Search Results (138)

Background/Objectives: In the context of accelerating climate change and growing food insecurity, improving crop resilience to abiotic stresses such as drought, salinity, heat, and cold is a critical agricultural and scientific challenge. Understanding the biochemical mechanisms that underlie plant stress responses is essential for developing resilient crop varieties This review aims to provide an integrative overview of how metabolomics can elucidate biochemical mechanisms underlying stress tolerance and guide the development of stress-resilient crops. Methods: We reviewed the recent literature on metabolomic studies addressing abiotic stress responses in various crop species, focusing on both targeted and untargeted approaches using platforms such as nuclear magnetic resonance (NMR), liquid chromatography–mass spectrometry (LC-MS), and gas chromatography–mass spectrometry (GC-MS). We also included emerging techniques such as capillary electrophoresis–mass spectrometry (CE-MS), ion mobility spectrometry (IMS-MS), Fourier transform infrared spectroscopy (FT-IR), and data-independent acquisition (DIA). Additionally, we discuss the integration of metabolomics with transcriptomics and physiological data to support system-level insights. Results: The reviewed studies identify common stress-responsive metabolites, including osmoprotectants, antioxidants, and signaling compounds, which are consistently linked to enhanced tolerance. Novel metabolic biomarkers and putative regulatory hubs are highlighted as potential targets for molecular breeding and bioengineering. We also address ongoing challenges related to data standardization and reproducibility across analytical platforms. Conclusions: Metabolomics is a valuable tool for advancing our understanding of plant abiotic stress responses. Its integration with other omics approaches and phenotypic analyses offers promising avenues for improving crop resilience and developing climate-adaptive agricultural strategies. Full article

The fermentation of prune juice significantly enhances its nutritional profile, antioxidant capacity, and flavor characteristics. In this study, Non-Saccharomyces cerevisiae and Lactiplantibacillus plantarum were used to co-ferment prune juice to systematically investigate the dynamic changes in physicochemical properties and antioxidant activity during fermentation. The evolution of volatile compounds across fermentation stages was analyzed using gas chromatography–ion mobility spectroscopy (GC-IMS) combined with chemometric methods, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that after fermentation, the total acidity (TA), total phenolic content (TPC), and total flavonoid content (TFC) increased by 37.35%, 20.28%, and 28.95%, respectively. Meanwhile, the pH, total soluble solids (TSS), and reducing sugars (RS) decreased by 16.87%, 23.36%, and 39.94%, respectively. Additionally, the DPPH radical scavenging capacity and ABTS radical scavenging capacity improved by 76.16% and 57.25% during fermentation process. A total of 37 volatile compounds were identified across the four fermentation stages of prune juice (PJ). These compounds included 14 esters, 8 alcohols, 7 aldehydes, 4 terpenoids, 3 ketones, and 1 amine. Considerable quantities of organic acids and free amino acids were detected in samples from all fermentation phases. Among these, lactic acid, citric acid, and D-glucuronic acid exhibited significant increases in their concentration (p < 0.05). In the free amino acid profile of fermented prune juice (FPJ), asparagine was the most abundant component, followed by glutamine and proline. Full article

Twenty-two types of highland barley (HB) raw materials (including 10 common varieties and 5 main planting regions in the Qinghai province) were selected as the experimental materials to investigate their differences in the cooking characteristics, sensory quality, and characteristic flavor of cooked HB. The key volatile flavor components were identified using Gas Chromatography–Ion Mobility Spectroscopy (GC-IMS) combined with relative odor activity value (ROAV) analysis. The results indicated that the highland barley raw materials of Kunlun 15 (M5), Kunlun 14 (M9), Chaiqing 1 (M13) and Kunlun 14 (M14), and Chaiqing 1 (M20) and Kunlun 15 (M21) showed superior cooking quality, texture, and sensory scores. A total of 44 volatile flavor compounds were identified, including 16 aldehydes, 10 alcohols, 9 ketones, 7 esters, 1 acid, and 1 furan. Among these, 13 aldehydes, 4 alcohols, 4 ketones, 7 esters, and 1 furan were found across different cooked HB samples. Notably, ethyl, ethyl 2-methylbutanoate dimer, 2-methylbutanoic acid methyl ester, 2-butanone, 1-octen-3-ol, 1-pentanol dimer, and 2-pentyl furan contributed more significantly to the overall volatile profile. Cluster analysis combining principal component analysis revealed that Kunlun 16 (M16), Kunlun 17 (M17), Kunlun 14 (M18), Kunlun 15 (M19), as well as Chaiqing 1 (M20) and Kunlun 15 (M21), were the most suitable raw materials for cooking due to their better cooking quality, sensory attributes, and flavors, followed by Kunlun 15 (M10) and Kunlun 18 (M12), and Chaiqing 1 (M13) and Kunlun 14 (M14). These findings could help us identify specific HB varieties in corresponding regions with advantages, thus providing a theoretical basis for cooking HB. Full article

Deep eutectic solvents (DESs) are regarded as highly promising solvent systems for redox flow batteries. DESs, composed of choline halides (ChX, X = F⁻, Cl⁻, Br⁻, I⁻) and ethylene glycol (EG), exhibit distinct physicochemical properties at their eutectic points, including halide-dependent phase behavior, viscosity, polarity, conductivity, and solvation dynamics. In this study, we investigate the effects of the halide identity on the solvation properties of ChX:EG mixtures at varying mol % of ChX salt content. The solvatochromic polarity based on E_T(30) measurements indicates higher polarity for larger halides (I⁻ > Br⁻) than for smaller halides (Cl⁻ > F⁻), which exhibit larger compensating solvation shells. The ionic conductivity follows the trend of the solvent fluidity (the inverse of the viscosity), namely ChCl > ChBr > ChI > ChF, influenced by the ion mobility and solvodynamic radii. Measurements of the liquidus temperatures (T_L) reveal that the system with ChCl exhibits the deepest eutectic point (at ~20 mol % ChCl), while ChBr and ChI have shallower minima at ~10 mol % ChBr and ~3 mol % ChI, respectively. ChF does not display a eutectic transition but instead appears to readily supercool at salt concentrations above 30 mol % ChF. Consistent with the phase transition measurements, femtosecond transient absorption spectroscopy shows that in the ChCl system, the solvation dynamics become faster with an increasing salt concentration up to ~16.67 mol %, after which the dynamics slow down with further increases in the salt content. The ChF-based system exhibits similar behavior, though with slower dynamics. In contrast, the solvation dynamics of the systems containing ChBr and ChI monotonously slow down with an increasing salt concentration, in agreement with the phase transition measurements, which show that the eutectic points occur at low salt concentrations. These measurements suggest that the solvent composition and, in particular, the identity of the halide anion play a significant role in the solvation behavior of these ethylene-glycol-based DESs, offering a foundation for tuning the DES properties for specific applications. Full article

The aim of the study was to investigate the fixation of Cr(VI) ions from contaminated sediments using synthetic zeolite 4A and natural zeolite clinoptilolite. Parameters such as pH, contact time, adsorption mass and temperature were investigated. If the ions of the heavy metals were mobile, they would become toxic to the environment. After sediment digestion, the initial and final concentrations of Cr(VI) were measured in sediment samples with or without zeolite. Inductively coupled plasma with optical emission spectroscopy (ICP-OES) and X-ray diffraction (XRD) were used to characterize the material. The adsorption kinetics were investigated using a pseudo-first order model, a pseudo-second order model, and an intra-particle diffusion model. The results showed that the zeolites enhanced the fixation of Cr(VI). Chemisorption was the main mechanism when using acid-modified zeolite. Full article

Using novel SiO₂ surface passivation and ultraviolet (UV) light anneal, a 12 nm thick SnO p-type FET (pFET) shows hole effective mobilities (µ_eff) of more than 100 cm²/V·s and 31.1 cm²/V·s at hole densities (Q_h) of 1 × 10¹¹ and 5 × 10¹² cm⁻², respectively. To further improve the on-current/off-current (I_ON/I_OFF), an ultra-thin 7 nm thick SnO nanosheet pFET shows a record-breaking I_ON/I_OFF of 6.9 × 10⁶ and remarkable µ_eff values of ~70 cm²/V·s and 20.7 cm²/V·s at Q_h of 1 × 10¹¹ cm⁻² and 5 × 10¹² cm⁻², respectively. This is the first report of an oxide semiconductor transistor achieving a hole effective mobility µ_eff that reaches 20% of that in single-crystal Si pFETs at an ultra-thin body thickness of 7 nm. In sharp contrast, the control SnO nanosheet pFET without surface passivation or UV anneal exhibits a small I_ON/I_OFF of 1.8 × 10⁴ and a µ_eff of only 6.1 cm²/V·s at 5 × 10¹² cm⁻² Q_h. The enhanced SnO pFET performance is attributed to reduced defects and improved quality in the SnO channel, as confirmed by decreased charges related to sub-threshold swing (SS) and threshold voltage (Vth) shift. Such a large improvement is further supported by the increased Sn²⁺ after passivation and UV anneal, as evidenced by X-ray photoelectron spectroscopy (XPS) analysis. The I_ON/I_OFF ratio exceeding six orders of magnitude, remarkably high hole µ_eff, and excellent two-month stability demonstrate that this pFET is a strong candidate for integration with SnON nFETs in next-generation ultra-high-definition displays and monolithic three-dimensional integrated circuits (3D ICs). Full article

In addition to its flavor and nutritional value, the origin of kelp has become a crucial factor influencing consumer choices. Nevertheless, research on kelp’s origin traceability by volatile organic compound (VOC) analysis is lacking, and the application of deep learning in this field remains scarce due to its black-box nature. To address this gap, we attempted to identify the origin of kelp by analyzing its VOCs in conjunction with explainable deep learning. In this work, we identified 115 distinct VOCs in kelp samples using gas chromatography coupled with ion mobility spectroscopy (GC-IMS), of which 68 categories were discernible. Consequently, we developed a comprehensible one-dimensional convolutional neural network (1D-CNN) model that incorporated 107 VOCs exhibiting significant regional disparities (p < 0.05). The model successfully discerns the origin of kelp, achieving perfect metrics across accuracy (100%), precision (100%), recall (100%), F1 score (100%), and AUC (1.0). SHapley Additive exPlanations (SHAP) analysis highlighted the impact of features such as 1-Octen-3-ol-M, (+)-limonene, allyl sulfide-D, 1-hydroxy-2-propanone-D, and (E)-2-hexen-1-al-M on the model output. This research provides deeper insights into how critical product features correlate with specific geographic information, which in turn boosts consumer trust and promotes practical utilization in actual settings. Full article

A two-step annealing treatment was applied on a fully transparent amorphous InGaZnO4 (a-IGZO) top-gate thin-film transistor (TG-TFT) to improve the device performance. The electrical properties and stabilities of a-IGZO TG TFTs were significantly improved as the first-annealing temperature increased from 150 °C to 350 °C with a 300 °C second-annealing treatment. The a-IGZO TG-TFT with the 300 °C first-annealing treatment demonstrated the overall best performance, which has a mobility of 13.05 cm²/(V·s), a threshold voltage (V_th) of 0.33 V, a subthreshold swing of 130 mV/dec, and a I_on/I_off of 1.73 × 10⁸. The V_th deviation (ΔV_th) was −0.032 V and −0.044 V, respectively, after a 7200 s positive and negative bias stress under the gate bias voltage V_G = ±3 V and V_D = 0.1 V. The Photoluminescence spectra results revealed that the distribution and the density of defects in a-IGZO films were changed after the first-annealing treatment, whereas the X-ray photoelectron spectroscopy results displayed that contents of the oxygen vacancy and Ga-O bond varied in annealed a-IGZO films. In addition, a-IGZO TG-TFTs had achieved a transmittance of over 90%. Research on the effects of the first-annealing treatment will contribute to the fabrication of highly stable top-gate TFTs in the fields of transparent flexible electronics. Full article

In this research, Hall effect experiments and optical fittings were mainly conducted to elucidate the effect of hydrogen annealing on the electronic properties of polycrystalline Al-doped Zinc Oxide thin films by distinguishing the scattering by ion impurities and the scattering by grain boundaries. By comparing the carrier density and those mobilities of H₂-annealed samples with Ar-annealed samples, the effect of H₂ annealing was highlighted. AZO thin films were prepared on the quartz glass substrate at R.T. by an RF magnetron sputtering method, and the carrier density was controlled by changing the number of Al chips on the Zn target. After fabricating them, they were post-annealed in hydrogen or argon gas. Optical fitting was based on the Drude model using the experimental data of Near-Infrared spectroscopy, and the mobility at grain boundaries was analyzed by Seto’s theory. Other optical and crystalline properties were also checked by SEM, EDX, XRD and profilometer. It is indicated that the H₂ annealing would improve both carrier density and mobility. The analysis referring to Seto’s theory implied that the improvement of mobility was caused by the carrier generation from introduced hydrogen atoms both at the grain boundary and its intragrain region. Furthermore, the effect of H₂ annealing is relatively pronounced especially in low-doped region, which implies that Al and H have some interaction in AZO thin film. The interaction between Al and H in AZO thin film is still not confirmed, but this result implied that this interaction negatively affects the mobility at grain boundary. Full article

This study aimed to determine the structure–function relationship (SFR) for ChCl–glycerol mixtures, a deep eutectic solvent (DES), by investigating their microscopic solvation dynamics and how it relates to their macroscopic properties across varying concentrations of ChCl. Femtosecond transient absorption (fs-TA) spectroscopy revealed two distinct solvation dynamics time constants: τ₁, governed by glycerol–glycerol interactions, and τ₂, dominated by the choline response. The τ₂ minimum at 25–30 mol % ChCl closely aligned with the eutectic composition (~33.33 mol % ChCl), where the glycerol network was the most organized and the choline ions exhibited the fastest relaxation. The viscosity decreased sharply up to ~25 mol % ChCl and then plateaued, while the conductivity increased monotonically with ChCl concentration, reflecting enhanced ionic mobility. The density decreased with both increasing ChCl concentration and temperature, indicating disrupted hydrogen bonding and reduced molecular packing. The polarity, measured using betaine-30 (B30) and the E_T(30) polarity scale, increased steeply up to approximately 25 mol % ChCl before reaching a plateau. These findings identified the eutectic composition as the optimal concentration range for balancing stability, fluidity, conductivity, and enhanced dynamics within the glycerol system. Full article

Zinc oxide (ZnO) has recently gained considerable attention due to its exceptional properties, including higher electron mobility, good thermal conductivity, high breakdown voltage, and a relatively large exciton-binding energy. These characteristics helped engineers to develop low dimensional heterostructures (LDHs)-based advanced flexible/transparent nanoelectronics, which were then integrated into thermal management systems. Coefficients of thermal expansion $\mathsf{\alpha }\left(\mathrm{T}\right),$ phonon dispersions ${\mathsf{\omega }}_{\mathrm{j}}(\overrightarrow{\mathrm{q}})$, and Grüneisen parameters ${\mathsf{\gamma }}_{\mathrm{j}}\left(\overrightarrow{\mathrm{q}}\right)$ can play important roles in evaluating the suitability of materials in such devices. By adopting a realistic rigid-ion model in the quasi-harmonic approximation, this work aims to report the results of a methodical study to comprehend the structural, lattice dynamical, and thermodynamic behavior of zinc-blende (zb) ZnO. Systematic calculations of ${\mathsf{\omega }}_{\mathrm{j}}(\overrightarrow{\mathrm{q}})$, ${\mathsf{\gamma }}_{\mathrm{j}}\left(\overrightarrow{\mathrm{q}}\right),$ and $\mathsf{\alpha }\left(\mathrm{T}\right)$ have indicated negative thermal expansion (NTE) at low T. Soft transverse acoustic shear mode gammas ${\mathsf{\gamma }}_{\mathrm{T}\mathrm{A}}$ at critical points offered major contributions to NTE. Our results of ${\mathsf{\omega }}_{\mathrm{j}}(\overrightarrow{\mathrm{q}})$ at ambient pressure compare reasonably well with Raman scattering spectroscopy measurements and first-principles calculations. By adjusting the layers of materials with positive and negative thermal expansion, it is possible to create LDHs with near-zero $\mathsf{\alpha }\left(\mathrm{T}\right)$. Such a nanostructure might experience a minimal dimensional change with T fluctuations, making it ideal for devices where precise dimensional stability is crucial. Full article

This study presents a groundbreaking method for extracting lithium from beta-spodumene while simultaneously achieving the sustainable synthesis of LTA-type zeolite, designated as LPM-15, without relying on organic solvents or calcination. Lithium extraction was efficiently performed using sodium salts, accompanied by the recycling of the mother liquor, with lithium content in the supernatant precisely quantified via atomic absorption spectroscopy (AAS). The optimized synthesis route enables the concurrent production of Li₂CO₃ and LPM-15, distinguished by a powdered appearance without a well-defined geometric framework and a unique cubic morphology with spherical facets, respectively. To gain deeper insights into the process, density functional theory (DFT) simulations were conducted to analyze how different cation exchanges (Na⁺ replacing Al³⁺, NH₄⁺ replacing Al³⁺, and Ca²⁺ replacing Al³⁺) influence the structural stability and diffusion dynamics within the zeolitic pores of LPM-15. Additionally, cation-exchange capacity (CEC) measurements further assessed ion mobility within the LPM-15 framework. This integrative approach not only sheds light on the fundamental mechanisms underpinning LTA-type zeolite synthesis but also demonstrates their versatile applications, with particular emphasis on water purification technologies. Full article

Dansyl labeling is a widely used approach for enhancing the detection of small molecules by UV spectroscopy and mass spectrometry. It has been successfully applied to identify and quantify a variety of biological and environmental specimens. Despite clear advantages, the dansylation reaction has found very few applications in the study of proteins. We reasoned that the mild labeling conditions, small size, and rapid reaction could be beneficial for studying protein structure and dynamics. To test this, we investigated the impact of dansylation on protein fold, stability, protein–protein, and protein–cofactor interactions. We selected two model proteins, myoglobin and alcohol dehydrogenase, for analysis using native mass spectrometry and ion mobility mass spectrometry. Our work establishes the utility of dansyl chloride as a covalent probe to study protein structure and dynamics under native conditions. Full article

In order to characterize the volatile chemical components of Schisandra chinensis processed by different Traditional Chinese Medicine Processing methods and establish fingerprint profiles, headspace–gas chromatography–ion mobility spectrometry (HS-GC-IMS) technology was employed to detect, identify, and analyze Schisandra chinensis processed by five different methods. Fingerprint profiles of volatile chemical components of Schisandra chinensis processed by different methods were established; a total of 85 different volatile organic compounds (VOCs) were detected in the experiment, including esters, alcohols, ketones, aldehydes, terpenes, olefinic compounds, nitrogen compounds, lactones, pyrazines, sulfur compounds, thiophenes, acid, and thiazoles. Principal component analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), and Pearson correlation analysis methods were used to cluster and analyze the detected chemical substances and their contents. The analysis results showed significant differences in the volatile chemical components of Schisandra chinensis processed by different methods; the Variable Importance in Projection (VIP) values of the OPLS-DA model and the P values obtained from one-way ANOVA were used to score and screen the detected volatile chemical substances, resulting in the identification of five significant chemical substances with the highest VIP values: Alpha-Farnesene, Methyl acetate,1-octene, Ethyl butanoate, and citral. These substances will serve as marker compounds for the identification of Schisandra chinensis processed by different methods in the future. Full article

Mass spectral identification (in particular, in metabolomics) can be refined by comparing the observed and predicted properties of molecules, such as chromatographic retention. Significant advancements have been made in predicting these values using machine learning and deep learning. Usually, model predictions do not contain any indication of the possible error (uncertainty) or only one criterion is used for this purpose. The spread of predictions of several models included in the ensemble, and the molecular similarity of the considered molecule and the most “similar” molecule from the training set, are values that allow us to estimate the uncertainty. The Euclidean distance between vectors, calculated based on real-valued molecular descriptors, can be used for the assessment of molecular similarity. Another factor indicating uncertainty is the molecule’s belonging to one of the clusters (data set clustering). Together, all three factors can be used as features for the uncertainty assessment model. Classification models that predict whether a prediction belongs to the worst 15% were obtained. The area under the receiver operating curve value is in the range of 0.73–0.82 for the considered tasks: the prediction of retention indices in gas chromatography, retention times in liquid chromatography, and collision cross-sections in ion mobility spectroscopy. Full article