jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yuanyuan Shao | Shengheng Ji | Guantao Xuan | Yanyun Ren | Wenjie Feng | Huijie Jia | Qiuyun Wang | Shuguo He
Source: Agronomy (article, 2024-01-21)
Field: Chemistry — Analytical Chemistry

Detection and Analysis of Chili Pepper Root Rot by Hyperspectral Imaging Technology The objective is to develop a portable device capable of promptly identifying root rot in the field. This study employs hyperspectral imaging technology to detect root rot by analyzing spectral variations in chili pepper leaves during times of health, incubation, and disease under the stress of root rot. Two types of chili pepper seeds (Manshanhong and Shanjiao No. 4) were cultured until they had grown two to three pairs of true leaves. Subsequently, robust young plants were infected with Fusarium root rot fungi by the root-irrigation technique. The effective wavelength for discriminating between distinct stages was determined using the successive projections algorithm (SPA) after capturing hyperspectral images. The optimal index related to root rot between each normalized difference spectral index (NDSI) was obtained using the Pearson correlation coefficient. The early detection of root rot illness can be modeled using spectral information at effective wavelengths and in NDSI, together with the application of partial least squares discriminant analysis (PLS-DA), least squares support vector machine (LSSVM), and back-propagation (BP) neural network technology. The SPA-BP model demonstrates outstanding predictive capabilities compared with other models, with a classification accuracy of 92.3% for the prediction set. However, employing SPA to acquire an excessive number of efficient wave-lengths is not advantageous for immediate detection in practical field scenarios. In contrast, the NDSI (R445, R433)-BP model uses only two wavelengths of spectral information, but the prediction accuracy can reach 89.7%, which is more suitable for rapid detection of root rot. This thesis can provide theoretical support for the early detection of chili root rot and technical support for the design of a portable root rot detector. Hyperspectral imaging ; Root rot ; Mathematics ; Pepper ; Linear discriminant analysis ; Partial least squares regression ; Root (linguistics) ; Horticulture ; Artificial intelligence ; Pattern recognition (psychology) ; Computer science ; Statistics ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Remote Sensing in Agriculture
Authors: Fabian Denner
Source: Physics of Fluids (preprint, 2024-05-01)
Field: Materials Science — Materials Chemistry

The Kirkwood–Bethe hypothesis for bubble dynamics, cavitation, and underwater explosions Pressure-driven bubble dynamics is a major topic of current research in fluid dynamics, driven by innovative medical therapies, sonochemistry, material treatments, and geophysical exploration. First proposed in 1942, the Kirkwood–Bethe hypothesis provides a simple means to close the equations that govern pressure-driven bubble dynamics as well as the resulting flow field and acoustic emissions in spherical symmetry. The models derived from the Kirkwood–Bethe hypothesis can be solved using standard numerical integration methods at a fraction of the computational cost required for fully resolved simulations. Here, the theoretical foundation of the Kirkwood–Bethe hypothesis and contemporary models derived from it are gathered and reviewed, as well as generalized to account for spherically symmetric, cylindrically symmetric, and planar one-dimensional domains. In addition, the underpinning assumptions are clarified and new results that scrutinize the predictive capabilities of the Kirkwood–Bethe hypothesis with respect to the complex acoustic impedance experienced by curved acoustic waves and the formation of shock waves are presented. Although the Kirkwood–Bethe hypothesis is built upon simplifying assumptions and lacks some basic acoustic properties, models derived from it are able to provide accurate predictions under the specific conditions associated with pressure-driven bubble dynamics, cavitation, and underwater explosions. Bubble ; Cavitation ; Underwater explosion ; Physics ; Shock wave ; Underwater ; Shock (circulatory) ; Statistical physics ; Mechanics ; Planar ; Flow (mathematics) ; Classical mechanics ; Computer science ; Geology Ultrasound and Cavitation Phenomena ; Planetary Science and Exploration
Authors: Mengjie Ma | Yueyue Liu | Shuaizhong Zhang | Yongkai Yuan
Source: Foods (review, 2024-12-06)
Field: Materials Science — Biomaterials

Edible Coating for Fresh-Cut Fruit and Vegetable Preservation: Biomaterials, Functional Ingredients, and Joint Non-Thermal Technology This paper reviews recent advances in fresh-cut fruit and vegetable preservation from the perspective of biomacromolecule-based edible coating. Biomaterials include proteins, polysaccharides, and their complexes. Compared to a single material, the better preservation effect was presented by complexes. The functional ingredients applied in the edible coating are essential oils/other plant extracts, metals/metal oxides, and organic acids, the purposes of the addition of which are the improvement of antioxidant and antimicrobial activities and/or the mechanical properties of the coating. The application of edible coating with other preservation technologies is an emerging method, mainly including pulsed light, short-wave ultraviolet, modified atmosphere packaging, ozonation, and γ-irradiation. In the future, it is crucial to design coating formulations based on preservation goals and sensory characteristics. The combination of non-thermal preservation technology and edible coating needs to be strengthened in research on food preservation. The application of AI tools for edible coating-based preservation should also be focused on. In conclusion, edible coating-based preservation is promising for the development of fresh-cut fruits and vegetables. Coating ; Food science ; Materials science ; Modified atmosphere ; Shelf life ; Chemistry ; Nanotechnology Nanocomposite Films for Food Packaging ; Postharvest Quality and Shelf Life Management ; Essential Oils and Antimicrobial Activity
Authors: Massimo Pica Ciamarra | Wencheng Ji | Matthieu Wyart
Source: Proceedings of the National Academy of Sciences (article, 2024-05-24)
Field: Materials Science — Materials Chemistry

Local vs. cooperative: Unraveling glass transition mechanisms with SEER Which phenomenon slows down the dynamics in supercooled liquids and turns them into glasses is a long-standing question of condensed matter. Most popular theories posit that as the temperature decreases, many events must occur in a coordinated fashion on a growing length scale for relaxation to occur. Instead, other approaches consider that local barriers associated with the elementary rearrangement of a few particles or "excitations" govern the dynamics. To resolve this conundrum, our central result is to introduce an algorithm, Systematic Excitation ExtRaction, which can systematically extract hundreds of excitations and their energy from any given configuration. We also provide a measurement of the activation energy, characterizing the liquid dynamics, based on fast quenching and reheating. We use these two methods in a popular liquid model of polydisperse particles. Such polydisperse models are known to capture the hallmarks of the glass transition and can be equilibrated efficiently up to millisecond time scales. The analysis reveals that cooperative effects do not control the fragility of such liquids: the change of energy of local barriers determines the change of activation energy. More generally, these methods can now be used to measure the degree of cooperativity of any liquid model. Fragility ; Supercooling ; Relaxation (psychology) ; Glass transition ; Statistical physics ; Quenching (fluorescence) ; Chemical physics ; Cooperativity ; Excitation ; Energy landscape ; Scale (ratio) ; Physics ; Energy (signal processing) ; Chemistry ; Thermodynamics ; Fluorescence ; Polymer ; Quantum mechanics ; Nuclear magnetic resonance Material Dynamics and Properties ; Theoretical and Computational Physics ; Spectroscopy and Quantum Chemical Studies
Authors: Kieran B. Spooner | Maud Einhorn | Daniel W. Davies | David O. Scanlon
Source: The Journal of Open Source Software (article, 2024-05-25)
Field: Materials Science — Materials Chemistry

ThermoParser: Streamlined Analysis of ThermoelectricProperties Thermoelectric materials, which convert heat into electricity, could be an important renewable energy source to help slow the encroaching climate crisis, not only by displacing fossil fuels, but by recycling waste heat, which makes up around 50 % of generated energy. With the growing computational capacity and development of several codes to calculate the key properties of thermoelectrics, they have become an increasingly popular area of computational materials research in recent years. Thermal transport packages include Phonopy, Phono3py, ShengBTE/ almaBTE, ALAMODE, TDEP and HiPhive; and electronic transport packages include BoltzTraP, BoltzTraP2, EPW, EPA, EPIC STAR, AMSET, Perturbo, TOSSPB and ElecTra. While separate packages are required for such different calculations, this makes data analysis complex, needing to load in different file formats, account for different data arrangements (e.g. array shapes), and convert to consistent units, even before one begins analysing anything. ThermoParser deals with these time-consuming and error-prone problems by loading data from multiple codes into a consistent data format with informative metadata, and facilitates the post-processing of thermoelectric properties by using this to accurately calculate and visualise them through an easy-to-use command-line interface (CLI) and a fully customisable Python package. Some of its utility can be seen by its use in the literature (sometimes under its former name, ThermoPlotter). Thermoelectric effect ; Materials science ; Engineering physics ; Physics ; Thermodynamics Machine Learning in Materials Science ; Advanced Thermoelectric Materials and Devices ; Thermal properties of materials
Authors: Do Duc Trung
Source: EPJ Applied Metamaterials (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Using RAM method for optimal selection of flame retardant nanocomposite material fabrication solution This study aimed to optimize the selection of manufacturing solutions for flame retardant nanocomposite materials based on polyvinyl chloride (PVC). A total of eight different options were considered. The first option utilized PVC as the base material, and the subsequent options were carried out by adding specific amounts of reinforcing agents, including aluminum hydroxide (ATH) and zinc borate (ZB). The seven following options were denoted by their respective symbols: 5ATH/PVC, 10ATH/PVC, 15ATH/PVC, 5ZB/PVC, 10ZB/PVC, 15ZB/PVC, and 5ATH/5ZB/PVC. The number preceding the symbol of the reinforcing agent represents the percentage of the reinforcing agent added to the PVC material. For example, 5ATH/PVC signifies the addition of 5% of ATH reinforcing agent to the PVC material. To evaluate each option, five different indices were employed. The weight for each index was determined using four different methods, including the Equal method, Entropy method, MEREC method, and LOPCOW method. The RAM method was used to select the best option. The combination of the RAM method and the four weight determination methods generated four different datasets of option rankings. In all four of these datasets, the best and worst options consistently matched. The results indicated that the 15ATH/PVC option was deemed the best, while the pure PVC option was the worst. Fire retardant ; Fabrication ; Nanocomposite ; Materials science ; Selection (genetic algorithm) ; Material selection ; Composite material ; Computer science Flame retardant materials and properties ; Additive Manufacturing and 3D Printing Technologies ; Material Properties and Applications
Authors: Alina Ruxandra Caramitu | Magdalena Valentina Lungu | Romeo Cristian Ciobanu | Ioana Ion | Mihai Marin | Virgil Marinescu | Jana Pintea | Sebastian Aradoaei | Oliver Daniel Schreiner
Source: Polymers (article, 2024-04-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Recycled Polypropylene/Strontium Ferrite Polymer Composite Materials with Electromagnetic Shielding Properties This paper presents the obtaining and characterization of recycled polypropylene/strontium ferrite (PP/SrFe<sub>12</sub>O<sub>19</sub>) polymer composite materials with applications in the electromagnetic shielding of vehicle interiors (mainly automotive electronics-carcasses) from the electromagnetic radiation emitted mainly by exterior sources-electrical lines and supply sources-in terms of the development of the new electrical vehicles. With this aim, suitable polymer composite materials were developed using SrFe<sub>12</sub>O<sub>19</sub> filler in two forms (powder and concentrate). The recycled PP polymer and composite materials with a PP/SrFe<sub>12</sub>O<sub>19</sub> weight ratio of 75/25 and 70/30 were obtained in two stages, i.e., pellets by extrusion and samples for testing through a melt injection process. The characterization of the obtained materials took into account the requirements imposed by the desired applications. It consisted of determining the mechanical and dielectric properties, and microstructure analyses, along with the determination of the resistance to the action of a temperature of 70 °C, which is higher than the temperatures created during the summer inside vehicles. The performance of these materials as electromagnetic shields was assessed through functional tests consisting of the determination of magnetic permeability and the estimation of the electromagnetic shielding efficiency (SE). The obtained results confirmed the improvement of the mechanical, dielectric, and magnetic properties of the PP/SrFe<sub>12</sub>O<sub>19</sub> composites compared to the selected PP polymers. It is also found that all the composite materials exhibited reflective shielding properties (SE<sub>R</sub> from -71.5 dB to -56.7 dB), with very little absorption shielding. The most performant material was the composite made of PP/SrFe<sub>12</sub>O<sub>19</sub> powder with a weight ratio of 70/30. The promising results recommend this composite material for potential use in automotive shielding applications against electromagnetic pollution. Materials science ; Composite material ; Ferrite (magnet) ; Electromagnetic shielding ; Polypropylene ; Composite number ; Microstructure ; Dielectric ; Polymer ; Extrusion ; Optoelectronics Electromagnetic wave absorption materials ; Radiation Shielding Materials Analysis ; Advanced Energy Technologies and Civil Engineering Innovations
Authors: Yutian Gu | Qin Zhang | Honglin Huang | Kwun Hei Willis Ho | Yufan Zhang | Changqing Yi | Yifan Zheng | Raymond Chuen‐Chung Chang | E Wang | Mo Yang
Source: Theranostics (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Tau‑targeting multifunctional nanocomposite based on tannic acid-metal for near-infrared fluorescence/magnetic resonance bimodal imaging-guided combinational therapy in Alzheimer's disease <b>Rationale:</b> Alzheimer's disease (AD) is hallmarked by amyloid-β (Aβ) plaques and hyperphosphorylated tau (p-tau) neurofibrillary tangles. While Aβ-centric therapies have shown promise, the complex pathology of AD requires a multifaceted therapeutic approach. The weak association between Aβ levels and cognitive decline highlights the need for alternative theranostic strategies. Currently, oxidative stress and tau hyperphosphorylation are now recognized as critical pathological events in AD. Thus, therapies that concurrently attenuate oxidative stress damage and inhibit tau pathology hold great potential for AD treatment. <b>Methods:</b> Herein, a multifunctional neuron-targeted nanocomposite is devised to realize dual imaging-guided AD therapy, integrating the inhibition of tau pathology and reactive oxygen species (ROS)-neutralizing biofunctions. The construction of the nanocomposite incorporates polyphenolic antioxidants tannic acid (TA)-based nanoparticles carrying manganese ions (Mn<sup>2+</sup>) and fluorescent dye IR780 iodide (IR780), coupled with a neuron-specific TPL peptide. The resulting IR780-Mn@TA-TPL nanoparticles (NPs) are comprehensively evaluated in both <i>in vitro</i> and <i>in vivo</i> AD models to assess their imaging capabilities and therapeutic efficacy. <b>Results:</b> The nanocomposite facilitates Mn-enhanced magnetic resonance (MR) imaging and near-infrared (NIR) fluorescence imaging. It effectively neutralizes toxic ROS and reduces tau hyperphosphorylation and aggregation. In AD rat models, the nanocomposite restores neuronal density in the hippocampus and significantly improves spatial memory. <b>Conclusions:</b> Such a neuron‑targeting multifunctional nanocomposite represents a potential theranostic strategy for AD, signifying a shift towards bimodal imaging-guided treatment approaches. Tannic acid ; Magnetic resonance imaging ; Fluorescence ; Fluorescence-lifetime imaging microscopy ; Nuclear magnetic resonance ; Chemistry ; Medicine ; Pathology ; Biophysics ; Biology ; Radiology ; Organic chemistry ; Optics Advanced Nanomaterials in Catalysis ; Cholinesterase and Neurodegenerative Diseases ; Nanoplatforms for cancer theranostics
Authors: Ahmed Yar Akhtar | Hing‐Ho Tsang
Source: Chemical Engineering Journal (article, 2024-06-21)
Field: Materials Science — Polymers and Plastics

Dynamic leaching assessment of recycled polyurethane-coated tire rubber for sustainable engineering applications Assessing the material ramifications of waste tire rubber stands as a pivotal endeavor for its practical utility. Dynamic leaching analysis emerges as indispensable in delineating its potentialities within sustainable engineering domains. Waste materials stemming from tire recycling industries, notably polyurethane-coated rubber (PUcR), may exhibit promising viability owing to attenuated leaching, thus fostering the circular economy paradigm. Towards this end, up-flow column percolation leaching tests were conducted on recycled rubber-soil mixture (RSM) alongside PU-coated rubber-soil mixture (PUcRSM). Analysis through Inductively Coupled Plasma-Atomic Emission Spectroscopy (ICP-AES) unveiled the leaching dynamics of assorted metals in RSM and PUcRSM, notably showcasing markedly diminished cumulative zinc content (by 99.4 %) in PUcRSM, coupled with mitigated electrical conductivity, redox potential, and eluate pH. Leveraging HYDRUS-1D for analytical modeling predicated on the advection–dispersion equation further underscored these insights. These findings suggest that waste PUcR presents itself as a viable option, distinguished by its diminished leachability, suitable for a wide array of applications. These applications include vibration damping in infrastructure, tunnel linings, asphalt roads, rubberized concrete, and lightweight backfill materials for bridges and retaining walls, among others. This initiative will contribute to recycling a substantial quantity of over 1 billion used tires produced annually, ultimately supporting the circular economy ethos through assured and adaptable repurposing of waste from tire rubber recycling industries. Leaching (pedology) ; Polyurethane ; Natural rubber ; Waste management ; Materials science ; Environmental science ; Composite material ; Engineering Polymer Science and PVC ; Microplastics and Plastic Pollution ; Polymer Nanocomposites and Properties
Authors: Weinan Li | Yang Guo | Weiguang Yang | Longyu Huang | Jianhua Zhang | Jun Peng | Yubin Lan
Source: Remote Sensing (article, 2024-12-11)
Field: Chemistry — Analytical Chemistry

Severity Assessment of Cotton Canopy Verticillium Wilt by Machine Learning Based on Feature Selection and Optimization Algorithm Using UAV Hyperspectral Data Verticillium wilt (VW) represents the most formidable challenge in cotton cultivation, critically impairing both fiber yield and quality. Conventional resistance assessment techniques, which are largely reliant on subjective manual evaluation, fail to meet the demands for precision and scalability required for advanced genetic research. This study introduces a robust evaluation framework utilizing feature selection and optimization algorithms to enhance the accuracy and efficiency of the severity assessment of cotton VW. We conducted comprehensive time-series UAV hyperspectral imaging (400 to 995 nm) on the cotton canopy in a field environment on different days after sowing (DAS). After preprocessing the hyperspectral data to extract wavelet coefficients and vegetation indices, various feature selection methods were implemented to select sensitive spectral features for cotton VW. By leveraging these selected features, we developed machine learning models to assess the severity of cotton VW at the canopy scale. Model validation revealed that the performance of the assessment models responded dynamically as VW progressed and achieved the highest R2 of 0.5807 at DAS 80, with an RMSE of 6.0887. Optimization algorithms made a marked improvement for SVM in severity assessment using all observation data, with R2 increasing from 0.6986 to 0.9007. This study demonstrates the potential of feature selection and machine learning methods based on hyperspectral data in enhancing VW management, promising advancements in high-throughput automated disease assessment, and supporting sustainable agricultural practices. Hyperspectral imaging ; Feature selection ; Verticillium wilt ; Canopy ; Computer science ; Selection (genetic algorithm) ; Remote sensing ; Artificial intelligence ; Pattern recognition (psychology) ; Algorithm ; Agricultural engineering ; Environmental science ; Agronomy ; Geology ; Engineering ; Biology ; Botany Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Smart Agriculture and AI
Authors: Eman A. Allam | Salama M. El-Darier | Zekry F. Ghattass | Amal M. Fakhry | Roufaida M. Elghobashy
Source: BMC Plant Biology (article, 2024-05-28)
Field: Chemistry — Organic Chemistry

Application of chitosan nanopriming on plant growth and secondary metabolites of Pancratium maritimum L Applying chitosan nanoparticles in priming seeds might be a simple and effective way to improve the quantity of secondary metabolites of Pancratium maritimum L. valuable medicinal plant. Germination ; Biology ; Seedling ; Shoot ; Petri dish ; Horticulture ; Biomass (ecology) ; Botany ; Plant propagation ; Agronomy Chemical synthesis and alkaloids ; Plant tissue culture and regeneration ; Allelopathy and phytotoxic interactions