Evidence map›Paper›PMID 42161959›Full record

ReviewNature communications2026

AI-driven green processing and life cycle assessment for sustainable perovskite solar cells.

Hee Jung Kim, Wenning Chen, Jae Myeong Lee, Hyun Suk Jung

Abstract readReview
In one paragraph

Review in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hee Jung Kim *School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, South Korea.ORCID http://orcid.org/0000-0002-7947-1088
Wenning Chen *Department of Future Energy Engineering, Sungkyunkwan University, Suwon, South Korea.ORCID http://orcid.org/0000-0002-0997-7083
Jae Myeong Lee *School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, South Korea.
Hyun Suk JungSchool of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, South Korea. hsjung1@skku.edu.ORCID http://orcid.org/0000-0002-7803-6930

Funding

Ministry of Knowledge Economy | Korea Institute of Energy Technology Evaluation and Planning (KETEP) RS-2025-25450823National Research Foundation of Korea (NRF) RS-2025-00522430National Research Foundation of Korea (NRF) RS-2025-02316700
6 · The paper itself

Abstract

Despite rapid advances in perovskite solar cells, solvent selection remains a central determinant of safety, process robustness, and end-of-life outcomes. These constraints are multi-dimensional and involve competing trade-offs, making them challenging to resolve through experimental optimization alone. This Perspective integrates green solvent engineering with artificial intelligence (AI) and life cycle assessment (LCA) to provide a unified sustainability framework. We discuss solvent-precursor coordination and processing-window robustness as governing factors. We also highlight how AI can accelerate solvent discovery and reduce key life cycle inventory gaps, while LCA quantifies trade-offs and mitigates burden shifting. This combined lens clarifies sustainability-relevant priorities for the field.

Identifiers

PMID42161959
PMCPMC13190722

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.