Evidence map›Paper›PMID 42845854›Full record

ArticleNanophotonics (Berlin, Germany)2026

Toward Plasmonic Neuronal Architectures at the Nanometer Scale.

Christopher G O Weiß, Tobias Eul, Emily Kruel, Mario F Pfeiffer, Bert Lägel, Benjamin Stadtmüller, Martin Aeschlimann

Abstract read
In one paragraph

Article in Nanophotonics (Berlin, Germany), 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

7 authors.

Christopher G O WeißDepartment of Physics and Research Center OPTIMAS RPTU University Kaiserslautern-Landau Kaiserslautern Rhineland-Palatinate Germany.ORCID https://orcid.org/0009-0003-2335-4282
Tobias EulExperimentalphysik II Institute of Physics University of Augsburg Augsburg Bavaria Germany.ORCID https://orcid.org/0000-0002-7362-6448
Emily KruelDepartment of Physics and Research Center OPTIMAS RPTU University Kaiserslautern-Landau Kaiserslautern Rhineland-Palatinate Germany.ORCID https://orcid.org/0009-0006-0160-2806
Mario F PfeifferDepartment of Physics and Research Center OPTIMAS RPTU University Kaiserslautern-Landau Kaiserslautern Rhineland-Palatinate Germany.ORCID https://orcid.org/0009-0003-7101-4557
Bert LägelDepartment of Physics and Research Center OPTIMAS RPTU University Kaiserslautern-Landau Kaiserslautern Rhineland-Palatinate Germany.ORCID https://orcid.org/0000-0002-6540-6218
Benjamin StadtmüllerExperimentalphysik II Institute of Physics University of Augsburg Augsburg Bavaria Germany.ORCID https://orcid.org/0000-0001-8439-434X
Martin AeschlimannDepartment of Physics and Research Center OPTIMAS RPTU University Kaiserslautern-Landau Kaiserslautern Rhineland-Palatinate Germany.ORCID https://orcid.org/0000-0003-3413-5029

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce a plasmonic computing platform that unites multiplexed optical inputs, static weighting, and nonlinear activation within a single nanoscale architecture-marking a critical step toward the realization of a plasmonic neural cell. In this approach, the orbital angular momentum (OAM) of light serves as an orthogonal and inherently parallel encoding scheme, enabling distinct optical channels to be directed into individual plasmonic waveguides. The weighting of input signals is governed by precisely engineered nanoscale gaps, whereas the system's nonlinear activation is revealed through two-photon photoemission, spatially resolved using photoemission electron microscopy (PEEM). By confining electromagnetic fields far below the diffraction limit and minimizing surface plasmon polariton (SPP) propagation lengths, the design mitigates optical absorption losses while fully exploiting the unique field enhancement capabilities of plasmonic nanostructures. This physically integrated platform is compatible with scalable nanofabrication defined through a two-step electron-beam lithography (EBL) process and provides a compact, energy-efficient building block for ultrafast neuromorphic photonic circuits. Together, these results outline a tangible route toward dense plasmonic neural networks capable of performing all-optical information processing at the native speed of light.

Indexed as

dielectric‐loaded SPP waveguides (DLSPPWs)neuromorphic computingorbital angular momentum (OAM) multiplexingphotoemission electron microscopy (PEEM)plasmonic neural cellsurface plasmon polaritons (SPPs)

Identifiers

PMID42845854
PMCPMC13642609

What OpenQuestion holds

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Registered trials

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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.