Anti-reflection zinc oxide nanocones for higher efficiency thin-film silicon solar cells

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 77-80).Thin film silicon solar cells, which are commonly made from microcrystalline silicon ([mu]c-Si) or amorphous silicon (a-Si), have been considered inexpensive alternatives to thick polycrystalline silicon (polysilicon) solar cells. However, the low solar efficiency of these thin film cells has become a major problem, which prevents thin film silicon cells from being able to compete with other solar cells in the market. One source of inefficiency is the light reflection off the interface between the thin film cell's top Transparent Conducting Oxide (TCO) and the light absorbing silicon. In this work, we demonstrate the use of nanocone textured ZnO as the anti-reflection surface that mitigates this problem. The tapered structure of the nanocone forms a smooth transition of refractive index on the interface between the TCO (ZnO) and the silicon, effectively acting as a wideband Anti-Reflection coating (AR coating). Finite Difference Time Domain simulation is used to estimate the optimal ZnO nanocone parameter (periodicity and height) to be applied on a single junction microcrystalline silicon ([mu]c-Si) solar cell. Relative improvement over 25% in optical performance is achieved in the simulated structure when compared to state-of-the-art [mu]c-Si cell structure. Cheap and scalable colloidal lithography method is then developed to fabricate ZnO nanocone with the desired geometry. Since the ZnO texturing technique works by depositing ZnO on nanocone-textured glass substrate, the technique is potentially applicable to Transparent Conducting Oxides other than ZnO as well, making it a useful TCO texturing technique for solar cell applications.by Jonathan P. Mailoa.M.Eng

Multi-Constraint Molecular Generation using Sparsely Labelled Training Data for Localized High-Concentration Electrolyte Diluent Screening

Recently, machine learning methods have been used to propose molecules with desired properties, which is especially useful for exploring large chemical spaces efficiently. However, these methods rely on fully labelled training data, and are not practical in situations where molecules with multiple property constraints are required. There is often insufficient training data for all those properties from publicly available databases, especially when ab-initio simulation or experimental property data is also desired for training the conditional molecular generative model. In this work, we show how to modify a semi-supervised variational auto-encoder (SSVAE) model which only works with fully labelled and fully unlabelled molecular property training data into the ConGen model, which also works on training data that have sparsely populated labels. We evaluate ConGen's performance in generating molecules with multiple constraints when trained on a dataset combined from multiple publicly available molecule property databases, and demonstrate an example application of building the virtual chemical space for potential Lithium-ion battery localized high-concentration electrolyte (LHCE) diluents

Protein-Ligand Complex Generator & Drug Screening via Tiered Tensor Transform

The generation of small molecule candidate (ligand) binding poses in its target protein pocket is important for computer-aided drug discovery. Typical rigid-body docking methods ignore the pocket flexibility of protein, while the more accurate pose generation using molecular dynamics is hindered by slow protein dynamics. We develop a tiered tensor transform (3T) algorithm to rapidly generate diverse protein-ligand complex conformations for both pose and affinity estimation in drug screening, requiring neither machine learning training nor lengthy dynamics computation, while maintaining both coarse-grain-like coordinated protein dynamics and atomistic-level details of the complex pocket. The 3T conformation structures we generate achieve significantly higher accuracy in active ligand classification than traditional ensemble docking using hundreds of experimental protein conformations. Furthermore, we demonstrate that 3T can be used to explore distant protein-ligand binding poses within the protein pocket. 3T structure transformation is decoupled from the system physics, making future usage in other computational scientific domains possible

Enhancing the Infrared Photoresponse of Silicon by Controlling the Fermi Level Location within an Impurity Band

Strong absorption of sub-band gap radiation by an impurity band has recently been demonstrated in silicon supersaturated with chalcogen impurities. However, despite the enhanced absorption in this material, the transformation of infrared radiation into an electrical signal via extrinsic photoconductivity—the critical performance requirement for many optoelectronic applications—has only been reported at low temperature because thermal impurity ionization overwhelms photoionization at room temperature. Here, dopant compensation is used to manipulate the optical and electronic properties and thereby improve the room-temperature infrared photoresponse. Silicon co-doped with boron and sulfur is fabricated using ion implantation and nanosecond pulsed laser melting to achieve supersaturated sulfur concentrations and a matched boron distribution. The location of the Fermi level within the sulfur-induced impurity band is controlled by tuning the acceptor-to-donor ratio, and through this dopant compensation, three orders of magnitude improvement in infrared detection at 1550 nm is demonstrated.Engineering and Applied Science

A 2-terminal perovskite/silicon multijunction solar cell enabled by a silicon tunnel junction

With the advent of efficient high-bandgap metal-halide perovskite photovoltaics, an opportunity exists to make perovskite/silicon tandem solar cells. We fabricate a monolithic tandem by developing a silicon-based interband tunnel junction that facilitates majority-carrier charge recombination between the perovskite and silicon sub-cells. We demonstrate a 1 cm[superscript 2] 2-terminal monolithic perovskite/silicon multijunction solar cell with a V [subscript OC] as high as 1.65 V. We achieve a stable 13.7% power conversion efficiency with the perovskite as the current-limiting sub-cell, and identify key challenges for this device architecture to reach efficiencies over 25%.Bay Area Photovoltaic Consortium (Contract DE-EE0004946)United States. Dept. of Energy (Contract DE-EE0006707

Improved Cu 2 O-Based Solar Cells Using Atomic Layer Deposition to Control the Cu Oxidation State at the p-n Junction

Chemistry and Chemical Biolog

Chalcogen-hyperdoped germanium for short-wavelength infrared photodetection

Obtaining short-wavelength-infrared (SWIR; 1.4 μm–3.0 μm) room-temperature photodetection in a low-cost, group IV semiconductor is desirable for numerous applications. We demonstrate a non-equilibrium method for hyperdoping germanium with selenium or tellurium for dopant-mediated SWIR photodetection. By ion-implanting Se or Te into Ge wafers and restoring crystallinity with pulsed laser melting induced rapid solidification, we obtain single crystalline materials with peak Se and Te concentrations of 1020 cm−3 (104 times the solubility limits). These hyperdoped materials exhibit sub-bandgap absorption of light up to wavelengths of at least 3.0 μm, with their sub-bandgap optical absorption coefficients comparable to those of commercial SWIR photodetection materials. Although previous studies of Ge-based photodetectors have reported a sub-bandgap optoelectronic response only at low temperature, we report room-temperature sub-bandgap SWIR photodetection at wavelengths as long as 3.0 μm from rudimentary hyperdoped Ge:Se and Ge:Te photodetectors

Role of solvent-anion charge transfer in oxidative degradation of battery electrolytes

Electrochemical stability windows of electrolytes largely determine the limitations of operating regimes of lithium-ion batteries, but the degradation mechanisms are difficult to characterize and poorly understood. Using computational quantum chemistry to investigate the oxidative decomposition that govern voltage stability of multi-component organic electrolytes, we find that electrolyte decomposition is a process involving the solvent and the salt anion and requires explicit treatment of their coupling. We find that the ionization potential of the solvent-anion system is often lower than that of the isolated solvent or the anion. This mutual weakening effect is explained by the formation of the anion-solvent charge-transfer complex, which we study for 16 anion-solvent combinations. This understanding of the oxidation mechanism allows the formulation of a simple predictive model that explains experimentally observed trends in the onset voltages of degradation of electrolytes near the cathode. This model opens opportunities for rapid rational design of stable electrolytes for high-energy batteries