Optimization of photocrosslinkable resin components and 3D printing process parameters

Journal Pre-Proof Full length article Optimization of Photocrosslinkable Resin Components and 3D Printing Process Parameters Antonio J. Guerra, Jan Lammel, Alex Katko, Alex Kleinfehn, Ciro A. Rodríguez, Luiz H. Catalani, Matthew L. Becker, Joaquim Ciurana, David Dean PII: DOI: Reference:

S1742-7061(19)30534-3 https://doi.org/10.1016/j.actbio.2019.07.045 ACTBIO 6279

To appear in:

Acta Biomaterialia

Received Date: Revised Date: Accepted Date:

15 February 2019 19 July 2019 24 July 2019

Please cite this article as: Guerra, A.J., Lammel, J., Katko, A., Kleinfehn, A., Rodríguez, C.A., Catalani, L.H., Becker, M.L., Ciurana, J., Dean, D., Optimization of Photocrosslinkable Resin Components and 3D Printing Process Parameters, Acta Biomaterialia (2019), doi: https://doi.org/10.1016/j.actbio.2019.07.045

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2019 Published by Elsevier Ltd on behalf of Acta Materialia Inc.

JOURNAL PRE-PROOF

Optimization of Photocrosslinkable Resin Components and 3D Printing Process Parameters Antonio J. Guerra1,2, Jan Lammel2,5, Alex Katko2, Alex Kleinfehn3, Ciro A. Rodríguez2,5, Luiz H. Catalani4, Matthew L. Becker3, Joaquim Ciurana1, David Dean2,*

F

Authors Affiliations

PR

O

O

1. Mechanical Engineering and Industrial Construction, Universitat de Girona, Girona, Spain. 2. Department of Plastic and Reconstructive Surgery, The Ohio State University, Columbus, OH 43210, United States. 3. Department of Polymer Science, University of Akron, Akron, United States. 4. Department of Fundamental Chemistry, University of Sao Paulo, Sao Paulo, Brazil. 5. Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Monterrey, N.L. 64849, Mexico. *Communicating Author’s Contact Information

E-

Running head Resin Constituent and Process Parameter Optimization

Abstract Words 303 words

R N

Figures 7

AL

Manuscript Words 4165 words

PR

Prepared for submission to Acta Biomaterialia

Tables 4

JO

U

Keywords Poly(propylene fumarate); Polymer Resin; Cytotoxicity; Stereolithography (SLA); Digital Light Processing (DLP); Mask Projection; 3D printing; Additive Manufacturing; Scaffold; Bone Tissue Engineering Abbreviations Stereolithography (SLA), Digital Light Processing (DLP), bisacylphosphine oxide (BAPO), 2hydroxy-4-methoxybenzophenone (HMB), Poly(propylene fumarate) (PPF), diethyl fumarate (DEF), ethyl acetate (EA), Vd (Voxel Depth), Et (Exposure Time), Cd (Cure Depth), Od (Overcure Depth), Rc (Resin Components), Li (Light Intensity), ROP (ring opening polymerization).

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

F

Abstract

PR

O

O

The role of 3D printing in the biomedical field is growing. In this context, photocrosslink-based 3D printing procedures for resorbable polymers stand out. Despite much work, more studies are needed on photocuring stereochemistry, new resin additives, new polymers and resin components. As part of these studies it is vital to present the logic used to optimize the amount of each resin constituent and how that effects printing process parameters.

PR

E-

The present manuscript aims to analyze the effects of poly(propylene fumarate) (PPF) resin components and their effect on 3D printing process parameters. Diethyl fumarate (DEF), bisacylphosphine oxide (BAPO), Irgacure 784, 2-hydroxy-4-methoxybenzophenone (HMB) and, for the first time, in biomedical 3D printing, ethyl acetate (EA), were the resin components under investigation in this study. Regarding printing process parameters, Exposure Time, Voxel Depth, and Overcuring Depth were the parameters studied. Taguchi Design of Experiments was used to search for the effect of varying these resin constituent concentrations and 3D printing parameters on the curing behavior of 3D printable PPF resins.

JO

U

R N

AL

Our results indicate that resins with higher polymer cross-link density, especially those with a higher content of PPF, are able to be printed at higher voxel depth and with greater success (i.e., high yield). High voxel depth, as long as it does not sacrifice required resolution, is desirable as it speeds printing. Nevertheless, the overall process is governed by the correct setup of the voxel depth in relation to overcuring depth. In regards to resin biocompatibility, it was observed that EA is more effective than DEF, the material we had previously relied on. Our preliminary in vitro cytotoxicity tests indicate that the use of EA does not reduce scaffold biocompatibility as measured by standard cytotoxicity testing (i.e., ISO 10993-5). We demonstrate a workpath for resin constituent concentration optimization through thin film tests and photocrosslinkable process optimization.

DRAFT 04.29.2019

Page 2

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

1. Introduction

PR

O

O

F

Current tissue engineering strategies to repair tissue and organs can be broadly categorized into three main approaches: (I) entirely inert devices, (II) cell-based therapy, and (III) the implantation of constructs laden with cells, coatings of those cell’s ECMs (extracellular matrix), and/or growth factors (cytokines) (1). Much work is currently going into the development of new biomaterials and manufacturing techniques, especially the fabrication of three dimensional (3D) resorbable and cellladen scaffolds. One of the better known biomaterials for this work is poly(propylene fumarate) (PPF). Indeed, PPF resin and process parameter optimization for stereolithography (SLA; a.k.a. Stereolithographic Assembly) and/or digital light processing (DLP; a.k.a. mask projection) 3D printing are longstanding areas of biomedical device fabrication research (2). Different photocrosslinkers, co-crosslinkers, solvents, dyes, and functionalization components have been investigated in the attempt to modify 3D scaffold manufacturing, mechanical properties, and/or biological properties. Unlike other photocrosslinkable resin systems, PPF has long shown its relevance to preparing solid-cured scaffolds that are appropriate for bone tissue engineering, including the preparation of cytokine-surface-functionalized scaffolds (3).

JO

U

R N

AL

PR

E-

In 2003, Cooke et al. (4) reported on the first scaffold fabrication via 3D printing of a resorbable material developed for tissue engineering. They used the SLA 3D printing technique with a resin consisting of PPF as the polymer, DEF as a solvent, and BAPO as a photoinitiator. This resin mixture was successfully crosslinked resulting in scaffolds that accurately represented the computer aided design file that was guiding the 3D printer. In so doing, they demonstrated SLA as a viable process to prefabricate custom-fitting, tissue engineered scaffolds for critical-size bone defects. In 2007, Lee et al. (5) also studied the effect of resin formulation and SLA parameters to obtain bone tissue engineering scaffolds. They employed a resin mixture based on PPF, DEF, and BAPO. They observed that PPF/DEF mixtures resins with viscosity up to 1.8 Pa·s are the upper limit for the stereolithography processes. These authors, therefore, chose a PPF/DEF 60:40 ratio with 1 wt% BAPO content. In 2009, Lan et al. (6) designed and fabricated 3D porous scaffolds (65% of porosity) by SLA with PPF:DEF ratio of 70:30 and 1% wt/wt BAPO as a photoinitiator. Scaffolds were well fabricated with a line width of 90 µm, pore size of 250 µm, and layer thickness of 110 µm. Samples showed 25% of isotropic shrinkage compared to the design. These scaffolds were coated with a hydroxyapatite layer. MC3T3-E1 cells showed good cell attachment in the coated scaffold group. In 2012, Dean et al. (7) used continuous digital light processing (cDLP) to manufacture bone tissue engineering scaffolds with high accuracy (60 µm layer thickness). The resin used in that study included PPF, titanium dioxide (TiO2) as a dye, BAPO as a photoinitiator, and DEF as a solvent. Results showed an increase in green strength (i.e., strength during and just after 3D printing and before post-printing exposure to heat or additional light) with respect to PPF scaffolds previously 3D printed by SLA. More recently, the significant reduction in polydispersity offered by ring opening polymerization (ROP) synthesis (8) of PPF has allowed better control over 3D printed scaffold accuracy (9) and resorption kinetics (10). However, despite the longstanding research into PPF 3D printing, the availability of low polydispersity PPF has provided the opportunity to dramatically improve control over scaffold manufacturing accurate, mechanical, and biological properties including resorption kinetics. Understanding how resin component concentrations and 3D printing process parameters effect a photocrosslink-based 3D printing process is crucial. This study aimed to analyze the effect PPF resin component concentration and printing process parameters have on 3D printed scaffold yield. Diethyl fumarate (DEF), bisacylphosphine oxide (BAPO), Irgacure 784, and 2-hydroxy-4-

DRAFT 04.29.2019

Page 3

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

methoxybenzophenone (HMB) and for the first time in biomedical 3D printing, ethyl acetate (EA), were the resin components under investigation. Regarding printing process parameters, Exposure Time, Voxel Depth, and Overcuring Depth were the parameters under investigation. Taguchi’s method for optimizing the Design of Experiments (11) was used to search the effect these components and parameters have on the curing behavior of PPF resins. 2. Materials & Methods

F

2.1.1. Methodology

PR

𝐶𝑑 = 𝐴 · ln(𝐸𝑡 ) − 𝐵

O

O

Photocrosslink-based 3D printing processes work by focusing an Ultraviolet (UV) light or Visible Light onto a vat of photopolymerizable resin. These processes are governed by curing thickness, which is also known as cure depth (Cd). Cd mainly depends on the resin components (Rc), light intensity (Li), and exposure time (Et). With relatively low concentrations of non-polymer components, Rc, and relatively low Li, Cd curve can be approximated by an exponential equation (Figure 1a) as follows: (1)

E-

Where A and B are constants that depend on Rc. Cd should be larger than the layer height, referred to as voxel depth (Vd), in a photocrosslink-based 3D printing process. The scaffold object (i.e., 3D shape) is digitally sliced into layers for 3D printing, and this is done to ensure the correct overcuring depth (Od), thus insuring the proper adhesion, or “stitching”, between layers (Figure 1b) (12).

PR

The modeling of the relationship between cure depth and overcuring depth can be expressed mathematically as follows: (2)

𝑂𝑑 ≥ 𝐶 · 𝐶𝑑

(3)

𝐶𝑑 = 𝑓(𝑅𝑐 , 𝐿𝑖 , 𝐸𝑡 )

(4)

AL

𝑂𝑑 = 𝐶𝑑 − 𝑉𝑑

U

R N

Where C is a constant that depends on the resin formulation and on the contact surface area between consecutive layers (13). Both, resin interlayer crosslinking and the ratio of surface contact area to the overall volume of the part, are obtained empirically. In addition to interlayer crosslinking density, it is important to understand the effects Rc and Et have on Cd for a fixed Li. This makes it possible to demonstrate the strong influence that Vd and Od have on 3D printing yield. This study was able to efficiently accomplish this goal via the following parameter search space methodology for the variables studied (Figure 2).

JO

2.2. Materials

1400 Da (Dalton) Poly(propylene fumarate) (PPF) was synthesized via the previously described ring opening method (8). DEF (Sigma, St. Louis, MO) was selected as solvent and co-crosslinker (i.e., a reactive diluent). Solvents reduce the viscosity of the solution and may also effect the stereochemistry of the photocrosslinking reaction. Therefore, different solvent types and concentrations may promote or inhibit photocrosslinking. Therefore, the use of reactive and non-reactive solvents is hypothesized to provide different results when manufacturing scaffolds. In order to study the effect of other solvents, Ethyl Acetate (EA, Fischer Chemical, Pittsburgh, PA) was used as a second solvent in this study, and to our knowledge, for the first time in biomedical 3D printing. EA is a widely used industrial solvent. It is known to be especially well-suited for use with aliphatic polyesters and

DRAFT 04.29.2019

Page 4

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

polyanhydrides. It is inexpensive, virtually transparent in the UV-Visible light range, and its residues are easily detectable by conventional techniques. EA is highly soluble in water, acetone, and benzene. It is also miscible in ethanol, ethyl ether, and chloroform. It has a relatively high vapor pressure (90 mmHg at 25oC) and relatively low viscosity (0.4 mPa/s at 25ºC) EA has an intermediate dielectric constant of 6.0 and an intermediate LogP of 0.73. Bisacylphosphine oxide (BAPO; Ciba Specialty Chemicals [BASF], Tarrytown, NY), and Irgacure 784 (Ciba Specialty Chemicals [BASF], Tarrytown, NY) were used as photoinitiators. Finally, 2-hydroxy-4-methoxybenzophenone (HMB; Sigma Aldrich, St. Louis, MO) was selected as a light attenuator (a.k.a., dye or pigment).

F

2.3. Design of Experiments

PR

O

O

In order to determine the effects the Rc would have on curing behavior, a Taguchi Method Design of Experiment (DOE) was set up in Quantum XL (Digital Computations Inc., Orlando, FL) (Table 1). Originally developed by Genichi Taguchi (11), this particular Design of Experiment methods has a strong record in efficiently improving the quality of manufacturing processes. This statistical method can help reduce the number of experiments in studies with many input variables, as is the case with resin formulations and 3D printing process parameters.

PR

E-

The Taguchi Design of Experiment Method was chosen with the aim of efficiently searching the resin component concentration space in order to optimize the effect of those variables on single layer cure depth, inter-layer overcuring depth of 3D printed scaffolds, and most importantly 3D printed scaffold yield. The Taguchi Designed (i.e., sub-sampled) experiments begin from the non-subsampled data obtained from initial thin film cure tests, since 3D printing is much more time consuming and expensive than thin film testing.

AL

In order to know the effects that the Vd and Od have on the printability of PPF resins, a Design of Experiment was created (Table 2) employing three random resins, namely, RESIN 03, RESIN 12, and RESIN 13, from Table 1. The random choice was to reduce the number of experiments and prove if Rc has a strong effect on printability. Depending on the resin, different Et should be chosen to keep Cd constant. Printed samples were analyzed qualitatively and categorized as successful or not successful.

R N

2.4. Characterization 2.4.1. 3D Printer

U

Characterization tests, i.e., curing depth tests (Section 2.4.2) and 3D scaffold printability tests (Section 2.4.3), were performed employing a Micro® Printer (EnvisionTEC, Inc., Dearborn, MI) in UV Mode at 500 mW/cm2 of Li.. 2.4.2. Cure Depth Testing

JO

Cure depth tests were performed as previously reported (2). Briefly, transparent rectangular glass slides of 25mm x 75 mm x 1 mm (Fischer Scientific, Pittsburgh, PA) were placed upon the printer basement plate. A 1 mL pipette was used to place four drops of the resin on each slide. Then, four 10 mm2 squares were irradiated at 30, 60, 90 and 120 seconds. Following each cure depth test, the slides were carefully cleaned to remove all the uncured material and covered with another rectangular slide. A Digimatic Series 500 (Mitutoyo, Kawasaki, Japan) digital caliper was used to measure Cd. 2.4.3. 3D Printability Testing

DRAFT 04.29.2019

Page 5

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

Printability tests were done following the technique that Lara-Padilla et al. (13) developed to show that printability of highly porous PPF scaffolds depends on resin formulation, green strength and other properties (e.g., shrinkage) of the polymer as it cures during 3D printing, and the profile of the scaffold´s inter-layer, cross-sectional contact area.

PR

2.4.4. Resin Biocompatibility Testing

O

O

F

To study the effects Vd and Od have on the printability, a high porosity pore geometry with little contact surface between consecutive layers was designed employing the Triply Periodic Minimal Surfaces (TPMS) Schoen Gyroid that had been previously encoded in Matlab® (9). With this scaffold pore geometry, we can control the surface area, the most important variable affecting resorption (10) with only one design parameter, the constant “C”. In the cylindrical scaffolds studied, those features are: pore diameter (700 um), strut diameter (200 um), overall scaffold diameter (4 mm), overall scaffold height (5 mm), and porosity (89%) (Figure 3). This scaffold geometry was selected because it has small but uniform contact surface between layers. The small contact surface area relative to the overall volume of the part makes it more challenging to print via DLP-based 3D printing and thus yield will readily reflect resin constituent optimization.

E-

In order to determine the relative biocompatibility of scaffolds with varying resins component concentrations, biocompatibility tests were undertaken in two steps: (I) Sample preparation (II) Sample Seeding.

AL

PR

Sample Preparation: (I) 10 mm2 thin films were printed, employing resins used for the printability tests; (II) washed in acetone for 10 minutes in static conditions to remove the uncured material; (III) post cured during 40 min in a UV oven at 420 nm of wavelength to ensure complete curing of samples; and, (IV) sterilized by keeping films in PBS for 5 minutes, then they were transferred to a solution of 49% acetone, 21% ethanol and 30% distilled water and sonicated for 25 minutes on a Branson 2800 (Emerson Electric Co., St. Louis, MO). Samples were transferred to PBS and left soaking for 5 minutes. This step was repeated 3 times. Then, the samples were autoclaved in the liquid cycle for 30 minutes at a temperature of 121ºC.

JO

U

R N

Sample seeding: Samples were seeding with 5,000 murine L929 American Type Culture Collection (ATCC, Rockville, MD, USA) fibroblasts counted manually. Adherent 2D controls were likewise processed with the same number of seeded cells. Samples and 2D control were placed in a low attachment well for culture in Dulbecco's Modified Eagle's Medium (DMEM; Gibco, Walthman, MA, USA) supplemented with 10% horse serum, 1% L-glutamine, 1% sodium pyruvate, 50 U/mL penicillin and 50 ug/mL streptomycin (HyClone, Logan, UT, USA). Samples and 2D control were kept at 37 ºC and 5% CO2 atmosphere during 72 hours. After that, cell proliferation was recorded using the PrestoBlue® (Invitrogen, MA, USA) assay and the number of cells present was calculated using a standard curve. Effluent samples were collected in triplicate and measured as per the assay's instructions. Results were reported as average total cells per well. 2.4.5. Statistical

Regression analysis and analysis of variance (ANOVA) were carried out at a 95% confidence level (α=0.05). All data are expressed as mean ± standard error (SE). For all resin component characterization tests four replicas were taken (n = 4). 3. Results & Discussion 3.1. Cure Depth Results

DRAFT 04.29.2019

Page 6

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

Results showed the strong influence the resins’ components and, especially, the exposure time have on the final Cd. Figure 4 shows the increase in Cd as Et increases, according to equation 1. This same trend was observed with non-ROP PPF in previous works (2) .

PR

O

O

F

Although every resin showed different curing behaviors, it was possible to perform the curing depth tests with all of them. This fact proves that every resin that we tested, is predicted to be to be 3D printable with high yield (i.e., within the printable range). This is a major difference with the step growth synthesized material, where the high polydispersity required a lengthy search for printable resin chemistries. Increasing the polymer length and available double bonds in the polymer increases a higher final polymer network density. Although the mechanical properties increase, the degradability also increases, and in bone implant applications this is detrimental as bone won’t be able to fill the space completely. However, considering the exponential behavior of the cure depth curve, some untested resins would not be expected to be 3D printable at the required high Vd due to the highly anisotropic Cd that would be needed to obtain the correct Od. For example, resins 06, 08, 14, 16, and 18 will not be profitable to print samples given that they would need a Cd of more than 150 µm.

E-

Based on Equation 1, the Et needed to obtain a desired Cd can be calculated (Table 3). This table should be useful for future research once it is tied to resorption kinetics, mechanical properties, or other manufacturing properties.

PR

Figure 5 shows the clear influence the DEF, EA, BAPO, and Irgacure 784 have on Cd. Regression analysis showed the strong influence (statistical significance is p<0.05) the DEF, EA, BAPO, and Irgacure 784 have on Cd. However, HMB seems to be significant only in conjunction with BAPO and Irgacure 784. This is as expected from the opposing components of a dye-initiator package as previously shown (14,15).

R N

AL

It is hypothesized that the non-reactive solvent, EA, would be a better performing solvent than DEF in term of final viscosity. However, it was observed that the vapor pressure of EA hindered the resins’ preparation due to it evaporates during the process. As expected the resins with higher EA concentration exhibited higher variability between repetitions than other resins, once it is more complicated to control the quantity of EA during the printing process. However, EA proved to be effective at low concentrations and improves the printability of all resins with no defects. It will be interesting in the future to more specifically delineate conditions in which the effectiveness of EA as a solvent begins to wane as the concentration of solvent decreases through evaporation while 3D printing progresses. Once 3D printing is complete, the concentration of EA is no longer consequential.

U

3.2. 3D Printing Yield Results

JO

To obtain the Cd and the subsequent Od designed in Table 2, cure depth equations from the different resins were used to calculate the Et needed (Table 4). As cure depth equations were obtained empirically from Cure Tests, Et was incremented 10% to compensate for the possible error. For the first two layers, known as build plate starting layers, two times the Et was used to ensure the proper attachment between the scaffold and the build plate. Results from this study show the influence Rc has on the printability of samples. That is, it was observed that higher viscosity resin had an overall higher yield (i.e., reduced occurrence of printing failures). For resins 03 and 13 it was able to 3D print samples at Vd = 50 m as long as the Od exceeded

DRAFT 04.29.2019

Page 7

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

400% (Figure 6a-b). However, resin 12 was not possible to be printed at 50 m of Vd regardless of the Od (Figure 6c). This is due to resins 03 and 13 having a higher viscosity than resin 12 because of their higher content of PPF (Table 1). At 25 m of Vd and with Od beyond 450% every resin worked (Figure 6d).

F

Figure 6 evidences the influence Vd has on the printability of samples when using lower green strength. The reduction of the Vd increases the contact volume between consecutive layers (a.k.a. inter-layer crosslinking or “stitching”), making the printing process more stable irrespective of the resin’s green strength. This fact identifies Vd one of the most important 3D printing process parameters in DLP 3D printing, as it determines inter-layer contact surface area.

O

O

In regards to Od, our results (Figure 6) show a strong influence that this parameter has on 3D printability. The best example of this is the counter-intuitive finding that Rc or Vd, Od must be higher than 400% for PPF resins (Figures 6e and 6f).

PR

3.3. Resin Biocompatibility Results

PR

E-

Results showed that EA is an adequate solvent for PPF resin preparation. Figure 7 showed that cytotoxicity did not decrease as the quantity of EA increased in the tested resins. Figure 7 showed cell viability and cell proliferation depend on the resins’ components. It seems that the EA we are using leaves no toxic or other unsafe residues. This may be caused by the high vapor pressure of EA. Its high vapor pressure produces rapid evaporation during the printing process, completely leaving the implant during printing and/or post-processing.

AL

Once a particular therapy is identified, such as bone tissue engineering, further work to examine how resin component concentrations affect bone progenitor cell viability and proliferation would be useful. However, at this stage there is no reason to think that cytotoxicity due to the solvent, EA, will be significant, and points for it to be safely applied in stereolithography for cytocompatible scaffold preparation, as it’s likely no EA present at the end. 4. Conclusions

U

R N

The present manuscript has analyzed the effects of the following resin components: poly(propylene fumarate) (PPF), diethyl fumarate (DEF), ethyl acetate (EA), bisacylphosphine oxide (BAPO), Irgacure 784, and 2-hydroxy-4-methoxybenzophenone (HMB), and the most important 3D printing process parameters, namely, Exposure Time, Voxel Depth, and Overcuring Depth have on Cure Depth (Cd) and 3D printability.

JO

Results have shown the strong effect the concentration of resin components has on the single layer curing behavior of PPF resins. However, inter-layer surface area and green strength also have a strong effect on 3D printability. As noted in previous works, the correct combination of BAPO, Irgacure 784, and HMB (i.e., dye-initiator packages) is critical in this regard. Nevertheless, within these ranges of resin constituents, all of the tested resins were “printable”. Therefore, printability also depends critically on the optimization of voxel depth. In regards to 3D printing process parameters, resins’ components, voxel depth, and overcuring depth have a strong influence on printability. Increasing green strength is highly correlated with higher PPF concentration. Regardless of resin components in the optimized range or voxel depth, overcuring depth of 400% also appears critical. A new PPF resin solvent, ethyl acetate, was found to have a strong effect on viscosity and is also biocompatible. Finally, it should be noted that a 3 day ISO

DRAFT 04.29.2019

Page 8

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

10993-5 cytotoxicity test is not a complete biocompatibility study. As noted in section 3.3, that process can commence once a particular therapeutic application has been chosen. It may begin with further in vitro studies using cells specific to the therapy. If successful that work ma y continue to in vivo small animal model to test for inflammation and other signs of biocompatibility problems and sampling of organ accumulation of degraded materials, associated deleterious effects, as well as the ability of the construct to facilitate the intended therapy. Finally, the candidate device would be tested in the same way in the most appropriate large animal model of the intended human application.

F

5. Disclosures

O

Drs. Dean and Becker have founded a company, 3DBioResins [21MedTech, LLC, Akron, OH], that produces Ring Opening Polymerization-synthesized PPF. Both Drs. Dean and Becker hold founders equity in this company.

O

6. Acknowledgements

7. References

PR

E-

PR

AG acknowledges the financial support from the Ministry of Economy and Competitiveness (MINECO) and the Government of Spain for a PhD scholarship and grants from DPI2016-77156-R and EEBB-I-18-12797. Also, the authors want to thank the financial support from the University of Girona (Spain) MPCUdG2016/036. DD and MLB acknowledge partial support was provided by the Akron Functional Materials Center. DD received partial support from the Army, Navy, NIH, Air Force, VA, and Health Affairs to support the AFIRM II effort under award Nº. W81XWH-14–20004. DD and LHC acknowledge partial support from FAPESP-OSU Global Gateway grant #2015/50241-0. The US Army Medical Research Acquisition Activity is the awarding and administering acquisition office for award Nº. W81XWH-14–2-0004. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the US Department of Defense.

Pereira RF, Bártolo PJ. 3D Photo-Fabrication for Tissue Engineering and Drug Delivery. Engineering. 2015;1(1):090–112.

2.

Eric J. Mott, Mallory Busso, Xinyi Luo, Courtney Dolder, Martha O.Wang, John P.Fisher, David Dean. Digital micromirror device (DMD)-based 3D printing of poly(propylene fumarate) scaffolds. Mater Sci Eng C [Internet]. 2016;61:301–11.

R N

Xu Y, Luong D, Walker JM, Dean D, Becker ML. Modification of Poly(propylene fumarate)-Bioglass Composites with Peptide Conjugates to Enhance Bioactivity. Biomacromolecules. 2017;18(10):3168– 77.

U

3.

AL

1.

Cooke MN, Fisher JP, Dean D, Rimnac C, Mikos AG. Use of Stereolithography to Manufacture Critical-Sized 3D Biodegradable Scaffolds for Bone Ingrowth. J Biomed Mater Res - Part B Appl Biomater. 2003;64(2):65–9.

JO

4.

5.

Lee KW, Wang S, Fox BC, Ritman EL, Yaszemski MJ, Lu L. Poly(propylene fumarate) bone tissue engineering scaffold fabrication using stereolithography: Effects of resin formulations and laser parameters. Biomacromolecules. 2007;8(4):1077–84.

6.

Lan PX, Lee JW, Seol Y-J, Cho D-W. Development of 3D PPF/DEF scaffolds using microstereolithography and surface modification. J Mater Sci Mater Med. 2009;20(1):271–9.

7.

Dean D, Wallace J, Siblani A, Wang MO, Kim K, Mikos AG, John P. Fisher. Continuous digital light processing (cDLP): Highly accurate additive manufacturing of tissue engineered bone scaffolds. Virtual Phys Prototyp [Internet]. 2012;7(1):13–24.

DRAFT 04.29.2019

Page 9

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

Luo Y, Dolder CK, Walker JM, Mishra R, Dean D, Becker ML. Synthesis and Biological Evaluation of Well-Defined Poly(propylene fumarate) Oligomers and Their Use in 3D Printed Scaffolds. Biomacromolecules. 2016;17(2):690–7.

9.

Walker JM, Bodamer E, Kleinfehn A, Luo Y, Becker M, Dean D. Design and mechanical characterization of solid and highly porous 3D printed poly(propylene fumarate) scaffolds. Prog Addit Manuf. 2017;2(1–2):99–108.

10.

Walker JM, Bodamer E, Krebs O, Luo Y, Kleinfehn A, Becker ML, Dean D. Effect of Chemical and Physical Properties on the In Vitro Degradation of 3D Printed High Resolution Poly(propylene fumarate) Scaffolds. Biomacromolecules. 2017;18(4):1419–25.

11.

Rao RS, Kumar CG, Prakasham RS, Hobbs PJ. The Taguchi methodology as a statistical tool for biotechnological applications: A critical appraisal. Biotechnol J. 2008;3(4):510–23.

12.

P.F. J. Rapid Prototyping & Manufacturing: Fundamentals of StereoLithography. 1992.

13.

Lara-Padilla H. Fabrication of Porous Scaffolds using Additive Manufacturing with Potential Applications in Bone Tissue Engineering. Tecnologico de Monterrey, Mexico; 2018.

14.

Wallace J, Wang MO, Thompson P, Busso M, Belle V, Mammoser N, Kim K, Fisher JP, Siblani A, Xu Y, Welter JF, Lennon DP, Sun J, Caplan AI, Dean D. Validating continuous digital light processing (cDLP) additive manufacturing accuracy and tissue engineering utility of a dye-initiator package. Biofabrication. 2014;6(1).

15.

Dean D, Mott E, Luo X, Busso M, Wang MO, Vorwald C, Ali Siblani, John P. Fisher. Multiple initiators and dyes for continuous Digital Light Processing (cDLP) additive manufacture of resorbable bone tissue engineering scaffolds: A new method and new material to fabricate resorbable scaffold for bone tissue engineering via continuous Digital Light Processing. Virtual Phys Prototyp. 2014;9(1):3–9.

PR

450 375 300 225 150 75 -

50

Et (sec)

R N

0

AL

Cd (µm)

E-

PR

O

O

F

8.

(a)

100

Vd Cd

Cured Resin

LAYER 1

Od

Uncured Resin

LAYER 2

150

Light Source

(b)

JO

U

Figure 1. Photocrosslink-Based Processes (a) Curing Depth Curve (b) Photocrosslink-Based 3D printing Scheme. Note the critical overcure depth (Od) between layers in Figure 1b. That depth insures the crosslinking of layers to one another as the object is being built.

DRAFT 04.29.2019

Page 10

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

5 Factors 3 Levels 2 External Points 20 Different Resins

Guerra Et Al.

Three Resins Voxel Depth Overcuring Depth

Four Exposure Times Curing Depth Curves Curing Depth Tests

Resin Preparation

Printability Tests

z

O

F

Figure 2. The Taguchi Design of Experiments Method was used to Optimize Scaffold Manufacturing Parameters to insure maximum scaffold yield (i.e., lowest part failure rate).

x

x

Front View

PR

O

y

Superior View

3D View

R01 R11

R03 R13

R04 R14

R05 R15

R06 R16

R07 R17

R08 R18

R09 R19

R10 R20

AL

400 300

200

R N

Cure Depth (um)

500

R02 R12

PR

E-

Figure 3. Scaffolds for 3D Printability Tests

100 -

20

40

60 80 Exposure Time (sec)

100

120

140

Figure 4. Curing Depth Curves

JO

U

0

DRAFT 04.29.2019

Page 11

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

30 sec

60 sec

90 sec

Guerra Et Al.

120 sec

5

10

15

20 DEF (%)

25

30

0.7 HMB (%)

1.2

O 15 25 Ethyl Acetate (%)

35

E-

(c)

2

3 BAPO (%)

4

5

AL

1

PR

Cure Depth (µm)

O 5

(b) 300 270 240 210 180 150 120 90 60 30 0

300 270 240 210 180 150 120 90 60 30 0

PR

Cure Depth (µm)

0.2

(d)

Cure Depth (µm)

Cure Depth (µm)

(a) 300 270 240 210 180 150 120 90 60 30 0

35

F

Cure Depth (µm)

300 270 240 210 180 150 120 90 60 30 0

270 240 210 180 150 120 90 60 30 0 0.15 0.25 0.35 0.45 0.55 0.65 Irgacure (%)

(e)

JO

U

R N

Figure 5. Testing the Effect of Each Resin Component: (a) DEF in samples with 0.7% HMB, 20% Ethyl Acetate, 3% BAPO. and 0.4% Irgacure 784 (b) HMB in samples with 20% DEF, 20% Ethyl Acetate, 3% BAPO, and 0.4% Irgacure 784 (c) Ethyl Acetate in samples with 0.7% HMB, 20% DEF, 3% BAPO, and 0.4% Irgacure 784 (d) BAPO in samples with 0.7% HMB, 20% DEF, 20% Ethyl Acetate, and 0.4% Irgacure 784 (e) Irgacure 784 in samples with 20% DEF, 0.7% HMB, 20% DEF, and 3% BAPO.

(a)

DRAFT 04.29.2019

(b)

(c)

Page 12

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

F

(d) (e) (f) Figure 6. Effects Rc, Vd, and Od on Printability (a) RUN 06 (b) RUN 18 (c) RUN 12 (d) RUN 09 (e) RUN 03 (f) RUN 02. Print C and F have clearly failed at some point while the others were completely successful. Indeed, success or failure for this scaffold geometry was binary. There were no partial failures or minor defects.

8 % EA

20 % EA

2.00E+04 1.50E+04

O

Living Cells (#)

2.50E+04

10 % EA

O

1.00E+04

5.00E+03

PR

0.00E+00 03

12 Resin (#)

Cell Seeded in Day 0

13

PR

450 375 300 225 150 75 0

AL

Cd (µm)

E-

Figure 7. Cell Viability Results. Cell alive after 3 days of culture. Resins sample’s Number is according to Table 1.

50

Et (sec)

R N

(a)

100

Vd Cd

Cured Resin

LAYER 1

Od

Uncured Resin

LAYER 2

150

Light Source

(b)

JO

U

Figure 1. Photocrosslink-Based Processes (a) Curing Depth Curve (b) Photocrosslink-Based 3D printing Scheme. Note the critical overcure depth (Od) between layers in Figure 1b. That depth insures the crosslinking of layers to one another as the object is being built.

DRAFT 04.29.2019

Page 13

JOURNAL PRE-PROOF

Guerra Et Al.

PR

O

O

F

Resin Constituent and Process Parameter Optimization

5 Factors 3 Levels 2 External Points 20 Different Resins

E-

Four Exposure Times Curing Depth Curves Curing Depth Tests

Printability Tests

PR

Resin Preparation

Three Resins Voxel Depth Overcuring Depth

JO

U

R N

AL

Figure 2. The Taguchi Design of Experiments Method was used to Optimize Scaffold Manufacturing Parameters to insure maximum scaffold yield (i.e., lowest part failure rate).

DRAFT 04.29.2019

Page 14

JOURNAL PRE-PROOF

Guerra Et Al.

z

O

O

F

Resin Constituent and Process Parameter Optimization

x

x

Front View

PR

y

Superior View

3D View

JO

U

R N

AL

PR

E-

Figure 3. Scaffolds for 3D Printability Tests

DRAFT 04.29.2019

Page 15

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

R01 R11

R03 R13

R04 R14

R05 R15

R06 R16

R07 R17

R08 R18

R09 R19

R10 R20

F

400

300

O

200 100 20

40

60 80 Exposure Time (sec)

100

120

140

PR

0

O

Cure Depth (um)

500

R02 R12

Guerra Et Al.

JO

U

R N

AL

PR

E-

Figure 4. Curing Depth Curves

DRAFT 04.29.2019

Page 16

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

30 sec

60 sec

90 sec

Guerra Et Al.

120 sec

5

10

15

20 DEF (%)

25

30

0.7 HMB (%)

1.2

O O 15 25 Ethyl Acetate (%)

35

E-

300 270 240 210 180 150 120 90 60 30 0

5

(c)

2

3 BAPO (%)

4

AL

1

PR

Cure Depth (µm)

(b)

300 270 240 210 180 150 120 90 60 30 0

PR

Cure Depth (µm)

0.2

(d)

5

Cure Depth (µm)

Cure Depth (µm)

(a) 300 270 240 210 180 150 120 90 60 30 0

35

F

Cure Depth (µm)

300 270 240 210 180 150 120 90 60 30 0

270 240 210 180 150 120 90 60 30 0 0.15 0.25 0.35 0.45 0.55 0.65 Irgacure (%)

(e)

JO

U

R N

Figure 5. Testing the Effect of Each Resin Component: (a) DEF in samples with 0.7% HMB, 20% Ethyl Acetate, 3% BAPO. and 0.4% Irgacure 784 (b) HMB in samples with 20% DEF, 20% Ethyl Acetate, 3% BAPO, and 0.4% Irgacure 784 (c) Ethyl Acetate in samples with 0.7% HMB, 20% DEF, 3% BAPO, and 0.4% Irgacure 784 (d) BAPO in samples with 0.7% HMB, 20% DEF, 20% Ethyl Acetate, and 0.4% Irgacure 784 (e) Irgacure 784 in samples with 20% DEF, 0.7% HMB, 20% DEF, and 3% BAPO.

DRAFT 04.29.2019

Page 17

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

(b)

(c)

F

(a)

Guerra Et Al.

JO

U

R N

AL

PR

E-

PR

O

O

(d) (e) (f) Figure 6. Effects Rc, Vd, and Od on Printability (a) RUN 06 (b) RUN 18 (c) RUN 12 (d) RUN 09 (e) RUN 03 (f) RUN 02. Print C and F have clearly failed at some point while the others were completely successful. Indeed, success or failure for this scaffold geometry was binary. There were no partial failures or minor defects.

DRAFT 04.29.2019

Page 18

JOURNAL PRE-PROOF

Resin Constituent and Process Parameter Optimization

Guerra Et Al.

Living Cells (#)

2.50E+04

8 % EA

20 % EA

2.00E+04 1.50E+04

10 % EA

1.00E+04

Cell Seeded in Day 0

5.00E+03 0.00E+00 03

12 Resin (#)

13

Table 1. Taguchi Design of Experiments. E.A (%) 10 30 10 30 10 30 10 30 20

BAPO Irgacure 784 (%) (%) 4.5 0.6 4.5 0.2 1.5 0.6 1.5 0.2 1.5 0.2 1.5 0.6 4.5 0.2 4.5 0.6 3 0.4

PPF (%) 74.55 54.95 76.85 57.25 57.95 37.55 54.25 33.85 67.90

Resin (#) 10 11 12 13 14 15 16 17 18

DEF (%) 32 20 20 20 20 20 20 20 20

HMB (%) 0.70 0.28 1.12 0.70 0.70 0.70 0.70 0.70 0.70

E.A (%) 20 20 20 8 32 20 20 20 20

PR

HMB (%) 0.35 0.35 1.05 1.05 0.35 0.35 1.05 1.05 0.70

E-

DEF (%) 10 10 10 10 30 30 30 30 8

BAPO Irgacure 784 (%) (%) 3 0.4 3 0.4 3 0.4 3 0.4 3 0.4 1.2 0.4 4.8 0.4 3 0.16 3 0.64

PPF (%) 43.90 56.32 55.48 67.90 43.90 57.70 54.10 56.14 55.66

JO

U

R N

AL

PR

Resin (#) 01 02 03 04 05 06 07 08 09

O

O

F

Figure 7. Cell Viability Results. Cell alive after 3 days of culture. Resins sample’s Number is according to Table 1.

DRAFT 04.29.2019

Page 19

JOURNAL PRE-PROOF

Guerra Et Al.

Od (%) 300 450 600 300 450 600 300 450 600

Run (#) 10 11 12 13 14 15 16 17 18

Resin (#) 12 12 12 13 13 13 13 13 13

PR

Vd (um) 25 25 25 50 50 50 25 25 25

E-

Resin (#) 03 03 03 03 03 03 12 12 12

Vd (um) 50 50 50 25 25 25 50 50 50

Od (%) 300 450 600 300 450 600 300 450 600

JO

U

R N

AL

PR

Run (#) 01 02 03 04 05 06 07 08 09

O

Table 2. Design of Experiments for Voxel Depth and Overcuring Depth Tests.

O

F

Resin Constituent and Process Parameter Optimization

DRAFT 04.29.2019

Page 20

JOURNAL PRE-PROOF

Guerra Et Al.

Table 3. Coefficients of DOE Resins A (#)

B (#)

Et (s) [Cd 150 µm]

01 02 03 04 05 06 07 08 09 10

81.721 101.25 132.18 193.69 228.48 108.46 92.792 60.750 104.25 113.20

203.19 302.62 384.28 619.24 700.19 373.51 220.58 182.39 273.66 347.13

75.33 87.38 56.94 53.06 41.31 124.8 54.25 237.8 58.20 80.77

RESIN (#)

A (#)

B (#)

PR

RESIN (#)

O

O

F

Resin Constituent and Process Parameter Optimization

115.40 113.01 110.53 -1.304 193.65 63.930 113.37 97.684 112.08 113.76

273.20 261.93 222.18 -102.35 606.55 196.51 296.93 331.73 320.90 322.62

39.14 38.29 29.00 49.74 225.9 51.53 138.5 66.78 75.33

JO

U

R N

AL

PR

E-

11 12 13 14 15 16 17 18 19 20

Et (s) [Cd 150 µm]

DRAFT 04.29.2019

Page 21

JOURNAL PRE-PROOF

Guerra Et Al.

O

F

Resin Constituent and Process Parameter Optimization

Od (%) 300 450 600 300 450 600 300 450 600

Cd (um) 75.00 112.5 150.0 150.0 225.0 300.0 75.00 112.5 150.0

A () 132.18 132.18 132.18 132.18 132.18 132.18 113.01 113.01 113.01

B () 384.28 384.28 384.28 384.28 384.28 384.28 261.93 261.93 261.93

Et (s) 35.51 47.16 62.63 62.63 110.4 194.8 21.68 30.22 42.11

Run (#) 10 11 12 13 14 15 16 17 18

Resin (#) 12 12 12 13 13 13 13 13 13

Vd (um) 50 50 50 25 25 25 50 50 50

Od (%) 300 450 600 300 450 600 300 450 600

Cd (um) 150.0 225.0 300.0 75.00 112.5 150.0 150.0 225.0 300.0

PR

Vd (um) 25 25 25 50 50 50 25 25 25

E-

Resin (#) 03 03 03 03 03 03 12 12 12

A () 113.01 113.01 113.01 110.53 110.53 110.53 110.53 110.53 110.53

B () 261.93 261.93 261.93 222.18 222.18 222.18 222.18 222.18 222.18

Et (s) 42.11 81.78 158.8 16.18 22.72 31.89 31.89 62.87 123.9

JO

U

R N

AL

PR

Run (#) 01 02 03 04 05 06 07 08 09

O

Table 4. Exposure Times Needed To Obtain The Desired Curing Depths Following Creation of the Build Plate Starting Layers.

DRAFT 04.29.2019

Page 22