Advances in hole transport materials engineering for stable and efficient perovskite solar cells

TL;DR: In this paper, the role of hole transporting materials (HTMs) in perovskite solar cells (PSCs) is discussed, as well as their role in photovoltaic parameters.

About: This article is published in Nano Energy.The article was published on 2017-04-01 and is currently open access. It has received 335 citations till now.

Summary

1. Introduction

• Various studies have highlighted the complex interactions between climate and aerosol microphysical, chemical and radiative properties, particularly its carbonaceous components (Penner et al., 1992; Liousse et al., 1996; Heintzenberg et al., 1997; Cachier, 1998; Cooke et al., 1999).
• Recently, it has been suggested that, due to complex aerosol absorption/diffusion radiative characteristics and brief atmospheric residence times, reduction policies targetting at aerosol emissions could be more rapidly effective against climate change than greenhouse gases (Jacobson, 2002; Bond and Sun, 2005).
• A few requirements on aerosol modelling emerge from recent papers, basically about size distributions and chemical compo- ∗Corresponding author.
• In these models, such major aerosol outputs as radiative effects, quite sensitive to aerosol size distributions and to aerosol mixing state (internal/external), are poorly evaluated.

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• Evolving size distributions were also introduced for single component aerosols (dust in Tegen and Lacis, 1996, sulfates in Chin et al., 1996) as well as for multi-component ones (inorganic species (sulfates, nitrates, ammonia) in Adams et al. (1999), Jacobson (2001a) and Adams and Seinfeld (2002), inorganics and dust in Rodriguez and Dabdub (2004) and Spracklen et al. (2005)).
• Here such an approach has been extended to the global scale.
• Though the model also provides other aerosol components, focus is here on the concentrations of carbonaceous aerosol components BC and OC.
• Also, as a prerequisite to these tests, a detailed description of new BC and OCp emission inventories (Liousse et al., 2004; Junker and Liousse, 2006) is presented and with special interest on Europe where more and more stringent anthropic emission controls, mainly on fossil fuels, are applied, with increasing needs to evaluate their impacts.

2. ORISAM aerosol modelling in TM4

• The salient features of both models are first briefly described.
• Then, the adaptations made in ORISAM and in TM4 for implementation purpose are presented.

2.1. The basic TM4 chemistry-transport host model

• The basic TM4, hereafter described, refers to TM4 before any modification for implementation purpose.
• Transport equations are solved for mass mixing ratios of 31 gaseous species using Russell and Lerner’s (1981) advection scheme at 3◦ × 2◦ horizontal resolution and 31 hybrid sigma-pressure vertical levels.
• Overall sulphate to ammonia ratios in the TM4 particulate phase are computed using only bulk microphysics.
• The dry deposition scheme is after Ganzeveld et al. (1998).
• At the upper boundary (10 hPa), ozone climatology, CH4 Tellus 59B (2007), 2 ORISAM-TM4 285 stratospheric fluxes and CH4 mixing ratios are fixed with prescribed HNO3/O3 ratios from satellite UARS CLAES data.

2.2. The aerosol model ORISAM

• In ORISAM, the sectional approach has been selected due to its potential for detailed aerosol microphysical processes without a priori assumptions on size distributions.
• Nitrate heterogeneous chemistry (Jacob, 2000) is also implemented.
• GP partitioning for inorganics is solved using ISORROPIA (Nenes et al., 1998), while empirical partitioning coefficients Kp are used for organics (Odum et al., 1996).

2.3. Implementation of ORISAM in TM4 and due adaptations

• To implement ORISAM in TM4, several modifications and improvements had to be brought to both models.
• In the tests reported here, current use is made of a nine-level, eight-bin version.
• SOA formation requires gas-phase chemistry schemes apt to effectively treat major volatile, semivolatile and non-volatile organics at successive oxidation stages.
• Another approach, ‘the full-equilibrium solution’ is used, considering the long time step (1800s) in ORISAM-TM4.
• The condensed mass is transferred to bins according to weights derived from condensation factors (Zhang et al., 2004).

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• Particles (typical diameters below 2.5 μm) and dynamical transfer for coarser ones (Pilinis et al., 2000) will be tested.
• Therefore, even if ORISAMTM4 provides an estimate of the condensed mass, still ongoing works aims at relating this latter to the hydrophobic/hydrophilic transformation processes.
• Therefore, in the tracer version with particles of mass diameters below 0.6 μm, a reference washout coefficient of 0.05 mm−1 was adopted (Dana and Hales, 1976).
• Aerosol dry deposition parametrization in the TM4 dry deposition scheme has been already mentioned, with particle deposition velocities after Seinfeld and Pandis (1998).

3. Emission inventories of carbonaceous aerosols

• The authors main focus here with ORISAM-TM4 being on carbonaceous aerosols, strong prerequisites on BC and OCp emissions are needed for OC modelling.
• These emissions are still hampered by severe uncertainties (Bond et al., 2004) resulting from large differences in the choice of emission factors.
• In the following, updates of BC and OCp emission inventories implemented in ORISAM-TM4 are detailed source-by-source.

3.1. Fossil fuel sources

• Two major different approaches for deriving fossil fuel BC and OCp emission inventories are currently available, Cooke et al. (1999) and Bond et al. (2004), the main difference being in technology differentiations.
• This, even stronger, applies to semi-developed and developing countries.
• Estimation of the part of uncontrolled emissions is at the origin of the largest differences between the two approaches above, with higher estimated emissions for the major fuels (coal, diesel, peat, lignite and coke) in Cooke et al.
• Concerning Europe, this harmonization consists to introduce new technologies and emission controls, which are rapidly evolving in Europe, while keeping high EF values for uncontrolled emissions.
• (2) S2 scenario, using the ‘low scenario’ in Guillaume and Liousse (2006), with BC emission inventory based on Cooke et al.

3.2. Biomass burning

• Updated biomass burning BC and OCp emissions from Liousse et al. (2004) were selected for ORISAM-TM4 simulations since two main differences on EF appear when compared to previous inventories.
• The first one is on the development of OCp emissions instead of total OC, OCp emissions being more suitable here since ORISAM-TM4 explicitly treats SOA formation with ensuing variable OCp/OC ratios.
• The second difference lies in OCp emission factors with separate values from aircraft and ground measurements.
• Aircraft measurements incorporate Tellus 59B (2007), 2.

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• Aged particles with SOA, less the case for ground measurements, mostly dealing with fresh OCp emissions (Liousse et al., 2004).
• Since using ORISAM-TM4 for SOA formation, OCp ground emissions were used here.

3.4. Further characteristics of BC and OCp emission inventories

• Further characteristics of these emissions in ORISAM-TM4 are described now, namely their seasonality, injection heights and initial size distributions, listed in Table 3 for the first two ones.
• Biofuel domestic combustion (fuelwood, charcoal and charcoal making) as well as savanna/forest/agricultural fires follow an imposed seasonal variation (Liousse et al., 1996).
• Additionally, the vertical distribution of injected emissions between the ground and these n-levels is as follows: 50% are injected at level n, 25% at level n–1,etc..
• The size distributions of emitted BC and OC particles, relying on measurements during the Escompte 2001 campaign (Cousin et al., 2005), are parametrized as two lognormal modes.

4.1. General overview

• BC and OC being the target aerosol components, two model versions have been used: the full ORISAM-TM4 including SOA formation and sectional microphysics and a reduced tracer version.
• In the following, OC calculated with the full ORISAMTM4 refers to the sum of OCp (primary OC) and SOAc, with a distinction in SOAc between the anthropogenic and biogenic fractions.
• Preliminary comparative tests were made between these model results and worldwide measurements at representative polar, temperate and tropical sites.
• Most generally, the tracer version appeared rather satisfactory for BC, but not for OC.

4.2. Comparisons for BC

• The global BC surface concentrations for August 2002 (upper frame) and January 2003 (lower frame) are displayed in Fig.
• Rather than proceeding to general comments on this Fig. 3, the authors concentrate on three particular major points in tropical areas.
• The first one concerns the interhemispheric seasonality of biomass burning over the African continent and its oceanic extent through emitted BC plumes.

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• There) are possibly mainly due to fossil fuels and biofuels (urban and industrial) emissions, over Johannesburg and the industrial Vaal triangle.
• Updated inventories in the TM4 tracer version, together with improved precipitation rates (in the ERA40 reanalyses) have brought major improvements at some stations, as discussed below.
• Arctic haze is due to the transport of European, Asian and North American pollution to boreal regions as can bee seen in Fig. 7(a), occasionally enhancing BC concentrations over Greenland up to 0.5 μg m–3.
• In summer, BC heavily precipitates over the Gulf of Guinea due to widespread biomass burning sources in southern Africa.
• First, the sensitivity of the TM4 tracer version was tested to such different BC emission inventories with comparisons to seasonal European observations.

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• In Fig. 10, S2 scenario (regression line slope near 0.8) clearly appears as the best performing of all four scenarios.
• With higher uncontrolled emissions than S1 but also integrating more detailed controlled emissions than S3 and S4, simulated and observed BC concentrations in S2 scenario much more agree, with only 20% underestimation.
• 2.3.2. One-day samples weekly collected during the EC-OC campaign.
• Comparisons with modelled BC concentrations at five cities are shown in Fig. 11.

4.3. Simulated vs. observed OC using the full ORISAM-TM4 model

• Few global models deal with primary and SOAs, particularly with a discrimination between anthropogenic and biogenic SOA.
• Available global OC budgets and lifetimes in literature and the present one are displayed in Table 4.
• For the secondary fraction, a comparison is made with SOA implemented within TM3 (Tsigaridis and Kanakidou, 2003).
• Among the different cases simulated by these latter authors, their case S2 has the closest assumptions to those in ORISAM-TM4.

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• Tellus 59B (2007), 2 ORISAM-TM4 295 comparison lets appear higher SOABc and SOAAc in TM4, possibly due to the main difference between these two models, namely the additional feature in ORISAM-TM4 of sizedistributed SOA.
• OC burdens from these authors have similar values (736–738 Gg), since they use only slightly different transport schemes processing the same OM emission inventory, after Liousse et al. (1996) for biomass burning and after Cooke et al. (1999) for fossil fuels sources.
• Global distributions of OCp, of the anthropogenic and biogenic fractions of secondary OC for August 2002 are displayed in Fig. 12.
• High SOAc values are found in the latitude range 0◦–5◦N, with model predicted SOAAc about 10 times lower than SOABc.

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• In winter, VOC photochemistry being less active and OCp enhanced (domestic heating), OCp/OC ratios are mostly above 0.8 in the northern hemisphere, especially over Europe.
• OC as a tracer clearly underestimates the observations by an average factor of 4 at all stations, whereas OC from ORISAM-TM4 more closely agrees with the observations, with 5% differences only.
• OCp emissions and SOA formation are two basic ingredients in total OC, observed and modelled, both subject to several limitations.
• In spite of these limitations, comparisons were made over Europe, an intense OC source region, between modelled and observed concentrations (Fig. 15), these latter based on a review of experimental OC data by Solmon et al. (2005).

4.4. Size distributions of carbonaceous aerosols

• Simulated aerosol size distributions have been reported for inorganic species, but only few studies deal with carbonaceous aerosols: here, this is one of the few attempts at global sectional modelling of carbonaceous aerosols, involving BC, OCp and SOA formation.
• Lack of data most generally hampers systematic model to measurements comparisons, though some experimental data appear to be available.
• As a preliminary modelling result, Fig. 17 displays yearly averaged size differentiated aerosol Tellus 59B (2007), 2.

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• The three following components are discriminated: BC, OCp and SOAc.
• ORISAM-TM4 predicts primary (BC and OCp) particle ratios, respectively, about 39% (global scale) and 48% against total carbonaceous aerosol mass, mostly due to less biogenic SOA formation in .
• Now, when scrutinizing at detailed chemical speciation between bins, two salient features appear.
• Further simulations and measurements are still required.

5. Conclusions and Prospects

• A new global aerosol model is presented, coupling the sectional aerosol model ORISAM to the CTM TM4.
• Due adaptations for this implementation have been detailed, before focusing upon aerosol components, BC, OCp and SOA formation.
• In particular, processing European emission inventory with more realistic fractional controlled/uncontrolled emission scenarios in the ORISAM-TM4 tracer version has resulted in better agreement between model results and observations.
• Due to different predominant carbonaceous aerosol emission sources, BC/OCp ratios modelled by ORISAM-TM4 (Fig. 17) are higher in Europe than at the global Tellus 59B (2007), 2 scale.
• At this stage, several prospects can be consid- ered.

Figures

Table 2 A comparison of state-of-the-art open circuit voltage obtained using various halide perovskites in conjunction with a diverse range of electron and hole selective contacts. The Conduction band (CB) and VB edges for MAPbI3 and MAPbBr3 are ( 3.9/ 5.4) eV and ( 3.4/ 5.6) eV, respectively. Table is reproduced with permission from Ref. [32]. Copy right of AIP Publishing.

Fig. 5. External electroluminescence yield (EQEEL) as a function of the injection current. Dashed lines show the calculated EQE EL. The injection current as a function of applied voltage is shown in the inset (solid lines) including a fit to a shunt resistance (dashed), which is used to calculate the dashed lines in the main figure. Figure is reproduced with permission from Ref. [82]. Copyright of John Wiley and Sons.

Fig. 21. (a) PV performance of various PSCs as a function of time stored under illumination at AM1.5G and a humidity ~45%. The PSCs compared in (a) employ spiroOMeTAD, TSHBC and TSHBC/graphene [323] as HTM. Figure (b) shows normalized PCE of PEDOT: PSS and CuI based PSCs as a function of storage time in air [58]. Figure reproduced with permission from the references.

Fig. 20. (a) Effect of protective HTM layers on perovskite films at elevated temperature and humidity. The colour of PSCs changes from almost black to yellow for all organic HTMs except for the films covered with PMMA only or a composite of CNT and PMMA, (b) PCE of PSCs employing range of HTMs as a function of temperature [53]. Figure reproduced with permission from the reference. Copy right of American Chemical Society.

Fig. 22. Stability test of PSCs based on various HTMs (a) TTF-1 pristine and spiroOMeTAD doped HTM [133], (b) SAF-OMe and spiroOMeTAD [329], (c) efficiencies of PSCs with 2TPA-n-DP(n=1, 2, 3, 4) as a function of storage time [34], (d) PEDOT, GO/PEDOT, and GO [330], (e) normalized PCE of cells using Spiro-OMeTAD (red) and RGO (blue) [331], and (f) long-term stability for the PSCs containing (FA)0.25(MA)0.75PbI3 [332]. Figures are reproduced with permission from the references.

Table 5 Perovskite solar cells employing the three common polymer hole transporting materials (P3HT, PTAA and PEDOT: PSS) along with their device architecture, and details perovskite deposition method.

Fig. 16. Comparison of the contact angle between HTM (Spiro-OMeTAD) and perovskite layer without (a) and (b) with GO, and (c) J-V curve for the champion device with GO layer. Figures are reproduced with permission from Ref. [65]. Copy right of Royal Society of Chemistry.

Fig. 1. The various common device designs employed for PSCs. The designs employ both ETL and HTM (a, c, and d), an insulating scaffold that replaces conducting ETL (b), and PSCs that employ only one of the two selective contacts, such as ETL-free (e) and HTM-free (f). Figures (c and d) refer to conventional (n-i-p) and inverted (p-i-n) architectures that represents if the electron or holes are to be collected at the conducting substrate, respectively. Figure adapted with permission from Ref. [32]. Copy right of AIP Publishing.

Fig. 6. (a): Chemical structures of most common small molecules based hole transport materials in perovskite solar cells. Chemical structures of the HTMs are reproduced with permission from references [47,48]. Copyright of John Wiley and Sons. (b): Chemical structures of most common polymers based hole transport materials in perovskite solar cells. Chemical structures of the HTMs are reproduced with permission from Refs. [47,48]. Copyright of John Wiley and Sons.

Table 1 An account of various common hole transporting materials in perovskite solar cells.

Fig. 17. Factors inducing instability in perovskite solar cells can be classified as external, i.e., temperature [275,276], moisture [277,278], oxygen [279], light (including UV light) [280 282] and electric field [283 287], and internal [206,281].

Fig. 18. (a) Illustration of the possible degradation pathway of the perovskite in the presence of water. A water molecule, a, is required to initiate the decomposition process where both hydrogen iodide (b, soluble in water) and methyl ammonia (c, volatile and dissolve in water). Finally a yellow solid is formed showing presence of PbI2, d [293], and (b) schematic of perovskite degradation when exposed to sunlight [204]. Figure reproduced with permission from the reference. Copy right of American Chemical Society.

Fig. 11. (a) SEM image of CH3NH3PbI3-coated mp-TiO2 film (top view), (b) a cross-sectional image of mp-TiO2/CH3NH3PbI3/PTAA/Au device, and (c) J-V curve for the best performing cells fabricated using PTAA and spiroOMeTAD as HTMs. Figure are reproduced with permission from Ref. [2]. Copy right of nature publishing group.

Fig. 2. Top view of CH3NH3PbI3 xClx film with (a) and without (b) poly(3-hexylthiophene) P3HT. Figure reproduced with permission from Ref. [43]. Copy right of Elsevier.

Fig. 12. (a) X-ray spectroscopy image confirm diffusion of Cu atoms into the perovskite layer at the interface of perovskite/CuI (rectangular box), (b) Cross sectional FE SEM images of theTiO2/perovskite/CuI layer, (c) Photon-to-electron conversion efficiency of PSCs with CuI (red curve) and Spiro- OMTAD (blue curve) as HTM, and (d) J-V curves of devices prepared with CuI as the HTM in the scan direction of forward bias to short circuit (FB SC) and short circuit to forward bias (SC FB). Figure are reproduced with permission from Ref. [198]. John Wiley and Sons.

Fig. 19. Comparison of normalized PV parameters (a d) of the planar PSCs as a function of irradiation and without irradiation time for 90 min at high humidity (50 60%), (e and f) SEM images of fresh and degraded perovskite layer in dark, (g) normalized PV parameters and their comparison with the renewal of Au electrode, and (h) compared the XRD pattern of exposed device and unexposed one [295]. Figure reproduced with permission from the reference. Copy right of The Royal Society of Chemistry.

Table 7 A comparison of stability of various hole transporting materials or HTM free (with and without dopants).

Fig. 10. (a) Double-twisted fibrous PSCs structure (PMMA layer not shown), (b) J-V curve of Double-twisted PSCs with best PCE~3.03% and (c) The photograph of the double-twisted fibrous PSCs warped onto a capillary tube with curvature radius of 0.3 mm. Figure are reproduced with permission from Ref. [156]. Copyright of John Wiley and Sons.

Fig. 9. (a) Normalized life time for P3HT and P3HT/GD HTL based PSCs, (b) J-V characteristic curve of the same. Figure are reproduced with permission from Ref. [145]. Copy right of Wiley (c) Cross-section of the complete device showing P3HT/SWNTs nanohybrid mesh in-filled with PMMA and (d) its current voltage curve of the complete device with (red curve) and without PMMA (grey curve). Figure are reproduced with permission from Ref. [53]. Copy right of American Chemical Society.

Fig. 6. (a): Chemical structures of most common small molecules based hole transport materials in perovskite solar cells. Chemical structures of the HTMs are reproduced with permission from references [47,48]. Copyright of John Wiley and Sons. (b): Chemical structures of most common polymers based hole transport materials in perovskite solar cells. Chemical structures of the HTMs are reproduced with permission from Refs. [47,48]. Copyright of John Wiley and Sons.

Fig. 3. Energy levels of various common HTMs together with iodide and bromide based halide-perovskites. It is important to note that the energy levels are those of isolated materials and that upon formation of the multilayer device, changes in the energy scheme and alignment may occur due to interfacial dipoles, band bending, trap states and impurities. The minus ( ) sign corresponding to the energy levels is omitted for simplicity. The Figure is drawn for free of scale for illustration only.

Frequently asked questions

Q1. What are the main characteristics of a good HTM?

A good HTM possesses relevant energy levels that ensure facile passage of photogenerated holes from the perovskite layer into the HTM (i.e. matching ionization potentials) whilst also ensuring selectivity, i.e. imped ing the recombination of electrons at such a contact (thus low electron affinities are sought). 

Q2. What contributions have the authors mentioned in the paper "Advances in hole transport materials engineering for stable and efficient perovskite solar cells" ?

This article reviews the various hole transporting materials ( HTMs ) used in perovskite solar cells ( PSCs ) in achieving high photo conversion efficiency ( PCE ) and operational stability. This article critically approaches role of structure, electrochemistry, and physical properties of varied of choice of HTMs categorized diversely as small and long polymers, organometallic, and inorganic on the photovoltaic parameters of PSCs conceived in various device configurations. 

Q3. What is the effect of HTM on the charge collection characteristics of PSCs?

As RREC is inversely proportional to recombination kinetics in the film [76,77], it is evident that inclusion of HTM improves the charge collection characteristics of PSCs. 

Q4. What is the effect of the HTMs on the performance of the perovskite?

Being one of the three main layers constituting the perovskite solar cell, apart from the electrodes, HTMs have a huge bearing on performance, i.e. power conversion efficiency and stability. 

Q5. What is the effect of a mismatch in energy bands between PEDOT and perovs?

A mismatch in energy bands between HTM and perovskite will not only effect the VOC but also will reduce the charge transfer at the interface [177]. 

Q6. Why is the enhancement of JSC and FF due to the improved electrical conductivity of 5?

The enhancement of JSC and FF is due to the improved electrical conductivity of 5 at% Cu: NiOx which enabled more efficient charge extraction from the CH3NH3PbI3 absorber. 

Q7. What is the reason for the low charge mobility and poor conductivity in spiroOM?

The low charge mobility and poor conductivity in pristine spiroOMeTAD arises from its inherent triangular pyramid configuration that leads to large intermolecular distances [92,96]. 

Q8. What are the main factors inducing instability in PSCs?

Whereas intrinsic instability in the devices arises from (i) structural instability, (ii) ionic polarization of perovskite crystals in presence of electric field (hysteresis), and (iii) selective contacts, i.e., ETL and HTM and their interfaces with perovskite, the external instability is caused due to electrical biasing, prolonged light soaking, UV irradiation, humidity, oxygen, and temperature [29] [174,274]. 

Q9. What is the main reason why the authors recommend Cu2O as HTM?

low cost, facile synthesis, and high device performance, recommended Cu2O as HTM for facilitating the devel opment of industrial scale perovskite solar cell technology. 

Q10. Why is P3HT used in organic photovoltaic devices?

owing to its relatively cheaper synthesis cost, is a widelyemployed conducting polymer in organic photovoltaic devices [144] as well as in PSCs [145]. 

Q11. How can the authors improve the PCE of PSCs?

Although PSCs can be fabricated via solution processing, a method that can be applied for cost effective mass production, and their PCE has reached a value as high as ~22.1% [21], they are typically unstable when exposed to humidity, high temperatures, and light [271,272]. 

Q12. What is the role of the HTM in the performance of the PSCs?

It is clear that deposition method of the HTM, as well as that of the perovskite absorber, play an important role in the performance of the PSCs. 

Q13. What is the effect of doping on the performance of PSCs?

Initially it was observed that HTMs in their pristine form yielded inferior performance due to their poor charge mobility; however, recently PSCs with high performance were fabricated even without doping. 

Q14. What is the reason why wei et al. reported higher degradation in planar P?

Subsequently Wei et al. [295] reported higher degradation in planar counterparts where thinner TiO2 ETLs should be less effected by UV light. 

Q15. Why was the degradation of the PSCs irreversible?

the fact that most of the photoinduced degradation was irreversible led to an assumption that the degradation might be due to moisture because the devices were tested at the ambient condition. 

Q16. What is the effect of a thicker HTM layer on the fill factor of the device?

one must note that a thicker HTM layer will also add to RS of the film which would reduce the fill factor (FF) of the device. 

Q17. What is the simplest way to collect electrons from the metal back contact?

It is mainly used in inverted planar PSCs (Table 5), an architecture that typically employ organic compact charge extraction layers on the substrates to collect holes whereas the electrons are collected from the metal back contact.