Wide-bandgap halide perovskites for indoor photovoltaics

LJ acknowledges the funding through the UKRI-Future Leaders Fellowship (MR/T022094/1).Indoor photovoltaics (IPVs) are receiving great research attention recently due to their projected application in the huge technology field of Internet of Things (IoT). Among the various existing photovoltaic technologies such as silicon, Cadmium Telluride (CdTe), Copper Indium Gallium Selenide (CIGS), organic photovoltaics, and halide perovskites, the latter are identified as the most promising for indoor light harvesting. This suitability is mainly due to its composition tuning adaptability to engineer the bandgap to match the indoor light spectrum and exceptional optoelectronic properties. Here, in this review, we are summarizing the state-of-the-art research efforts on halide perovskite-based indoor photovoltaics, the effect of composition tuning, and the selection of various functional layer and device architecture onto their power conversion efficiency. We also highlight some of the challenges to be addressed before these halide perovskite IPVs are commercialized.Publisher PDFPeer reviewe

Organic Radical Polymers for Energy Storage

Organic radical polymers were studied from two aspects – electron/ion transfer during the reduction-oxidation reaction and its application as a battery electrode. The former revealed fundamental reaction mechanisms that govern electrochemical behaviors of the organic radical polymers, while the latter tackled practical issues of electrode dissolution using a synthetic approach. The doping mechanism of nitroxide radical polymer PTMA was quantitatively investigated using quartz crystal microbalance with dissipation monitoring (EQCM-D) during electrochemical processes. Results showed that two doping mechanisms exist – doping by lithium expulsion and anion uptake. The relative dominance of one over the other was controlled by anion type, electrolyte concentration, and timescale. These results could apply in any scenario in which electrolyte is in contact with a non-conjugated redox-active polymer and present a means of quantifying doping effects. A one-step post-synthetic, carbon-compatible crosslinking method was developed to effectively crosslink the PTMA electrode and prevent its dissolution. The highest electrode capacity of 104 mAh g-1 (vs. a theoretical capacity of 111 mAh g-1) was achieved by introducing 1mol% of the crosslinker, whereas the highest capacity retention (99.6%) was obtained with 3mol% crosslinker. Both lithium expulsion and anion uptake were observed in doping, and the dominance was related to crosslinking density (i.e. free volume) in the electrode. This study indicated the importance of forming a network using a minimum amount of crosslinker, persevering radical content during crosslinking, and allowing enough free volume for electrolyte penetration. The electron and ion transfer mechanism of conjugated radical polymers (CRPs) with intentionally varied radical loadings (0, 25 or 100%) was studied to understand their inferior capacity compared to their non-conjugated partners. Results showed that the electron transfer shifted from delocalized electron transfer to localized electron hopping under higher radical loading. The extent of internal charge transfer between the conjugated backbone and the pendant radical was dominated by the radical loading. Doping occurred by exchanging one anion and one solvent molecule for every electron transferred in the CRP with 100% radical loading. For future design, the trade-off between radical loading and electronic conductivity need to be balanced

LO-Net: Deep Real-time Lidar Odometry

We present a novel deep convolutional network pipeline, LO-Net, for real-time lidar odometry estimation. Unlike most existing lidar odometry (LO) estimations that go through individually designed feature selection, feature matching, and pose estimation pipeline, LO-Net can be trained in an end-to-end manner. With a new mask-weighted geometric constraint loss, LO-Net can effectively learn feature representation for LO estimation, and can implicitly exploit the sequential dependencies and dynamics in the data. We also design a scan-to-map module, which uses the geometric and semantic information learned in LO-Net, to improve the estimation accuracy. Experiments on benchmark datasets demonstrate that LO-Net outperforms existing learning based approaches and has similar accuracy with the state-of-the-art geometry-based approach, LOAM

Incorporating Connectivity among Internet Search Data for Enhanced Influenza-like Illness Tracking

Big data collected from the Internet possess great potential to reveal the ever-changing trends in society. In particular, accurate infectious disease tracking with Internet data has grown in popularity, providing invaluable information for public health decision makers and the general public. However, much of the complex connectivity among the Internet search data is not effectively addressed among existing disease tracking frameworks. To this end, we propose ARGO-C (Augmented Regression with Clustered GOogle data), an integrative, statistically principled approach that incorporates the clustering structure of Internet search data to enhance the accuracy and interpretability of disease tracking. Focusing on multi-resolution %ILI (influenza-like illness) tracking, we demonstrate the improved performance and robustness of ARGO-C over benchmark methods at various geographical resolutions. We also highlight the adaptability of ARGO-C to track various diseases in addition to influenza, and to track other social or economic trends

Unemployment Duration and Job-Match Quality in Urban China: The Dynamic Impact of 2008 Labor Contract Law

We assess the unemployment duration-dependent impact of the 2008 Labor Contract Law on job finding probabilities and subsequently job-match quality, including job security, wages and employer-provided social insurance. Dynamic endogeneity underlying individuals’ sequential labor market outcomes is addressed by sharp regression discontinuity and correlated individual unobservables settling into non-parametric joint distribution. The law protracts employment only in the short-term. After job match, the law stabilizes employment and increases wages and insurance coverage, all in the short-term with substantial differences between urban locals and migrant workers and heterogeneity in gender

Unemployment Duration and Job-Match Quality in Urban China: The Dynamic Impact of 2008 Labor Contract Law

We assess the unemployment duration-dependent impact of the 2008 Labor Contract Law on job finding probabilities and subsequently job-match quality, including job security, wages and employer-provided social insurance. Dynamic endogeneity underlying individuals’ sequential labor market outcomes is addressed by sharp regression discontinuity and correlated individual unobservables settling into non-parametric joint distribution. The law protracts employment only in the short-term. After job match, the law stabilizes employment and increases wages and insurance coverage, all in the short-term with substantial differences between urban locals and migrant workers and heterogeneity in gender

Hysteresis in hybrid perovskite indoor photovoltaics

L.K.J. acknowledges funding from UKRI-FLF through grant no MR/T022094/1.Halide perovskite indoor photovoltaics (PV) are a viable solution to autonomously power the billions of sensors in the huge technology field of the Internet of Things. However, there exists a knowledge gap in the hysteresis behaviour of these photovoltaic devices under indoor lighting conditions. The present work is the first experimental study dedicated to exploring the degree of hysteresis in halide perovskite indoor photovoltaic devices by carrying out both transient J-V scan and steady state maximum power point tracking (MPPT) measurements. Dependence of hysteresis on device architecture, selection of electron transporting layers and the composition of the perovskite photoactive layers were investigated. Under indoor illumination, the p-i-n MAPbI3-based devices show consistently high power conversion efficiency (PCE) (stabilized PCE) of greater than 30% and negligible hysteresis behaviour, whereas the n-i-p MAPbI3 devices show poor performance (stabilized PCE ∼ 15%) with pronounced hysteresis effect. Our study also reveals that the n-i-p triple cation perovskite devices are more promising (stabilized PCE ∼ 25%) for indoor PV compared to n-i-p MAPbI3 due to their suppressed ion migration effects. It was observed that the divergence of the PCE values estimated from the J-V scan measurements, and the maximum power point tracking method is higher under indoor illumination compared to 1 Sun, and hence for halide perovskite-based indoor PV, the PCE from the MPPT measurements should be prioritized over the J-V scan measurements. The results from our study suggest the following approaches for maximizing the steady state PCE from halide perovskite indoor PV: (i) select perovskite active layer composition with suppressed ion migration effects (such as Cs-containing triple cation perovskites) and (ii) for the perovskite composition such as MAPbI3, where the ion migration is very active, p-i-n architecture with organic charge transport layers is beneficial over the n-i-p architecture with conventional metal oxides (such as TiO2, SnO2) as charge transport layers. This article is part of the theme issue 'Developing resilient energy systems'.Publisher PDFPeer reviewe