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By harnessing mechanical and optical resonances in tandem one can enhance the magnitude of actuation and optical response in dynamically reconfigurable nanostructures driven by microwatt optical signals and low-intensity acoustic vibrations. We review recent work on structures exhibiting profound opto-mechanical nonlinearity and bistability.

The resolution of conventional microscopy is limited to a half of the wavelength of light. We report on recent advances in applications of deep learning and topologically structured light to far-field nondestructive imaging with deep subwavelength resolution and to picometric metrology.

Scattering of topologically structured light is highly sensitive to the position of a scattering object. We show that the position of a coronavirus-like 100 nm polystyrene sphere can be measured optically with deeply subwavelength accuracy.

The first realization of sub-Brownian motion metrology is reported. The position of a nanowire is measured with resolution better than 100 picometers via deep learning analysis of topologically structured light scattering on the nanowire

The relative positions of nanostructures can be measured with picometric resolution using scattering of free electrons or topologically structured light at sharp edges of the structures. Through artificial intelligence enabled analysis of scattered coherent light, sub-atomic resolution is achievable in single-shot measurements.

Scattering by a subwavelength particle in a structured light field containing phase singularities is highly sensitive to the particle’s position. Artificial intelligence-enabled analysis of superoscillatory light field scattering, at a wavelength of 490 nm, provides for experimental determination of the 3D position of 100 nm polystyrene spheres with nanometric accuracy.

The optical response of a nanowire metamaterial can be controlled by resonant ponderomotive nonthermal optical forces. The coupling of optical and mechanical resonances facilitates a strong optical nonlinearity enabling all-optical transmission modulation at microwatt power levels.

We experimentally observe that fluctuations in metamaterial optical properties peak at the frequencies of the nanostructures’ natural mechanical modes, due to ‘Brownian’ motion. Fluctuations in flexural phonon density are the underlying mechanism for this motion, which is observed as fluctuations in optical properties reaching 1% at room temperature.

Resonant ponderomotive non-thermal optical forces can control the optical response of a nanowire metamaterial. Strong optical nonlinearity achieved via coupling of optical and mechanical resonances enables all-optical transmission modulation at microwatt power levels.

We demonstrate that fluctuations in the optical properties of nanomechanical photonic metamaterials can reach 1% at room temperature. Such fluctuations arise from ‘Brownian’ motion and peak at the frequencies of the nanostructures’ natural mechanical modes.

Carbon pricing is increasingly used by governments to reduce emissions. The effect of carbon pricing on economic outcomes as well as mitigating factors has been studied extensively since the early 1990s. One mitigating factor that has received less attention is education quality. If technological change that reduces the reliance of production on emissions is skill-biased, then carbon pricing may increase the skill premium of earnings and subsequent wage inequality; however, a more elastic skill supply through better education quality may mitigate adverse economic outcomes, including wage inequality, and enhance the effect of carbon pricing on technological change and subsequently emissions. A general equilibrium, overlapping-generations model is proposed, with endogenous skill investment in which the average skill level of the workforce can affect the need for emissions in an aggregate production function. This study uses data on industrial emissions linked to the Organisation for Economic Co-operation and Development’s Programme for International Assessment of Adult Competencies dataset for European Union countries. The findings show that, within countries, cognitive skills are positively associated with employment in industries that rely less on emissions for production and in industries that, over time, have been able to reduce their reliance on emissions for production. In the estimated general equilibrium model, higher cognitive skills reduce an economy’s reliance on emissions for production. Having higher quality education—defined as the level of cognitive skills attained by workers per unit of cost—increases the elasticity of skill supply and, as a result, mitigates a carbon tax’s economic costs including output loss and wage inequity, and enhances its effect on emissions reduction. The implication is that investments in education quality are needed for better enabling green technological innovation and adaptation and reducing inequality that results from carbon pricing.

We demonstrate metrology and odometry (detection of change in position over time) with resolution in the nanometric - picometric scales by analyzing electrons or topologically structured light scattered from the nanostructures using artificial intelligence. We show how these techniques can be applied to characterization and optimization of nano-opto-mechanical metamaterials and the fundamental studies of dynamics of thermal motion and the physics of phonons in photonic nanostructures.

We report on recent advances in applications of deep learning and topologically structured light to far-field non-destructive imaging with deep subwalength resolution and picometric metrology.