Evidence map›Paper›PMID 41868254›Full record

ReviewACS energy letters2026

Underexplored Dimensions of Emerging Indoor Photovoltaics.

G Krishnamurthy Grandhi, Bruno Damien, Zeynab Skafi, Kezia Sasitharan, Hani Kanaan, Hasan Alkhatib, Sadok Ben Dkhil, Matthew J Carnie, Marina Freitag, Thomas M Brown and 1 more

Abstract readReview
In one paragraph

Review in ACS energy letters, 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

11 authors.

G Krishnamurthy GrandhiHybrid Solar Cells, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, FI-33014, Finland.ORCID https://orcid.org/0000-0001-9986-1000
Bruno Damiene-peas S.A., Boulevard Baudouin 1er, 19, 1348 Louvain-La-Neuve, Belgium.
Zeynab SkafiCHOSE (Centre for Hybrid and Organic Solar Energy), Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.
Kezia SasitharanSchool of Natural and Environmental Science, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom.ORCID https://orcid.org/0000-0003-4677-3896
Hani KanaanDracula Technologies, 2 Place Edmond Regnault, 26000 Valence, France.
Hasan AlkhatibDracula Technologies, 2 Place Edmond Regnault, 26000 Valence, France.
Sadok Ben DkhilDracula Technologies, 2 Place Edmond Regnault, 26000 Valence, France.
Matthew J CarnieSPECIFIC-IKC, Department of Materials Science and Engineering, Faculty of Science and Engineering, Swansea University, Swansea, SA1 8EN, United Kingdom.ORCID https://orcid.org/0000-0002-4232-1967
Marina FreitagSchool of Natural and Environmental Science, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom.ORCID https://orcid.org/0000-0002-4954-6851
Thomas M BrownCHOSE (Centre for Hybrid and Organic Solar Energy), Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.ORCID https://orcid.org/0000-0003-2141-3587
Paola VivoHybrid Solar Cells, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, FI-33014, Finland.ORCID https://orcid.org/0000-0003-2872-6922

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Indoor photovoltaics (IPVs) can significantly reduce reliance on disposable batteries in Internet of Things (IoT) devices. Yet, most evaluations use idealized lighting setups and single performance metrics, neglecting the influence of real indoor environments on device performance. This Perspective advances a deployment-centered approach: (i) realistic testing under mixed or hybrid lighting (daylight + artificial); (ii) intelligent integration that aligns absorber bandgap, series-connected cells, geometric fill factor, and power management integrated circuits with workloads and duty cycles; and (iii) IoT-ready stability assessed under the same realistic indoor scenes and light/dark sequences. We propose a compact field-to-lab pipeline, translate it into voltage-matching design rules, and use photon-to-compute metrics to link harvested power to on-device sensing and learning. The goal is low-maintenance, battery-free nodes that scale reliably in buildings, logistics, and wearable applicationsultimately cutting electronic waste.

Identifiers

PMID41868254
PMCPMC13004493

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.