The Mars–van Krevelen mechanism is the foundation for oxide-catalyzed oxidation reactions and relies on spatiotemporally separated redox steps. Herein, we demonstrate the tunability of this separation with peroxide species formed by excessively adsorbed oxygen, thereby modifying the catalytic activity and selectivity of the oxide. Using CuO as an example, we show that a surface layer of peroxide species acts as a promotor to significantly enhance CuO reducibility in favor of H ₂ oxidation but conversely as an inhibitor to suppress CuO reduction against CO oxidation. Together with atomistic modeling, we identify that this opposite effect of the peroxide on the two oxidation reactions stems from its modification on coordinately unsaturated sites of the oxide surface. By differentiating the chemical functionality between lattice oxygen and peroxide, these results are closely relevant to a wide range of catalytic oxidation reactions using excessively adsorbed oxygen to activate lattice oxygen and tune the activity and selectivity of redox sites.

Using synchrotron-based ambient-pressure X-ray photoelectron spectroscopy, we report the tuning of the deoxygenation process of bulk dissolved oxygen in copper via a combination of H₂ gas flow and elevated temperature. We show that a critical temperature of ∼580 °C exists for driving segregation of bulk dissolved oxygen to form chemisorbed oxygen on the Cu surface, which subsequently reacts with hydrogen to form OH species and then H₂O molecules that desorb from the surface. This deoxygenation process is tunable by a progressive stepwise increase of temperature that results in surface segregation of oxygen from deeper regions of bulk Cu. Using atomistic simulations, we show that the bulk-dissolved oxygen occupies octahedral sites of the Cu lattice and the deoxygenation process involves oxygen migration between octahedral and tetrahedral sites with a diffusion barrier of ∼0.5 eV.

A method to grow few-layer graphene in the form of an “inverted pagoda” is proposed by controlling the pressure and the flow rate in a circulating chemical vapor deposition system. Such single-crystal few-layer graphene consists of one- to eight-layer graphene areas exhibiting layer growth characteristics. Moreover, each layer within this kind of few-layer graphene is in Bernal stacking. In this work, with increasing growth pressure, the self-limiting effect of graphene was successfully overcome, and the growth of graphene in the vertical direction was achieved. By controlling the ratio of H₂/CH₄, the morphology and the number of layers of the multilayer graphene under the single-layer graphene were modulated.

In this paper, a potentiometric method is used for monitoring the concentration of glutamine in the bioprocess by employing silicon nanowire biosensors. Just one hydrolyzation reaction was used, which is much more convenient compared with the two-stage reactions in the published papers. For the silicon nanowire biosensor, the Al₂O₃ sensing layer provides a highly sensitive to solution-pH, which has near-Nernstian sensitivity. The sensitive region to detect glutamine is from ≤40 μM to 20 mM. The Sigmoidal function was used to model the pH-signal variation versus the glutamine concentration. Compared with the amperometric methods, a consistent result from different devices could be directly obtained. It is a fast and direct method achieved with our real-time setup. Also, it is a label-free method because just the pH variation of the solution is monitored. The obtained results show the feasibility of the potentiometric method for monitoring the glutamine concentrations in fermentation processes. Our approach in this paper can be applied to various analytes.

Highly sensitive flexible pressure sensors are crucial for wearable health monitoring and human–machine interaction. While the emerging iontronic sensors inherently offer high sensitivity, this can be further improved by engineering microstructured interfaces. In this study, we employ four different types of common fiber materials as substrates for fabricating ionic dielectric layers by a simple impregnation of ionic liquid (IL). A comparative study reveals that the porosity and microstructural architecture (e.g., fiber diameter) of the substrate material directly influences the amount of adsorbed IL and consequent sensing performance. We achieved the highest sensitivity by using a thin electrospun TPU/IL nanofiber mat (33 μm), which exhibited high sensitivities of 3.10 kPa⁻¹, 1.85 kPa⁻¹, and 1.02 kPa⁻¹ in the pressure ranges of 0–200 kPa, 200–400 kPa, and 400–700 kPa, respectively. Furthermore, the sensor exhibited an excellent fast response (2.71 ms) and recovery time (8.71 ms), along with outstanding cyclic stability. This work provides valuable guidance for selecting and utilizing common fiber materials to develop high-sensitivity iontronic pressure sensors, paving the way for their practical application in next-generation wearable electronics.

Artificial taste sensors mimicking human tongue enables a non-destructive, rapid, and objective method for taste assessment, and the integration of multiple sensing units to fully emulate human gustatory system remains challenge. Here, we present a dielectric-response-based taste (DRT) sensor with a facile structure for generic liquid identification. The representative tastants of the five basic tastes have been identified with a wide range (10 μM–100 mM), a low limit of the detection (5 μM), and long-term stability (>30 d). Moreover, mixtures of tastants can be distinguished by combining the potential and conductance measurement modes of the DRT sensor. An accuracy of 98.98% has been achieved on recognizing the types of six different beverages by the proposed sensor with the assistance of machine learning. The DRT sensor based on the idea of direct acquiring dielectric responses shows excellent performances in transcending human gustatory senses, providing an efficient, stable and low-cost method for applications in food industry, pharmaceutics, and environment monitoring.