jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shih‐Hsiu Huang | Pin Chieh Wu
Source: Nanophotonics (article, 2024-01-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Exploring plasmonic gradient metasurfaces for enhanced optical sensing in the visible spectrum While conventional optical sensors hold historical significance, they face inherent limitations in sensitivity, operational intricacies, and bulky size. A breakthrough in this realm comes from the advent of metasurface sensors, which leverage nanoscale optical effects, thereby expanding the horizons of optical sensing applications. However, past methods employed in metasurface sensors predominantly rely on wavelength shifts or intensity changes with high-<i>Q</i> resonances, thereby significantly restricting the detection bandwidth. In response to these challenges, this study introduces a plasmonic gradient metasurface-based sensor (PGMS) designed for refractive index detection across a wide wavelength spectrum. Through the utilization of the Pancharatnam-Berry phase method, the PGMS achieves a distinctive 2<i>π</i> phase shift, facilitating the simultaneous generation of specular and deflected beams. The introduction of a far-field intensity ratio (<i>I</i>* = <i>I</i> <sub>+1</sub>/<i>I</i> <sub>0</sub>) amplifies the change in optical response by maximizing the deflected beam's intensity while minimizing specular reflection. Experimental validation attests to the PGMS's consistent performance across diverse media and wavelengths, successfully overcoming challenges associated with oxidation issues. Furthermore, the incorporation of a normalization factor enhances the PGMS's sensing performance and versatility for broadband optical sensing, accommodating variations in the refractive index. Particularly sensitive in green wavelengths, the PGMS demonstrates its potential in visible spectrum applications, such as biomedical diagnostics and environmental monitoring. This research not only addresses challenges posed by conventional sensors but also propels optical sensing technologies into a realm of heightened sensitivity and adaptability. Plasmon ; Optics ; Refractive index ; Optoelectronics ; Wavelength ; Specular reflection ; Materials science ; Computer science ; Broadband ; Physics Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Optical Wireless Communication Technologies
Authors: Xiaoxin Chen | Hailan Qin | Hongtian Li | Yuxiao Du | Shenghao Wang | Peifeng Li | Yongming Hu | Laijun Liu | Jianwei Zhao | Dawei Wang
Source: Journal of the American Ceramic Society (article, 2024-01-30)
Field: Materials Science — Materials Chemistry

Significant impact of TiO <sub>2</sub> purity on the phase structure and electrical properties of BiFeO <sub>3</sub> –BaTiO <sub>3</sub> lead‐free piezoelectric ceramics Abstract In many studies, the properties of BiFeO 3 –BaTiO 3 (BF–BT) ceramics vary greatly using different raw reagents, which makes it challenging to obtain reliable and repeatable properties of BF–BT‐based devices. In this work, 0.7BiFeO 3 –0.3BaTiO 3 (0.7BF–0.3BT) ceramics were fabricated by a conventional solid‐phase synthesis using TiO 2 reagents with varied purities of 98%, 99%, 99.9%, and 99.99%, respectively. The phase structure, microstructure, ferroelectric, and piezoelectric properties were comprehensively studied. All compositions of the ceramics exhibit a pseudo‐cubic phase perovskite structure, and the fraction of the rhombohedral phase increases with increasing the TiO 2 purity. Additionally, backscattered electron images and energy‐dispersive spectroscopy revealed an obvious core–shell structure within grains. In particular, the 0.7BF–0.3BT ceramics prepared with 98% purity TiO 2 exhibited superior ferroelectric and piezoelectric properties, d 33 ∼ 220 pC/N and ∼ 230 pm/V. The ceramics prepared with higher purity TiO 2 suffered from severe leakage conduction, which can be well addressed by adding excess TiO 2 . Our work reveals the importance of different grades of purity TiO 2 on the electrical properties of BF–BT ceramics. Piezoelectricity ; Materials science ; Ceramic ; Lead (geology) ; Phase (matter) ; Ferroelectricity ; Mineralogy ; Composite material ; Dielectric ; Optoelectronics ; Chemistry ; Geology Ferroelectric and Piezoelectric Materials ; Multiferroics and related materials ; Dielectric properties of ceramics
Authors: Yeye Chen | Jia‐Hong Tian | Han‐Wen Tian | Rong Ma | Ze-Han Wang | Yu‐Chen Pan | Xin‐Yue Hu | Dong‐Sheng Guo
Source: Sensors (article, 2024-06-08)
Field: Materials Science — Materials Chemistry

Calixarene-Based Supramolecular Sensor Array for Pesticide Discrimination The identification and detection of pesticides is crucial to protecting both the environment and human health. However, it can be challenging to conveniently and rapidly differentiate between different types of pesticides. We developed a supramolecular fluorescent sensor array, in which calixarenes with broad-spectrum encapsulation capacity served as recognition receptors. The sensor array exhibits distinct fluorescence change patterns for seven tested pesticides, encompassing herbicides, insecticides, and fungicides. With a reaction time of just three minutes, the sensor array proves to be a rapid and efficient tool for the discrimination of pesticides. Furthermore, this supramolecular sensing approach can be easily extended to enable real-time and on-site visual detection of varying concentrations of imazalil using a smartphone with a color scanning application. This work not only provides a simple and effective method for pesticide identification and quantification, but also offers a versatile and advantageous platform for the recognition of other analytes in relevant fields. Pesticide ; Supramolecular chemistry ; Analyte ; Pesticide residue ; Identification (biology) ; Sensor array ; Nanotechnology ; Computer science ; Chemistry ; Materials science ; Chromatography ; Organic chemistry ; Biology ; Molecule ; Machine learning Luminescence and Fluorescent Materials ; Advanced biosensing and bioanalysis techniques ; Molecular Sensors and Ion Detection
Authors: Nimesha Rathnayake | Savankumar Patel | Ibrahim Gbolahan Hakeem | Ganesh Veluswamy | Ibrahim Al-Waili | Shivani Agnihotri | Arun Krishna Vuppaladadiyam | Aravind Surapaneni | David Bergmann | Kalpit Shah
Source: Water (article, 2024-11-26)
Field: Materials Science — Materials Chemistry

The Pyrolysis of Biosolids in a Novel Closed Coupled Pyrolysis and Gasification Technology: Pilot Plant Trials, Aspen Plus Modelling, and a Techno-Economic Analysis Pyrolysis is gaining recognition as a sustainable solution for biosolid management, though scaling it commercially presents challenges. To address this, RMIT developed a novel integrated pyrolysis and gasification technology called PYROCO™, which was successfully tested in pilot-scale trials. This study introduces PYROCO™ and its application to produce biochar, highlighting the biochar properties of the results of the initial trials. In addition, an energy analysis using semi-empirical Aspen Plus modelling, paired with a preliminary techno-economic assessment, was carried out to evaluate the feasibility of this technology. The results show that the PYROCO™ pilot plant produced biochar with a ~30 wt% yield, featuring beneficial agronomic properties such as high organic carbon (210–220 g/kg) and nutrient contents (total P: 36–42 g/kg and total N: 16–18 g/kg). The system also effectively removed contaminants such as PFASs, PAHs, pharmaceuticals, and microplastics from the biochar and scrubber water and stack gas emissions. An energy analysis and Aspen Plus modelling showed that a commercial-scale PYROCO™ plant could operate energy self-sufficiently with biosolids containing &gt;30% solids and with a minimum calorific value of 11 MJ/kg. The process generates excess energy for drying biosolids and for electricity generation. Profitability is sensitive to biochar price; prices rise from AUD 300 to AUD 1000 per tonne, the NPV improves from AUD 0.24 million to AUD 4.31 million, and the payback period shortens from 26 to 12 years. The low NPV and high payback period reflect the use of a relatively high discount rate of 8%, chosen to be on the conservative side given the novel nature of the technology. Biosolids ; Pyrolysis ; Waste management ; Environmental science ; Pilot plant ; Economic analysis ; Bioenergy ; Engineering ; Biofuel ; Agricultural economics ; Economics Graphite, nuclear technology, radiation studies ; Thermochemical Biomass Conversion Processes ; Recycling and Waste Management Techniques
Authors: Marvin Krüger | Thomas Zemanek | Dominik Wuttke | Maximilian Dinkel | Albrecht Serfling | Elias Böckmann
Source: Plant Methods (article, 2024-10-03)
Field: Chemistry — Analytical Chemistry

Hyperspectral imaging for pest symptom detection in bell pepper Hyperspectral images can be used to distinguish sucking pests on bell peppers on the basis of single leaves and intact potted bell pepper plants under controlled conditions. Wavelength reduction methods offer options for multispectral camera usage in high-grown vegetable greenhouses. The application of automated platforms similar to the one tested in this study could be possible, but for successful pest detection under greenhouse conditions, algorithms should be further developed fully considering real-world conditions. Hyperspectral imaging ; Context (archaeology) ; Greenhouse ; PEST analysis ; Integrated pest management ; Myzus persicae ; VNIR ; Identification (biology) ; Automation ; Agricultural engineering ; Computer science ; Remote sensing ; Artificial intelligence ; Environmental science ; Biology ; Agronomy ; Horticulture ; Ecology ; Engineering ; Geography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Date Palm Research Studies
Authors: Pablo Aparicio-Ruiz | Elena Barbadilla-Martín | José Guadix Martín | Jesús Muñuzuri
Source: Building Simulation (article, 2024-03-16)
Field: Materials Science — Polymers and Plastics

Predicting the clothing insulation through machine learning algorithms: A comparative analysis and a practical approach Abstract Since indoor clothing insulation is a key element in thermal comfort models, the aim of the present study is proposing an approach for predicting it, which could assist the occupants of a building in terms of recommendations regarding their ensemble. For that, a systematic analysis of input variables is exposed, and 13 regression and 12 classification machine learning algorithms were developed and compared. The results are based on data from 3352 questionnaires and 21 input variables from a field study in mixed-mode office buildings in Spain. Outdoor temperature at 6 a.m., indoor air temperature, indoor relative humidity, comfort temperature and gender were the most relevant features for predicting clothing insulation. When comparing machine learning algorithms, decision tree-based algorithms with Boosting techniques achieved the best performance. The proposed model provides an efficient method for forecasting the clothing insulation level and its application would entail optimising thermal comfort and energy efficiency. Clothing ; Computer science ; Machine learning ; Algorithm ; Engineering ; Artificial intelligence ; Mechanical engineering ; History Textile materials and evaluations ; Sleep and Work-Related Fatigue
Authors: Steffen Seitz | Thomas Götz | Christopher Lindenberg | Ronald Tetzlaff | Stephan Schlegel
Source: IEEE Transactions on Power Delivery (article, 2024-02-26)
Field: Materials Science — Materials Chemistry

Towards Generalizable Classification of Partial Discharges in Gas-Insulated HVDC Systems Using Neural Networks: Protrusions and Particles Undetected partial discharges (PDs) are a safety critical issue in high voltage (HV) gas-insulated systems (GIS). While the diagnosis of PDs under AC voltage is well-established, the analysis of PDs under DC voltage remains an active research field. A key focus of these investigations is the classification of different PD sources to enable subsequent sophisticated analysis. In this paper, we present an analysis of a 1D-CNN-based approach for classifying laboratory PD signals caused by metallic protrusions and conductive particles on the insulator of HVDC GIS, under both negative and positive potentials. Most notably, our study demonstrates that this type of neural network, regardless of the training order, can generalize learnings to operating voltage multiples that it has not previously encountered. We evaluate this generalization performance under the presence of additional white Gaussian noise and investigate the influence of excluding the amplitude-related information in the signal. Further, we compare the network's performance when using input signals in both the time and frequency domain. Artificial neural network ; Partial discharge ; Engineering ; Electrical engineering ; Computer science ; Materials science ; Voltage ; Artificial intelligence High voltage insulation and dielectric phenomena ; Aerosol Filtration and Electrostatic Precipitation ; Power Transformer Diagnostics and Insulation
Authors: Ramy N. R. Ghaly | Ali Al Ibrahim | Sherif S. M. Ghoneim | Ahmed Abu‐Siada | Mohit Bajaj | Євген Зайцев | Hilmy Awad
Source: Scientific Reports (article, 2024-09-27)
Field: Materials Science — Materials Chemistry

Impact of atmospheric conditions on the flash-over voltage of the transmission line insulators using central composite design The insulators of overhead power lines play a crucial role in maintaining the reliability of transmission and distribution networks. Because they are exposed to harsh and dynamic environmental conditions, it is essential to investigate the impact of environmental parameters such as pollution, inclined angle with the cross arm, and temperature on the dielectric performance of the insulators of overhead lines. Conventionally, the effect of such parameters can be investigated through experimental measurements of the insulator flashover voltage. However, this approach is costly and time-consuming and calls for the isolation of the lines to conduct the test, causing interruption to the entire grid. As such, there is an essential need to develop a new methodology to quantify the flashover voltage of overhead insulators operating under various environmental conditions, which is the main aim of this paper. The Central Composite Design is employed to develop a mathematical correlation between the insulator flash over voltage as a dependent variable and three environmental parameters: pollution level, inclined angle, and temperature as independent variables. The robustness of the developed equation is validated through extensive experimental measurements of the insulator's flash overvoltage under various conditions. Results reveal a good agreement between the actual and predicted flashover voltage using the developed correlation, as the absolute error for all investigated samples is less than 6%. Composite number ; Transmission line ; Central composite design ; Transmission (telecommunications) ; Voltage ; Line (geometry) ; Flash (photography) ; Materials science ; Computer science ; Environmental science ; Electrical engineering ; Composite material ; Telecommunications ; Engineering ; Physics ; Mathematics ; Optics ; Response surface methodology High voltage insulation and dielectric phenomena ; Thermal Analysis in Power Transmission ; Aerosol Filtration and Electrostatic Precipitation
Authors: Phanankosi Moyo | Michael Ofori | Olusola Bodede | Madelien Wooding | Ndivhuwo Kevin Khorommbi | Lyndy J. McGaw | Cynthia Amaning Danquah | Vinesh Maharaj
Source: Scientific Reports (article, 2024-06-25)
Field: Chemistry — Organic Chemistry

Investigation of the antimycobacterial activity of African medicinal plants combined with chemometric analysis to identify potential leads The emergence of drug-resistant Mycobacterium tuberculosis strains is a threat to global health necessitating the discovery of novel chemotherapeutic agents. Natural products drug discovery, which previously led to the discovery of rifamycins, is a valuable approach in this endeavor. Against this backdrop, we set out to investigate the in vitro antimycobacterial properties of medicinal plants from Ghana and South Africa, evaluating 36 extracts and their 252 corresponding solid phase extraction (SPE) generated fractions primarily against the non-pathogenic Mycobacterium smegmatis and Mycobacterium aurum species. The most potent fraction was further evaluated in vitro against infectious M. tuberculosis strain. Crinum asiaticum (bulb) (Amaryllidaceae) emerged as the most potent plant species with specific fractions showing exceptional, near equipotent activity against the non-pathogenic Mycobacterium species (0.39 µg/ml ≤ MIC ≤ 25 µg/ml) with one fraction being moderately active (MIC = 32.6 µg/ml) against M. tuberculosis. Metabolomic analysis led to the identification of eight compounds predicted to be active against M. smegmatis and M. aurum. In conclusion, from our comprehensive study, we generated data which provided an insight into the antimycobacterial properties of Ghanaian and South African plants. Future work will be focused on the isolation and evaluation of the compounds predicted to be active. Antimycobacterial ; Mycobacterium tuberculosis ; Mycobacterium smegmatis ; Mycobacterium kansasii ; Biology ; Tuberculosis ; Traditional medicine ; Mycobacterium ; Microbiology ; Medicine ; Bacteria Chemical synthesis and alkaloids ; Alkaloids: synthesis and pharmacology ; Microbial Natural Products and Biosynthesis
Authors: Zhipeng Ding | Wei Su | Lipengan Ye | Yuanhang Zhou | Wenlong Li | Riaz Ali | Bin Tang | Hongbing Yao
Source: Chinese Optics Letters (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Customizable multifunctional metasurface absorber based on bidirectional deep neural networks covering the quasi-entire terahertz band In this work, we propose a novel approach that combines a bidirectional deep neural network (BDNN) with a multifunctional metasurface absorber (MMA) for inverse design, which can effectively address the challenge of on-demand customization for absorbers.The inverse design of absorption peak frequencies can be achieved from 0.5 to 10 terahertz (THz), covering the quasi-entire THz band.Based on this, the BDNN is extended to broadband absorption, and the inverse design yields an MMA at the desired frequency.This work provides a broadly applicable approach to the custom design of multifunctional devices that can facilitate the evaluation and design of metasurfaces in electromagnetic absorption. Terahertz radiation ; Optics ; Artificial neural network ; Computer science ; Metamaterial ; Materials science ; Optoelectronics ; Physics ; Artificial intelligence Metamaterials and Metasurfaces Applications ; Acoustic Wave Phenomena Research ; Thermal Radiation and Cooling Technologies
Authors: Atieh Rezaei Namjoo | Ayla Hassani | Hassan Amini | Fateme Nazaryabrbekoh | Sepideh Saghati | Mohammad Ali Ebrahimi Saadatlou | Ali Baradar Khoshfetrat | Nafiseh Didar Khosrowshahi | Reza Rahbarghazi‬
Source: BMC Biotechnology (article, 2024-04-26)
Field: Materials Science — Biomaterials

Multiprotein collagen/keratin hydrogel promoted myogenesis and angiogenesis of injured skeletal muscles in a mouse model Volumetric loss is one of the challenging issues in muscle tissue structure that causes functio laesa. Tissue engineering of muscle tissue using suitable hydrogels is an alternative to restoring the physiological properties of the injured area. Here, myogenic properties of type I collagen (0.5%) and keratin (0.5%) were investigated in a mouse model of biceps femoris injury. Using FTIR, gelation time, and rheological analysis, the physicochemical properties of the collagen (Col)/Keratin scaffold were analyzed. Mouse C2C12 myoblast-laden Col/Keratin hydrogels were injected into the injury site and histological examination plus western blotting were performed to measure myogenic potential after 15 days. FTIR indicated an appropriate interaction between keratin and collagen. The blend of Col/Keratin delayed gelation time when compared to the collagen alone group. Rheological analysis revealed decreased stiffening in blended Col/Keratin hydrogel which is favorable for the extrudability of the hydrogel. Transplantation of C2C12 myoblast-laden Col/Keratin hydrogel to injured muscle tissues led to the formation of newly generated myofibers compared to cell-free hydrogel and collagen groups (p < 0.05). In the C2C12 myoblast-laden Col/Keratin group, a low number of CD31<sup>+</sup> cells with minimum inflammatory cells was evident. Western blotting indicated the promotion of MyoD in mice that received cell-laden Col/Keratin hydrogel compared to the other groups (p < 0.05). Despite the increase of the myosin cell-laden Col/Keratin hydrogel group, no significant differences were obtained related to other groups (p > 0.05). The blend of Col/Keratin loaded with myoblasts provides a suitable myogenic platform for the alleviation of injured muscle tissue. Myogenesis ; Biology ; Keratin ; Angiogenesis ; Cell biology ; Anatomy ; Myocyte ; Cancer research ; Genetics Silk-based biomaterials and applications ; Wound Healing and Treatments ; Electrospun Nanofibers in Biomedical Applications
Authors: Weiyan Zhou | Conor L. O’Neill | Tianben Ding | Oumeng Zhang | Jai S. Rudra | Matthew D. Lew
Source: ACS Nano (article, 2024-03-13)
Field: Materials Science — Biomaterials

Resolving the Nanoscale Structure of β-Sheet Peptide Self-Assemblies Using Single-Molecule Orientation–Localization Microscopy Synthetic peptides that self-assemble into cross-β fibrils are versatile building blocks for engineered biomaterials due to their modularity and biocompatibility, but their structural and morphological similarities to amyloid species have been a long-standing concern for their translation. Further, their polymorphs are difficult to characterize by using spectroscopic and imaging techniques that rely on ensemble averaging to achieve high resolution. Here, we utilize Nile red (NR), an amyloidophilic fluorogenic probe, and single-molecule orientation-localization microscopy (SMOLM) to characterize fibrils formed by the designed amphipathic enantiomers KFE8<sup>L</sup> and KFE8<sup>D</sup> and the pathological amyloid-beta peptide Aβ42. Importantly, NR SMOLM reveals the helical (bilayer) ribbon structure of both KFE8 and Aβ42 and quantifies the precise tilt of the fibrils' inner and outer backbones in relevant buffer conditions without the need for covalent labeling or sequence mutations. SMOLM also distinguishes polymorphic branched and curved morphologies of KFE8, whose backbones exhibit much more heterogeneity than those of typical straight fibrils. Thus, SMOLM is a powerful tool to interrogate the structural differences and polymorphism between engineered and pathological cross-β-rich fibrils. Fibril ; Biophysics ; Peptide ; Materials science ; Fiber diffraction ; Crystallography ; Nanotechnology ; Chemistry ; Biochemistry ; Biology ; X-ray crystallography ; Diffraction Supramolecular Self-Assembly in Materials ; Alzheimer's disease research and treatments ; Connective tissue disorders research