All-Perovskite Tandem Solar Cells: A Roadmap to Uniting High Efficiency with High Stability
Bibliographic record
Abstract
ConspectusOrganic–inorganic halide perovskite photovoltaics (PVs)─only a decade-old field─have reached impressive power conversion efficiencies (PCEs) and passed industrial stability requirements (IEC 61215:2016 Damp Heat and Humidity Freeze tests), solidifying their status among candidates for next generation PVs. Among the various perovskite PV technologies, all-perovskite tandem solar cells (PTSCs) are frontrunners for commercialization. PTSCs unite a narrow-bandgap (NBG; Eg ≈ 1.2 eV) perovskite back cell with a wide-bandgap (WBG; Eg ≈ 1.7–1.9 eV) perovskite front cell. Despite their nascency, PTSCs have achieved certified PCEs of 24.8% and 24.2% for small-area (0.049 cm2) and large-area devices (1.041 cm2), respectively. With further advances in materials development, PTSCs are capable of moving beyond the PCE limits of single-junction cells due to reduced thermalization losses and improved utilization of the solar spectrum. By contrast, the PCE of single-junction perovskite devices is already approaching its saturation level, which is already very close to the device’s Shockley–Queisser limit for a bandgap of around 1.55 eV. The tandem architecture, thus, provides the most viable path forward to further exploiting the potential of perovskite solar cells.However, PTSC technology faces a set of challenges distinct from those in perovskite single-junction devices because (i) NBG perovskites─typically achieved by Pb–Sn alloying─are prone to oxidation (Sn2+ to Sn4+), which results in a high density of Sn vacancies that degrade the optoelectronic performance of NBG perovskite films, (ii) practically complete photon absorption and charge extraction require thick, NBG perovskite films having long carrier diffusion lengths, and (iii) WBG perovskites with high Br/(I + Br) ratio experience large voltage losses and inferior light stability due to surface trap states and phase segregation.In this Account, we discuss how to manage these considerations and maximize the power output in PTSCs via light management. We then review strategies, including composition- and additive-engineering, defect passivation, and matching charge transport layers, for enhancing the carrier diffusion length of NBG perovskite cells and mitigating voltage losses in WBG perovskite cells. We also summarize the advances made in the fabrication of PTSCs on the device level, especially the evolution of tunnel recombination junctions and tandem device architectures. Finally, we highlight further research efforts needed to overcome roadblocks to commercialization (e.g., improving the environmental, thermal, and operating stability of these devices) and offer our perspective on the future development of this rapidly advancing field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".