Effective Interfacing of Surface Homojunctions on Chemically Identical g-C3N4 for Efficient Visible-Light Photocatalysis without Sacrificial Agents.

Developing efficient homojunctions on g-C3N4 promises metal-free photocatalysis to realize truly sustainable artificial photosynthesis. However, current designs are limited by hindered charge separation due to inevitable grain boundaries and random formation of ineffective homojunctions embedded within the photocatalyst. Here, efficient photocatalysis is driven by introducing effective surface homojunctions on chemically and structurally identical g-C3N4 through leveraging its size-dependent electronic properties. Using a top-down approach, the surface layer of bulk g-C3N4 is partially exfoliated to create sheet-like g-C3N4 nanostructures on the bulk material. This hierarchical design establishes a subtle band energy offset between the macroscopic and nanoscopic g-C3N4, generating homojunctions while maintaining the chemical and structural integrities of the original g-C3N4. The optimized g-C3N4 homojunction demonstrates superior photocatalytic degradation of antibiotic pollutants at >96% efficiency in 2 h, even in different real water samples. It achieves reaction kinetics (≈0.041 min-1) up to fourfold better than standalone materials and their physical mixture. Mechanistic studies highlight the importance of the unique design in boosting photocatalysis by effectively promoting interfacial photocarrier manipulation and utilization directly at the point-of-catalysis, without needing co-catalysts or sacrificial agents. This work presents enormous opportunities for developing advanced and green photocatalytic platforms for sustainable light-driven environmental, energy, and chemical applications.

Harmonizing Plasmonic and Photonic Effects to Boost Photocatalytic H2 Production over 550 mmol ⋠h-1 ⋠gcat -1.

Integrating plasmonic nanoparticles with photonic crystals holds immense potential to enhance green hydrogen photosynthesis by amplifying localized electromagnetic field through generating surface plasmons and slow photons. Current plasmonic photonic designs primarily employ semiconductor-based structural backbone deposited with plasmonic nanoparticles. However, the competition between various optical phenomena in these ensembles hinders effective field enhancement rather than facilitating it. This limitation creates a formidable performance bottleneck that retards hydrogen evolution. Herein, we enhance plasmonic catalysis for efficient hydrogen evolution by effectively harmonizing plasmonic and photonic effects. This is achieved by using inert SiO2 opal as a non-photoabsorbing photonic framework. By aligning the excitation wavelengths of surface plasmons and slow photons, our optimized plasmonic photonic crystals demonstrates a remarkable H2 evolution rate of 560 mmol h-1 gAg -1, surpassing bare plasmonic Ag nanoparticles by >106-fold and other high-performance photocatalytic designs by 280-fold. Mechanistic studies highlight the pivotal role of the non-photoabsorbing photonic backbone in facilitating effective light confinement through the photonic effect. This in turn boosts the plasmonic field for enhanced photocatalytic H2 evolution, even without needing additional co-catalysts. Our work offers valuable insights for future design of electromagnetically hot plasmonic catalysts to achieve efficient light-to-chemical transformations in diverse energy, chemical, and environmental applications.

Chaotropic Nanoelectrocatalysis: Chemically Disrupting Water Intermolecular Network at the Point-of-Catalysis to Boost Green Hydrogen Electrosynthesis.

Efficient green hydrogen production through electrocatalytic water splitting serves as a powerful catalyst for realizing a carbon-free hydrogen economy. However, current electrocatalytic designs face challenges such as poor hydrogen evolution reaction (HER) performance (Tafel slope, 100-140 mV dec-1 ) because water molecules are thermodynamically trapped within their extensive hydrogen bonding network. Herein, we drive efficient HER by manipulating the local water microenvironment near the electrocatalyst. This is achieved by functionalizing the nanoelectrocatalyst's surface with a monolayer of chaotropic molecules to chemically weaken water-water interactions directly at the point-of-catalysis. Notably, our chaotropic design demonstrates a superior Tafel slope (77 mV dec-1 ) and the lowest overpotential (0.3 V at 10 mA cm-2 ECSA ), surpassing its kosmotropic counterparts (which reinforces the water molecular network) and previously reported electrocatalytic designs by up to ≈2-fold and ≈3-fold, respectively. Comprehensive mechanistic investigations highlight the critical role of chaotropic surface chemistry in disrupting the water intermolecular network, thereby releasing free/weakly bound water molecules that strongly interact with the electrocatalyst to boost HER. Our study provides a unique molecular approach that can be readily integrated with emerging electrocatalytic materials to rapidly advance the electrosynthesis of green hydrogen, holding immense promise for sustainable chemical and energy applications.

Dynamic Liquid-Liquid Interface: Applying a Spinning Interfacial Microreactor to Actively Converge Biphasic Reactants for the Enhanced Interfacial Reaction.

A liquid-liquid interfacial reaction combines reactants with large polarity disparity to achieve greener and more efficient chemistry that is otherwise challenging in traditional single-phase systems. However, current interfacial approaches suffer from the need for a large amount of solvent/reactant/emulsifier and poor reaction performance arising from intrinsic thermodynamic constraints. Herein, we achieve an efficient interfacial reaction by creating a magnetic-responsive, microscale liquid-liquid interface and exploit its dynamic spinning motion to generate vortex-like hydrodynamic flows that rapidly converge biphasic reactants to the point-of-reaction. Notably, the spinning of this functional interface at 800 rpm boosts the reaction efficiency and its apparent equilibrium constant by > 500-fold and 105-fold, respectively, higher than conventional methods that utilize bulk and/or non-dynamic liquid interfaces, even with external mechanical stirring. By driving reaction equilibrium toward favorable product formation, our unique design offers enormous opportunities to realize efficient multiphasic reactions crucial for diverse applications in chemical synthesis, environmental remediation, and even molecular recycling.

Solid-State Fermented Okara with Aspergillus spp. Improves Lipid Metabolism and High-Fat Diet Induced Obesity.

Okara is a major by-product of soymilk and tofu production. Despite retaining abundant nutrients after the process, okara is often under-utilized. In this study, solid-state fermentation (SSF) of okara was carried out using a koji starter (containing both Aspergillus oryzae and Aspergillus sojae) with the intention of releasing its untapped nutrients. Its effects on lipid metabolism in diet-induced obesity (DIO) were observed. The nutritional profile of fermented okara was elucidated using the following parameters: total phenolic content (TPC), pH, protein content, dietary fiber, amino acid content, and free sugar content. In vivo experiments were conducted using high-fat diets supplemented with unfermented okara and fermented okara over three weeks. Supplementation with fermented okara reduced body weight gain, adipose tissue weight, the serum triglyceride profile, and lipid accumulation in the liver, and altered the mRNA expression levels related to lipid metabolism; however, it did not affect pH and short-chain fatty acid (SCFA) production in this study. In conclusion, high-fat diets supplemented using okara fermented with Aspergillus spp. improved the lipid metabolism in mice, due to their high nutritional value, such as TPC, soy protein, and amino acids, and their synergistic effects without altering the gut microbiota.

Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min.

Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes.

Multiplex Surface-Enhanced Raman Scattering Identification and Quantification of Urine Metabolites in Patient Samples within 30 min.

Successful translation of laboratory-based surface-enhanced Raman scattering (SERS) platforms to clinical applications requires multiplex and ultratrace detection of small biomarker molecules from a complex biofluid. However, these biomarker molecules generally exhibit low Raman scattering cross sections and do not possess specific affinity to plasmonic nanoparticle surfaces, significantly increasing the challenge of detecting them at low concentrations. Herein, we demonstrate a "confine-and-capture" approach for multiplex detection of two families of urine metabolites correlated with miscarriage risks, 5ß-pregnane-3α,20α-diol-3α-glucuronide and tetrahydrocortisone. To enhance SERS signals by 1012-fold, we use specific nanoscale surface chemistry for targeted metabolite capture from a complex urine matrix prior to confining them on a superhydrophobic SERS platform. We then apply chemometrics, including principal component analysis and partial least-squares regression, to convert molecular fingerprint information into quantifiable readouts. The whole screening procedure requires only 30 min, including urine pretreatment, sample drying on the SERS platform, SERS measurements, and chemometric analyses. These readouts correlate well with the pregnancy outcomes in a case-control study of 40 patients presenting threatened miscarriage symptoms.