Performance-limiting nanoscale trap clusters at grain junctions in halide perovskites

Abstract

Halide perovskite materials have promising performance characteristics for low-cost optoelectronic applications. Photovoltaic devices fabricated from perovskite absorbers have reached power conversion efficiencies above 25 per cent in single-junction devices and 28 per cent in tandem devices1,2. This strong performance (albeit below the practical limits of about 30 per cent and 35 per cent, respectively3) is surprising in thin films processed from solution at low-temperature, a method that generally produces abundant crystalline defects4. Although point defects often induce only shallow electronic states in the perovskite bandgap that do not affect performance5, perovskite devices still have many states deep within the bandgap that trap charge carriers and cause them to recombine non-radiatively. These deep trap states thus induce local variations in photoluminescence and limit the device performance6. The origin and distribution of these trap states are unknown, but they have been associated with light-induced halide segregation in mixed-halide perovskite compositions7 and with local strain8, both of which make devices less stable9. Here we use photoemission electron microscopy to image the trap distribution in state-of-the-art halide perovskite films. Instead of a relatively uniform distribution within regions of poor photoluminescence efficiency, we observe discrete, nanoscale trap clusters. By correlating microscopy measurements with scanning electron analytical techniques, we find that these trap clusters appear at the interfaces between crystallographically and compositionally distinct entities. Finally, by generating time-resolved photoemission sequences of the photo-excited carrier trapping process10,11, we reveal a hole-trapping character with the kinetics limited by diffusion of holes to the local trap clusters. Our approach shows that managing structure and composition on the nanoscale will be essential for optimal performance of halide perovskite devices.

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Fig. 1: Photoemission electron microscopy revealing the spatial distribution of trap sites leading to non-radiative power losses.
Fig. 2: Probing the composition of grains associated with nanoscale trap clusters.
Fig. 3: High-resolution diffraction and compositional properties of nanoscale trap-rich heterojunctions.
Fig. 4: Nanoscale photo-excited carrier trapping dynamics.

Data availability

The data that support the findings of this study are available at https://doi.org/10.17863/CAM.48273 or from the corresponding authors upon request.

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Acknowledgements

T.A.S.D. acknowledges support of a National University of Ireland (NUI) Travelling Studentship. The work received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (HYPERION, grant agreement no. 756962). A.J.W., S.K., V.P., C.E.P., E L.W., J.M., M.K.L.M. and K.M.D. acknowledge that this work was supported by the Femtosecond Spectroscopy Unit of the Okinawa Institute of Science and Technology Graduate University. The authors acknowledge the support for this work from the Imaging Section and Engineering Support Section of the Okinawa Institute of Science and Technology Graduate University. This work was supported by JSPS KAKENHI Grant Number JP19K05637. S.M. acknowledges funding from the Summer Fellowship Programme of the Japan Society for the Promotion of Science and from a UK Engineering and Physical Sciences Research Council (EPSRC) studentship. S.D.S. acknowledges the Royal Society and Tata Group (UF150033). We thank Diamond Light Source and beamline scientists J. Parker, P. Quinn, M. Danaie and T. Slater for access and support in use of beamline I14 (proposal nos. sp19023-1 and sp19023-2) and the electron Physical Science Imaging Centre (ePSIC instrument E02 and proposal nos. EM19793-1, EM19793-2) that contributed to the results presented here. F.U.K. thanks the Jardine Foundation and Cambridge Trust for a doctoral scholarship. P.A.M. thanks the EPSRC for financial support under grant no. EP/R008779/1. E.M.T. acknowledges funding from the EPSRC under grant reference EP/R023980/1 and has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 841265. S.D.S. and E.M.T. acknowledge funding from the EPSRC grant "Centre for Advanced Materials for Integrated Energy Systems (CAM-IES)" EP/P007767/1 and Cambridge Royce facilities grant EP/P024947/1. M.A. acknowledges funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie actions grant agreement no. 841386. Y.-H.C. acknowledges support of a Cambridge Trust-Taiwan scholarship. M.A.-J. thanks Cambridge Materials Limited, Wolfson College, University of Cambridge, and EPSRC (grant no. EP/M005143/1) for their funding and technical support. Z.A.-G. acknowledges funding from a Winton Studentship and an ICON Studentship from the Lloyd’s Register Foundation. This work was supported by a National Research Foundation of Korea grant funded by the Korean government (MSIT) (no. 2018R1C1B6008728).

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Contributions

T.A.S.D. collected, analysed and interpreted SED, XRD, SEM, HAADF and STEM-EDX data, prepared samples and performed microscopy correlations. A.J.W. collected, analysed and interpreted PEEM and TR-PEEM data, and collected confocal PL data. S.M. prepared samples, collected confocal and hyperspectral PL data, collected optical absorption data, analysed data and assisted in interpretation of data. D.N.J. collected, analysed and interpreted SED data. V.P. built the laser set-up for the TR-PEEM measurements. E.M.T. collected and analysed KPFM data. S.K. collected, analysed and interpreted PEEM and AFM data. F.U.K. collected and analysed STEM-HAADF images and STEM-EDX data. M.A. collected hyperspectral PL data. M.A-J. prepared samples and performed PDS measurements. Z.A-G. prepared samples. Y.-H.C. prepared and tested devices and collected SEM data. C.E.P. and E L.W. assisted in interpretation of data. J.M. assisted in interpretation of data and built the laser set-up for the TR-PEEM measurements. M.K.L.M. assisted in analysis and interpretation of data. G.D. and C.D. supervised F.U.K.. P.A.M. supervised D.N.J. and aided in interpretation of SED data. K.M.D. supervised A.J.W, V.P., S.K., E L.W., C.E.P., J.M. and M.K.L.M. S.D.S supervised T.A.S.D., S.M., E.M.T., Y.-H.C. and M.A. A.W., J.-S.P. and Y.-K.J. provided input on data interpretations. S.D.S. and K.M.D. conceived and designed the work. All authors contributed to writing the manuscript.

Corresponding authors

Correspondence to Keshav M. Dani or Samuel D. Stranks.

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S.D.S. is a co-founder of Swift Solar, Inc.

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Extended data figures and tables

Extended Data Fig. 1 Optical spectroscopy of mixed-cation films.

a, b, PL spectra with 532-nm excitation of (a) (Cs0.05FA0.78MA0.17)Pb(I0.83Br0.17)3 and (b) (Cs0.05FA0.78MA0.17)PbI3 films. c, d, Photothermal deflection spectroscopy (PDS) of (c) (Cs0.05FA0.78MA0.17)Pb(I0.83Br0.17)3 and (d) (Cs0.05FA0.78MA0.17)PbI3 films, showing a negligible sub-bandgap absorption.

Extended Data Fig. 2 Normalized PL maps and key device performance metrics.

PL maps were acquired using a pulsed 404-nm laser (repetition rate 2 MHz), focused through an objective lens (100× magnification, 0.9 NA) with an average power of 1.3 nW (~6 suns). a, PL map of a (Cs0.05FA0.78MA0.17)Pb(I0.83Br0.17)3 cation film deposited on a SiN window. b, PL map of a (Cs0.05FA0.78MA0.17)Pb(I0.83Br0.17)3 film in a full device stack (ITO/PTAA/PFN-P2/perovskite/PCBM/BCP/Ag). Both PL maps exhibit similar spatial variations in luminescent properties. c, Top-view SEM image of film deposited on SiN. d, Top-view SEM image of film deposited on ITO showing similar morphology and grain size to c. e, Performance metrics of a solar cell fabricated from the same material sample batch as ad. FF, fill factor; Jsc, short-circuit current density; PCE, power conversion efficiency; PSK, perovskite; Voc, open-circuit voltage.

Extended Data Fig. 3 Control experiments for PEEM measurements under strong and extended UV exposure (~7 h of 100 nJ cm−2 per pulse, ~10 kJ cm−2 total dose) on (Cs0.05FA0.78MA0.17)Pb(I0.83Br0.17)3 samples.

a, Optical absorption on freshly made samples (black squares), samples shipped under N2 (red dots) and shipped samples after extensive UV exposure in PEEM (blue triangles). b, Optical reflectivity image of an area partially exposed to UV in PEEM (red dashed oval, partly shown). c, Normalized PL emission of fresh, shipped and UV-exposed samples. Inset, PL intensity from unexposed (red dots) and UV-exposed (blue squares). d, PL map of the location in b, showing a slight reduction in PL intensity in the UV-exposed region. e, f, PEEM images of the traps (4.65-eV probe) at the beginning (e) and end (f) of the 7-h UV exposure. g, Intensity histograms for the images in e and f.

Extended Data Fig. 4 Control measurements under normal measurement conditions.

a, XRD measurements averaged over ~30 × 30 μm2 on freshly made (Cs0.05FA0.78MA0.17)Pb(I0.83Br0.17)3 samples (black line) and samples after shipping and PEEM imaging (blue line). b, Five repeated TR-PEEM measurements (1.55-eV pump, 4.65-eV probe) on a (Cs0.05FA0.78MA0.17)PbI3 sample taken in sequence and the corresponding real time of exposure shown on the bottom x-axis. The signal is averaged over the 10-μm FOV. We see an increase of ~4% in the trap density (for example, the flat plateaus at negative time delays, represented by the dashed grey lines) over the 80 min of measurement time.

Extended Data Fig. 5 Trap size and distance distributions.

a, Normalized PEEM image of the traps for the Cs0.05FA0.78MA0.17Pb(I0.83Br0.17)3 sample. b, Size distribution of the traps in image a. c, The distribution of distances between nearest neighbouring traps in a, resulting in a mean neighbour distance of 166 ± 95 nm (± standard deviation). d, Normalized PEEM image of traps in the Cs0.05FA0.78MA0.17PbI3 sample. e, Size distribution of the traps in image d. f, The distribution of distances between nearest neighbouring traps in d, resulting in a mean neighbour distance of 250 ± 90 nm (± standard deviation). Note that images a and d are on a logarithmic intensity scale.

Extended Data Fig. 6 Energy-resolved PEEM images and selected-area photoemission spectra.

ac, Energy-resolved PEEM images of Cs0.05FA0.78MA0.17Pb(I0.83Br0.17)3 at E − EF = −2.0 eV, −1.5 eV and −1.0 eV, respectively. d, The extracted photoemission spectra from the regions circled in red (away from a trap) and blue (at trap sites) in ac. eg, Energy-resolved PEEM images of a Cs0.05FA0.78MA0.17PbI3 sample at E − EF = −1.8 eV, −1.5 eV and −1.0 eV, respectively. h, The extracted photoemission spectra from the blue and red circled regions shown in eg.

Extended Data Fig. 7 KPFM–PEEM intensity correlation and PL–PEEM intensity correlation.

a, PEEM map of a Cs0.05FA0.78MA0.17Pb(I0.83Br0.17)3 film. b, KPFM map of the same region as a, revealing dark regions with CPD deviating from the surrounding bulk. c, Overlay of PEEM (blue) and KPFM (grey), illustrating the strong correlation between the location of the PEEM spots and the KPFM features. d, Statistically significant negative correlation between the CPD and the PEEM intensity (Pearson’s correlation coefficient −0.58, P-value <0.001). The difference in CPD observed between the regions at a trap site, and away from a trap site, is similar to the energy resolution of our PEEM set-up (~150–200 meV). e, PL–PEEM pixel-by-pixel moving average intensity correlation of Fig. 1c. This reproduces the correlation behaviour seen spatially, where high-intensity PL only occurs at pixels with low PEEM intensity, and high-intensity PEEM pixels only show low PL intensity.

Extended Data Fig. 8 Extended structural and compositional characterization of a Cs0.05FA0.78MA0.17Pb(I0.83Br0.17)3 thin film.

a, Pb Lα peak intensity map obtained from STEM-EDX measurements. b, Peak intensity map of the ratio Br Kα:Pb Lα for the same region as a. c, Peak intensity map of the ratio I Lα:Pb Lα. All maps are normalized between 0 and 1 by dividing by the maximum value extracted from the respective maps of peak intensity ratio. d, PCA scree plot of the parent bulk region indicated in inset to d. Components are plotted in order of decreasing variance and the knee point is illustrated by a vertical line. Red triangles represent high-variance components, blue circles low-variance components. e, Mean diffraction pattern extracted from the grain in Fig. 3c revealed by the three-factor non-negative matrix factorization (NMF) of the region indicated in d inset. Vector lengths marked 1 and 2 are 0.889 A−1 and 0.456 A−1 respectively. These lengths compare closely to the predicted lengths of the (\(40\bar{4}\)) reflection (0.898 A−1) and the (\(02\bar{2}\)) reflection (0.449 A−1) in cubic FAPb(I0.83,Br0.17)3. The calculated angle between 1 and 2 is 60.6°. The predicted angle between the (\(40\bar{4}\)) and (\(02\bar{2}\))reflections in cubic FAPb(I0.83,Br0.17)3 is 60°. Together, these results index the diffraction pattern (Fig. 3c and Extended Data Fig. 8e) of the grain shown in Fig. 3a–d to be near the [111] zone axis of a cubic FAPb(I0.83,Br0.17)3 structure. f, PCA scree plot of the compositionally inhomogeneous region indicated in f inset. Components are plotted in order of decreasing variance, and the knee point is illustrated by a vertical line. Red triangles represent high-variance components, blue circles low-variance components. g, Mean diffraction pattern extracted from the grain in Fig. 3g by the five-factor NMF of the region indicated in f – inset. The diffraction pattern cannot be definitively indexed to either a perovskite or PbI2 structural model.

Extended Data Fig. 9 TR-PEEM data from a Cs0.05FA0.78MA0.17Pb(I0.83Br0.17)3 thin film sample.

a, Percentage change in the PEEM intensity (4.65-eV probe) after pump excitation (1.55 eV), averaged over all trap sites in the ~10 × 10 μm2 field of view. Here, the pump fluence is ~100 μJ cm−2 per pulse, due to the low absorption at this photon energy. The grey line is a fit to a double exponential, yielding the amplitudes and time constants A1 = 2.0 ± 0.3, A2 = 4.2 ± 0.4, τ1 = 1.3 ± 0.5 ps and τ2 = 300 ± 80 ps, where the error is the standard error of the fit . b, Zoom-in of the signal at shorter time delays, where the fast component of the signal can be more easily seen. c, PEEM image of a cluster of trap sites. d, TR-PEEM difference images of c at several pump-probe time delays.

Extended Data Fig. 10 Additional selected PL–PEEM overlays and TR-PEEM images for the Cs0.05FA0.78MA0.17PbI3 sample.

a, c, e, g, i, k, PL–PEEM overlays of selected regions of higher (ae) and lower (gk) PL yield. b, d, f, h, j, l, TR-PEEM difference images for the same locations at several time delays.

Extended Data Fig. 11. Comparison of different fitting functions for analysing trapping kinetics in a Cs0.05FA0.78MA0.17)PbI3 thin film.

a, Single-exponential fit (red dashed line) to the integrated TR-PEEM data, with log-scale inset. b, c, The corresponding single-exponential time constants (b) and amplitudes (c) as a function of the bin intensity I0. d, Double-exponential fit to the data (same as shown in Fig. 4c), with log-scale inset. e, f, The corresponding time constants (e) and amplitudes (f) for the double-exponential fit as a function of the bin intensity. g, Stretched exponential fit to the TR-PEEM data, with log-scale inset. h, i, The corresponding time constants (h) and amplitudes (i) for the stretched exponential fit as a function of bin intensity. For all fit parameters, the error bars represent the standard error from fitting for each intensity bin, where the number of traps measured for each bin is shown by the histogram in Extended Data Fig. 12b. Empty bins or bins with no signal (that is, fit routine fails) are excluded.

Extended Data Fig. 12 Intensity bin analysis of trapping dynamics in a (Cs0.05FA0.78MA0.17)PbI3 thin film.

a, PEEM image of traps, with the Au marker masked out. b, Intensity histogram of the spots identified in a for 50 equally spaced intensity bins. c, TR-PEEM dynamics (spots) and double-exponential fits (grey lines) for four of the intensity bins in b. d, e, Fitted time constants (d) and amplitudes (e) as a function of the binned trap intensity (I0), where the number of traps in each intensity bin is shown by the histogram in b.

Supplementary information

41586_2020_2184_MOESM1_ESM.mp4

TR-PEEM video of the change in photoemission intensity (I(t) – I_0), corresponding to hole trapping, from a region of poor PL yield and several trap clusters.

41586_2020_2184_MOESM2_ESM.mp4

TR-PEEM video of the change in photoemission intensity (I(t) – I_0), from a region of good PL yield and few trap clusters. The low image intensity (same intensity scale as Figures 4d, 4e, and SI Video 1) indicates there is significantly less hole trapping.

Supplementary Video 1 | Animated video of the TR-PEEM images taken at the region of dark PL indicated in Figure 4a

TR-PEEM video of the change in photoemission intensity (I(t) – I_0), corresponding to hole trapping, from a region of poor PL yield and several trap clusters.

Supplementary Video 2 | Animated video of the TR-PEEM images taken at the region of bright PL indicated in Figure 4a.

TR-PEEM video of the change in photoemission intensity (I(t) – I_0), from a region of good PL yield and few trap clusters. The low image intensity (same intensity scale as Figures 4d, 4e, and SI Video 1) indicates there is significantly less hole trapping.

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Doherty, T.A.S., Winchester, A.J., Macpherson, S. et al. Performance-limiting nanoscale trap clusters at grain junctions in halide perovskites. Nature 580, 360–366 (2020). https://doi.org/10.1038/s41586-020-2184-1

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