Modelling the 3D printing of nanocellulose hydrogels

Transcription

1 Modelling the 3D printing of nanocellulose hydrogels Tatu Pinomaa VTT Technical Research Centre of Finland Ltd

2 Contents Motivation Nanocellulose-based hydrogels Material characterisation CFD models Printer head Deposition process Validation experiments Conclusions 2

3 Motivation Bio-based dispersions for direct-write-printable structures with embedded sensing for health care applications (BioDisp3D) Academy of Finland, VTT and the University of Tampere; years Goal: to study the potential of nanocellulose-based pastes for the fabrication of sheets or 3D structures with special functionality for medical applications For example: Custom wound pads with the possibility to monitor healing without removing the pad. For large, hard-to-treat wounds. Modelling goals Predict the 3D printability of the material candidates Predict the sensitivity of the outcome to the process parameters 3

4 Direct write paste -technology Direct write technique for printing pastes Micro-dispensing environment based on nscrypt technology Prints 3D structures on 2D and 3D surfaces Post-treatments are usually needed (drying, sintering, UVcuring, laser, etc.) Compatible with all kinds of Nordson EFD tips and needles Line widths from 20 to 3000 μm, thicknesses from 5 μm upwards 4

5 Nanocellulose hydrogels Three-dimensional networks that consist of nanostructured forms of cellulose in a water matrix Reference material (TCNF) TEMPO-oxidised cellulose nanofibrils in water Produced from never-dried bleached hardwood kraft pulp Dry matter content of 1.06 wt-% 5

6 Rheometry Material models based on rheological characterisation Dynamic viscosity as a function of shearing conditions (incl. transient) Yield stress behaviour Anton Paar MCR-301 rheometer vane spindle and concentric cylinder geometries Measuring procedure Pre-shear at 100 s -1 for 60 seconds Rest period at 0.01% strain and 1 Hz for 300 seconds Gel strength: shear strain sweep from 0.01% to 100% at 1 Hz frequency Viscosity: shear rate sweep from s -1 to 3160 s -1 Dispersing with an impeller, Ultra-Turrax and a sonifier 6

7 Viscosity: steady-state behaviour How does the paste settle? Apparent power-law fluid in the measured range Dependence on measurement geometry η = kγ n 1 k cc, n cc k va, n va How far does the power-law hold? How does it level?

8 Goniometry Contact angle in a sessile drop experiment

9 CFD models for the printer heads Cylindrical steel tip Conical plastic tip Axisymmetric mesh 9 One-phase system of hydrogel Driven by a constant velocity boundary condition Volume of fluid (VOF) method used for compatibility with the deposition model No turbulence modelling applied Used to predict the dependence of hydrogel mass flux on the operating pressure Employs the open-source software OpenFOAM 2.3.x

10 Analytical solution for power-law fluids Q s = πr s 3 1 n + 3 Q t = πr t 3 1 n + 3 ΔP 2 1 r s 2l s k ΔP 1 0 r t 2l t k 1 n 1 n Q s = Q t ΔP 2 1 = ΔP 1 0 = 1 n + 3 πr s 3 1 n + 3 πr t 3 n n 2l s k r s 2l t k r t Q s n Q t n l s l t P 2 P 1 d s d t P 0 v t, Q t v s, Q s 10

11 CFD model for the deposition process Printer head boundary condition 11 Two-phase system of hydrogel and air Volume of fluid (VOF) method & Reynoldsaveraged stress (RAS) model for turbulence Mobile substrate and air flow boundary conditions used to simulate printer head movement Wettability of the plastic substrate determined by an experimental contact angle Used to establish a connection between the paste rheology, printing parameters and the line profile

12 Validation experiments Step 1: pressure-massflux dependency Hydrogel printed on the substrate for a fixed time at various operating pressures, then weighed 12

13 Validation results Step 1: pressure-massflux dependency (analytical predictions based on rheometry) 200 μm steel tip 510 μm steel tip 13

14 Validation results Step 1: pressure-massflux dependency (analytical predictions based on rheometry) 200 μm steel tip 510 μm steel tip Pressure loss is dictated by the asymptotic behaviour of viscosity at high shear rates 14

15 Validation results Step 1: pressure-massflux dependency (numerical predictions based on rheometry & the massflux data) 510 μm steel tip 200 μm steel tip Behaviour explained by an effective power-law model with viscosity cut-offs and slightly slower shear-thinning 15

16 Validation results Step 1: pressure-massflux dependency Effective power-law fluid model with viscosity cut-offs at both low and high shear rates 16 Viscosity curves of CNF suspensions: rheometry with the parallel plate geometry Kumar et al. (2016) Ind Eng Chem Res 55:3603

17 Validation results Step 2: printing parameters-line profile dependency Option A: 2D image analysis (for the TCNF gel) Option B: 3D profilometry (for more rigid gels) 17

18 Validation results Step 2: printing parameters-line profile dependency Sensitive to the contact angle value Roughly 100 μm resolution feasible with successful massflux prediction 18

19 Conclusions & further work Modelling the 3D printing of nanocellulose hydrogels is feasible with currently available CFD tools Conventional rheometry is not necessarily a sufficient basis for the needed rheology models High shear rate behaviour dominates the flow within the printer head Low shear rate behaviour dominates the deposition process To be considered Rheometry (or capillary viscosimetry) at higher shear rates Thixotropic effects Boundary conditions at solid surfaces (slip etc.) 19

20 Summary Rheometry Goniometry Experiments Rheology model Something Printer head model Deposition model CFD simulations Predicts hydrogel mass flow for a given operating pressure Predicts deposition profile for given printing conditions