases with the increase in the dredged silt mixing ratio, and reaches a maximum value at mixing ratio of 1.0. SP materials can partially replace cement, the appropriate proportion of SP and cement can synergistically improve the strength of solidified municipal sludge, and the optimal SP mixing ratio is 50%. Furthermore, the strength prediction model constructed with independent variables such as dredged silt mixing ratio, curing age, water-to-cement ratio, and SP mixing ratio demonstrates better predictability for the strength development of solidified municipal sludge. Silt ; Compressive strength ; Sodium silicate ; Cement ; Materials science ; Mixing (physics) ; Curing (chemistry) ; Environmental science ; Geotechnical engineering ; Composite material ; Waste management ; Geology ; Engineering Magnesium Oxide Properties and Applications ; Concrete and Cement Materials Research ; Innovative concrete reinforcement materials
Authors: Mansoor Asif | Khaled Al-Soufi | Umer Amir Khan | Luai M. Alhems
Source: IEEE Access (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Intensification of Electric Field Stresses in Field Aged 380-kV Composite Insulators Due to Loss of Hydrophobicity Polymer based composite high voltage insulators (HVIs) due to their hydrophobic surfaces have consistently outperformed the traditional ceramic insulators in highly contaminating coastal-desert environments. However, the harsh environment causes polymer surfaces of these HVIs undergo rapid ageing leading to permanent loss of hydrophobicity. In this paper, we have presented three samples of 380 kV composite HVIs with a service life of over ten years near west coast of the Kingdom of Saudi Arabia. Material investigation using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy revealed substantial surface deterioration and change in the composition. Hydrophobicity investigations revealed that surface of the HVIs have become hydrophilic leading to accumulation of continuous films of water. Electrical withstand strength was evaluated using steam fog test showing significant decrease from the rated values. The distribution of electric field around an insulator is a key design criterion for HVIs. The consequences of loss of hydrophobicity on the electric field distribution across insulator surface is explained analytically and through numerical simulations based on Finite Element Method (FEM). The pristine and field aged HVIs are modelled and were covered with realistic water distributions observed during hydrophobicity tests. It has been observed that the intensity of electric field on field aged insulator surpasses the corona inception threshold at certain areas of the insulator, resulting in the initiation of corona discharge on the insulator’s surface. This corona inception further causes surface deterioration and accelerated ageing in composite HVI. Electric field ; Composite number ; Materials science ; Composite material ; Field (mathematics) ; Physics ; Mathematics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Thermal Analysis in Power Transmission
Authors: Jianping Bao | M. Y. Yu | Jiaxin Li | Guanli Wang | Zhihui Tang | Jinhu Zhi
Source: Scientific Reports (article, 2024-09-06)
Field: Chemistry — Analytical Chemistry

Determination of leaf nitrogen content in apple and jujube by near-infrared spectroscopy The nitrogen content of apple leaves and jujube leaves is an important index to judge the growth and development of apple trees and jujube trees to a certain extent. The prediction performance of the two samples was compared between different models for leaf nitrogen content, respectively. The near-infrared absorption spectra of 287 apple leaf samples and 192 jujube leaf samples were collected. After eliminating the outliers by Mahalanobis distance method, the remaining spectral data were processed by six different preprocessing methods. BP neural network (BP), random forest regression (RF), least partial squares (PLS), K-Nearest Neighbor (KNN), and support vector regression (SVR) were compared to establish prediction models of nitrogen content in apple leaves and jujube leaves. The results showed that the determination coefficient (R<sup>2</sup>), root mean square error (RMSE) and residual prediction deviation (RPD) of the models established by different combined pretreatment methods were compared among the five methods. Compared with the performance of the other four models, the modeling method of SG + SD + CARS + RF was suitable for the prediction of nitrogen content in apple leaves, and its modeling set R<sup>2</sup> was 0.85408, RMSE was 0.082188, and RPD was 2.5864. The validation set R<sup>2</sup> is 0.75527, RMSE is 0.099028, RPD is 2.1956. The modeling method of FD + CARS + PLS was suitable for the prediction of nitrogen content in jujube leaves. The modeling set R<sup>2</sup> was 0.7954, RMSE was 0.14558, and RPD was 2.4264; the validation set R<sup>2</sup> is 0.81348, RMSE is 0.089217, and RPD is 2.4552.In the prediction modeling of apple leaf nitrogen content in the characteristic band, the model quality of RF was better than the other four prediction models. The model quality of PLS in predictive modeling of nitrogen content of jujube leaves in characteristic bands is superior to the other four predictive models, These results provide a reference for the use of near-infrared spectroscopy to determine whether apple trees and jujube trees are deficient in nutrients. Nitrogen ; Content (measure theory) ; Near-infrared spectroscopy ; Infrared spectroscopy ; Infrared ; Spectroscopy ; Horticulture ; Botany ; Chemistry ; Biology ; Mathematics ; Physics ; Optics ; Organic chemistry ; Neuroscience Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Phytochemicals and Antioxidant Activities