J. of Supercritical Fluids 160 (2020) 104786 Contents lists available at ScienceDirect The Journal of Supercritical Fluids journal homepage: www.elsevier.com/locate/supflu Surface morphology and drug loading characterization of 3D-printed methacrylate-based polymer facilitated by supercritical carbon dioxide Truc T. Ngo a,∗ , Lauren Hoffman a , Gordon D. Hoople b , William Trevena a , Udeema Shakya a , Gregory Barr a a Department of Industrial and Systems Engineering, Shiley-Marcos School of Engineering, University of San Diego, 5998 Alcala Park, San Diego, CA, USA b Department of Integrated Engineering, Shiley-Marcos School of Engineering, University of San Diego, 5998 Alcala Park, San Diego, CA, USA h i g h l i g h t s g r a p h i c a l a b s t r a c t • Drug loading, surface roughness are tunable with 3DP and scCO2 process parameters. • Thicker 3DP layer settings are more desired due to lower surface rough- ness and cost. • Higher scCO2 process temperature results in higher drug loading but rougher surface. • Drug loading and surface roughness are modeled after 3DP and CO2 pro- cess parameters. a r t i c l e i n f o a b s t r a c t Article history: Polymers have been shown to have viable applications in the biomedical ﬁeld, from controlled drug Received 14 November 2019 delivery systems to biological implants. The preparation and processing of polymers into bio-systems Received in revised form 5 February 2020 have nevertheless encountered some technical challenges in part customization and adverse effects to Accepted 10 February 2020 the human body functions and recovery. This study proposes the utilization of 3D printing technology and Available online 12 February 2020 supercritical carbon dioxide (scCO2 ) processing to deliver a drug-impregnated polymeric material system which can be engineered and tuned to suit a particular implantation procedure and dramatically improve Keywords: patient outcomes. In this work, an acrylate-based polymer is 3D-printed using stereolithography, then Polymer Supercritical carbon dioxide impregnated with ﬂurbiprofen drug using scCO2 . Drug loading above 24 % by mass is achievable under the Flurbiprofen tested conditions. The correlation of drug loading and material surface roughness with different process Drug loading parameters, including 3D printing layer thickness, scCO2 processing temperature, pressure and treatment Surface roughness time, are investigated and empirically modeled using the linear regression methods. © 2020 Elsevier B.V. All rights reserved. 1. Introduction The last decade has seen rapid innovation in 3D printing tech- nologies [1–4]. Originally used primarily for rapid prototyping during the design process, the technology has evolved to be a key ∗ Corresponding author. manufacturing tool across multiple industries . There are now E-mail address: firstname.lastname@example.org (T.T. Ngo). https://doi.org/10.1016/j.supﬂu.2020.104786 0896-8446/© 2020 Elsevier B.V. All rights reserved. 2 T.T. Ngo, L. Hoffman, G.D. Hoople et al. / J. of Supercritical Fluids 160 (2020) 104786 hundreds of different 3D printing approaches that can be used to higher the partitioning coefﬁcient (deﬁned as the ratio of solute print metals, plastics, ceramics, and even living biological speci- concentrations between the polymer phase and the ﬂuid phase), mens [2,4]. One major advantage of utilizing 3D printed parts is the higher the drug loading. Drug impregnation yield can be con- the ability to create geometries with sharp corners, overhangs, trolled and optimized by manipulating operating temperature and or undercuts that would be difﬁcult to manufacture using tradi- pressure, making the process adaptable to different polymer/API tional approaches such as casting, machining or casting . For systems and suitable for a variety of material applications [5,21,22]. many 3D printed parts with such geometry, it is often necessary Secondly, scCO2 processing leaves the implant free of any resid- to print support material to prevent the layers from collapsing as ual compounds that could potentially have a negative impact they are deposited. Polymers are particularly well suited to 3D on patient health and safety . Additionally, in comparison to printing due to their chemical makeup . Thermoplastic poly- traditional impregnation processes using organic solvents, scCO2 mers can be heated and extruded through a nozzle while thermoset processing has signiﬁcant sustainability and processing advan- polymers can be polymerized in a carefully controlled manner. tages. Since the Industrial Evolution, 81 % of all greenhouse gas that Many polymer-based 3D printing approaches take a layer by layer humanity has produced has been CO2 , and greenhouse gas emis- approach where parts are created by slicing the geometry into thin sions are projected to increase by 50 % by 2050 with a 70 % increase (0.001 – 0.100 mm) layers. The part is then “printed” by stacking in CO2 emissions alone . CO2 concentration in the atmosphere these layers one on top of the other. 3D printed materials often has been linked to an increase in global temperature and other show strong anisotropic behavior due to this layer-based approach, signiﬁcant environmental consequences [24,25]. The beneﬁcial uti- an ongoing challenge for these materials . lization of this abundant greenhouse gas not only reduces the 3D printing has emerged as a particularly promising technology amount of greenhouse gas emissions into the atmosphere, but also for biomedical applications . The nature of many implantable reduces the amount of waste output from a material treatment pro- health interventions is that they must be customized to the indi- cess. ScCO2 processing can be conducted in closed loop systems, in vidual patient and they often have complicated geometries. 3D which the output CO2 gas stream from the process can be captured, printing is ideally suited to satisfy this need by allowing for the scrubbed, ﬁltered, pressurized and recycled back into the process creation of customized implants with complex geometries on short for continuous usage. In combination with the ﬁnancial beneﬁts of time scales. For example, 3D printed dental implants have made it recycling the processing medium, utilizing scCO2 in drug loading possible for dentists to create custom parts for their patients in a eliminates the need for post-processing puriﬁcation steps that are matter of days instead of weeks . necessary when processing with conventional organic solvents . After implantation, patients typically receive pharmacological This study focuses on examining the ways in which a 3D printed treatments to inhibit infections, improve the integration of the facsimile of poly(methyl methacrylate) (or PMMA) can be loaded implant into surrounding tissue, or reduce postoperative discom- with the anti-inﬂammatory drug ﬂurbiprofen using supercritical fort . A recent trend in implant design is toward controlled carbon dioxide. Potential applications for the developed materi- drug release systems (CDRS) with active pharmaceutical ingredi- als include targeted drug-controlled release systems and biological ents (APIs) imbedded directly into the implantable device, allowing implants. PMMA was selected due to its biocompatibility, low some of the challenges and risks associated with oral delivery meth- cost, lack of toxic contents, advantageous mechanical properties ods to be avoided [5–8]. and success as a drug carrier [26,27]. Various applications include APIs are typically incorporated into the polymer ﬁlament prior dental prosthetics , contact and intraocular lens , verte- to 3D printing when fused deposition modeling (FDM) is used in bral spacers , scaffolding in tissue engineering  and bone processing [9–11]. This is done mainly by impregnation, such as in cement composite that acts as a space-ﬁller to provide stabiliza- the case of the loading of a polyvinyl alcohol (PVA) ﬁlament with the tion between bone and implant . More recently PMMA has also drug ﬂuorescein by swelling the polymer in a solution of ethanol shown promise as a carrier for therapeutic drugs . Many studies . This process requires that the drug be thermostable so that have explored drug loading of PMMA with APIs for speciﬁc appli- it does not degrade during the 3D-printing process. In addition, cations such as intraocular lenses  and PMMA microspheres impregnation is based on passive diffusion and requires a high con-  as well as more basic science research about the behavior of a centration of drug, making the process time-consuming and costly range of drugs when impregnated in PMMA [36,37]. However, no . Alternatively, the incorporation of therapeutic drugs into 3D- one has reported the impregnation of drug into 3D-printed PMMA printed polymeric materials after printing is accomplished using for applications in the biomedical ﬁeld, especially when supercrit- supercritical ﬂuid technologies. The ﬂuid is selected so that it has ical carbon dioxide is used as a transport medium during the drug a high diffusivity in the chosen polymer and does not damage or loading process. degrade the polymer . Drug impregnation using supercritical ﬂuids has been largely studied for polymeric materials, but there is limited available research for subsequent impregnation of 3D- 2. Materials and methods printed materials with APIs. Supercritical CO2 (scCO2 ) processing has emerged as a promis- 2.1. Materials ing approach for loading drugs into implants [5,15,16] due to several advantages. First, it is a low temperature process, suitable Polymer samples used in the experiments were prepared from for thermosensitive drugs that would be damaged or destroyed in a proprietary Clear Resin v4, appearing as light yellow liquid resin, traditional, high temperature drug loading processes. CO2 has a rel- supplied by Formlabs, Inc (Massachusetts, USA). Clear Resin v4 con- atively low critical pressure and temperature (Pc =73.8 bar, Tc =304 tains a mixture of monomers, oligomers of methacrylic acid esters K), allowing for a low energy transition to a supercritical region. and photoinitiator, with boiling point and ﬂash point > 373 K, den- Relatively high drug solubilities can be achieved in scCO2 . In the sity of 1.09–1.12 g/cm3 and viscosity of 850–900 cps. Flurbiprofen case of ﬂurbiprofen, solubility of 0.022 g/L to 0.90 g/L in scCO2 are (C15 H13 FO2 , CAS 5104-49-4) was purchased from Sigma-Aldrich possible without the use of co-solvents for temperature range of (USA) in white powder form with a melting temperature range of 303–323 K and pressure range of 88–245 bar [17,18]. Drug loading 383–385 K, and was used without further puriﬁcation. ACS reagent- of polymers in scCO2 is made possible by the CO2 -induced swelling grade liquid ethanol (C2 H6 O, CAS 64-17-5) was obtained from of polymer matrix and the favorable partitioning of drug molecules Arcos Organics (USA), 99.5 % purity, and was used as the solvent (i.e. solutes) in the polymer phase over the ﬂuid phase [5,19,20]. The for ﬂurbiprofen and drug loading determination. Isopropyl alcohol T.T. Ngo, L. Hoffman, G.D. Hoople et al. / J. of Supercritical Fluids 160 (2020) 104786 3 Fig. 1. SEM for non-treated polymer samples 3D-printed with different layer thicknesses. (C3 H8 O, 91 % pure, purchased from Target in San Diego, Califor- h drying the support material was removed using a small needle nia, USA) was used to wash 3D-printed samples post printing. USP nose clipping tool. No UV post cure was applied. medical grade carbon dioxide, purchased from Airgas (San Diego, Printed ﬁlm thickness was measured at two to three different California, USA) with > 99.9 % purity, was used in all scCO2 treat- points on each sample using a ball-tip digital micrometer with mea- ments. surement accuracy of ± 0.004 mm. Locations of measurements on each sample were chosen to avoid areas where the 3D printing manual supports had been attached. Six to ten samples were ran- domly selected from each printing batch. While the starting ﬁles 2.2. Sample preparation to print samples were the same, varying layer thickness setting (0.025 mm, 0.050 mm, 0.100 mm) resulted in a slightly different All polymer samples were printed using a FormLabs Form 2 overall part thickness for each sample and each batch. Result for 3D printer. This printer created parts using a process known as sample thickness measurements is shown in Table 1, with both stereolithography where a laser was used to crosslink polymer pre- within-sample variation and sample-to-sample variation of less cursors in a liquid bath. Polymer crosslinking happened on a ﬂexible than 5%. The overall average sample thickness (combining all sam- polydimethylsiloxane (PDMS) layer at the bottom of the resin tank ple batches) is calculated to be 0.307 ± 0.029 mm. located inside the Form 2 printer. The laser was able to penetrate through the optically clear membrane. In between printed lay- ers, the part was raised on a Z-stage and was brieﬂy peeled away 2.3. Supercritical carbon dioxide processing from the bottom PDMS window. The part was then lowered to 0.025, 0.050 or 0.100 mm away from the window depending on 3D printed polymer samples were ﬁrst cut into two halves along the desired layer thickness. The printing process repeated until the the longest side prior to scCO2 processing. Each sample was cleaned programmed number of layers were completed. with low-pressure compressed air to remove any loose particles on In all cases parts were printed with “Clear Resin v4 which has its surface, and weighed separately prior to loading. ScCO2 process- material properties very similar to poly(methyl methacrylate) (or ing was performed in the same manner described in , as a batch PMMA) with manufacturer-cited , post-cured tensile strength process at a speciﬁc temperature and pressure condition. Two dif- of 65 MPa, Young’s modulus of 2.8 GPa, ﬂexural modulus of 2.2 ferent temperatures were tested (313 K and 323 K), in combination GPa, and 6.2 % elongation at failure (compared to PMMA’s tensile with four different pressure settings (115 bar, 125 bar, 135 bar and strength of 63–78 MPa, Young’s modulus of 3.2–3.4 GPa, ﬂexural 148 bar). All experiments were carried out in 316 stainless steel, modulus of 3.4–3.5 GPa, and 2–6% elongation ). Solidworks was high-pressure reactors equipped with calcium ﬂuoride optical win- used to create a computer-aided design (CAD) model of a thin rect- dows for in-situ system monitoring. Temperature was measured angular part with dimensions of 20 mm × 10 mm × 0.300 mm (L × using a type-K Omega thermocouple and controlled constantly at W×H). The CAD ﬁle was exported as an. STL format and imported an appropriate set point. Processing pressure was monitored using to PreForm, FormLabs 3D printing control software. There the part a digital Keller LEO Record pressure transducer and indicator. was angled to 30◦ relative to the build platform. Six supports points Each reactor was loaded with up to three polymer samples, sep- were manually selected – four at the corners and two at the center arated sufﬁciently from one another inside the reactor chamber to along the longest (20-mm) side – and then the PreForm software avoid any contact during treatment. An excess amount of ﬂurbipro- autogenerated the support structure design and incorporated into fen powder (four times the drug solubility limit under the same the build ﬁle. The part design was copied 27 times across the build temperature and pressure conditions) was loaded into the reactor platform to generate 28 identical parts in one single batch. along with the polymer samples for each experiment to ensure that Three different versions of the part were printed by varying the drug availability was not a limiting factor in the process. This was layer thickness in the print settings: 0.025 mm, 0.050 mm, and veriﬁed by in-situ monitoring of the process, showing ﬂurbipro- 0.100 mm. The 0.025-mm parts required 300 layers to print and fen UV peak absorbance at 250-nm wavelength reached saturation took 3.8 h; the 0.050-mm parts required 182 layers to print and after approximately one hour of pressurization and remained sat- took 3.2 h; and the 0.100-mm parts required 123 layers to print urated throughout the duration of the experiment. The referenced and took 2.9 h. Note that two versions of the 0.100 mm part were solubility data of ﬂurbiprofen in scCO2 was calculated using the printed. The two batches had slight variations in thickness and are model established by Duarte et al. based on Chrastil’s density-based therefore reported separately in Table 1. After printing was ﬁnished approach, as displayed in Table 2 . the parts were physically separated from the support structure on The reactor was purged with CO2 gas prior to pressurization to the build platform. They were then cleaned using the Form Wash remove all air initially inside the reactor chamber. After purging, the tool (also purchased from FormLabs), which consisted of an ultra- reactor was pressurized with CO2 (using a SFT-10 CO2 pump) and sonic bath ﬁlled with 91 % isopropyl alcohol. Parts were submerged heated to a desired setpoint (using four 65 W Omega CSS cartridge in this bath for ten minutes, then removed and allowed to air dry heaters connected to an Omega DP7001 temperature controller). while still attached to the support material. After a minimum of 12 The processing condition was held constant for a pre-determined 4 T.T. Ngo, L. Hoffman, G.D. Hoople et al. / J. of Supercritical Fluids 160 (2020) 104786 Table 1 3D printed polymer sample thickness. 3D printing layer thickness setting 0.025 mm 0.050 mm 0.100 mm(batch i) 0.100 mm(batch ii) Average sample thickness (mm) 0.309 0.273 0.333 0.274 Within-sample standard variation (mm) 0.008 0.006 0.014 0.009 Sample-to-sample standard deviation (mm) 0.006 0.005 0.013 0.009 Table 2 viously reported in similar studies with different material systems Solubility of ﬂurbiprofen in scCO2 at various experimental conditions. [5,17]. Both the average and standard deviation were calculated for Temperature(K) Pressure(bar) Flurbiprofen solubility in scCO2 (g/L) each set of replicate measurements of each sample. 115 0.15 Mass of extracted drug 125 0.19 Drug Loading (%) = × 100 (1) 313 Pre − process mass of polymer 135 0.23 148 0.28 115 0.06 2.4.2. Surface morphology 125 0.13 Scanning electron microscopy (SEM) was used to characterize 323 135 0.20 the surface morphology of pre- and post-processed polymer sam- 148 0.29 ples. The samples were cut in halves or quarters so that imaging of both the internal structure and the surface was possible. Samples were prepared for imaging using sputter deposition with a 60/40 period of time, typically for 24 h. Three to four sample replicates gold/palladium alloy source for two minutes at 25-mA in an argon- were experimented for each of the processing conditions. In addi- rich chamber. Images of the surface and edges of the samples were tion to the 24-h runs, two additional experimental runs with 4-h captured at varying magniﬁcations (100x, 200x, 500x and 1000x) treatment duration were performed (with three replicates per run) using a Hitachi S-3400 N scanning electron microscope at 15-kV to examine the impact of treatment time on drug loading. During setting. all sample processing the solution content was constantly stirred To characterize surface roughness of polymer samples, SEM by two small magnetic stir bars and two micro stir plates. images were analyzed using Motic Images Plus 3.0 ML software. When the experiment was complete, the reactor was removed Surface roughness here is deﬁned as the percentage of top surface from heat and allowed to cool naturally to room temperature. CO2 area of the elevated regions in the whole sample surface, as shown depressurization was done at room temperature and kept at a suf- in Eq. 2: ﬁciently slow rate to prevent foaming of the polymer samples. Top surface area of elevated regions Once the reactor was fully depressurized, polymer samples were Surface Roughness (%) = × 100% (2) Total surface area of sample removed and inspected for any damage. Low-pressure compressed Based on Eq. 2, a higher value of surface roughness typically air was applied to each processed sample thoroughly to remove corresponds to a sample with a rougher overall surface. For each any loose drug particles from its surfaces. The treated samples sample type (either treated or non-treated), SEM images were were then weighed and prepared for post-processing, such as SEM obtained for up to three replicate samples. Within each sample, imaging or ethanol soak for drug loading determination. two to three separate SEM images were taken at various locations on the sample, and three different measurements were extracted 2.4. Material characterization from each SEM image. The reported data was derived from up to 27 measurements for each of the non-treated, scCO2 -only treated 2.4.1. Drug loading or scCO2 -ﬂurbiprofen treated conditions. After being removed from the processing chamber and air- cleaned, scCO2 /drug-treated polymer samples were weighed and 3. Results and discussion compared to pre-processing weights. Although the pre- and post- processing weight measurements did not accurately reﬂect the 3.1. Surface morphology of 3D-printed polymer level of drug loading for each sample, the values were used for crude veriﬁcation of any major sample damage or destruction that had Fig. 1 shows SEM image comparison among non-treated poly- occurred during scCO2 processing. For more accurate quantiﬁca- mer samples 3D-printed (3DP) under 0.025-mm, 0.050-mm and tion of drug loading, treated polymer samples were soaked in 80 mL 0.100-mm layer thickness settings. Thinner layer setting resulted of ethanol solution for 48–72 h at room temperature while sealed in more visible ridges on sample surfaces. This might be explained air-tight. The 48-h minimum soak duration was tested and proven by the fact that the polymer samples were printed at 30◦ angle to be more than adequate for complete drug extraction out of the per manufacturer’s printing recommendation. This angle served polymer phases and dissolution into the ethanol solution phase. to minimize the surface area for each layer, thereby reducing the After drug dissolution was complete, the solution was well stirred chance of part failure during the printing process. Also, the sample and three separate samples were drawn from the stock solution for surface was observed to be more pitted at lower layer thickness repeatability validation. A USB 2000+ Ocean Optics UV–vis spec- settings, most likely due to variations in forces associated with the trometer with UV-transparent optical ﬁbers was used to measure peeling process of the layers as they were removed from the PDMS UV peak absorbance of ﬂurbiprofen at 249-nm wavelength, with 24 print window (see section 2.2). While the cause of this pitting is not scans and an integration time of one second. Dilution of each sample fully understood, it was possible that thinner layers had resulted in was performed as needed based on the level of drug concentration less structural integrity and were more likely to pit when removed and UV peak absorption intensity. Flurbiprofen concentration in from the PDMS window. Qualitative SEM observations correlate solution and the total drug amount extracted from each polymer with the calculated surface roughness for each sample type (using sample were then calculated using a previously established cali- Eq. 2), as shown in Fig. 2. Surface roughness seemed to be relatively bration curve between UV absorbance and ﬂurbiprofen solubility the same for 0.025-mm and 0.050-mm 3DP layer thicknesses. How- in ethanol . Final drug loading is determined based on Eq. 1. ever, it was signiﬁcantly lower (a 44 % reduction) for 0.100-mm 3DP This method of drug loading calculation is consistent to those pre- layer thickness. T.T. Ngo, L. Hoffman, G.D. Hoople et al. / J. of Supercritical Fluids 160 (2020) 104786 5 25 % with ibuprofen (more soluble in scCO2 than ﬂurbiprofen) at 323 K and 138 bar . It was also noted that the PMMA matrices used in these previous studies were prepared using conventional methods such as solution casting and extrusion molding. Although no other 3DP polymer/drug system similar to what was experi- mented in this work had been investigated and reported in the past, the currently observed drug loading capability shows promising results with highly ﬂexible, potential applications in the biomedical ﬁeld. An ANOVA (with replicates) was performed on the collected data to investigate the dependency of drug loading on various input parameters. At 95 % conﬁdence, there was a strong corre- lation between drug loading and scCO2 processing temperature (p-value = 2.58 × 10−8 ). Average drug loading increased by 19 %–88 % when temperature increased from 313 K to 323 K, with the largest impact observed at 135 bar of scCO2 processing pres- Fig. 2. Surface roughness for non-treated 3D-printed polymer samples. sure and polymer samples printed at 0.050-mm layer thickness setting. The positive effect of temperature on drug loading has been widely reported in multiple studies [34,46–49]. Increasing temperature encouraged chain mobility inside the polymer matrix, leading to higher sorption of CO2 inside the matrix. Moreover, temperature also has a positive effect on ﬂurbiprofen solubil- ity in scCO2 at pressures above 110 bar . The combination of a higher presence of drug molecules in the ﬂuid phase and higher CO2 sorption in the polymer resulted in higher drug load- ing inside the polymer matrix. This observation was consistent with past results reported by Ngo et al.  with ﬂurbiprofen- impregnated PMMA-based biocomposites facilitated by scCO2 processing. Higher scCO2 processing pressure (past 115 bar), however, did not always result in higher drug loading as one might have pre- dicted. Increasing pressure under constant temperature would lead to increasing ﬂurbiprofen solubility in scCO2 , according to data reported by Duarte et al. . However, in order for the drug loading Fig. 3. Drug loading for 3DP polymer samples under various scCO2 -ﬂurbiprofen to also increase, the molecular interactions between the drug and 24-h treatments. the polymer matrix must also increase to keep the drug molecules locked into the polymer instead of diffusing back out of the poly- 3.2. Drug loading of ﬂurbiprofen in 3DP polymer facilitated by mer matrix. If these interactions are not improving at a similar rate scCO2 as the interaction between drug and CO2 molecules in the ﬂuid phase, then the ﬂurbiprofen partitioning in polymer may not follow Drug loading data for each scCO2 -ﬂurbiprofen treatment condi- the same positive trend as pressure increases. Consequently, drug tion is summarized in Fig. 3, with three to four repeated samples loading is not always favorable at higher pressure ranges. Similar per each experimental setting. Input parameters included 3DP layer results were reported by others with comparable polymer-based thickness setting, scCO2 processing temperature, and scCO2 pro- drug delivery systems [47,50–53]. cessing pressure. A shorter run time was also tested for 0.050-mm Two-factor ANOVA (while keeping pressure constant) also 3DP samples. At 313 K and 115 bar, 4-h scCO2 treatment resulted shows that 3DP layer thickness had a more statistically signiﬁ- in 14.68 ± 0.28 % drug loading (based on 3 repeated samples) com- cant impact on drug loading at a lower pressure range (115−125 pared to 19.08 ± 0.46 % drug loading with 24-h treatment. Similarly, bar; p-value ≤ 0.0008) than at a higher pressure range (135−148 at 323 K and 115 bar, 4-h scCO2 treatment showed an average of bar; p-value > 0.05). Thicker 3DP layers seemed to cause slightly 15.79 ± 1.02 % drug loading (also based on 3 repeated samples) higher drug loading, as seen in Fig. 3. For example, at the 313 K compared to 23.60 ± 0.78 % drug loading with 24-h treatment. Data and 125 bar scCO2 processing condition, drug loading increased suggest that drug loading required longer than 4 h of scCO2 treat- from 12.79 ± 0.49 % to 16.67 ± 1.05 % (i.e. a 30 % change) as 3DP ment time to reach stabilization, which was consistent with past layer thickness increased from 0.025 mm to 0.100 mm; This could observation in other similar scCO2 processing systems [40,41]. This be explained by the differences in surface roughness among the result also indicates that drug loading can be modulated with scCO2 polymer sample types. 0.100-mm 3DP samples showed a more treatment time to reach desired levels of drug loading, depending uniform surface across the sample (see Fig. 1) with lower sur- on speciﬁc material applications. face roughness. Smoother surfaces might allow more efﬁcient CO2 Results show that a drug loading of over 24 % was achiev- swelling of the polymer and potentially more consistent drug dif- able under the tested experimental conditions. The level of drug fusion into the polymer surface. Although the effect of 3DP layer loading can clearly be modulated by scCO2 treatment time and pro- thickness on drug loading was not consistent for all scCO2 tempera- cessing conditions such as temperature and pressure. According ture and pressure conditions, data suggests that thicker 3DP layers to Champeau et al. , PMMA had been shown to achieve drug could be most beneﬁcial for certain material applications where loading facilitated by scCO2 of about 8% with ketoprofen (sim- less surface roughness, better surface uniformity and higher drug ilar solubility in scCO2 compared to ﬂurbiprofen) at 313 K and loading are desired. Moreover, thicker 3DP layer settings typically 100 bar [42,43], approximately 20 % with triﬂusal (more soluble mean shorter printing times (2.9 h for 0.025-mm layer thickness in scCO2 than ﬂurbiprofen) at 308 K and 200 bar  and about versus 3.8 h for 0.100-mm layer thickness; a 22 % time saving 6 T.T. Ngo, L. Hoffman, G.D. Hoople et al. / J. of Supercritical Fluids 160 (2020) 104786 Table 3 Comparison between experimental and predicted drug loadings. Experimental drug loading(%) Predicted drug loading(%) Deviation(%) 16.00 16.26 1.59 16.67 15.62 −6.30 15.63 15.34 −1.84 13.49 15.30 13.45 19.08 16.26 −14.80 16.99 15.62 −8.08 12.72 15.34 20.63 16.45 15.30 −6.97 13.30 16.26 22.22 12.79 15.62 22.09 18.45 15.34 −16.84 14.79 15.30 3.47 22.58 23.95 6.05 23.28 21.99 −5.57 24.08 21.22 −11.88 21.75 21.10 −2.96 Fig. 4. Surface roughness for scCO2 -treated polymer samples (24-h treatment). 23.60 23.95 1.49 23.05 21.99 −4.59 23.90 21.22 −11.24 3.3. Surface morphology of scCO2 -treated 3DP polymer in 19.57 21.10 7.83 presence of ﬂurbiprofen 22.66 23.95 5.68 21.18 21.99 3.83 21.88 21.22 −3.03 Surface roughness was calculated for scCO2 -treated polymer 18.44 21.10 14.44 samples using Eq. 2 and SEM data (up to 27 measurements per each treatment), summarized in Fig. 4. Surface morphology analysis was focused mostly on 3DP samples at 0.025-mm and 0.100-mm layer thickness settings, investigating the effect of 3DP layer thickness in this case), thus lowering the overall cost of material prepara- on surface roughness. Surface morphology for scCO2 -only-treated tion. (no drug presence) polymer 3DP at 0.025-mm layer thickness set- Based on the observed inﬂuence of temperature on drug load- ting was also examined, showing a lower surface roughness value ing, a linear regression model was ﬁtted for drug loading in polymer compared to non-treated samples and scCO2 /drug-treated sam- samples as a function of CO2 density and ﬂurbiprofen solubility in ples. This result suggests no negative impact of scCO2 processing on CO2 . CO2 density was obtained either directly or through interpola- the surface integrity of the polymer. On the other hand, scCO2 pro- tion based on the tested experimental conditions in this work and cessing might have cleaned the polymer surface, washing away any Anwar and Carroll reference data . Flurbiprofen solubility data loosely trapped impurities present on the surface after 3D printing. was used per Table 2 based on previous work by Duarte et al. . In the case of 0.025-mm 3DP samples, the polymer surface rough- As discussed previously, drug loading behavior was inﬂuenced by ness was reduced from 36.91 % to 31.62 % (about 14 % reduction) several competing factors: drug solubility in the ﬂuid phase, CO2 when treated with pure scCO2 in absence of ﬂurbiprofen at 323 K sorption in polymer, and the intermolecular interactions between and 148 bar. the drug and the polymer matrix. Drug partitioning between the No change in the surface integrity was observed when the poly- polymer phase and the ﬂuid phase seems to be the main driving mer was treated with scCO2 in the presence of ﬂurbiprofen. Fig. 5 factor for drug loading. Literature has shown that solute partition- compares SEM images of treated polymer samples under 323 K and ing between the ﬂuid phase and the polymer phase depends on 148 bar. The treated polymer surface appeared comparable to the both ﬂuid density and solute solubility in the ﬂuid phase [18,55]. original, non-treated surface shown in Fig. 1. In addition, no foam- As a result, both CO2 density and drug solubility were selected for ing was noted on any scCO2 -treated samples, proving sufﬁciently input parameters in the regression model instead of temperature controlled CO2 depressurization was performed during the exper- since they best represent the combined variations of temperature iments. Unintended foaming of polymer surface due to high CO2 and pressure during the experiments. Using average drug load- depressurization rates at elevated temperatures could compromise ing data in Fig. 3, the amount of drug loading in 3DP polymer material surface integrity, making the material less desirable for samples is empirically modeled as shown in Eq. 3, with p-values most applications . < 0.05 for the intercept and all coefﬁcients. There was no sta- Based on two-factor ANOVA (with replication and at 95 % con- tistically signiﬁcant interactive impact on drug loading observed ﬁdence, while keeping 3DP layer thickness constant), temperature between CO2 density and drug solubility (p-value > 0.05), thus appeared to be the most statistically signiﬁcant inﬂuence on the this interaction was not included in the regression model. Despite surface roughness of polymer samples when treated in scCO2 in the some scattering in the experimental data (R-square = 0.76), this presence of ﬂurbiprofen (p-value < 0.05). As temperature increased, model helps predict drug loading in 3DP polymer processing with surface roughness also seemed to increase. However, pressure a known ﬂuid density and drug solubility in the processing medium. variation alone was determined to have no signiﬁcant impact on Table 3 compares the actual, experimental drug loadings to the material surface roughness. Some interactive impact of both tem- predicted drug loadings using Eq. 3. Again, data scattering in the perature and pressure on surface roughness was also noted for model was mainly due to the complexity of multiple competing 0.025-mm treated samples. These observations were consistent factors occurring simultaneously in the polymer/ﬂuid/drug system. with the results shown with drug loading of the polymer. Data suggests that increasing drug loading could also lead to increasing surface roughness of the polymer. Drug Loading (%) = 51.72 − 0.05492 × CO2 Density 3DP layer thickness also appeared to have an effect on the sur- + 22.47 × Drug Solubility (3) face roughness of the polymer treated in scCO2 and ﬂurbiprofen. A single-factor ANOVA was applied for scCO2 /drug-treated samples at 323 K and 148 bar for a 24-h treatment duration. Results show T.T. Ngo, L. Hoffman, G.D. Hoople et al. / J. of Supercritical Fluids 160 (2020) 104786 7 Fig. 5. SEM of scCO2 -treated polymer in presence of ﬂurbiprofen at 313 K and 148 bar, for different 3DP layer thicknesses. Table 4 4. Conclusion Comparison between experimental and predicted surface roughness. Experimental surface Predicted Deviation(%) 3D-printed acrylate-based polymer was impregnated with roughness surface roughness ﬂurbiprofen in supercritical carbon dioxide to create a multi- (%) (%) component polymeric system with potential applications in the 35.90 35.47 −1.20 biomedical ﬁeld. Drug loading and surface roughness were shown 36.37 37.27 2.50 to be tunable with different process parameters, making the pro- 39.83 38.77 −2.67 cess viable for speciﬁc application needs, from drug delivery to 39.41 40.58 2.96 37.80 36.93 −2.29 biological implants. An average drug loading range of 12.72–24.08 24.08 24.54 1.91 % was achievable under the tested conditions (313–323 K and 27.29 26.35 −3.44 115–148 bar). Thicker layer settings in the 3D-printing process 26.81 27.84 3.86 (corresponding to shorter print time) showed better material sur- 29.92 29.65 −0.90 face smoothness while not negatively impacting drug loading. Temperature had the most signiﬁcant effects on drug loading and surface roughness. Increasing temperature resulted in an increase in drug loading of ﬂurbiprofen into the polymer matrix and also that material surface roughness decreased as 3DP layer thickness an increase in surface roughness of the material. Both CO2 density increased (F = 24.7 > F critical = 3.23; p-value = 1.17 × 10−7 < 0.05). and drug solubility seemed to be important inﬂuencing factors for A 27.5 % reduction in surface roughness was noted when 3DP layer drug loading and material surface roughness. Finally, linear regres- thickness increased from 0.025 mm to 0.100 mm. This was consis- sion empirical models were established for predicting drug loading tent with observations made with non-treated samples. Once again, and surface roughness of the polymer based on processing ﬂuid analysis of this data suggests that drug loading has the same level density, drug solubility, and 3DP layer thickness. All of these pro- of effect on polymer surface roughness, regardless of the starting cess parameters are believed to play important roles in the drug state of the material. loading behavior and surface integrity of the polymer, and possibly Because surface roughness appeared to depend on multiple pro- affecting the drug delivery performance of the material when used cess parameters, a multiple linear regression model was ﬁtted to in speciﬁc applications. The investigation and modeling of drug the experimental data. The inﬂuence of temperature and the inter- release characteristics will be reported in a follow-up study. The active effect of temperature and pressure suggest the use of CO2 3D printing and scCO2 processing methods included in this study ﬂuid density as one of the input parameters in the model. As previ- could be applied to other material systems, as long as they satisfy ously discussed, drug loading has an impact on surface roughness. the following three requirements: 1) the polymerization of starting Since drug solubility in scCO2 has a direct effect on drug loading, polymer liquid resin can be accomplished through UV light initia- and drug loading had shown some inﬂuence on surface rough- tion, 2) the polymer matrix can expand upon CO2 absorption, and ness, the solubility of ﬂurbiprofen in scCO2 was also used as an 3) the impregnating drug has some solubility in scCO2 . The models independent variable in the regression model. In addition, 3DP established in this study are useful towards the prediction of drug layer thickness was included in the model due to its direct impact loading, enabling the engineering design of material systems to suit on surface roughness. Eq. 4 shows the multiple linear regression speciﬁc biomedical applications. model obtained from experimental data (R-square = 0.98). Based on this empirical model, while drug solubility imposes a posi- tive effect on polymer surface roughness, both 3DP layer thickness Declaration of Competing Interest and CO2 density have negative effects on the material surface. Table 4 compares the experimental surface roughness calculated The authors declare that they have no known competing ﬁnan- from SEM data to the predicted surface roughness using Eq. 4. Due cial interests or personal relationships that could have appeared to to a high goodness of ﬁt with the data, deviations between the inﬂuence the work reported in this paper. experimental and predicted values maintain to be less than 4%. Acknowledgements Surface Roughness (%) = 53.73 − 145.6 × 3DP Layer Thickness This research was made possible by the funding received from − 0.02549 × CO2 Density + 24.59 × Drug Solubility (4) the Provost’s Ofﬁce and the Shiley-Marcos School of Engineering at the University of San Diego. The authors would also like to thank Michael Sween for his assistance with the 3D printing of polymer, 8 T.T. Ngo, L. Hoffman, G.D. Hoople et al. / J. of Supercritical Fluids 160 (2020) 104786 and the Externship Program at High Tech High International for  United States Environmental Protection Agency, Overview of Greenhouse enabling part of our research collaboration. Gases, 2019 https://www.epa.gov/ghgemissions/overview-greenhouse-gases.  S. Ramakrishna, J. Mayer, E. Wintermantel, K.W. Leong, Biomedical applications of polymer-composite materials: a review, Compos. Sci. Technol. 61 (2001) 1189–1224, http://dx.doi.org/10.1016/S0266-3538(00)00241-4.  U. Ali, K. Karim, N.A. 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