ACS Applied Engineering Materials最新文献

Disaccharides, composed of two monosaccharide units, are crucial cornerstones in the regulation of various forms of cellular activities. Identifying disaccharides is, however, extremely challenging because of the stereochemistry of monomeric subunits and the regioisomeric diversity of glycosidic linkages. To tackle this fundamental challenge, we devise an automated and unbiased platform that employs quantum tunneling and explainable artificial intelligence (AI) to detect each disaccharide constitutional isomer and regioisomer with good sensitivity and specificity. Explainable AI calling of the three most widely known disaccharides, sucrose, lactose, and maltose, as well as six regioisomers of α-d-glucopyranosyl-d-fructose, is performed simultaneously, and 99.2% accuracy is achieved. From the global and local analysis of the degree of influence of each input variable in calling disaccharide isomers, we aim to provide a better understanding of the AI decision-making process. AI-integrated quantum tunneling technology for sequencing disaccharides, which has never been previously reported, could be valuable in decoding complex structure–function relationships of polysaccharides.

Wound healing remains a persistent challenge in clinical medicine due to the high susceptibility of skin injuries to bacterial infections. The development of nanocomposite hydrogels with potent antibacterial properties is therefore critical to enhancing wound closure and tissue regeneration. Herein, we report a self-healing hydrogel platform that integrates ultrasonic-triggered piezocatalytic therapy for the effective treatment of bacteria-infected wounds. The hydrogel was engineered by incorporating calcium titanate (CaTiO₃, CT) nanoparticles into a chitosan/vanillin matrix, with dynamic Schiff base linkages conferring autonomous self-healing behavior. Upon ultrasonic stimulation, the embedded CT nanoparticles generate reactive oxygen species (ROS) via a strong built-in electric field, achieving high antibacterial efficacy localized to the wound site and thereby improving therapeutic biosafety. The self-healing nature of the hydrogel ensures continuous protection and facilitates rapid tissue repair. Notably, the system demonstrates a synergistic antibacterial mechanism through the combined effects of mechanical disruption and catalytic ROS generation. This study underscores the potential of piezocatalytic self-healing hydrogels as advanced wound dressings and provides a promising platform for the development of intelligent, stimuli-responsive biomaterials for precision regenerative therapies.

Over the past decade, bacterial calcite (BC) has been gaining popularity among scientists and engineers as a sustainable building material. In this article, we wanted to explore the performance of bacterial mortar (BM) as a function of BC precipitation. A step-by-step rational approach was adopted that helped in correlating calcite precipitation in bacterial cultures with the strength of the BM produced by the same. The optimized BM samples thus produced were stronger (up to 70% increase in compressive strength), more resistant to water absorption than normal mortar (up to 24% reduction in water absorption), and exhibited remarkable self-healing effects. The mechanical properties of the mortar samples were assessed through compressive and flexural strength tests, while self-healing effects were confirmed through the capacity to autoheal an entirely split BM cube. Microstructural analyses of the BM samples were done using FESEM–EDS and XRD data which helped in providing mechanistic insights into the observed characteristics of BM. The optimized BM formulations when used for coating concrete beams imparted higher strengths to the same compared to the uncoated beams as derived through their higher flexural strengths (26% approx.). Our developed BM, possessing improved mechanical properties coupled with its water-resistant features and excellent self-healing properties, makes it an economically and environmentally sustainable repairing material for existing and upcoming concrete structures.

Radioactive iodine pollution from nuclear waste poses a significant threat to the environment and human health, making its capture and safe storage of utmost importance. In this study, we developed an acridine-based nitrogen-rich porous organic polymer (Ac_POP-5) via Schiff base polycondensation. The polymer, designed with electron-rich aromatic rings and nitrogen centers, exhibits strong iodine adsorption capabilities. Our results show that Ac_POP-5 achieves exceptional iodine uptake across various conditions: 8.11 g/g at elevated temperature, 3.02 g/g at room temperature, and 4975.39 mg/g in aqueous media, respectively. The porous organic polymer Ac_POP-5, produced through a simple and scalable method, exhibits outstanding chemical and thermal stabilities, enabling it to maintain its iodine uptake capacity through at least five cycles of use without substantial efficiency loss, even in high-temperature, humid, basic, and acidic environments. These characteristics, combined with Ac_POP-5's excellent recyclability and low cost, make it an up-and-coming candidate for capturing volatile iodine during nuclear fuel reprocessing.

The current research presents a promising approach to synthesizing a phosphate-intercalated multiphase ternary metal layered double hydroxide using a one-pot method. This innovative approach facilitates the slow release of phosphate inhibitors, which is vital for forming a sustainable iron phosphate inhibitive layer on demand. UV-photometric analysis confirmed that the multiphase system offers a more persistent inhibitor release profile compared with conventionally prepared layered double hydroxides. The anticorrosion performance of the multiphase pigment incorporated into an epoxy coating was assessed through electrochemical impedance spectroscopy (EIS) over 1000 h in an aggressive saline medium. The results demonstrated excellent long-term barrier properties, with the coating maintaining a high coating resistance (R_c = 5.68 × 10⁸ Ω·cm²) after 2 months of immersion. The critical insights into the protective capabilities delve deeper into the active inhibition mechanism using X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). The current synthetic strategy opens an avenue through a simple production process and effectively enhances steel protection under challenging saline conditions.

We report the mechanical reinforcement of polymer-derived silicon oxycarbide (SiOC) through incorporating boron nitride nanotubes (BNNTs). Adding small amounts of BNNTs (up to 1.0 wt %) in SiOC precursors results in a remarkable 2.5-fold increase in flexural strength and a 3.3-fold increase in fracture toughness. The study reveals a brittle-to-ductile transition in BNNT-SiOC nanocomposites, increasing the deformability of the SiOC matrix. The introduction of small amounts of BNNTs noticeably reduces matrix porosity and promotes appreciable increases in matrix crystallinity. The findings demonstrate the potential of BNNTs as effective reinforcing fillers in polymer-derived ceramics, opening avenues for developing lightweight, high-strength, tough, and durable ceramic materials.

The complex composition of industrial waste oil poses a severe challenge to efficient separation and recycling, urgently necessitating the development of membrane materials that combine high separation efficiency, excellent high-temperature stability, and antifouling performance. In this paper, a carbon nanotube (CNT)/polydimethylsiloxane polytetrafluoroethylene hollow fiber membrane (PPHFM) was fabricated via the wet impregnation method. Results indicated that CNTs were uniformly dispersed within the PDMS matrix, synergistically constructing a hierarchically rough surface and endowing the membrane with superhydrophobic and superoleophilic properties. The optimized membrane pore structure conferred molecular sieving ability, achieving a separation efficiency of 94.32% for water-in-oil emulsified oil. Simultaneously, the membrane exhibited excellent permeation flux: the initial flux for kerosene reached 454.96 L^–1 m^–2 h^–1 bar^–1, and the flux for waste oil at 150 °C was 47.39 L^–1 m^–2 h^–1 bar^–1. The poly(p-phenylene terephthalamide) reinforcement layer endowed the membrane with ultrahigh mechanical strength (tensile strength >450 MPa). The optimized CM-2 membrane (CNTs 2 wt %) exhibited outstanding antifouling properties and cycling stability: after 4 consecutive operational cycles, the flux recovery ratio remained at 81.8% in the high-temperature waste oil system; it maintained a high flux even after long-term operation with high-temperature waste oil. This study successfully fabricated a CNT/PPHFM material. This membrane can efficiently treat industrial waste oil and exhibits enhanced durability, demonstrating broad application potential in demanding environments.

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li₄Ti₅O₁₂), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

Additive manufacturing (AM) has been proposed as a route to improve circularity in plastics through local recycling by consumers of their plastic waste into filaments for 3D printing. Polypropylene (PP) would be a promising feedstock in this scenario as PP is one of the largest plastic waste streams and historically has a low recycling rate. However, PP is challenging to accurately print into useable objects due to crystallization-induced warping and delamination during printing. Here, the objective is to overcome these challenges to enable the printability of recycled PP with transferable approaches to the 3D printing user community for sustainable filaments. We demonstrate a simple approach that is translatable to virgin and recycled PP through the inclusion of a natural rod-like clay, sepiolite, and maleated PP compatibilizer to improve the printability of PP through material extrusion AM. Inclusion of 10 wt % sepiolite leads to improvements to the printability, dimensional accuracy, and strength of the printed parts for both virgin and recycled PP resins. Higher filler loading can lead to backflow in the hot end from high viscosity of the nanocomposite. Lower filler content reduces warping and distortions from crystallization of PP relative to the neat PP, but the dimensional accuracy generally improves with increasing sepiolite loading. The broad compositional range for sepiolite to enhance printability provides an opportunity for admixes for recycling PP into filaments through concentrated master batching of sepiolite with PP for consumers wishing to upcycle their PP waste through 3D printing.