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Abstract Manufacturing of ceramics is challenging due to their low toughness and high hardness. Additive Manufacturing (AM) has been explored to create complex ceramic structures, but current techniques face a tradeoff between precisely controlled feature sizes and high shrinkage at the microscales. Here, we introduce 3D‐AJP, a novel freeform ceramic fabrication method that enables highly complex microscale 3D ceramic architectures—such as micropillars, spirals, and lattices—with minimal shrinkage and no auxiliary support. Using a near‐binder‐free nanoparticle ink in an Aerosol Jet (AJ) 3D printer, our approach precisely controls feature sizes down to 20 µm with aspect ratios up to 30:1. The resulting structures exhibit exceptionally low linear shrinkage of 2‐6% upon sintering, spanning five orders of magnitude in length scale. Bi‐material 3D architectures (zinc oxide/zirconia, zinc oxide/titania, titania/zirconia) and hybrid ceramics further demonstrate the technique’s versatility. We showcase two key applications. First, 3D ceramic photocatalysts improve water purification performance, achieving a 400% increase in photocatalytic efficiency compared to bulk ceramics. Second, we develop a highly sensitive Her2 biomarker sensor for breast cancer detection, achieving a 22‐second response time and a record‐low detection limit of 0.0193 fm. Our technique will lead to high‐performance sensing, filtration, microelectronics packaging, catalysis, and tissue regeneration technologies. 

Abstract To quantify the volatility of organic aerosols (OA), a comprehensive campaign was conducted in the Chinese megacity. Volatility distributions of OA and particle‐phase organic nitrate (pON) were estimated based on five methods: (a) empirical method and (b) kinetic model based on the measurement of a thermodenuder (TD) coupled with an aerosol mass spectrometer; (c) Formula‐based SIMPOL model‐driven method; (d) Element‐based estimations using molecular formula measurements of OA; and (e) gas/particle partitioning. Our results demonstrate that the ambient OA volatility distribution shows good agreement between the two heating methods and the formula‐based method when assuming ambient OA was mainly composed of organic nitrate (pON), organic sulfate and acid groups using the SIMPOL model. However, the element‐based method tends to overestimate the volatility of OA compared to the above three methods, suggesting large uncertainties in the parameterizations or in the representativeness of the molecular measurements that need further refinement. The volatility of ambient OA is generally lower than that of the laboratory‐derived secondary OA, emphasizing the impact of aging. A large fraction at the higher and lower volatility ranges (approximately logC* ≤ −9 and ≥2 μg m⁻³) was found for pON, implying the importance of both extremely low volatile and semi‐volatile species. Overall, this study evaluates different methods for volatility estimation and gives new insight into the volatility of OA and pON in urban areas. 

Abstract Sensing of clinically relevant biomolecules such as neurotransmitters at low concentrations can enable an early detection and treatment of a range of diseases. Several nanostructures are being explored by researchers to detect biomolecules at sensitivities beyond the picomolar range. It is recognized, however, that nanostructuring of surfaces alone is not sufficient to enhance sensor sensitivities down to the femtomolar level. In this paper, we break this barrier/limit by introducing a sensing platform that uses a multi-length-scale electrode architecture consisting of 3D printed silver micropillars decorated with graphene nanoflakes and use it to demonstrate the detection of dopamine at a limit-of-detection of 500 attomoles. The graphene provides a high surface area at nanoscale, while micropillar array accelerates the interaction of diffusing analyte molecules with the electrode at low concentrations. The hierarchical electrode architecture introduced in this work opens the possibility of detecting biomolecules at ultralow concentrations.