Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (16/16 displayed)

  • 2022Piezoresistive 3D graphene-PDMS spongy pressure sensors for IoT enabled wearables and smart products29citations
  • 20213D Printed Graphene-Coated Flexible Lattice as Piezoresistive Pressure Sensor15citations
  • 2021Optimizing harbor seal whisker morphology for developing 3D-printed flow sensor10citations
  • 2021Optimizing harbor seal whisker morphology for developing 3D-printed flow sensor10citations
  • 2021Biomimetic Soft Polymer Microstructures and Piezoresistive Graphene MEMS Sensors using Sacrificial Metal 3D Printing48citations
  • 2021Fabrication of polymeric microstructurescitations
  • 2021Bioinspired PDMS-graphene cantilever flow sensors using 3D printing and replica moulding36citations
  • 2021Bioinspired PDMS-graphene cantilever flow sensors using 3D printing and replica moulding36citations
  • 2020PDMS Flow Sensors With Graphene Piezoresistors Using 3D Printing and Soft Lithography5citations
  • 2019Bioinspired Cilia Sensors with Graphene Sensing Elements Fabricated Using 3D Printing and Casting64citations
  • 2019Fish-inspired flow sensing for biomedical applicationscitations
  • 2019Laser-Sustained Plasma (LSP) Nitriding of Titanium: A Review49citations
  • 2019Laser-sustained plasma (LSP) nitriding of titanium:A review49citations
  • 2017A two-step laser-sustained plasma nitriding process for deep-case hardening of commercially pure titanium23citations
  • 2017Enhancement of CP-titanum wear resistance using a two-step CO2 laser-sustained plasma nitriding process20citations
  • 2016Effect of CO 2 Laser-Sustained Nitrogen Plasma on Heat and Mass Transfer During Laser-Nitriding of Commercially-Pure Titanium8citations

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Sengupta, Debarun
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Kottapalli, Ajay Giri Prakash
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Jayawardhana, Bayu
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Smit, Quinten
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Zheng, Xingwen
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Pei, Yutao T.
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Todd, Judith A.
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Copley, Stephen M.
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Co-Authors (by relevance)

  • Sengupta, Debarun
  • Kottapalli, Ajay Giri Prakash
  • Jayawardhana, Bayu
  • Smit, Quinten
  • Zheng, Xingwen
  • Harish, Vinayak Sagar
  • Cao, Ming
  • Pei, Yutao T.
  • Todd, Judith A.
  • Copley, Stephen M.
  • Segall, Albert E.
OrganizationsLocationPeople

document

Fish-inspired flow sensing for biomedical applications

  • Kottapalli, Ajay Giri Prakash
  • Kamat, Amar M.
Abstract

Intravenous (IV) infusions, wherein the required medication is directly pumped into the patient’s bloodstream at a controlled rate using an infusion pump, represent a ubiquitous element of modern medicinal care. Although infusion pumps are a clinical boon, they are notorious for causing more injuries/deaths and being the subject of more FDA recalls than any other medical device. For instance, out of approximately 1.5 million adverse drug events (ADEs) that are reported to the FDA each year, around 54% are believed to be due to infusion pump errors, a further 61% of which are serious or life-threatening. A primary reason for this situation is that there is no way to verify the 'live rates' of an infusion which often causes over/under infusions and, consequently, costly ADEs. There thus exists a critical need and a market opportunity for a sensor capable of real-time monitoring of IV flows rates to prevent over/under infusions and avoid preventable ADEs.To address this problem, we take inspiration from the blind cavefish which is bestowed with ultrasensitive neuromast flow sensors capable of detecting extremely low water flows down to 1 µm/s. In this work, we develop artificial neuromast-like microelectromechanical systems (MEMS) flow sensors that imbibe the morphology and sensing principles of the blind cavefish, achieving high sensitivity and extremely low threshold detection limits. The MEMS sensor features a tiny hair-like structure that protrudes into the flow and translates the flow induced moment into a measureable voltage using a gold strain gauge patterned on a liquid crystal polymer (LCP) membrane. The sensors are ideal for IV flow sensing by being miniaturized (5mm×5mm), low-cost (< €1), ultrasensitive, biocompatible (polymer), accurate (< 10 ml/hr), low-powered (50 mW) and scalable (batch fabrication). Further, we describe a newly-developed, cleanroom-free, processing flow featuring 3D printing, soft polymer casting, and graphene drop-casting that can be used to fabricate flexible flow sensors. Our ultimate objective is to create low-cost and disposable microsensors that embed within the IV line to measure the real infusion flow rates and correct erroneous dosages through a feedback mechanism. This will allow remote monitoring of infusions, nurse workload reduction, and preventive maintenance. The technology has implications for safe homecare, healthy aging, and nurse shortage alleviation in the EU, and is expected to result in healthcare savings of €3mn per hospital per year, tapping into a market opportunity of €2b/yr.

Topics
  • impedance spectroscopy
  • morphology
  • gold
  • casting
  • aging
  • aging
  • liquid crystal