Hidden polymorphism of FAPbI3 discovered by Raman spectroscopy

Formamidinium lead iodide FAPbI3 can be used in its cubic, black form as a light absorber material in single junction solar cells. It has a band gap 1.5 eV close to the maximum of the Shockley Queisser limit, and reveals a high absorption coefficient. Its high thermal stability up to 320 C has also a downside, which is the instability of the photo active form at room temperature RT . Thus, the black amp; 945; phase transforms at RT with time into a yellow non photo active amp; 948; phase. The black phase can be recovered by annealing of the yellow state. In this work, a polymorphism of the amp; 945; phase at room temperature was found as synthesized amp; 945;i , degraded amp; 945; amp; 948; and thermally recovered amp; 945;rec . They differ in the Raman spectra and PL signal, but not in the XRD patterns. Using temperature dependent Raman spectroscopy, we identified a structural change in the amp; 945;i polymorph at ca. 110 C. Above 110 C, the FAPbI3 structure has undoubtedly cubic Pm[3 with combining macron]m symmetry high temperature phase amp; 945;HT . Below that temperature, the amp; 945;i phase was suggested to have a distorted perovskite structure with Im[3 with combining macron] symmetry. Thermally recovered FAPbI3 amp; 945;rec also demonstrated the structural transition to amp; 945;HT at the same temperature ca. 110 C during its heating. The understanding of hybrid perovskites may bring additional assets in the development of new and stable structure

Blind testing of shoreline evolution models

International audienceBeaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer timescales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for tairua beach, new Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. in general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999-2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014-2017), both approaches showed a decrease in models' capability to predict the shoreline position. this was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models. Quantitative prediction of beach erosion and recovery is essential to planning resilient coastal communities with robust strategies to adapt to erosion hazards. Over the last decades, research efforts to understand and predict shoreline evolution have intensified as coastal erosion is likely to be exacerbated by climatic changes 1-5. The social and economic burden of changes in shoreline position are vast, which has inspired development of a growing variety of models based on different approaches and techniques; yet current models can fail (e.g. predicting erosion in accreting conditions). The challenge for shoreline models is, therefore, to provide reliable, robust and realistic predictions of change, with a reasonable computational cost, applicability to a broad variety of systems, and some quantifiable assessment of the uncertainties

Elucidating the Effect of the Different Buffer Layers on the Thermal Stability of CIGSe Solar Cells

In this contribution, the impact of thermal stress on Cu In,Ga Se 2 CIGSe thin film photovoltaic devices is investigated. The tolerance of such devices to high temperatures is of particular interest for processing transparent conductive oxides TCOs in order to further close the gap to the theoretical efficiency limit and for their potential use as bottom devices in tandem applications in order to overcome the theoretical efficiency limit of single junction solar cells. When CdS buffered CIGSe high efficiency solar cells are subjected to thermal stress, elemental interdiffusion of Na and Cd between the absorber and the window layers as well as chemical reactions at the CIGSe CdS interface result in a degraded power conversion efficiency PCE . Here, we compare the degradation mechanisms of CdS and GaO x buffered CIGSe solar cells under thermal stress. A model explaining the observed degradation behaviors is propose