Evidence map›Paper›PMID 40546887›Full record

ArticleSmart materials & structures2025

3D printed CNT/TPU triboelectric nanogenerator for load monitoring of total knee replacement.

Osama Abdalla, Mahmood Chahari, Milad Azami, Amir Ameli, Emre Salman, Milutin Stanacevic, Ryan Willing, Shahrzad Towfighian

Abstract read
In one paragraph

Article in Smart materials & structures, 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

8 authors.

Osama AbdallaState University of New York at Binghamton, Binghamton, NY, United States of America.ORCID https://orcid.org/0009-0009-2036-2790
Mahmood ChahariState University of New York at Binghamton, Binghamton, NY, United States of America.ORCID https://orcid.org/0000-0003-4743-663X
Milad AzamiUniversity of Massachusetts Lowell, Lowell, MA, United States of America.
Amir AmeliUniversity of Massachusetts Lowell, Lowell, MA, United States of America.
Emre SalmanStony Brook University, Stony Brook, NY, United States of America.
Milutin StanacevicStony Brook University, Stony Brook, NY, United States of America.
Ryan WillingUniversity of Western Ontario, London, Ontario, Canada.
Shahrzad TowfighianState University of New York at Binghamton, Binghamton, NY, United States of America.ORCID https://orcid.org/0000-0002-5084-7395

Funding

Self-Powered Load Sensors for Total Knee Replacement Health MonitoringR01AR080798 · NIAMS · STATE UNIVERSITY OF NY,BINGHAMTON · PI Shahrzad Towfighian · 2022 to 2026
$2.2M
NIAMS NIH HHS R01 AR080798
6 · The paper itself

Abstract

This study presents the development and characterization of a novel triboelectric nanogenerator (TENG) designed as a self-powered sensor for load monitoring in total knee replacement (TKR) implants. The triboelectric layers comprise a 3D-printed thermoplastic polyurethane (TPU) matrix with carbon nanotube (CNT) nanoparticles and kapton tape, sandwiched between two copper electrodes. To optimize sensor performance, the proposed CNT/TPU TENG sensor is fabricated with varying CNT concentrations and thicknesses, enabling a comprehensive analysis of how material composition and structural parameters influence energy harvesting efficiency. The 1% CNT/TPU composite demonstrates the highest power output among the tested samples. The solid CNT/TPU-based TENG generated the apparent output power of 4.1

Indexed as

3D printingadditive manufacturingcarbon nanotubesfoam TPU printingpressure sensorsmart knee implanttriboelectric nanogenerator

Identifiers

PMID40546887
PMCPMC12177930

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.