RESUMEN
Defects in microarchitected materials exhibit a dual nature, capable of both unlocking innovative functionalities and degrading their performance. Specifically, while intentional defects are strategically introduced to customize and enhance mechanical responses, inadvertent defects stemming from manufacturing errors can disrupt the symmetries and intricate interactions within these materials. In this study, we demonstrate a nondestructive optical imaging technique that can precisely locate defects inside microscale metamaterials, as well as provide detailed insights on the specific type of defect.
RESUMEN
Nitrogen-vacancy (NV-) centers in nanodiamonds have emerged as a versatile platform for a wide range of applications, including bioimaging, photonics, and quantum sensing. However, the widespread adoption of nanodiamonds in practical applications has been hindered by the challenges associated with patterning them into high-resolution features with sufficient throughput. In this work, we overcome these limitations by introducing a direct laser-writing bubble printing technique that enables the precise fabrication of two-dimensional nanodiamond patterns. The printed nanodiamonds exhibit a high packing density and strong photoluminescence emission, as well as robust optically detected magnetic resonance (ODMR) signals. We further harness the spatially resolved ODMR of the nanodiamond patterns to demonstrate the mapping of two-dimensional temperature gradients using high frame rate widefield lock-in fluorescence imaging. This capability paves the way for integrating nanodiamond-based quantum sensors into practical devices and systems, opening new possibilities for applications involving high-resolution thermal imaging and biosensing.
RESUMEN
Recent advances in two-photon polymerization fabrication processes are paving the way to creating macroscopic metamaterials with microscale architectures, which exhibit mechanical properties superior to their bulk material counterparts. These metamaterials typically feature lightweight, complex patterns such as lattice or minimal surface structures. Conventional tools for investigating these microscale structures, such as scanning electron microscopy, cannot easily probe the internal features of these structures, which are critical for a comprehensive assessment of their mechanical behavior. In turn, we demonstrate an optical confocal microscopy-based approach that allows for high-resolution optical imaging of internal deformations and fracture processes in microscale metamaterials under mechanical load. We validate this technique by investigating an exemplary metamaterial lattice structure of 80 × 80 × 80 µm3 in size. This technique can be extended to other metamaterial systems and holds significant promise to enhance our understanding of their real-world performance under loading conditions.
RESUMEN
We present a novel method for fabricating highly customizable three-dimensional structures hosting quantum sensors based on nitrogen vacancy (NV) centers using two-photon polymerization. This approach overcomes challenges associated with structuring traditional single-crystal quantum sensing platforms and enables the creation of complex, fully three-dimensional, sensor assemblies with submicroscale resolutions (down to 400 nm) and large fields of view (>1 mm). By embedding NV center-containing nanoparticles in exemplary structures, we demonstrate high sensitivity optical sensing of temperature and magnetic fields at the microscale. Our work showcases the potential for integrating quantum sensors with advanced manufacturing techniques, facilitating the incorporation of sensors into existing microfluidic and electronic platforms, and opening new avenues for widespread utilization of quantum sensors in various applications.
RESUMEN
Biological nervous systems rely on the coordination of billions of neurons with complex, dynamic connectivity to enable the ability to process information and form memories. In turn, artificial intelligence and neuromorphic computing platforms have sought to mimic biological cognition through software-based neural networks and hardware demonstrations utilizing memristive circuitry with fixed dynamics. To incorporate the advantages of tunable dynamic software implementations of neural networks into hardware, we develop a proof-of-concept artificial synapse with adaptable resistivity. This synapse leverages the photothermally induced local phase transition of VO2 thin films by temporally modulated laser pulses. Such a process quickly modifies the conductivity of the film site-selectively by a factor of 500 to "activate" these neurons and store "memory" by applying varying bias voltages to induce self-sustained Joule heating between electrodes after activation with a laser. These synapses are demonstrated to undergo a complete heating and cooling cycle in less than 120 ns.