Evidence map›Paper›PMID 37870205›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2023

Embodying Multifunctional Mechano-Intelligence in and Through Phononic Metastructures Harnessing Physical Reservoir Computing.

Yuning Zhang, Aditya Deshmukh, Kon-Well Wang

Open access · goldAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.3field-weighted citation impact, top 9% of its field
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

5 citing papers in PubMed, 13 citations in OpenAlex.

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  4. Review
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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

3 authors at 1 institution in 1 country.

Yuning ZhangDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID https://orcid.org/0009-0003-0276-0548
Aditya DeshmukhDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
Kon-Well WangDepartment of Mechanical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.ORCID https://orcid.org/0000-0002-9163-2614
University of Michigan · US

Funding

Automotive Research Center/US Army DEVCOM Ground Vehicle Systems Center, Warren, MI W56HZV-19-2-0001University of Michigan Collegiate Professorship
6 · The paper itself

Abstract

Recent advances in autonomous systems have prompted a strong demand for the next generation of adaptive structures and materials to possess built-in intelligence in their mechanical domain, the so-called mechano-intelligence (MI). Previous MI attempts mainly focused on specific case studies and lacked a systematic foundation in effectively and efficiently constructing and integrating different intelligent functions. Here, a new approach is uncovered to create multifunctional MI in adaptive structures using physical reservoir computing (PRC). That is, to concurrently embody computing power and the key elements of intelligence, namely perception, decision-making, and commanding, directly in the mechanical domain, advancing from conventional reliance on add-on computers and massive electronics. As an exemplar platform, a mechanically intelligent phononic metastructure is developed by harnessing its high-degree-of-freedom nonlinear dynamics as PRC power. Through analyses and experiments, multiple intelligent structural functions are demonstrated ranging from self-tuning wave controls to wave-based logic gates. This research provides the much-needed basis for creating future smart structures and materials that greatly surpass the state of the art-such as lower power consumption, more direct interactions, and better survivability in harsh environments or under cyberattacks. Moreover, it enables the addition of new functions and autonomy to systems without overburdening the onboard computers.

Indexed as

mechano-intelligencephononic metastructurephysical reservoir computingself-adaptive wave transmissionwave-based logic gates

Identifiers

PMID37870205
PMCPMC10700179
OpenAlexW4387865439

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.