Evidence map›Paper›PMID 39932424›Full record

ArticleACS nano2025

Kelvin Probe Force Microscopy Imaging of Plasticity in Hydrogenated Perovskite Nickelate Multilevel Neuromorphic Devices.

Tamal Dey, Xinyuan Lai, Sukriti Manna, Karan Patel, Ranjan Kumar Patel, Ravindra Singh Bisht, Yue Zhou, Shaan Shah, Eva Y Andrei, Subramanian K R S Sankaranarayanan and 3 more

Abstract read
In one paragraph

Article in ACS nano, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

13 authors.

Tamal DeyDepartment of Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854, United States.ORCID 0000-0003-4862-8107
Xinyuan LaiDepartment of Physics and Astronomy, Rutgers University, Piscataway, New Jersey 08854, United States.
Sukriti MannaCenter for Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, United States.
Karan PatelDepartment of Electrical Engineering & Computer Science, University of Tennessee, Knoxville, 1520 Middle Dr, Knoxville, Tennessee 37996, United States.ORCID 0000-0002-3653-6523
Ranjan Kumar PatelDepartment of Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-5778-4606
Ravindra Singh BishtDepartment of Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-8225-7306
Yue ZhouDepartment of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093, United States.
Shaan ShahDepartment of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093, United States.
Eva Y AndreiDepartment of Physics and Astronomy, Rutgers University, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-2516-2749
Subramanian K R S SankaranarayananCenter for Nanoscale Materials, Argonne National Laboratory, Lemont, Illinois 60439, United States.
Duygu KuzumDepartment of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California 92093, United States.
Catherine SchumanDepartment of Electrical Engineering & Computer Science, University of Tennessee, Knoxville, 1520 Middle Dr, Knoxville, Tennessee 37996, United States.
Shriram RamanathanDepartment of Electrical and Computer Engineering, Rutgers University, Piscataway, New Jersey 08854, United States.ORCID 0000-0002-6685-6798

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ion drift in nanoscale electronically inhomogeneous semiconductors is among the most important mechanisms being studied for designing neuromorphic computing hardware. However, nondestructive imaging of the ion drift in operando devices directly responsible for multiresistance states and synaptic memory represents a formidable challenge. Here, we present Kelvin probe force microscopy imaging of hydrogen-doped perovskite nickelate device channels subject to high-speed electric field pulses to directly visualize proton distribution by monitoring surface potential changes spatially, which is also supported with finite element-based electric field distribution studies. First-principles calculations provide mechanistic insights into the origin of surface potential changes as a function of hydrogen donor doping that serves as the contrast mechanism. We demonstrate 128 (7-bit) nonvolatile conductance levels in such devices relevant to in-memory computing applications. The synaptic plasticity measurements are implemented in spiking neural networks and show promising results for classification (SciKit Learn's Iris and Wine data sets) and control (OpenAI's CartPole-v1 and BipedalWalker-v3) simulation tasks.

Indexed as

imagingKelvin probe force microscopymemoryneural networksneuromorphic computingnickelatessynaptic plasticity

Identifiers

PMID39932424
PMCPMC12333431

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.