Evidence map›Paper›PMID 32382036›Full record

ArticleNature communications2020

Perovskite neural trees.

Hai-Tian Zhang, Tae Joon Park, Ivan A Zaluzhnyy, Qi Wang, Shakti Nagnath Wadekar, Sukriti Manna, Robert Andrawis, Peter O Sprau, Yifei Sun, Zhen Zhang and 19 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Perspective and Prospects for Ordered Functional Materials.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Article
  5. Article
  6. Low-temperature emergent neuromorphic networks with correlated oxide devices.Proceedings of the National Academy of Sciences of the United States of America · 2021
    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

29 authors.

Hai-Tian Zhang *School of Materials Engineering, Purdue University, West Lafayette, IN, 47907, USA. htzhang@purdue.edu.
Tae Joon Park *School of Materials Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Ivan A Zaluzhnyy *Department of Physics, University of California, San Diego, La Jolla, CA, 92093, USA.
Qi WangSchool of Materials Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Shakti Nagnath WadekarSchool of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Sukriti MannaCenter for Nanoscale Materials, Argonne National Laboratory, Argonne, IL, 60439, USA.
Robert AndrawisSchool of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA.ORCID http://orcid.org/0000-0002-8538-0641
Peter O SprauDepartment of Physics, University of California, San Diego, La Jolla, CA, 92093, USA.ORCID http://orcid.org/0000-0001-8965-5684
Yifei SunSchool of Materials Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Zhen ZhangSchool of Materials Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Chengzi HuangSchool of Materials Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Hua ZhouX-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Lemont, IL, 60439, USA.ORCID http://orcid.org/0000-0001-9642-8674
Zhan ZhangX-ray Science Division, Advanced Photon Source, Argonne National Laboratory, Lemont, IL, 60439, USA.ORCID http://orcid.org/0000-0002-7618-6134
Badri NarayananDepartment of Mechanical Engineering, University of Louisville, Louisville, KY, 40292, USA.
Gopalakrishnan SrinivasanSchool of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA.
Nelson HuaDepartment of Physics, University of California, San Diego, La Jolla, CA, 92093, USA.
Evgeny NazaretskiNational Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, 11973, USA.ORCID http://orcid.org/0000-0003-1207-8174
Xiaojing HuangNational Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, 11973, USA.
Hanfei YanNational Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, 11973, USA.
Mingyuan GeNational Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, 11973, USA.
Yong S ChuNational Synchrotron Light Source II, Brookhaven National Laboratory, Upton, NY, 11973, USA.
Mathew J CherukaraCenter for Nanoscale Materials, Argonne National Laboratory, Argonne, IL, 60439, USA.ORCID http://orcid.org/0000-0002-1475-6998
Martin V HoltCenter for Nanoscale Materials, Argonne National Laboratory, Argonne, IL, 60439, USA.ORCID http://orcid.org/0000-0003-2640-7100
Muthu KrishnamurthyDepartment of Mathematics, University of Iowa, Iowa City, IA, 52242, USA.
Oleg G ShpyrkoDepartment of Physics, University of California, San Diego, La Jolla, CA, 92093, USA.
Subramanian K R S SankaranarayananCenter for Nanoscale Materials, Argonne National Laboratory, Argonne, IL, 60439, USA.
Alex FranoDepartment of Physics, University of California, San Diego, La Jolla, CA, 92093, USA.ORCID http://orcid.org/0000-0001-9316-129X
Kaushik RoySchool of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, 47907, USA. kaushik@purdue.edu.
Shriram RamanathanSchool of Materials Engineering, Purdue University, West Lafayette, IN, 47907, USA. shriram@purdue.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Trees are used by animals, humans and machines to classify information and make decisions. Natural tree structures displayed by synapses of the brain involves potentiation and depression capable of branching and is essential for survival and learning. Demonstration of such features in synthetic matter is challenging due to the need to host a complex energy landscape capable of learning, memory and electrical interrogation. We report experimental realization of tree-like conductance states at room temperature in strongly correlated perovskite nickelates by modulating proton distribution under high speed electric pulses. This demonstration represents physical realization of ultrametric trees, a concept from number theory applied to the study of spin glasses in physics that inspired early neural network theory dating almost forty years ago. We apply the tree-like memory features in spiking neural networks to demonstrate high fidelity object recognition, and in future can open new directions for neuromorphic computing and artificial intelligence.

Identifiers

PMID32382036
PMCPMC7206050

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.