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We have studied the degradation of both full-sized modules and minimodules with PERC and Al-BSF cell variations in fields while considering packaging strategies. We demonstrate the implementations of data-driven tools to analyze large numbers of modules and volumes of timeseries data to obtain the performance loss and degradation pathways. This data analysis pipeline enables quantitative comparison and ranking of module variations, as well as mapping and deeper understanding of degradation mechanisms. The best performing module is a half-cell PERC, which shows a performance loss rate (PLR) of −0.27 ± 0.12% per annum (%/a) after initial losses have stabilized. Minimodule studies showed inconsistent performance rankings due to significant power loss contributions via series resistance, however, recombination losses remained stable. Overall, PERC cell variations outperform or are not distinguishable from Al-BSF cell variations.

Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants in exposure conditions of high humidity and temperature. This data-driven modeling technique enables the exploration of simultaneous pairwise and multiple regression relationships between variables in which several degradation modes are active in specific variants and exposure conditions. Durable and degrading variants are identified from the netSEM degradation mechanisms and pathways, along with potential ways to mitigate these pathways. A combination of domain knowledge and netSEM modeling shows that corrosion is the primary cause of the power loss in these glass/backsheet PV minimodules. We show successful implementation of netSEM to elucidate the relationships between variables in PV systems and predict a specific service lifetime. The results from pairwise relationships and multiple regression show consistency. This work presents a greater opportunity to be expanded to other materials systems.

GaN microdomes were fabricated and measured as both an antireflection surface and a light extraction enhancement structure. The combination of self-assembled micro/nanosphere lithography and reactive ion etching process was used to fabricate GaN microdomes with different aspect ratios. SiO2 microspheres with diameters of 1000 and 500 nm, deposited on top of the GaN substrate using a dip-coating method, serve as the mask for the formation of GaN microdomes. The GaN microdome shapes and sizes were determined through control of the plasma etching conditions. The antireflection properties of the GaN microdomes with different sizes and shapes were characterized. Two different mechanisms were proposed to explain the surface reflection properties of incidence wavelength below and above GaN band gap, respectively. The trend shows that the surface reflection is reduced with the increase in the aspect ratio of the GaN microdomes for incidence wavelength above the band gap. For incidence wavelength below the band gap, the trend is totally different. Studies indicate that the microdomes are applicable not only as antireflection structures in solar cells but for enhancing light extraction in light-emitting diodes as well.

A better understanding of the degradation modes and rates for photovoltaic (PV) modules is necessary to optimize and extend the lifetime of these modules. Lifetime and degradation science (L&DS) is used to understand degradation modes, mechanisms and rates of materials, components and systems to predict lifetime of PV modules. A PV module lifetime and degradation science (PVM L&DS) model is an essential component to predict lifetime and mitigate degradation of PV modules using reproducible open data science. Previously published accelerated testing data from Underwriter Laboratories on PV modules with fluorinated polyester backsheets, which included eight modules that were exposed up to 4000 hrs of damp heat (85% relative humidity at 85°C) and eight exposed up to 4000 hrs of ultraviolet light (80 W/m2 of 280-400 nm wavelengths at 60°C) (UV preconditioning) were used to determine statistically significant relationships between the applied stresses and measured responses. There were 15 different variables tracking aspects of system performance, degradation mechanisms, component metrics and time. Modules were analyzed for three system performance metrics (fill factor, peak power, and wet insulation). The results were statistically analyzed to identify variable transformations, statistically significant relationships (SSRs) and to develop the PVM L&DS model informed by a generalization of structural equation modeling techniques. The SSRs and significant model coefficients, combined with domain analytics, incorporating materials science, chemistry, and physics expertise, produced a pathway diagram ranking the variables' impact on the system performance, which were iteratively examined using sound statistical analysis and diagnostics. The SSRs determined from the damp heat exposure for the system response of Pmax corresponded to the degradation pathway of polyester terephthalate (PET) and ethylene vinyl acetate (EVA) hydrolysis. A linear change point for the damp heat exposure with the system response of Pmax was determined to be 1890 hrs. The UV preconditioning exposure did not induce sufficient degradation shown by the quality of the R2 values for many of the best fitting models. This exemplifies the development of a methodology to determine rank ordered lifetime and degradation pathways present in modules and their effects on module performance over lifetime.

Accelerated weathering exposures were performed on poly(ethylene-terephthalate) (PET) films. Longitudinal multi-level predictive models as a function of PET grades and exposure types were developed for the change in yellowness index (YI) and haze (%). Exposures with similar change in YI were modeled using a linear fixed-effects modeling approach. Due to the complex nature of haze formation, measurement uncertainty, and the differences in the samples' responses, the change in haze (%) depended on individual samples' responses and a linear mixed-effects modeling approach was used. When compared to fixed-effects models, the addition of random effects in the haze formation models significantly increased the variance explained. For both modeling approaches, diagnostic plots confirmed independence and homogeneity with normally distributed residual errors. Predictive R2 values for true prediction error and predictive power of the models demonstrated that the models were not subject to over-fitting. These models enable prediction under pre-defined exposure conditions for a given exposure time (or photo-dosage in case of UV light exposure). PET degradation under cyclic exposures combining UV light and condensing humidity is caused by photolytic and hydrolytic mechanisms causing yellowing and haze formation. Quantitative knowledge of these degradation pathways enable cross-correlation of these lab-based exposures with real-world conditions for service life prediction.

Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). The utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged-Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15-minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.

Real-world performance, durability and reliability of microinverters are critical concerns for microinverter-equipped photovoltaic systems. We conducted a data-driven study of the thermal performance of 24 new microinverters (Enphase M215) connected to 8 different brands of PV modules on dual-axis trackers at the Solar Durability and Lifetime Extension (SDLE) SunFarm at Case Western Reserve University, based on minute by minute power and thermal data from the microinverters and PV modules along with insolation and environmental data from July through October 2013. The analysis shows the strengths of the associations of microinverter temperature with ambient temperature, PV module temperature, irradiance and AC power of the PV systems. The importance of the covariates are rank ordered. A multiple regression model was developed and tested based on stable solar noon-time data, which gives both an overall function that predicts the temperature of microinverters under typical local conditions, and coefficients adjustments reecting refined prediction of the microinverter temperature connected to the 8 brands of PV modules in the study. The model allows for prediction of internal temperature for the Enphase M215 given similar climatic condition and can be expanded to predict microinverter temperature in fixed-rack and roof-top PV systems. This study is foundational in that similar models built on later stage data in the life of a device could reveal potential influencing factors in performance degradation.

The interband optical properties of polystyrene in the vacuum ultraviolet (VUV) region have been investigated using combined spectroscopic ellipsometry and VUV spectroscopy. Over the range 1.5?32 eV, the optical properties exhibit electronic transitions we assign to three groupings, E1, E2, and E3, corresponding to a hierarchy of interband transitions of aromatic (? ? ?*), non-bonding (n ? ?*, n ? ?*), and saturated (? ? ?*) orbitals. In polystyrene there are strong features in the interband transitions arising from the side-chain ? bonding of the aromatic ring consisting of a shoulder at 5.8 eV (E1?) and a peak at 6.3 eV (E1), and from the ? bonding of the C?C backbone at 12 eV (E3?) and 17.1 eV (E3). These E3 transitions have characteristic critical point line shapes associated with one-dimensionally delocalized electron states in the polymer backbone. A small shoulder at 9.9 eV (E2) is associated with excitations possibly from residual monomer or impurities. Knowledge of the valence electronic excitations of a material provides the necessary optical properties to calculate the van der Waals?London dispersion interactions using Lifshitz quantum electrodynamics theory and full spectral optical properties. Hamaker constants and the van der Waals?London dispersion component of the surface free energy for polystyrene were determined. These Lifshitz results were compared to the total surface free energy of polystyrene, polarity, and dispersive component of the surface free energy as determined from contact angle measurements with two liquids, and with literature values. The Lifshitz approach, using full spectral Hamaker constants, is a more direct determination of the van der Waals?London dispersion component of the surface free energy of polystyrene than other methods. [ABSTRACT FROM AUTHOR]

Optical immersion lithography using fluids with refractive indices greater than that of water (1.436) can enable numerical apertures of 1.55 or above for printing sub-45-nmlines. Two second-generation immersion fluid candidates, IF132 and IF169, both have indices above 1.64 and have been optimized to absorb less than 0.1 cm−1at 193.4 nm. These fluids, although meeting the requirements of index and absorption, must also be compatible with current resists and processes to image the required fine line patterns. Results of fluid-resist interactions, with water and high-index fluids on four commercial resists, are shown. Photoacid generator (PAG) leaching measurements reveal much less leaching into both high-index fluids than into water, and in two water-immersion dedicated resists, no leaching is detected with the high-index immersion fluids. Little resist thickness change and swelling is detected by a quartz crystal microbalance (QCM) on contact with the fluids. Resist profile and line height changes due to pre- and postexposure fluid contact varies from one resist to the next, but overall the changes are minimal. Misting defects from high-index fluid-resist contact show lower counts than for water, and imaging on an immersion interference printer produces 36-nmhalf-pitch lines. We find no serious impediments to the use of high-index liquids based on these results. [ABSTRACT FROM AUTHOR]

We have developed a number of second-generation high-index candidate immersion fluids that exceed the 1.6 refractive index requirement for immersion lithography at 193 nmto replace the water used in first-generation immersion systems. To understand the behavior and performance of different fluid classes, we use spectral index measurements, based on the prism minimum deviation method, to characterize the index dispersion. In addition to fluid absorbance and index requirements, the temperature coefficient of the refractive index is a key parameter. We have used a laser-based Hilger–Chance refractometer system to determine the thermo-optic coefficient (dndT)by measuring the index change versus temperature at two different laser wavelengths, 632.8 and 193.4 nm. Also, we determined the batch-to-batch (within a 6-monthperiod), before and after irradiation (at 193.4 nm), before and after air exposure, and before and after resist exposure (image printing test) variations of index and n. The optical properties of these second-generation immersion fluids mostly compare favorably to water; the ratio of index of refraction at 193.4 nmis 1.6441.437, the dispersion from d-line (n193-d)is 0.160 versus 0.103 and dndTat 193.4 is −550×10−6Kvs. −93×10−6K, respectively. [ABSTRACT FROM AUTHOR]

The optical properties of three grades of Teflon® AF—AF1300, AF1601, and AF2400—were investigated using a J.A. Woollam VUV-VASE spectroscopic ellipsometry system. The refractive indices for each grade were obtained from multiple measurements with different film thicknesses on Si substrates. The absorbances of Teflon® AF films were determined by measuring the transmission intensity of Teflon® AF films on CaF2 substrates. In addition to the refractive index and absorbance per cm (base 10), the extinction coefficient (k), and absorption coefficient (α) per cm (base e), Urbach parameters of absorption edge position and edge width, and two-pole Sellmeier parameters were determined for the three grades of Teflon® AF. We found that the optical properties of the three grades of Teflon® AF varied systematically with the AF TFE/PDD composition. The indices of refraction, extinction coefficient (k), absorption coefficient (α), and absorbance (A) increased, as did the TFE content, while the PDD content decreased. In addition, the Urbach edge position moved to a longer wavelength, and the Urbach edge width became wider. [ABSTRACT FROM AUTHOR]

Commercial buildings account for one third of the total electricity consumption in the United States and a significant amount of this energy is wasted. Therefore, there is a need for "virtual" energy audits, to identify energy inefficiencies and their associated savings opportunities using methods that can be non-intrusive and automated for application to large populations of buildings. Here we demonstrate virtual energy audits applied to large populations of buildings' time-series smart-meter data using a systematic approach and a fully automated Building Energy Analytics (BEA) Pipeline that unifies, cleans, stores and analyzes building energy datasets in a non-relational data warehouse for efficient insights and results. This BEA pipeline is based on a custom compute job scheduler for a high performance computing cluster to enable parallel processing of Slurm jobs. Within the analytics pipeline, we introduced a data qualification tool that enhances data quality by fixing common errors, while also detecting abnormalities in a building's daily operation using hierarchical clustering. We analyze the HVAC scheduling of a population of 816 buildings, using this analytics pipeline, as part of a cross-sectional study. With our approach, this sample of 816 buildings is improved in data quality and is efficiently analyzed in 34 minutes, which is 85 times faster than the time taken by a sequential processing. The analytical results for the HVAC operational hours of these buildings show that among 10 building use types, food sales buildings with 17.75 hours of daily HVAC cooling operation are decent targets for HVAC savings. Overall, this analytics pipeline enables the identification of statistically significant results from population based studies of large numbers of building energy time-series datasets with robust results. These types of BEA studies can explore numerous factors impacting building energy efficiency and virtual building energy audits. This approach enables a new generation of data-driven buildings energy analysis at scale.

Photolytic and hydrolytic degradation of poly(ethylene-terephthalate) (PET) polymers with different stabilizers were performed under multiple accelerated weathering exposures and changes in the polymers were monitored by various evaluation techniques. Yellowing was caused by photolytic degradation and haze formation was induced by combined effects of photolytic and hydrolytic degradation. The formation of light absorbing chromophores and bleaching of the UV stabilizer additive were recorded through optical spectroscopy. Chain scission and crystallization were found to be common mechanisms under both photolytic and hydrolytic conditions, based on the infrared absorption of the carbonyl (C = O) band and the trans ethylene glycol unit, respectively. The degradation mechanisms determined from these evaluations were then used to construct a set of degradation pathway network models using the network structural equation modeling (netSEM) approach. This method captured the temporal evolution of degradation by assessing statistically significant relationships between applied stressors, mechanistic variables, and performance level responses. Quantitative pathway equations provided the contributions from mechanistic variables to the response changes.