Optical absorption driven by intrinsic material loss is often viewed as a challenge to be overcome in photonic and metamaterials-based systems. In the context of applications such as optical communication, reducing absorption remains a key goal to maximize optical transmission. However, for many other applications related to sensing and detection, as well as heat transfer and energy, absorption and emission are essential. The overarching goal of this thesis is about taking advantage and embracing the loss in materials. Sometimes we have to lose to “gain”.In Chapter 1, we leveraged the loss in the epsilon near zero (ENZ) materials to build a broadband directional thermal emitter for the first time. We introduced and experimentally realized gradient epsilon-near-zero (ENZ) materials that enable broad spectrum directional control of thermal emission by supporting leaky electromagnetic modes that couple to free space at fixed angles over a broad bandwidth. We experimentally demonstrated two emitters consisting of multiple metal and semiconductor oxides in a photonic configuration that enable gradient ENZ behavior over long-wave infrared wavelengths. The structures exhibits high average emissivity (> 0.6 and > 0.7) in the p polarization between 7.7 and 11.5�m over an angular range of 70�-85�, and between 10.0 to 14.3�m over an angular range of 60�-75�, respectively. Outside these angular ranges, the emissivity reduces to 0.4 and lower for angles smaller than 50� and 40� respectively. The structures’ broadband thermal beaming capability enables radiative heat transfer only at particular angles and is experimentally verified through direct measurements of thermal emission. By decoupling conventional limitations on angular and spectral response, our approach opens new capabilities for applications such as thermal camouflaging, solar heating, radiative cooling and waste heat recovery. In Chapter 2, we further expanded our gradient ENZ thin film idea using doped III-V semiconductors to realize more continuous and precise control for the directional thermal radiation. Both experimentally and numerically we proved that, by increasing the total thickness of the gradient ENZ thin film made by Si-doped InAs, the high emissivity angle will move towards normal incidence. Also, by changing the doping level of the doped InAs film, we observed the functional bandwidth of the sample changes to a different range, which makes doped III-V semiconductors a more flexible directional thermal emitter candidate. In Chapter 3, we explored the beauty of loss in photonic crystals: in particular non-Hermitian photonic crystal where two materials only have a difference in the imaginary part of the permittivity. We found counter-intuitive behavior in this under-studied class of system, including loss-driven reflection. We characterized the band structure as well as the reflection response in both 1D and 2D non-Hermitian system. By introducing a lossy material in the crystal, a quasi-bandgap purely induced by loss opens up at the band edge. A sharp reflection peak is also observed within the quasi bandgap in both 1D and 2D non-Hermitian photonic crystals we proposed. In the end, we designed a selective reflector which consists a traditional 2D photonic crystal waveguide and a non-Hermitian photonic crystal. This selective reflector can guide light along the waveguide and have the light absorbed by the non-Hermitian part while only the light with certain wavelength can be reflected back, which distinguishes this selective reflector with the traditional reflectors such as a Bragg mirror. Finally in Chapter 4, lossy materials such as conductive polymers can potentially enable a revolution in building energy efficiency by dynamically controlling their thermal emissivity. We proposed a mechanism to decouple the mean radiant temperature from actual temperatures of interior surfaces by dynamically tuning the thermal emissivity of interior building surfaces. We quantitatively evaluated how much impact it will have on building energy saving in a building scale thought out a whole year. We showed that in cold weather, setting the emissivity of interior surfaces to a low value (0.1) can decrease the setpoint as much as 6.5�C from a baseline of 23�C. Conversely, in warm weather, low emissivity interior surfaces result in a 4.5�C cooling setpoint decrease relative to high emissivity (0.9) surfaces. EnergyPlus calculation shows that by implementing the tunable emissivity interior, more than 30% of the cooling and heating energy can be saved year-round in different climates.

Systematic instrumental uncertainties in astronomical analyses have been generally ignored in data analysis due to the lack of robust principled methods, though the importance of incorporating instrumental calibration uncertainty is widely recognized by both users and instrument builders. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. Lee et al. (2011) introduced a so-called pragmatic Bayesian method to address this problem. The method is "pragmatic" in that it introduces an ad hoc technique that simplifies computation by assuming that the current data is not useful in narrowing the uncertainty for the calibration product, i.e., that the prior and posterior distributions for the calibration products are the same.

In the thesis, we focus on incorporating calibration uncertainty into a principled Bayesian X-ray spectral analysis, specifically we account for uncertainty in the so-called effective area curve and the photon redistribution matrix. X-ray spectral analysis models the distribution of the energies of X-ray photons emitted from an astronomical source. The effective area curve of an X-ray detector describes its sensitive as a function of the energy of incoming photons, and the photon redistribution matrix describes the probability distribution of the recorded (discrete) energy of a photon as a function of the true (discretized) energy. Starting with the effective area curve, we follow Lee et al. (2011) and use a principle component analysis (PCA) to efficiently represent the uncertainty. Here, however, we leverage this representation to enable a principled, fully Bayesian method to account for calibration uncertainty in high-energy spectral analysis. For the photon redistribution matrix, we first model each conditional distribution as a normal distribution and then apply PCA to the parameters describing the normal models. This results in an efficient low-dimensional summary of the uncertainty in the redistribution matrix. Our methods for both calibration products are compared with standard analysis techniques and the pragmatic Bayesian method of Lee et al. (2011). The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product; we demonstrate this for the effective area curve. In this way, our fully Bayesian approach can yield more accurate and efficient estimates of the source parameters, and valid estimates of their uncertainty. Moreover, the fully Bayesian approach is the only method that allows us to make a valid inference about the effective area curve itself, quantifying which possible curves are most consistent with the data.

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