Resolution of spatial and energy distributions of trap states in metal halide perovskite solar cells


DLCP technique. (A) Diagram of the bending of p-type semiconductor zones with deep trap states in the n + -p junction. X denotes the distance from the connecting barrier, where the traps can dynamically change their charge states with a variable bias dV. dX denotes the differential change of X with respect to dV. Ew is the demarcation energy determined by Ew = kTln (w0 / w) (where k is the Boltzmann constant). EC, EV, and EF indicate the edge of the conduction band, the edge of the valence band, and the Fermi level, respectively. (B) Dependence of carrier density on the profiling distance of a solar cell Si at various AC frequencies measured by DLCP. The inset shows a diagram of the structure of the device. (C) Scheme for the synthesis of a bulk MAPbI3 single crystal in a solution in the open air. (D) Synthesis scheme of a two-layer thin MAPbI3 single crystal using the spatial growth method. (E) Trap density versus profiling distance of a MAPbI3 single crystal measured using DLCP. The inset shows the structure of the device. (F) Dependence of the trap density on the profiling distance of a two-layer thin MAPbI3 single crystal. The inset shows the SEM image of the cross section of a two-layer thin MAPbI3 single crystal. The thickness of the upper and lower single crystals was 18 and 35 mm, respectively. Courtesy: Science, doi: 10.1126 / science.aba0893.

In a new report published on The science, Zhenyi Ni and a research group in the field of applied physical sciences, mechanical engineering and materials science, computer engineering and energy in the United States, profiled the spatial and energy distribution of states of traps or defects in metal halide perovskite monocrystalline polycrystalline solar cells. Researchers attribute photovoltaic characteristics metal halide perovskites (MGP) to their high optical absorption coefficient, carrier mobility, long charge diffusion length and low energy Urbach (representing a mess in the system). Theoretical studies have demonstrated the possibility of forming deep charge traps on the surface of the material due to the low formation energy, structural defects and perovskite grain boundaries in order to direct the development of passivation methods (loss of chemical reactivity) in perovskite solar panelsThe states of the charge trap play an important role in the decomposition of perovskite solar panels and other devices, Understanding the distribution of trap states in their space and energy can clarify the effect of charge traps (defects) on charge transfer in perovskite materials and devices for their optimal operation.


Scientists widely used thermal spectroscopy (TAS) and thermally stimulated current (TSC) methods for measuring volatile traps density states (tDOS) in perovskite solar cells, Methods can typically reach trap depths approaching 0.55 eV – deep enough to make cellsto detect deeper trap states Researchers have used methods such as: surface photoelectric spectroscopy and the photocurrent of subband breaking. However, most methods cannot be applied to already equipped solar devices for measuring the spatial distribution of trap states. In this work, Ni et al. Demonstrated Drive Level Capacitance Profiling (DLCP) – Alternative capacitybased on the method to provide well-characterized spatial distributions of the carrier and trap density in perovskites. Scientists plotted the spatial and energy distribution of trap states in perovskite single crystals and thin polycrystalline films for direct comparison.

Resolution of spatial and energy distributions of trap states in metal halide perovskite solar cells

Change in junction capacitance with amplitude of AC bias for a Si solar cell. Change in the transition capacitance (C) of the solar cell Si with respect to the amplitude of the AC bias (δV) at various DC biases measured at the frequencies of the alternating current (a) 1 kHz and (b) 100 kHz. Courtesy: Science, doi: 10.1126 / science.aba0893.

The team developed the DLCP method (capacitance profiling at the drive level) to study the spatial distribution of defects in the band gap of amorphous and polycrystalline semiconductors, such as amorphous silicon, The method can directly determine the density of carriers in order to include both the density of free carriers and the density of traps in the band gap of semiconductors, as well as their distribution in space and energy. They estimated trap density by subtracting the estimated free carrier density measured at high frequencies of alternating current (AC) from the total carrier density measured at low frequencies of alternating current. The technique allowed the team to obtain the energy distribution of trap states. To confirm the accuracy of the carrier density measured using the DLCP method, scientists performed DLCP measurements on a silicon solar cell fabricated on a p-type Si (p-Si) crystal wafer with an n-type diffusion layer of Si (n).+) upstairs. The measurement corresponded to the dopant concentration in the p-Si wafer obtained by measuring the conductivity to confirm the accuracy of the carrier density measured using DLCP.

To profile the density of carriers and traps using DLCP, researchers examined through the device from one electrode to the counter electrode to understand the location of the compounds in a flat-structured perovskite solar panelsThe team conducted several experiments and found that perovskite cells usually retain+– Transition between device components. To determine the depth of the profile corresponding to the depth of the physical material, Ni et al. built a device containing a double layer methylammonium lead iodide (MAPbI3) thin crystals to find charge traps. When they profiled the density of traps of the designed device, they received a peak in the density of traps at a profiling distance of 18 μm.

Resolution of spatial and energy distributions of trap states in metal halide perovskite solar cells

Spatial distributions of trap states in a thin MAPbI3 single crystal. (A) Dependence of carrier density on the profiling distance of a 39 mm thick MAPbI3 single crystal at various AC frequencies measured using DLCP. (B) Dependence of the trap density on the profiling distance of a thin MAPbI3 single crystal measured at an ac frequency of 10 kHz. The carrier density, measured at 500 kHz, is considered as free carriers. (C) Schemes of a thin MAPbI3 single crystal on a PTAA / ITO substrate before mechanical polishing, after mechanical polishing, and after treatment with oxysal ((C8-NH3) 2SO4). (D) Capture density near the connecting barrier of a thin MAPbI3 single crystal before mechanical polishing, after mechanical polishing, and after treatment with oxysal. Courtesy: Science, doi: 10.1126 / science.aba0893.

The group then examined the distribution of traps in perovskite-based single-crystal solar cells and observed the highest energy conversion efficiency (PCE) from first registered MAPbI3 single crystal the solar battery should be only 17.9 percent; much lower than polycrystalline solar cells. They were unaware of the underlying mechanism that limited carrier diffusion in thin crystals, and performed DLCP measurements to investigate the relationship between trap density and trap distributions using synthetic crystal methods. The team observed the spatial distribution of carrier density throughout a typical MAPbI3 thin single crystal, which they synthesized using the spatial growth method at different frequencies and noted an increase in the carrier density with a decrease in the frequency of the alternating current, which indicates the presence of charge traps in MAPbI3 thin single crystal.

Resolution of spatial and energy distributions of trap states in metal halide perovskite solar cells

Dependent on the thickness of the density distribution of traps in thin MAPbI3 single crystals. (A) Dependence of trap density on the profiling distances of thin MAPbI3 single crystals with various crystal thicknesses measured at an ac frequency of 10 kHz. The location of the MAPbI3 / C60 interface for each chip is aligned for comparison. A black dashed arrow indicates a trend in the minimum density of the NT min trap in MAPbI3 single crystals of various thicknesses. (B) Dependence of NT min in a thin MAPbI3 single crystal on crystal thickness. The horizontal dashed line shows the minimum value of NT in the MAPbI3 single crystal. The inset shows a diagram of the laminar flow of a precursor solution between two PTAA / ITO glasses during crystal growth. The arrows indicate the direction of the laminar flow of the precursor solution, and the length of the arrow indicates the speed of the laminar flow. (C) tDOS of a thin MAPbI3 single crystal measured by the TAS method. The thickness of the thin MAPbI3 single crystal was 39 mm. (D) Spatial and energy mapping of the density of states of traps in a thin MAPbI3 single crystal, measured using DLCP. Courtesy: Science, doi: 10.1126 / science.aba0893.

To understand the origin of the density of deep traps at the perovskite interface, the team used high resolution transmission electron microscopy and studied perovskite samples of various compositions. They compared the density distributions of traps between perovskite single crystals and polycrystalline thin films with different compositions. Trap density distributions for thin single crystals were several orders of magnitude lower than in polycrystalline thin films. The results showed the importance of adequate surface modification processes to reduce the density of traps in perovskite single crystals at the polycrystalline thin film interface to increase the productivity of the device. The results indicate an important direction for increasing the productivity of solar panels based on perovskite and other electronic devices by reducing the density of traps at the interface.

Resolution of spatial and energy distributions of trap states in metal halide perovskite solar cells

Spatial and energy distribution of trap states in thin perovskite films. (A) J-V curve of thin-film solar cells Cs0.05FA0.70MA0.25PbI3. The inset shows the structure of the device. (B) Dependence of the trap density on the profiling distance for a thin perovskite film in a solar cell, measured at an AC frequency of 10 kHz. (C) tDOS thin-film perovskite solar cell measured by the TAS method. (D) Spatial and energy mapping of the density of states of traps of a thin film of perovskite in a solar cell, measured using DLCP. (E) Cross-sectional HR-TEM image of a perovskite stack and PTAA. Dotted squares indicate the regions in which fast Fourier transforms of the lattices were performed, with the white and yellow axis of the zones denoting (1 -1 -1) and (2 1 0), respectively. Red lines indicate the orientation of the faces. (F) Fast Fourier transforms of the domains indicated in (E). (G) Измеренные и смоделированные J-V кривые плоско структурированных солнечных элементов на основе поликристаллических тонких пленок MAPbI3. Тонкие (монокристаллические) объемные и интерфейсные плотности ловушек были приняты для моделирования. (H) Зависимость PCE тонкопленочного солнечного элемента MAPbI3 от объемных и интерфейсных плотностей ловушек. Пунктирные линии обозначают контурные линии определенных значений PCE, которые отмечены. Предоставлено: Science, doi: 10.1126 / science.aba0893.

Таким образом, Zhenyi Ni и коллеги использовали имитатор емкости солнечного элемента для моделирования тонкопленочных и монокристаллических перовскита солнечные элементы с различной плотностью ловушек. Range ловушки измеренные с помощью DLCP измерения были достаточно глубокими, чтобы предсказать поведение солнечных элементов и уменьшить объемную плотность улавливания материалов и повысить эффективность преобразования энергии (PCE) до 20 процентов. Уменьшая плотность интерфейса, они увеличили значения PCE ближе к PCE, наблюдаемому для тонкопленочного солнечного элемента без ловушек. Данные, смоделированные для монокристаллических солнечных элементов хорошо согласился с экспериментами, показывая, что PCE монокристаллического солнечного элемента может быть дополнительно улучшено на интерфейсе устройства для сбора большего количества солнечного света.


Инвертированные перовскитные солнечные элементы с КПД преобразования энергии 22,3%


Дополнительная информация:
Zhenyi Ni et al. Разрешение пространственных и энергетических распределений состояний ловушек в металлогалогенных перовскитных солнечных элементах, The science (2020). DOI: 10.1126 / science.aba0893

Джеймс М. Болл и соавт. Дефекты в перовскит-галогенидах и их влияние на солнечные элементы, Энергия природы (2016 г.). DOI: 10.1038 / nenergy.2016.149

Ци Цзян и соавт. Поверхностная пассивация пленки перовскита для эффективных солнечных элементов, Фотоника природы (2019). DOI: 10.1038 / s41566-019-0398-2

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                                                 Разрешение пространственного и энергетического распределения состояний ловушек в металлогалогенных перовскитных солнечных элементах (2020 г., 30 марта)
retrieved March 30, 2020
                                                 с https://phys.org/news/2020-03-spatial-energetic-states-metal-halide.html

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