Thermophotovoltaic power conversion utilizes thermal radiation from a local heat source to generate electricity in a photovoltaic cell. It was shown in recent years that the addition of a highly reflective rear mirror to a solar cell maximizes the extraction of luminescence. This, in turn, boosts the voltage, enabling the creation of record-breaking solar efficiency. Now we report that the rear mirror can be used to create thermophotovoltaic systems with unprecedented high thermophotovoltaic efficiency. This mirror reflects low-energy infrared photons back into the heat source, recovering their energy. Therefore, the rear mirror serves a dual function; boosting the voltage and reusing infrared thermal photons. This allows the possibility of a practical >50% efficient thermophotovoltaic system. Based on this reflective rear mirror concept, we report a thermophotovoltaic efficiency of 29.1 ± 0.4% at an emitter temperature of 1,207 °C.

Light trapping in solar cells allows for increased current and voltage, as well as reduced materials cost. It is known that in geometrical optics, a maximum 4n 2 absorption enhancement factor can be achieved by randomly texturing the surface of the solar cell, where n is the material refractive index. This ray-optics absorption enhancement (AE) limit only holds when the thickness of the solar cell is much greater than the optical wavelength. In subwavelength thin films, the fundamental questions remain unanswered: 1) what is the subwavelength AE limit and 2) what surface texture realizes this optimal AE? We turn to computational electromagnetic optimization in order to design nanoscale textures for light trapping in subwavelength thin films. For high-index thin films, in the weakly absorbing limit, our optimized surface textures yield an angle-and frequency-averaged enhancement factor ∼39. They perform roughly 30% better than randomly textured structures, but they fall short of the ray optics enhancement limit of 4n 2 ∼ 50. Index Terms-Light trapping, optimization, subwavelength.2156-3381 © 2013 IEEE

Fourier ptychographic microscopy allows for the collection of images with a high space-bandwidth product at the cost of temporal resolution. In Fourier ptychographic microscopy, the light source of a conventional widefield microscope is replaced with a light-emitting diode (LED) matrix, and multiple images are collected with different LED illumination patterns. From these images, a higher-resolution image can be computationally reconstructed without sacrificing field-of-view. We use deep learning to achieve single-shot imaging without sacrificing the space-bandwidth product, reducing the acquisition time in Fourier ptychographic microscopy by a factor of 69. In our deep learning approach, a training dataset of high-resolution images is used to jointly optimize a single LED illumination pattern with the parameters of a reconstruction algorithm. Our work paves the way for high-throughput imaging in biological studies.

This manuscript concerns the application of infrared birefringence imaging ͑IBI͒ to quantify macroscopic and microscopic internal stresses in multicrystalline silicon ͑mc-Si͒ solar cell materials. We review progress to date, and advance four closely related topics. ͑1͒ We present a method to decouple macroscopic thermally-induced residual stresses and microscopic bulk defect related stresses. In contrast to previous reports, thermally-induced residual stresses in wafer-sized samples are generally found to be less than 5 MPa, while defect-related stresses can be several times larger. ͑2͒ We describe the unique IR birefringence signatures, including stress magnitudes and directions, of common microdefects in mc-Si solar cell materials including: ␤-SiC and ␤-Si 3 N 4 microdefects, twin bands, nontwin grain boundaries, and dislocation bands. In certain defects, local stresses up to 40 MPa can be present. ͑3͒ We relate observed stresses to other topics of interest in solar cell manufacturing, including transition metal precipitation, wafer mechanical strength, and minority carrier lifetime. ͑4͒ We discuss the potential of IBI as a quality-control technique in industrial solar cell manufacturing.

In example-based super-resolution, the function relating low-resolution images to their high-resolution counterparts is learned from a given dataset. This data-driven approach to solving the inverse problem of increasing image resolution has been implemented with deep learning algorithms. In this work, we explore modifying the imaging hardware in order to collect more informative low-resolution images for better ultimate high-resolution image reconstruction. We show that this "physical preprocessing" allows for improved image reconstruction with deep learning in Fourier ptychographic microscopy.Fourier ptychographic microscopy is a technique allowing for both high resolution and high field-of-view at the cost of temporal resolution. In Fourier ptychographic microscopy, variable illumination patterns are used to collect multiple low-resolution images. These low-resolution images are then computationally combined to create an image with resolution exceeding that of any single image from the microscope. We use deep learning to jointly optimize the illumination pattern with the post-processing reconstruction algorithm for a given sample type, allowing for single-shot imaging with both high resolution and high field-of-view. We demonstrate, with simulated data, that the joint optimization yields improved image reconstruction as compared with sole optimization of the post-processing reconstruction algorithm.

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This manuscript concerns the application of infrared birefringence imaging ͑IBI͒ to quantify macroscopic and microscopic internal stresses in multicrystalline silicon ͑mc-Si͒ solar cell materials. We review progress to date, and advance four closely related topics. ͑1͒ We present a method to decouple macroscopic thermally-induced residual stresses and microscopic bulk defect related stresses. In contrast to previous reports, thermally-induced residual stresses in wafer-sized samples are generally found to be less than 5 MPa, while defect-related stresses can be several times larger. ͑2͒ We describe the unique IR birefringence signatures, including stress magnitudes and directions, of common microdefects in mc-Si solar cell materials including: ␤-SiC and ␤-Si 3 N 4 microdefects, twin bands, nontwin grain boundaries, and dislocation bands. In certain defects, local stresses up to 40 MPa can be present. ͑3͒ We relate observed stresses to other topics of interest in solar cell manufacturing, including transition metal precipitation, wafer mechanical strength, and minority carrier lifetime. ͑4͒ We discuss the potential of IBI as a quality-control technique in industrial solar cell manufacturing.

Efficient external luminescence is a prerequisite for high-voltage solar cells. To approach the Shockley-Queisser limit, a highly reflective rear mirror is required. This mirror enhances the voltage of the solar cell by providing internally luminescent photons with multiple opportunities for escaping out the front surface. Likewise, intermediate reflectors in a multibandgap solar cell can assist external luminescence to enhance the voltage for each cell in a stack. These intermediate reflectors must also transmit the subbandgap photons to the next cell in the stack. A practical implementation of an intermediate selective reflector is an air gap sandwiched by antireflection coatings.The air gap provides perfect reflection for angles outside the escape cone, and the antireflection coating transmits angles inside the escape cone. As the incoming sunlight is within the escape cone, it is transmitted on to the next cell, while most of the internally trapped luminescence is reflected. We calculate that air gap intermediate reflectors, along with a rear mirror, can provide an absolute efficiency increase of 5% in multibandgap cells.