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Persistent Identifier
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doi:10.18419/DARUS-5656 |
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Publication Date
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2026-03-03 |
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Title
| Data for: Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells |
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Author
| Kollenz, Philipphttps://ror.org/038t36y30ORCIDhttps://orcid.org/0000-0002-3439-164X |
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Point of Contact
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Use email button above to contact.
Deschler, Felix (Heidelberg University) |
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Description
| This dataset contains measurement data related to the paper "Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells". The data originates from optical and electrical experiments investigating neuromorphic reservoir computing based on opto-ionic dynamics in hybrid lead-halide perovskite devices.The measurements were performed on electrochemically gated MAPbBr₃ perovskite microcrystal films and single-crystal devices. Input signals were encoded as phase-modulated optical excitation pulses synchronized with an applied alternating voltage. The resulting system response was recorded primarily via spatially and temporally resolved photoluminescence (PL) microscopy, complemented by spectroscopic, lifetime, and X-Ray diffraction measurements. Photoluminescence intensity and dynamics represent the internal state of the opto-ionic reservoir. Spatial pixels or defined regions of interest correspond to computational nodes, while temporal evolution encodes memory effects arising from ion migration and excited-state recombination dynamics. Variations in signal amplitude, lifetime, and spatial distribution therefore reflect nonlinear system responses used for time-series processing and classification tasks. The dataset could be reused for - benchmarking physical or neuromorphic reservoir computing approaches - studies of opto-ionic coupling and excited-state dynamics in hybrid perovskites - image-based time-series analysis or dimensionality-reduction research. The data is organized according to experiment type - Modulation: Photoluminescence response to optical and electronic modulation - Stability: Replicates of the modulation experiment for different devices and as a function of device lifetime - BitScan: Photoluminescence response to the 4-bit binary classification benchmark - PL lifetime imaging: Photoluminescence lifetime microscopy data of single-crystal devices - GIWAXS: grazing incidence wide angle x-ray scattering of MAPbBr3 thin films and different stages of device fabrication - UV-VIS: Transmission spectra of MAPbBr3 thin films. |
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Subject
| Chemistry; Computer and Information Science; Physics |
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Keyword
| Reservoir Computing http://www.wikidata.org/entity/Q7315328 (Wikidata)
Neuromorphic Computing http://www.wikidata.org/entity/Q137425629 (Wikidata)
Opto-Ionics
Hybrid Perovskites https://doi.org/10.29172/57c5b6fb-0d61-4cce-9d84-505f5d6322e4 (PhySH)
Lead Halide Perovskites
Photoluminescence Microscopy
Excited State Dynamics
Mixed Conductors
Ion Migration
Photonic Computing
Dimensionality Reduction http://www.wikidata.org/entity/Q16000077 (Wikidata)
Spatiotemporal Data |
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Topic Classification
| Chemistry (DFGFO) https://w3id.org/dfgfo/2024/31
Computer Science (DFGFO) https://w3id.org/dfgfo/2024/443
Physics (DFGFO) https://w3id.org/dfgfo/2024/32 |
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Related Publication
| Is Cited By: P. Kollenz, C. Herrle, L. Göhringer, N. Solhtalab, T. Wickenhäuser, W. Pernice, R. Klingeler, F. Deschler. Excited State Opto-Ionic Reservoir Computing in Hybrid Perovskite Electrochemically-Gated Luminescent Cells.” Advanced Materials (2026): e12575. doi 10.1002/adma.202512575 https://doi.org/10.1002/adma.202512575 |
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Producer
| Deschler, Felix (Physikalisch-Chemisches Institut, Heidelberg University) |
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Production Location
| Im Neuenheimer Feld 229, Heidelberg, Germany |
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Contributor
| Data Collector: Kollenz, Philipp
Data Collector: Solhtalab, Nasrin
Data Collector: Herrle, Carina
Data Collector: Göhringer, Leonard
Project Member: Wickenhäuser, Tom
Supervisor: Pernice, Wolfram
Supervisor: Klingeler, Rüdiger
Supervisor: Deschler, Felix |
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Funding Information
| DFG: GRK 2948: 508754442
DFG: 533164536 |
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Depositor
| Kollenz, Philipp |
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Deposit Date
| 2026-01-14 |
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Software
| python, Version: 3.11.3
h5py, Version: 3.12.1
numpy, Version: 1.26.4
scikit-learn, Version: 1.7.2 |