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Tailoring TiO2 Morphology and Surface Chemistry for Optimized Photocatalytic Activity in rGO Hybrids
(2026)
TiO2–reduced graphene oxide (rGO) hybrids were investigated in this study to elucidate how TiO2 morphology and surface chemistry govern charge-transfer pathways and, ultimately, reaction selectivity. Three anatase TiO2 nanostructures were compared: bipyramids predominantly exposing {101} facets (bipy) and two nanosheet-like samples enriched in {001} facets, either fluorinated (n-sh) or thermally defluorinated and {101}-enriched (n-sh_873K). A constant rGO loading (2 wt.%) was introduced via in situ hydrazine reduction of graphene oxide in the presence of TiO2. Photocatalytic activity was evaluated under Xe-lamp irradiation in two model reactions probing oxidative and reductive pathways: phenol degradation and H2 evolution using formic acid as a scavenger. rGO systematically enhanced phenol degradation for all morphologies, with bipy+rGO showing the highest activity. In contrast, H2 evolution was consistently suppressed upon rGO incorporation across all TiO2 samples, although the bipyramidal morphology remained the most active within each series. These results highlight that facet exposure and surface functionalization dictate the beneficial or detrimental role of rGO depending on the targeted photocatalytic pathway.
Precipitate size evolution during room temperature high-pressure torsion (HPT) of a Mg-1.35wt.%Mn alloy was studied using scanning transmission electron microscopy (STEM) and Small-/Wide-angle X-ray scattering (SAXS/WAXS). The volume fraction of the nm-scale α-Mn particles increased with applied strain, however small angle X-ray scattering (SAXS) indicated that the majority of manganese remained in solution even after 10 HPT rotations, indicating that the reaction progress is still limited by the diffusivity of Mn. Analysis of the precipitate size distribution determined that the mean particle size did not increase over the course of HPT. This, in combination with the precipitate size distribution suggested that precipitate growth was subject to interfacial rather than diffusional control.
Scalable covalently functionalized black phosphorus hybrids for broadspectrum virucidal activity
(2025)
At the onset of viral outbreaks, broad-spectrum antiviral materials are crucial before specific therapeutics become available. We report scalable, biodegradable black phosphorus (BP) hybrids that provide mutation-resilient virucidal protection. BP sheets, produced via an optimized mechanochemical process, are covalently functionalized with 2-azido-4,6-dichloro- 1,3,5-triazine to form P=N bonds. Fucoidan, a sulfated polysaccharide with intrinsic antiviral activity, and hydrophobic chains are then incorporated to achieve irreversible viral deactivation. The material exhibits strong antiviral inhibition and complete virucidal activity against multiple viruses, including recent severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) variants. It maintains high biocompatibility, remains effective against viral mutations, and is shelf stable for at least five month. The combination of biodegradability, scalable synthesis, and synergistic antiviral and virucidal mechanisms establishes BP-conjugates as a new class of highly efficient antivirals. They offer a broad spectrum antiviral solutions that could bridge the gap between antiviral medicines and general antiseptics.
Posterior sampling by Monte Carlo methods provides a more comprehensive solution approach to inverse problems than computing point estimates such as the maximum posterior using optimization methods, at the expense of usually requiring many more evaluations of the forward model. Replacing computationally expensive forward models by fast surrogate models is an attractive option. However, computing the simulated training data for building a sufficiently accurate surrogate model can be computationally expensive in itself, leading to the design of computer experiments problem of finding evaluation points and accuracies such that the highest accuracy is obtained given a fixed computational budget. Here, we consider a fully adaptive greedy approach to this problem. Using Gaussian process regression as surrogate, samples are drawn from the available posterior approximation while designs are incrementally defined by solving a sequence of optimization problems for evaluation accuracy and positions. The selection of training designs is tailored towards representing the posterior to be sampled as good as possible, while the interleaved sampling steps discard old inaccurate samples in favor of new, more accurate ones. Numerical results show a significant reduction of the computational effort compared to just position-adaptive and static designs.
A key factor in ensuring the accuracy of computer simulations that model physical systems is the proper calibration of their parameters based on real-world observations or experimental data. Inevitably, uncertainties arise, and Bayesian methods provide a robust framework for quantifying and propagating these uncertainties to model predictions. Nevertheless, Bayesian methods paired with inexact models usually produce predictions unable to represent the observed datapoints. Additionally, the quantified uncertainties of these overconfident models cannot be propagated to other Quantities of Interest (QoIs) reliably. A promising solution involves embedding a model inadequacy term in the inference parameters, allowing the quantified model form uncertainty to influence non-observed QoIs. This paper introduces a more interpretable framework for embedding the model inadequacy compared to existing methods. To overcome the limitations of current approaches, we adapt the existing likelihood models to properly account for noise in the measurements and propose two new formulations designed to address their shortcomings. Moreover, we evaluate the performance of this inadequacy-embedding approach in the presence of discrepancies between measurements and model predictions, including noise and outliers. Particular attention is given to how the uncertainty associated with the model inadequacy term propagates to the QoIs, enabling a more comprehensive statistical analysis of prediction’s reliability. Finally, the proposed approach is applied to estimate the uncertainty in the predicted heat flux from a transient thermal simulation using temperature observations.
Simplified Sample Preparation and Lateral Flow Immunoassay for the Detection of Plant Viruses
(2025)
Lateral flow immunoassays (LFA) are widely used for decentralized testing, but their application for in-field plant virus diagnostics is often limited by tedious sample preparation. Here, we present a simplified dipstick LFA for the detection and monitoring of cowpea chlorotic mottle virus (CCMV) as a model plant pathogen. The assay employes a monoclonal mouse antibody for capture and a polyclonal rabbit antibody conjugated to 80-nm gold nanoparticles for detection. Conventional sample and conjugate pads are omitted, allowing the test strips to be dipped directly into wells containing plant extract and antibody-gold conjugate. In addition, no plastic casing was necessary, which significantly reduces waste. It was shown that CCMV concentrations as low as 4 μg/L or 400 pg per sample could be reliably detected in 15 minutes. Specificity tests confirmed that other plant viruses, cowpea mosaic virus (CPMV) and tobacco mosaic virus (TMV), did not produce false positive results. Furthermore, we describe a field-compatible sampling procedure using a manual punch and a disposable syringe. This step combines sample grinding, extraction, and conjugate reconstitution within the syringe frit, enabling the analysis of punched leaf discs without laboratory equipment. When applied to CCMV-infected cowpea plants, the assay revealed systemic infection before visual symptoms became apparent. This work demonstrates that simplified LFAs combined with innovative sampling techniques can provide sensitive, specific, and rapid diagnostics for crop monitoring and support early intervention strategies in agriculture.
A water-free ionothermal synthesis of porous magnesium-imprinted nitrogen-doped carbon (Mg–NC) materials is introduced to prepare a platform material to investigate electrocatalytic structure-performance relations. Atomically dispersed Co- and Fe-NCs isomorphic to the pristine Mg-NCs are prepared by ion-exchange reactions. The current Mg-templating strategy enables relatively high pyrolysis product yields of up to 50 wt% and resultant Fe-NC and Co-NC catalysts contain high and comparable active metal loading of up to 2.52 wt% Fe and 2.29 wt% Co, respectively. A combination of X-ray spectroscopies with DFT studies reveals a tetrapyrrolic structure of the coordination sites, originating from a pyrolytic magnesium template ion reaction within the ionothermal synthesis. Two sets of highly active isomorphic tetrapyrrolic Fe-NCs and Co-NCs are utilized to understand the differences in intrinsic electrocatalytic performance of Co-NCs and Fe-NCs towards the alkaline oxygen reduction reaction (ORR). Despite their superior valence electronic properties to facilitate the initial outer-sphere electron transfer to O2, Co-NCs show significantly lower performance than Fe-NC with comparable loading. Although the generally discussed weaker binding of peroxide intermediates to CoN4 sites compared to FeN4 sites is evident, experimental and theoretical investigation reveal that it is the underlying peroxide oxidation activity that suppresses the oxygen reduction activity of M-NCs. The high peroxide oxidation activity of Co-NCs explains their reduced alkaline ORR relative to Fe-NCs, shedding light on the understated significance of controlling peroxide chemistry for the optimizing cathodic performance.
Lithium isotopic fractionation is well-established in dynamic geochemical systems; however, its role in lithium-ion batteries (LIBs) remains uninvestigated. Herein, we report the first depth-resolved demonstration that isotopic separation occurs during Li-ion cell operation whose magnitude depends on the cycling history. Using depth-resolved glow discharge mass spectrometry, we monitored the 7Li/6Li ratio in LiNi0.333Mn0.333Co0.333O2 (NMC111)||graphite coin cell electrodes at defined life-cycle stages. Different charging rates were examined to get mechanistic insight into kinetic and thermodynamic control in the fractionation process. Although pristine electrodes exhibit a uniform isotopic ratio, cycled electrodes show a distinct 7Li enrichment in the positive electrode and a corresponding accumulation of 6Li at the surface of the negative electrode. The degree of isotopic separation varies with the charging rate. Isotopic signatures correlate with capacity fading, indicating lithium isotope mapping as a sensitive diagnostic tool for tracking electrode degradation and the evolution of the electrode–electrolyte interphases in LIBs.
Aging in lithium-ion batteries (LIBs) degrades performance and hinders sustainability, demanding advanced diagnostics for early failure prediction. We investigate lithium isotope fractionation (LIF) as an innovative probe of degradation in lithium cobalt oxide (LCO) coin cells aged over 0−700 cycles. High-precision multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) quantified δ7Li variations across cell stages: non-cycled (0 cycles), newly formed (5 cycles), semi-aged (250 cycles), and fully aged (700 cycles). During early cycling (≤ 45 cycles), chemical processes drive 7Li enrichment at the anode (δ7Li vs LSVEC = +12 ‰) through solid electrolyte interphase (SEI) formation, while the cathode depletes in 7Li (δ7Li vs LSVEC = −0.7 ‰). Beyond 45 cycles, electric field-induced migration predominates, promoting 6Li intercalation into the anode and increasing the δ7Li of the cathode by 8.1 ‰. Mass balance verifies isotope conservation, attributing shifts to redistribution and trapping. Complementary electrochemical impedance spectroscopy (EIS) and X-ray absorption spectroscopy and diffraction confirm SEI expansion, cobalt oxidation, lattice shrinkage, and changes in electrode structure, corroborating LIF trends. Notably, a δ7Li inflection at approximately 270 cycles anticipates end-of-life by 70 cycles, surpassing traditional methods in sensitivity. LIF emerges as a predictive indicator of aging mechanisms, informing optimized designs for durable LIBs.
This study presents an experimental determination of spectroscopic parameters for the less-abundant isotopologues 42CaF and 44CaF, alongside 40CaF, by high resolution laser-induced fluorescence spectroscopy in a skimmed free jet expansion. We recorded spectra near the natural linewidth limit and derived spectroscopic constants for both X2Σ+ and A2Π states, including the fine and 19F magnetic hyperfine parameters. We also estimated the r (44Ca/40Ca) isotope amount ratio, demonstrating the potential use of optical spectroscopy for isotope analysis.