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Abstract Active nanophotonic materials that can emulate and adapt between many different spectral profiles—with high fidelity and over a broad bandwidth—could have a far-reaching impact, but are challenging to design due to a high-dimensional and complex design space. Here, we show that a metamaterial network of coupled 2D-material nanoresonators in graphene can adaptively match multiple complex absorption spectra via a set of input voltages. To design such networks, we develop a semi-analytical auto-differentiable dipole-coupled model that allows scalable optimization of high-dimensional networks with many elements and voltage signals. As a demonstration of multi-spectral capability, we design a single network capable of mimicking four spectral targets resembling select gases (nitric oxide, nitrogen dioxide, methane, nitrous oxide) with very high fidelity ( $>90\mathrm{\%}$). Our results could impact the design of highly reconfigurable optical materials and platforms for applications in sensing, communication and display technology, and signature and thermal management. 

Additive manufacturing, such as 3D printing, offers unparalleled opportunities for rapid prototyping of objects, but typically requires simultaneous building of solid supports to minimize deformation and ensure contact with the printing surface. Here, we theoretically and experimentally investigate the concept of material extrusion on an “air bed”—an engineered ultrasonic acoustic field that stabilizes and supports the soft material by contactless radiation pressure force. We study the dynamics of polylactic acid filament—a commonly used material in 3D printing—as it interacts with the acoustic potential during extrusion. We develop a numerical radiation pressure model to determine optimal configurations of ultrasonic transducers to generate acoustic fields and conditions for linear printing. We build a concept prototype that integrates an acoustic levitation array with a 3D printer and use this device to demonstrate linear extrusion on an acoustic air bed. Our results indicate that controlled interactions between acoustic fields and soft materials could offer alternative support mechanisms in additive manufacturing with potential benefits such as less material waste, fewer surface defects, and reduced material processing time.