Centre for Additive Manufacturing
Printed silver/graphene transistor

Research Challenge 4: 

Controlled co-deposition of multimaterials

AIM: To investigate and demonstrate strategies for the macroscale co-deposition of functional and structural materials via piezo driven jetting, high temperature metal-jetting and functionalised multi-photon techniques.

Joint Leads: Chris Tuck and Mark Fromhold

Our goal is to achieve the co-deposition of disparate micro-droplet materials at the macroscale with controlled interactions at the interface, structural integrity and the functional performance required for their applications ranging from optoelectronic devices to pharma/healthcare uses.

By working closely with our industrial partners and building on the micro/nano-scale understanding of materials investigated in RC1, and the macroscale single material functionality gained in RC3 we can develop multifunctional 3D architectures. Multifunctional AM is informed by and feeds into the mathematical and computational frameworks developed in RC2. 

Microchannels that mimic vasculature fabricated using multi material inkjet printing RC4-injetting GIF 345-226
 
 

We have achieved and optimised co-deposition of multimaterials and have developed process strategies for manufacturing various structures, such as heterostructures based on low dimensional materials, and materials enabling controlled drug release, etc. 

To harness the full potential of AM for the co-deposition of functional materials, in RC4 we are further developing manufacturing and post deposition processes to achieve/control functional anisotropy and are expanding the range of materials available for co-deposition. These challenging tasks require optimisation of the process requirements and fundamental understanding of the interfaces between dissimilar materials, and will enable us to control and correlate the functional and structural properties of deposited layers. 

Exemplar arrangement of flakes used to predict conductivity characteristics of ink-jet printed graphene using a percolation Monte Carlo model Exemplar arrangement of flakes used to predict conductivity characteristics of ink-jet printed graphene using a percolation  Monte Carlo model
 
An encapsulated strain sensor made via multi-material inkjet 3D printing using UV conversion RC4 Ehab
 
 

Research Team 

Chris Tuck 120-150

Prof Chris Tuck

University of Nottingham

Mark Fromhold

Prof Mark Fromhold

University of Nottingham

Lyudmila 2020 120-150 

Dr Lyudmila Turyanska

University of Nottingham

 

Geoffrey Rivers 120-150

Dr Geoffrey Rivers

University of Nottingham

Jisun 2020 120-150

Dr Jisun Im

University of Nottingham

Feiran Wang

Dr Feiran Wang

University of Nottingham

 

rsz_1ana_valeria_gonzalez

Ana Valeria Gonzalez

University of Nottingham

 

Jonathan Gosling

Jonathan Gosling

University of Nottingham

Jonathan Austin 120-150

Jonathan Austin

University of Nottingham

 

Nur Fiqoh 120-150

Nur Rofiqoh Eviana Putri

University of Nottingham

 

 

Centre for Additive Manufacturing

Faculty of Engineering
The University of Nottingham
Nottingham, NG7 2RD


email: CfAM@nottingham.ac.uk