Terawatt-scale photovoltaics Haegel, Nancy M.; Margolis, Robert; Buonassisi, Tonio ...
Science (American Association for the Advancement of Science),
04/2017, Volume:
356, Issue:
6334
Journal Article
Peer reviewed
Open access
The annual potential of solar energy far exceeds the world's total energy consumption. However, the vision of photovoltaics (PVs) providing a substantial fraction of global electricity generation and ...total energy demand is far from being realized. What technical, infrastructure, economic, and policy barriers need to be overcome for PVs to grow to the multiple terawatt (TW) scale? We assess realistic future scenarios and make suggestions for a global agenda to move toward PVs at a multi-TW scale.
Abstract
Bayesian optimization (BO) has been leveraged for guiding autonomous and high-throughput experiments in materials science. However, few have evaluated the efficiency of BO across a broad ...range of experimental materials domains. In this work, we quantify the performance of BO with a collection of surrogate model and acquisition function pairs across five diverse experimental materials systems. By defining acceleration and enhancement metrics for materials optimization objectives, we find that surrogate models such as Gaussian Process (GP) with anisotropic kernels and Random Forest (RF) have comparable performance in BO, and both outperform the commonly used GP with isotropic kernels. GP with anisotropic kernels has demonstrated the most robustness, yet RF is a close alternative and warrants more consideration because it is free from distribution assumptions, has smaller time complexity, and requires less effort in initial hyperparameter selection. We also raise awareness about the benefits of using GP with anisotropic kernels in future materials optimization campaigns.
A new approach to ubiquitous sensing for indoor applications is presented, using low‐cost indoor perovskite photovoltaic cells as external power sources for backscatter sensors. Wide‐bandgap ...perovskite photovoltaic cells for indoor light energy harvesting are presented with the 1.63 and 1.84 eV devices that demonstrate efficiencies of 21% and 18.5%, respectively, under indoor compact fluorescent lighting, with a champion open‐circuit voltage of 0.95 V in a 1.84 eV cell under a light intensity of 0.16 mW cm−2. Subsequently, a wireless temperature sensor self‐powered by a perovskite indoor light‐harvesting module is demonstrated. Three perovskite photovoltaic cells are connected in series to create a module that produces 14.5 µW output power under 0.16 mW cm−2 of compact fluorescent illumination with an efficiency of 13.2%. This module is used as an external power source for a battery‐assisted radio‐frequency identification temperature sensor and demonstrates a read range by of 5.1 m while maintaining very high frequency measurements every 1.24 s. The combined indoor perovskite photovoltaic modules and backscatter radio‐frequency sensors are further discussed as a route to ubiquitous sensing in buildings given their potential to be manufactured in an integrated manner at very low cost, their lack of a need for battery replacement, and the high frequency data collection possible.
A new approach to ubiquitous sensing for indoor applications is presented, using low‐cost indoor perovskite photovoltaic cells as external power sources for backscatter sensors. Wide‐bandgap perovskite photovoltaic cells for indoor light energy harvesting are presented with the 1.63 and 1.84 eV devices that demonstrate efficiencies of 21% and 18.5%, respectively, under indoor compact fluorescent lighting.
Abstract
In materials science, the discovery of recipes that yield nanomaterials with defined optical properties is costly and time-consuming. In this study, we present a two-step framework for a ...machine learning-driven high-throughput microfluidic platform to rapidly produce silver nanoparticles with the desired absorbance spectrum. Combining a Gaussian process-based Bayesian optimization (BO) with a deep neural network (DNN), the algorithmic framework is able to converge towards the target spectrum after sampling 120 conditions. Once the dataset is large enough to train the DNN with sufficient accuracy in the region of the target spectrum, the DNN is used to predict the colour palette accessible with the reaction synthesis. While remaining interpretable by humans, the proposed framework efficiently optimizes the nanomaterial synthesis and can extract fundamental knowledge of the relationship between chemical composition and optical properties, such as the role of each reactant on the shape and amplitude of the absorbance spectrum.
Using a bottom-up cost model, we assess the impact of initial factory capital expenditure (capex) on photovoltaic (PV) module minimum sustainable price (MSP) and industry-wide trends. We find capex ...to have two important impacts on PV manufacturing. First, capex strongly influences the per-unit MSP of a c-Si module: we calculate that the capex-related elements sum to 22% of MSP for an integrated wafer, cell, and module manufacturer. This fraction provides a significant opportunity to reduce MSP toward the U.S. DOE SunShot module price target through capex innovation. Second, a combination of high capex and low margins leads to a poor financial rate of return, which limits the growth rate of PV module manufacturing capacity. We quantify the capex of Czochralski-based crystalline silicon (c-Si) PV manufacturing, summing to 0.68 $/W sub(aCap) ($ per annual production capacity in watts, $year/W) from wafer to module and 1.01 $/W sub(aCap) from polysilicon to module. At a sustainable operating margin determined by the MSP methodology for our bottom-up scenario, we calculate the sustainable growth rate of PV manufacturing capacity to be similar to 19% annually - below the historical trend of similar to 50% annually. We conclude with a discussion of innovation opportunities to reduce the capex of PV manufacturing through both incremental and disruptive process innovation with c-Si, platform innovations, and financial approaches.
Recently, we and others have proposed screening criteria for “defect-tolerant” photovoltaic (PV) absorbers, identifying several classes of semiconducting compounds with electronic structures similar ...to those of hybrid lead–halide perovskites. In this work, we reflect on the accuracy and prospects of these new design criteria through a combined experimental and theoretical approach. We construct a model to extract photoluminescence lifetimes of six of these candidate PV absorbers, including four (InI, SbSI, SbSeI, and BiOI) for which time-resolved photoluminescence has not been previously reported. The lifetimes of all six candidate materials exceed 1 ns, a threshold for promising early stage PV device performance. However, there are variations between these materials, and none achieve lifetimes as high as those of the hybrid lead–halide perovskites, suggesting that the heuristics for defect-tolerant semiconductors are incomplete. We explore this through first-principles point defect calculations and Shockley–Read–Hall recombination models to describe the variation between the measured materials. In light of these insights, we discuss the evolution of screening criteria for defect tolerance and high-performance PV materials.
The power conversion efficiency of solar cells based on copper (I) oxide (Cu2O) is enhanced by atomic layer deposition of a thin gallium oxide (Ga2O3) layer. By improving band‐alignment and ...passivating interface defects, the device exhibits an open‐circuit voltage of 1.20 V and an efficiency of 3.97%, showing potential of over 7% efficiency.
Defect tolerance, or the resilience of electronic transport properties of a crystalline material to the presence of defects, has emerged as a critical factor in the success of hybrid lead halide ...perovskites as photovoltaic absorbers. A key aspect of defect tolerance is the shallow character of dominant intrinsic defects. However, while qualitative heuristics to identify other defect-tolerant materials have been proposed, in particular, the presence of a partially oxidized ns2 cation such as Pb, no compelling comprehensive understanding of how these shallow defects arise has yet emerged. Using modern defect theory and defect calculations, we conduct a detailed investigation of the mechanisms and identify specific features related to the chemical composition and crystal structure that give rise to defect tolerance. We find that an ns2 cation is necessary but not sufficient to guarantee shallow cation vacancies in an s–p system, and that a compound’s crystal structure can ensure shallow anion vacancies in a variety of ways. Specifically, the crystal site symmetry can enforce weak interactions between the orbitals that form the defect states, thus ensuring that those defect states are shallow. We substantiate our findings by computing defect formation energies in several known as well as hypothetical materials and conclude by discussing prospects for identifying semiconductors that satisfy these criteria.
The conclusions reached by a diverse group of scientists who attended an intense 2‐day workshop on hybrid organic–inorganic perovskites are presented, including their thoughts on the most burning ...fundamental and practical questions regarding this unique class of materials, and their suggestions on various approaches to resolve these issues.
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