jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Govind Vyavahare | Ravishankar Patil | Jin Hee Park
Source: Plant Growth Regulation (article, 2025-09-11)
Field: Materials Science — Materials Chemistry

Nanoparticle-assisted elicitation of therapeutically important secondary metabolites in plants Plants are the major reservoir of bioactive compounds such as flavonoids, phenolics, proanthocyanidins, alkaloids, terpenoids, saponins, glycosides, essential oils, carotenoids, and natural dyes, some of which demonstrate bioactive properties. Bioactive compounds play a vital role in the food, fragrance, cosmetic, textile, and pharmaceutical sectors. Globally, the demand for plants as a whole and plant-based biomolecules is increasing to treat human diseases effectively. However, conventional production methods are time-consuming and fail to meet market demand. Recently, researchers have been exploring the potential of nanoparticles (NPs) as novel elicitors for increasing the levels of industrially important bioactive compounds in plants. Nanoparticles can be categorized into metallic, metal-oxide, non-metallic, bimetallic, and nanocomposites. Nanoparticles trigger the synthesis of reactive oxygen species (ROS), resulting in the upregulation of secondary metabolism to enhance bioactive compound synthesis. This review systematically discusses recent advancements in NPs assisted elicitation of bioactive plant metabolites in both in vitro and in vivo systems. The role of NPs in enhancing the production of secondary metabolites (SMs) has been comprehensively examined across various culture conditions. Several NPs, including silver, gold, zinc, cobalt, nickel, cerium, and aluminum, have shown promise as effective elicitors for boosting SM levels. However, some studies have reported phytotoxic effects, negatively affecting plant growth and SM accumulation. Accordingly, this review also highlights the potential adverse effects of NPs on plant systems and discusses the challenges associated with scaling up this technology. Overall, NPs present a novel and promising strategy for enhancing SM production in plants for industrial, pharmaceutical, and other applications. Secondary metabolism ; Plant physiology ; Plant metabolism ; Nanoparticle ; Metabolomics ; Metabolic engineering ; Plant growth Nanoparticles: synthesis and applications ; Medicinal Plants and Neuroprotection ; Allelopathy and phytotoxic interactions
Authors: Go Soma | Tomohiro Akazawa | Eisaku Kato | Kento Komatsu | Mitsuru Takenaka | Yoshiaki Nakano | Takuo Tanemura
Source: Nature Communications (article, 2025-11-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ultrafast one-chip optical receiver with functional metasurface High-speed optical receivers are crucial in modern optical communication systems. While complex photonic integrated circuits (PICs) are widely employed to harness the full degrees of freedom (DOFs) of light for efficient data transmission, their waveguide nature inherently constrains two-dimensional spatial scaling to accommodate a large number of optical signals in parallel. Here we present a scalable optical receiver platform that fully exploits the high spatial parallelism and ultrabroad bandwidth of light, while leveraging all DOFs-intensity, phase, and polarization. Our solution integrates a thin metasurface, composed of silicon nanoposts, with ultrafast membrane photodetectors on a compact chip. The metasurface provides all the functionalities of conventional PICs for normal-incident spatially parallelized light, enabling high-speed detection of optical signals in various modulation formats, including simultaneous detection of 320-gigabit-per-second four-channel four-level pulse amplitude modulation (PAM4) signals and coherent detection of 240-gigabit-per-second 64-ary quadrature amplitude modulation (64QAM) signals. Ultrashort pulse ; Photonics ; Bandwidth (computing) ; Photodetector ; Optical communication ; Modulation (music) ; Silicon photonics ; Scalability ; Amplitude modulation ; Photonic integrated circuit Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Photonic and Optical Devices
Authors: Tikhon V. Reztsov | Aleksey V. Chernykh | Tetiana Orlova | Nikolay V. Petrov
Source: Polymers (article, 2025-07-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Dynamic Analysis of Toron Formation in Chiral Nematic Liquid Crystals Using a Polarization Holographic Microscope Topological orientation structures in chiral nematic liquid crystals, such as torons, exhibit promising optical properties and are of increasing interest for applications in photonic devices. However, despite this attention, their polarization and phase dynamics during formation remain insufficiently explored. In this work, we investigate the dynamic optical response of a toron generated by focused femtosecond infrared laser pulses. A custom-designed polarization holographic microscope is employed to simultaneously record four polarization-resolved interferograms in a single exposure. This enables the real-time reconstruction of the Jones matrix, providing a complete description of the local polarization transformation introduced by the formation of the topological structure. The study demonstrates that torons can facilitate spin-orbit coupling of light in a manner analogous to q-plates, highlighting their potential for advanced vector beam shaping and topological photonics applications. Liquid crystal ; Holography ; Polarization (electrochemistry) ; Materials science ; Polarized light microscopy ; Optics ; Polarization Microscopy ; Microscope ; Microscopy ; Optoelectronics ; Chemistry ; Physics ; Physical chemistry Liquid Crystal Research Advancements ; Optical Polarization and Ellipsometry ; Digital Holography and Microscopy
Authors: Md Wadud Ahmed | J.L. Emmert | Mohammed Kamruzzaman
Source: Journal of the Science of Food and Agriculture (article, 2025-06-11)
Field: Chemistry — Analytical Chemistry

Non‐destructive quantification of egg yolk ratio using visible–near‐infrared hyperspectral imaging, machine learning and explainable <scp>AI</scp> This research highlights the effectiveness of Vis-NIR HSI integrated with ML and explainable AI as a rapid, reliable and non-destructive approach for egg yolk ratio assessment. The developed method offers significant advantages for egg quality monitoring, providing practical, interpretable and scalable solutions beneficial for food industry applications. © 2025 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. Hyperspectral imaging ; Yolk ; Pattern recognition (psychology) ; Artificial intelligence ; Infrared ; Chemistry ; Chromatography ; Computer science ; Food science ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Meat and Animal Product Quality
Authors: Fadi Abdeladhim Zidi | Abdelkrim Ouafi | Fares Bougourzi | Cosimo Distante | Abdelmalik Taleb‐Ahmed
Source: Computers and Electronics in Agriculture (article, 2025-07-30)
Field: Chemistry — Analytical Chemistry

Advancing wheat crop analysis: A survey of deep learning approaches using hyperspectral imaging <div> As one of the most widely cultivated and consumed crops, wheat is essential to global food security. However, wheat production is increasingly challenged by pests, diseases, climate change, and water scarcity, threatening yields. Traditional crop monitoring methods are labor-intensive and often ineffective for early issue detection. Hyperspectral imaging (HSI) has emerged as a non-destructive and efficient technology for remote crop health assessment. However, the high dimensionality of HSI data and limited availability of labeled samples present notable challenges. In recent years, deep learning has shown great promise in addressing these challenges due to its ability to extract and analysis complex structures. Despite advancements in applying deep learning methods to HSI data for wheat crop analysis, no comprehensive survey currently exists in this field. This review addresses this gap by summarizing benchmark datasets, tracking advancements in deep learning methods, and analyzing key applications such as variety classification, disease detection, and yield estimation. It also highlights the strengths, limitations, and future opportunities in leveraging deep learning methods for HSIbased wheat crop analysis. We have listed the current state-of-the-art papers and will continue tracking updating them in the following GitHubRepository. </div> Hyperspectral imaging ; Crop ; Remote sensing ; Agricultural engineering ; Environmental science ; Artificial intelligence ; Engineering ; Computer science ; Agronomy ; Geography ; Biology Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Remote-Sensing Image Classification
Authors: Rania M. Abdelazeem | Zienab Abdel‐Salam | Mohamed Abdel Harith
Source: Analytical and Bioanalytical Chemistry (article, 2025-03-05)
Field: Chemistry — Analytical Chemistry

Differentiating between normal and inflammatory blood serum samples using spectrochemical analytical techniques and chemometrics Inflammation detection in blood serum samples is commonly performed using clinical analyzers, which are expensive and complex and require specific labels or markers. Spectrochemical analytical techniques, such as laser-induced breakdown spectroscopy (LIBS) and laser-induced fluorescence (LIF), have emerged as alternative methods for qualitative and non-destructive analysis in various fields. This study explores applying LIBS and LIF techniques for label-free discrimination between normal and inflammatory blood serum samples. In the LIBS analysis, the serum samples are deposited on ashless filter paper and exposed to a high-power Nd:YAG laser source to induce plasma emission. The emitted light is dispersed in a spectrometer and an ICCD camera that captures the spectral lines. The LIF technique utilizes a diode-pumped solid-state laser source to excite the blood serum sample placed in a quartz cuvette. The resulting emission spectra are collected and analyzed using a spectrometer equipped with a CCD detector. The obtained spectroscopic data from both techniques is subjected to principal component analysis (PCA) and graph theory for classification and clustering. The PCA classified the two classes with a data variance of 85.4% and 92.8% based on the first two principal components (PCs) for LIBS and LIF spectra. The graph theory clustered the two classes with an accuracy of 76% and 100% based on LIBS and LIF spectra. The statistical methods effectively discriminate between normal and inflammatory serum samples, providing satisfactory results. The proposed spectrochemical methods offer several advantages over traditional clinical analyzers. They are cost-effective and rapid, making them suitable for the fast and reliable identification of serum samples in laboratories. The non-destructive nature of these techniques eliminates the need for specific labels or markers, further streamlining the analysis process. Chemometrics ; Analytical Chemistry (journal) ; Chemistry ; Chromatography Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Analytical chemistry methods development
Authors: Stefka Atanassova | Antoniya Petrova | Dimitar Yorgov | Roksana Mineva | Petya Veleva
Source: AgriEngineering (article, 2025-05-14)
Field: Chemistry — Analytical Chemistry

Visible and Near-Infrared Spectroscopy for Investigation of Water and Nitrogen Stress in Tomato Plants The main objective of this study was to evaluate the possibilities of visible-near-infrared spectroscopy for investigating water and nitrogen stress in tomato plants. Two varieties of tomato plants (Red Bounty and Manusa) were grown in a greenhouse. Plants were divided into three groups: control, reduced nitrogen fertilization, and reduced watering. Spectral measurements of tomato leaves were made on-site. A USB4000 spectrometer for 450–1100 nm and a handheld AlbaNIR for the 900–1650 nm region were used for the spectra acquisition. Twenty-four vegetative indices were calculated using the reflectance characteristics of plants. Soft Independent Modeling of Class Analogy (SIMCA) models were developed for classification. Additionally, aquagrams were calculated. Results show differences between the spectra of leaves from control and stressed plants for both tomato varieties. Aquagrams clearly show the differences in water structures in the three groups of plants. The performance of developed SIMCA models for discriminating plants according to growing conditions was very high. The total accuracy was between 86.89% and 97.09%. Several vegetation indices successfully differentiate control and stressed plants for both tomato varieties. The results show successful differentiation of the control and stressed tomato plants based on spectral characteristics of the plants’ leaves in the visible and near-infrared region. Water stress ; Nitrogen ; Spectroscopy ; Infrared spectroscopy ; Infrared ; Materials science ; Stress (linguistics) ; Environmental science ; Analytical Chemistry (journal) ; Environmental chemistry ; Chemistry ; Horticulture ; Optics ; Biology ; Physics ; Astronomy Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis
Authors: T. Ozawa | Sayaka Nakamura | Hiroaki Sato | Hideyuki Shinzawa | Hideaki Hagihara | Ryota Watanabe
Source: Analytical Chemistry (article, 2025-01-13)
Field: Chemistry — Spectroscopy

High-Resolution TG-TOFMS Coupled with Principal Component Analysis and Kendrick Mass Defect Analysis: Elucidation of Molecular-Scale Degradation Behavior of Glass Fiber Reinforced Polypropylene during Thermo-Oxidative Degradation This study presents a novel approach that combines thermogravimetric analysis with time-of-flight mass spectrometry (TG-TOFMS), principal component analysis (PCA), and Kendrick mass defect (KMD) analysis─referred to as TG-PCA-KMD─to investigate molecular-scale structural changes and quantitatively assess the progression of thermo-oxidative degradation in glass fiber reinforced polypropylene (GF/PP). TG-TOFMS enables the simultaneous and sensitive detection of both structural changes due to thermo-oxidative degradation and compositional changes in the filler and matrix. PCA and KMD analysis are crucial for identifying specific ion series derived from the degraded PP matrix in the high-resolution mass spectra obtained through TG-TOFMS. Additionally, PCA fitting was employed to selectively extract information on the degraded components of GF/PP from differential thermogravimetric profiles. Our findings demonstrate the advantages and utility of TG-PCA-KMD in the degradation analysis of composite materials. Thermogravimetric analysis ; Chemistry ; Principal component analysis ; Degradation (telecommunications) ; Polypropylene ; Analytical Chemistry (journal) ; Mass spectrometry ; Matrix (chemical analysis) ; Chromatography ; Organic chemistry Mass Spectrometry Techniques and Applications ; Polymer crystallization and properties ; Spectroscopy and Chemometric Analyses
Authors: Vincent A. Obakachi | Krishna K. Govender | Penny P. Govender
Source: In Silico Pharmacology (article, 2025-09-17)
Field: Chemistry — Organic Chemistry

Targeting Acute Myeloid Leukemia with 1,2,4-triazolo[4,3-b]pyridazine derivatives: a molecular docking, dynamics, and ADMET approach The online version contains supplementary material available at 10.1007/s40203-025-00418-1. Myeloid leukemia ; Leukemia ; Mutation ; Cancer ; Disease Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Click Chemistry and Applications
Authors: Fang Li | W. Q. Liu | Chao Ding | Shujuan Wang | Xiangpeng Meng
Source: Metals (review, 2025-05-20)
Field: Materials Science — Materials Chemistry

The Microstructures and Properties of Cu-Ni-Co-Si Alloys: A Critical Review This review provides an overview of recent advancements in Cu-Ni-Co-Si alloys, focusing on their processing methods, microstructures, and properties. Due to their non-toxic composition, enhanced mechanical properties, and excellent electrical conductivity, Cu-Ni-Co-Si alloys have emerged as a promising alternative to traditional Cu-Be alloys in the electrical and electronics industry. This review discusses various synthesis techniques, including casting, vacuum induction melting, and additive manufacturing, and evaluates their effects on the formed microstructures. In addition, it explores the influence of different elements and thermal treatments on the alloys’ microstructures and properties, discussing strategies to enhance the properties of Cu-Ni-Co-Si alloys. Key strengthening mechanisms—including precipitation hardening, grain boundary strengthening, and solid solution hardening—are examined in detail, with particular emphasis on their synergistic effects in optimizing alloy performance. Furthermore, future research directions are highlighted, focusing on the optimization of alloying element concentrations and heat treatment protocols to achieve an enhanced balance between strength and electrical conductivity. These improvements are critical for meeting the demanding requirements of advanced applications in electronics and high-reliability components. Microstructure ; Materials science ; Metallurgy Microstructure and mechanical properties ; Aluminum Alloys Composites Properties ; Aluminum Alloy Microstructure Properties
Authors: Yu-Hsiu Lin | William P. Comaskey | José L. Mendoza-Cortés
Source: Nanoscale Advances (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

How can we engineer electronic transitions through twisting and stacking in TMDC bilayers and heterostructures? a first-principles approach Layered two-dimensional (2D) materials exhibit unique properties not found in their individual forms, opening new avenues for material exploration. This study examines MX<sub>2</sub> transition metal dichalcogenides (TMDCs), where M is Mo or W, and X is S, Se or Te. These materials are foundational for the creation of hetero- and homo-bilayers with various stacking configurations. Recent interest has focused on twisted homogeneous bilayers, as critical twist angles can significantly alter material properties. This work highlights MX<sub>2</sub> TMDC bilayers with twisted angles that form Moiré patterns, essential to understanding the behaviors of these materials. We performed first-principles calculations using Density Functional Theory (DFT) with range-separated hybrid functionals on 30 combinations of six MX<sub>2</sub> materials with two stacking configurations, revealing that the building blocks and stacking arrangements influence the stability of the heterostructure and the band gap energy (<i>E</i> <sub>g</sub>). In particular, the MoTe<sub>2</sub>/WSe<sub>2</sub> heterostructure, shifted by 60°, exhibits a direct band gap, indicating potential for novel applications. Our investigation of homobilayers included fully relaxed and low-strain scenarios, examining various stacking styles and twisting angles. Under low-strain conditions, MoS<sub>2</sub>, WS<sub>2</sub>, and WSe<sub>2</sub> can exhibit direct or indirect band gaps at specific twist angles. Additionally, MoS<sub>2</sub> can transition between semiconductor and conductor states, showcasing diverse electronic properties. Critical twist angles, specifically 17.9° and its corresponding angles (42.1°, 77.9° and 102.1°), in twisted WS<sub>2</sub> and WSe<sub>2</sub> bilayers create symmetric Moiré patterns, leading to direct band gaps. The magnitude of the band gap energy can be tuned by varying the twist angles, which also affect the flatness of the electronic band. Like conventional stacking, most twisted TMDC bilayers exhibit favorable interlayer interactions but with more tailorable characteristics. Using heterostructures and controlled twist angles is a powerful approach in material engineering, enabling the manipulation of various electronic behaviors in advanced materials. Stacking ; Heterojunction ; Materials science ; Nanotechnology ; Condensed matter physics ; Engineering physics ; Engineering ; Optoelectronics ; Physics ; Nuclear magnetic resonance ZnO doping and properties ; Electronic and Structural Properties of Oxides ; Physics of Superconductivity and Magnetism
Authors: Lijing Wang | Shaowen Du | Zhiji Zhou | Yibo Guo | Qi Yang | Sai Yao | Haijun Zhang
Source: Materials (article, 2025-01-24)
Field: Materials Science — Polymers and Plastics

Enhanced Fire-Extinguishing Performance and Synergy Mechanism of HM/DAP Composite Dry Powder Phosphate resources are non-renewable and are increasingly depleting. Currently, the primary raw material for commercial ABC dry powder fire-extinguishing agents is a processed product derived from the limited reserves of phosphorus ore. Consequently, there is an urgent imperative to innovate and develop novel types of dry powder fire-extinguishing agents. In this work, a simple physical blending process was utilized to modify the abundant and cost-effective hydromagnesite (HM) powder, which has been proven to be a promising dry powder extinguishant with a pronounced physical cooling effect on fire suppression. The HM powder added to 10 wt.% diammonium hydrogen phosphate (DAP) showed a shorter extinguishing time and a lower agent dosage compared with the unmodified powder and commercially available monoammonium phosphate (MAP) in both the liquid and solid fire experiments. Notably, the HM/DAP composite dry powder extinguished fires with the lowest CO concentration, indicating superior environmental friendliness and human safety. These findings indicate the potential of the HM/DAP composite dry powder as a promising candidate for future fire-extinguishing applications. Composite number ; Materials science ; Raw material ; Diammonium phosphate ; Phosphate ; Waste management ; Composite material ; Chemical engineering ; Pulp and paper industry ; Chemistry ; Organic chemistry Flame retardant materials and properties ; Combustion and Detonation Processes ; Environmental and Industrial Safety