The latest NE by Samuel D Stranks team at University of Cambridge The impact of interface quality and nanoscale performance disorder on perovskite solar cell stability

The performance and stability of perovskite solar cells are influenced by nanoscale variations in their structure, composition, and photophysical properties. While performance can be improved through strategies such as compositional engineering, contact engineering, and surface passivation, the specific effects of these strategies on cell performance and stability at different scales remain unclear. To fully understand the performance and degradation of halide perovskites, developing microscopy techniques capable of measuring intact devices under operational conditions is crucial.

To address these challenges, Samuel D. Stranks' team employed a multimodal in situ microscopy toolkit to measure spatially correlated nanoscale charge transport losses, recombination losses, and chemical composition. The study found that devices with the highest macroscopic performance exhibited the lowest initial spatial heterogeneity in performance, a key missing link in traditional microscopy. Interface engineering is crucial for achieving robust devices. Once the interface is stabilized, compositional engineering to homogenize charge extraction and minimize local variations in power conversion efficiency is crucial for improving performance and stability.

The study found that perovskites can tolerate chemical spatial disorder, but not spatial disorder in charge extraction. Compositional engineering can minimize variations in charge extraction and local power conversion efficiency, thereby improving performance and stability.

Fig. 1 | Device operando microscopy reveals DCDH solar cell performance is tolerant to even dramatic spatial optoelectronic and chemical heterogeneity. a, Schematic of perovskite solar cell under bias being illuminated either by a white light-emitting diode (LED) array for the luminescence measurements or monochromatic hard X-rays for the nXRF measurements. Note that the optical and X-ray measurements are not simultaneously acquired. b, Hyperspectral PL spectra (at VOC and VMPP) of regions marked in e. c, Comparison of electrical JV curve (red, red arrow points to corresponding y axis) and area-averaged optical JV curve (black, black arrow points to corresponding y axis) of DCDH solar cell. Grey shaded areas show the distribution of JV curves across the map. d, Optical JV curves of the marked regions in e. e, PL centre of mass (COM) energy plot of a region of a DCDH solar cell at VOC. f, Br:Pb map from the marked region in b extracted by nXRF. g, Internal VOC (Δµ). h,i, Optical short circuit current extraction efficiency (ΦPL(0 V)) (h) and optical PCE (VMPP✕ΦPL(VMPP)) of the same region as shown in e (i).

Fig. 2 | Local reductions in performance are evident in microscopic JV curves of DCDH perovskite solar cells after extended operation. a,b, Optical PCE maps of the same area of a fresh (a) and operated (b) DCDH solar cell after 100 h at VOC, 65 °C and 1 sun illumination. c,d, show Br:Pb ratio maps extracted from nXRF from the two regions marked in b after the 100 h of operation. e,f, Optical JV curves before (e) and after (f) ageing from the points marked in a and b. Solid lines are reverse scans, dashed lines are forward scans. g,h, PL spectra from the same marked areas before (g) and after (h) ageing.

Fig. 3 | Multimodal microscopy on DCTH perovskite solar cells reveals reduced device stability and increased microscopic phase segregation compared to DCDH analogues.a,b, Optical PCE maps of the same area of a fresh (a) and operated (b) DCTH solar cell after 100 h at VOC, 65 °C and 1 sun illumination. c,d, Br:Pb ratio (c) and PL centre of mass energy maps (d) extracted from the region marked in b after the 100 h of operation. e,f, Optical JV curves (e) before and after (f) operational stress from the points marked in a and b. Solid lines are reverse scans, dashed lines are forward scans. g, Normalized Br:Pb ratio histograms for a pristine sample (orange) and the marked region of the operated (red) sample. h,i, PL spectra extracted from the same marked areas before (h) and after (i) ageing. j, Optical PCE histogram for this DCTH solar cell before (orange) and after (red) operation. Arrows in g and j are guides to the eye from fresh to operated.

Fig. 4 | Interfacial chemistry and spatial PCE disorder predict performance and stability of mixed-cation, mixed-halide perovskite solar cells.a–c, Optical PCE maps of pristine control 2PACz/TCTH (a), Me-4PACz/TCTH (b) and 2PACz/TCTH + PI (c) passivation devices. d, Representative JV curves of the pristine interface-modified devices mapped in panels a–c. e, Optical PCE distributions and corresponding Gaussian fits of the interface-modified devices. The numbers over the distributions represent the FWHM of the distribution. f, Initial optical PCE disorder (FWHM of PCE distribution) versus initial PCE (mean of PCE distribution) for a range of perovskite devices, where each point is an individual device. Linear regression shows a Pearson’s r value of −0.71,Spearman’s r value of −0.77 and a P value of «0.01 (two-sided tests). Shaded regions represent the 95% confidence interval of the linear fit from a Student’s t distribution percent points function (n = 75 devices). g, JV curves after operational stress of the representative devices shown in d. h, Scatter plot of initial PCE disorder versus PCE loss (%) during operation for the perovskite composition series on 2PACz. (Device numbers for comparison are DCDH = 4, DCTH = 4, TCTH = 8). i, Scatter plot of initial PCE disorder versus PCE loss (%)during operation for the interfacial modification series. (Device numbers for comparison are 2PACz/TCTH = 11, MeO-2PACz = 4, Me-4PACz/TCTH = 14,2PACz/TCTH + PI = 8, 2PACz/TCTH+LiF=4). Solid markers are the mean of a given device type, semi-transparent markers are individual devices. Error bars in h and i are standard deviations.


本文来源：DOI: 10.1038/s41560-024-01660-1

https://doi.org/10.1038/s41560-024-01660-1