Method of producing a part for a bioprocessing system and determining its bacterial attachment propensity

Abstract

The present disclosure relates to a method 100 of producing a part 300 for use in a bioprocessing system, the method 100 comprising: manufacturing 110 the part 300 using an additive manufacturing process; and post-processing 120 a surface of the part 300, wherein the surface is intended to be wetted in use; wherein the post-processed surface has one or more of the following surface roughness parameter values (e.g. measured in accordance with ISO 25178-2:2022), wherein the one or more surface roughness parameter values are measured for the surface after filtering the surface to remove surface features having long wavelengths (e.g. greater than about 54 µm): a reduced valley height Svk of less than about 5 µm; an arithmetic mean height Sa of less than about 2.5 µm 3 µm ‑2 a valley void volume Vvv of less than about 0.5 µm; and / or a five-point pit height S5v of less than about 15 µm.

Description

Technical Field

[0001] This disclosure relates to a method for producing parts for use in a biological treatment system, and a method for determining the tendency of bacteria to attach to the surface of the parts for use in a biological treatment system. Background Technology

[0002] 3D printing technology (also known as additive manufacturing (AM)) has existed since the 1980s, when it was primarily used for rapid prototyping in product development within certain industries. The technological advancements and mass production possibilities of different AM techniques have demonstrated their potential to complement or even replace traditional manufacturing technologies. Some advantages that AM brings to the bioprocessing industry include the ability to increase geometric complexity while reducing manufacturing skill requirements, and decreasing costs and material waste.

[0003] Among existing AM technologies, powder bed fusion (PBF) is the most developed and mature platform, capable of providing models with different shapes and sizes using powder-based materials. However, various technical and regulatory challenges hinder the implementation of PBF technology in the bioprocessing field. Specifically, technical aspects related to cleanability, sterility, surface finish, and dimensions should be designed according to good engineering principles to minimize bacterial adhesion on part surfaces. More specifically, an inherent challenge of PBF lies in its “stepped” layering method, which can affect surface quality. Furthermore, post-processing steps are necessary to smooth the printed parts as is and achieve surfaces similar to those of conventional manufacturing methods, limiting the applicability of PBF-manufactured parts in the bioprocessing field.

[0004] A primary concern for additively manufactured parts used in bioprocessing equipment is the control of biofilms during biopharmaceutical production. Beyond their health impacts, biofilm formation has significant economic implications across various sectors. For example, in the biopharmaceutical field, bacterial adhesion leading to biofilm formation inside bioprocessing equipment results in billions of dollars in lost revenue. Currently, there is a lack of understanding of how 3D-printed surfaces interact with bacteria and how to prevent bacterial growth and reduce biofilm formation to meet the high microbiological requirements for components used in contact with biological systems.

[0005] Biofilms are three-dimensional microbial communities embedded within their self-generated extracellular matrix (ECM) and capable of adhering to surfaces. As biofilms mature, the extracellular polymeric matrix (EPS) enhances cell adhesion and aggregation, thereby promoting the accumulation of microorganisms on the surface and the formation of tightly packed cell clusters. This results in the formation of well-structured and firmly attached biofilms. Therefore, once a biofilm is established, eradicating the bacteria within it or removing it from the surface becomes a challenging task.

[0006] Examining the interactions between the surfaces of bioprocessing equipment and microbial organisms has revealed numerous variables influencing early bacterial attachment and biofilm formation. These variables include bacterial traits such as cell wall composition, motility, exposure duration, and initial bacterial concentration. Surface properties of the bioprocessing equipment also play a significant role, including properties such as surface charge density, wetting characteristics, roughness, morphology, and stiffness. Specifically, the effects of surface texture and wettability on initial bacterial adhesion and subsequent biofilm formation have received considerable attention, highlighting their significant influence on the biofilm establishment process. However, there is currently no clear evidence on how these surface properties affect bacterial surface adhesion.

[0007] Therefore, an improved method is needed to verify the suitability of 3D-printed parts for use in biological processing systems. Specifically, a method is needed to provide more thorough verification of whether 3D-printed parts may lead to biofilm formation. Furthermore, an improved method is needed to manufacture 3D-printed parts to ensure their suitability for biological processing systems.

[0008] Therefore, the invention as defined by the appended claims is provided. Summary of the Invention

[0009] This invention describes concepts in more detail in specific embodiments. It should not be used to identify essential features of the claimed subject matter, nor to limit the scope of the claimed subject matter.

[0010] According to a first aspect of this disclosure, a method for producing a part for use in a biological processing system is provided, the method comprising: manufacturing the part using an additive manufacturing process; and post-processing the surface of the part, wherein the surface is intended to be wetted in use; wherein the post-processed surface has one or more of the following surface roughness parameter values ​​measurable according to ISO 25178-2:2022, wherein the one or more surface roughness parameter values ​​are measured for the surface after filtering the surface to remove surface features having long wavelengths (e.g., greater than about 55 µm, such as greater than 54 µm): a reduction valley height Svk less than about 5 µm; an arithmetic mean height Sa less than about 2.5 µm; and a surface roughness parameter value less than about 0.5 µm. 3 µm -2 The valley void volume Vvv; and / or the height of the five-point pits less than about 15 µm S5v.

[0011] The first approach allows for the fabrication of additively manufactured parts with surfaces exhibiting low bacterial adhesion susceptibility. Specifically, by adjusting post-processing to include one or more of the surface roughness parameter values ​​listed above, additively manufactured parts can be validated for low bacterial adhesion susceptibility without requiring inefficient and time-consuming validation methods. Current processes for validating bacterial adhesion to additively manufactured parts involve destructive testing of a number of prototypes, resulting in additional waste and reduced manufacturing efficiency. Specifically, alternative methods for validating bacterial adhesion to additively manufactured parts would involve contaminating a number of prototypes with specific bacteria to determine the extent to which such bacteria adhere to the prototype surfaces over time. Such methods are time-consuming because they require determining bacterial adhesion over time (e.g., 24 hours). These methods also involve manual work and the possibility of introducing additional contaminants due to manual handling of the selected prototypes being tested. Such methods require fabricating additional parts to be tested and may require testing many parts to provide statistical validity. Each surface also needs to be measured using a profilometer or microscope to determine if the part has a low bacterial adhesion susceptibility.

[0012] In contrast, the first aspect of the method allows verification that additively manufactured parts produced using the method have a low tendency for bacterial adhesion by adjusting the post-processing of the additively manufactured part surface to provide one or more surface roughness values ​​that correspond to the surface roughness values ​​of surfaces with a low tendency for bacterial adhesion.

[0013] According to a second aspect of this disclosure, an additively manufactured part for use in a biological processing system is provided, wherein the additively manufactured part includes a surface intended to be wetted in use, wherein the surface has one or more of the following surface roughness parameter values ​​measurable according to ISO 25178-2:2022, wherein the one or more surface roughness parameter values ​​are measured on the surface after filtering the surface to remove surface features having long wavelengths (e.g., greater than 54 µm): a reduction valley height Svk less than about 5 µm; an arithmetic mean height Sa less than about 2.5 µm; and a reduction valley height Svk less than about 0.5 µm. 3 µm -2 The valley void volume Vvv; and / or the height of the five-point pits less than about 15 µm S5v.

[0014] According to a third aspect of this disclosure, a method is provided for classifying the surface of a part as suitable for use in a biological treatment system, the method comprising: manufacturing the part, wherein the part includes a surface intended to be wetted in use; and one or more of the following: measuring the reduced valley height Svk of the surface after filtering the surface to remove surface features having long wavelengths, and classifying the surface as suitable for use in a biological treatment system if the reduced valley height Svk is less than about 5 µm; measuring the arithmetic mean height Sa of the surface after filtering the surface to remove surface features having long wavelengths, and classifying the surface as suitable for use in a biological treatment system if the arithmetic mean height Sa is less than about 2.5 µm; measuring the valley void volume Vvv of the surface after filtering the surface to remove surface features having long wavelengths, and classifying the surface as suitable for use in a biological treatment system if the valley void volume Vvv is less than about 0.5 µm. 3 µm -2 The surface is then classified as suitable for use in a biological processing system; and after filtering the surface to remove surface features with long wavelengths, the five-point pit height S5v of the surface is measured, and if the five-point pit height S5v of the surface is less than, for example, about 15 µm, the surface is classified as suitable for use in a biological processing system.

[0015] The third approach allows for the determination of whether the surface of a part (particularly additively manufactured parts) is suitable for use in a biological processing system due to its low susceptibility to bacterial adhesion. Current processes for determining the susceptibility of bacteria to additively manufactured parts involve destructive testing of a number of prototypes, resulting in additional waste and reduced manufacturing efficiency, as described above.

[0016] In contrast, the third approach allows for the determination of whether additively manufactured parts are suitable for use in biological processing systems due to their low susceptibility to bacterial adhesion. This determination is based on measurements of one or more surface roughness values ​​that are most strongly correlated with surfaces exhibiting low bacterial adhesion susceptibility. This allows for a more efficient verification of the suitability of additively manufactured parts for use in biological processing systems due to their low bacterial adhesion susceptibility. Attached Figure Description

[0017] The specific implementation scheme is described below by way of example and with reference to the accompanying drawings, wherein:

[0018] Figure 1 A flowchart is shown showing a method for producing parts for use in biological treatment systems.

[0019] Figure 2 A flowchart is shown illustrating a method for classifying the surfaces of parts for use in biological treatment systems.

[0020] Figure 3 A schematic diagram of a stud sample used for evaluating bacterial adhesion, according to this disclosure, is shown.

[0021] Figure 4 A graph showing the static contact angles of sample surfaces according to a first example is presented. These sample surfaces include surfaces produced by CNC milling, surfaces produced by injection molding, and surfaces produced by PBF, which have undergone different post-processing steps.

[0022] Figure 5 A graph showing the ratio of the unfolded interface area to the scale of the sample surface according to the first example is shown.

[0023] Figure 6 A graph showing the complexity versus scale of the sample surface based on the first example is shown.

[0024] Figure 7 The results of principal component analysis of the sample surface based on the first example are shown.

[0025] Figure 8 The variable projection importance of the roughness parameter of the sample surface according to the first example is shown.

[0026] Figures 9a to 9e illustrate the attachment of Escherichia coli and Staphylococcus aureus and biofilm growth on the sample surface according to the first example.

[0027] Figure 10 a to Figure 10 Image 1 shows a field emission scanning electron microscope (FE-SEM) image of a 48-hour Escherichia coli biofilm on the surface of a sample surface classified as a Class I sample according to the first example.

[0028] Figure 11 a to Figure 11 Image q shows a field emission scanning electron microscope (FE-SEM) image of a 4-hour Escherichia coli biofilm on the surface of a sample surface classified as a Class II sample surface according to the first example.

[0029] Figure 12 a to Figure 12 Image i shows a field emission scanning electron microscope (FE-SEM) image of a 48-h Staphylococcus aureus biofilm on the surface of a sample surface classified as a Class I sample according to the first example.

[0030] Figure 13 a to Figure 13 o shows a field emission scanning electron microscope (FE-SEM) image of a 48-hour Staphylococcus aureus biofilm on the surface of a sample surface classified as a Class II sample according to the first example.

[0031] Figure 14 a and Figure 14 b illustrates the attachment of Escherichia coli and Staphylococcus aureus and biofilm growth on the sample surface according to the first example.

[0032] Figures 15a to 15j The sample surface according to the first example is shown from Figure 8 The values ​​of the ten most relevant roughness parameters were obtained from the variable projection importance plot. Detailed Implementation

[0033] The specific embodiments of this disclosure are explained below with particular reference to manufacturing and determining the susceptibility of bacteria to adhere to surfaces of parts used in biological processing systems. However, it should be understood that the methods described herein can also be used to manufacture and determine the susceptibility of bacteria to adhere to surfaces of parts used in other environments. Furthermore, the specific embodiments of this disclosure are explained below with particular reference to determining the susceptibility of bacteria to adhere to surfaces of additively manufactured parts. However, it will be further understood that the methods described herein can also be used to determine the susceptibility of bacteria to adhere to surfaces of parts manufactured using other manufacturing techniques.

[0034] Figure 1 This is a flowchart of method 100 for producing parts.

[0035] At point 110, an additive manufacturing process is used to manufacture the part. For example, additive manufacturing processes such as powder bed melting (PBF), laser powder bed melting (LPBF), or electron beam melting (EBM) can be used to manufacture the part. Specifically, the PBF process may include selective layer sintering (SLS). In one example, the manufactured part is intended for use in a biological processing system and includes surfaces designed to be wetted when the part is used in the biological processing system. More specifically, the surface may include multiple boundaries between adjacent layers of the part.

[0036] At 120°, the surface of the part is post-treated to provide one or more surface roughness parameter values ​​within a certain range (e.g., surface roughness parameters as defined in ISO 25178-2:2022, as described below). In one example, the surface post-treatment includes chemical vapor smoothing of the surface.

[0037] In one example, one or more surface roughness parameters can be measured by analyzing surface images obtained using a confocal laser scanning microscope (CLSM), such as the VK-X1000 CLSM available from Keyence Corporation in Osaka, Japan. Surface roughness parameters involve scale-constrained surfaces, therefore measuring one or more surface roughness parameters first involves filtering one or more CLSM images of the part's surface according to an appropriate scale range. In the example described herein, surface features are filtered to remove surface features with long wavelengths, such as those unrelated to microbial / bacterial attachment (e.g., greater than 54 µm). However, it should be understood that the choice of filter affects the values ​​of the surface roughness parameters. Therefore, implementing different filters can change the values ​​of the surface roughness parameters listed below.

[0038] Post-processing of the part at 120 may include post-processing the surface to provide one or more surface wettability values ​​(e.g., static contact angle values) within a certain range.

[0039] The surface roughness parameter values ​​provided by post-processing the surface at 120 are related to surface roughness parameters that have been identified as being associated with a low susceptibility to bacterial adhesion to the surface. These surface roughness parameters have been determined by comparing two classes of surfaces: Class I (including surfaces produced by CNC milling, injection molding, and PBF post-processing with chemical vapor phase smoothing (VS); and Class II (including surfaces produced by PBF as is after printing and surfaces produced by PBF and post-processed using roller surface finishing). Class I surfaces represent surfaces used in the bioprocessing industry today and have been shown not to cause significant bacterial adhesion and biofilm formation. The determination of one or more associated roughness parameters is not part of method 100. Rather, it can be understood from the discussion below that comparing Class I and Class II to determine the most significant roughness parameter describing the difference between the categories yields the roughness parameter most associated with a low susceptibility to bacterial adhesion. Post-processing of the surface at 120 is performed to provide one or more surface roughness parameter values ​​for the most associated roughness parameter.

[0040] As further described in the examples below, Class I and Class II surfaces are compared to determine the surface roughness parameters that show the greatest difference between the two types of surfaces.

[0041] Standardized surface roughness parameters are defined in ISO 25178. Specifically, roughness parameters used to describe surface morphology are defined in ISO 25178-2:2022. Most existing studies on the influence of surface roughness on biofilm formation focus only on the arithmetic mean deviations Ra and Sa, which describe the average height of two-dimensional profiles and three-dimensional surfaces, respectively. In contrast, this disclosure involves considering many different surface roughness parameters, which have been found to be more correlated with the bacterial attachment tendency of surfaces than the arithmetic mean deviations Ra and Sa alone.

[0042] Specifically, the surface of the part can be post-processed at 120° to provide one or more surface roughness parameter values ​​related to one or more of the following 10 surface roughness parameters measured according to ISO 25178-2:2022: valley material ratio Smrk2 (%), valley reduction height Svk (µm), valley void volume Vvv (µm). 3 µm -2 The surface roughness parameters are: maximum pit depth Svkx (µm), arithmetic mean height Sa (µm), maximum pit depth Sv (µm), root mean square height Sq (µm), five-point pit height S5v (µm), material specific height difference Sdc (µm), and maximum height Sz (µm). In the following examples, these surface roughness parameters were determined to be the most significant parameters based on comparisons between surface categories with significant differences in bacterial adhesion tendency.

[0043] As mentioned above, the values ​​of the surface roughness parameters listed above depend on the scale to which the surface is constrained. The surface of the part can be post-processed at 120° to provide one or more surface roughness parameter values ​​within the range listed in the following paragraphs. The surface roughness parameter values ​​listed below are obtained by filtering the surface features to remove surface features with long wavelengths (e.g., greater than 54 µm).

[0044] Post-treatment of the surface at 120° can provide one or more of the following:

[0045] (i) A reduced valley height Svk of less than 5 µm, preferably less than 4 µm, more preferably less than 3 µm, more preferably less than 2 µm and most preferably less than 1 µm;

[0046] (ii) An arithmetic mean height Sa of less than 2.5 µm, preferably less than 2 µm, more preferably less than 1.5 µm and most preferably less than 1 µm;

[0047] (iii) Less than 0.5 µm 3 µm -2 More preferably less than 0.4 µm 3 µm-2 More preferably less than 0.3 µm 3 µm -2 More preferably less than 0.2 µm 3 µm -2 And most preferably less than 0.1 µm 3 µm -2 The void volume of the valley is Vvv;

[0048] (iv) The height of the five-point indentation S5v is less than 15 µm, preferably less than 12.5 µm, more preferably less than 10 µm, more preferably less than 7.5 µm, and most preferably less than 5 µm;

[0049] (v) The maximum pit depth Svkx is less than 20 µm, preferably less than 15 µm, more preferably less than 10 µm, and most preferably less than 5 µm;

[0050] (vi) The valley material ratio Smrk2 is between 85% and 95%, preferably between 86% and 93%, and more preferably between 87% and 91%;

[0051] (vii) A root mean square height Sq less than 4 µm, preferably less than 3.5 µm, more preferably less than 3 µm, more preferably less than 2.5 µm and most preferably less than 2 µm;

[0052] (viii) A maximum height Sz less than 20 µm, more preferably less than 17.5 µm, more preferably less than 15 µm, and most preferably less than 12.5 µm;

[0053] (ix) a maximum pit depth Sv less than 20 µm, preferably less than 15 µm, more preferably less than 10 µm, and most preferably less than 5 µm; and

[0054] The material height difference Sdc is less than 7 µm, preferably less than 6 µm, more preferably less than 5 µm, more preferably less than 4 µm, and most preferably less than 3 µm.

[0055] The post-processed surface may have more than one surface roughness parameter value listed at (i) to (x). In one instance, the post-processed surface may have all the surface roughness parameter values ​​listed at (i) to (x).

[0056] Given the strong correlation between these parameters and low bacterial adhesion tendency, if the values ​​of one or more of the aforementioned roughness parameters are similar to the corresponding values ​​for Class I surfaces, the surface of the manufactured part is likely to have a low bacterial adhesion tendency (and therefore a low biofilm development tendency). Therefore, post-processing the surface to include one or more of these values ​​may result in a surface with a low bacterial adhesion tendency.

[0057] As described above, post-processing of the part at 120° may include post-processing the surface to provide one or more surface wettability values ​​(e.g., static contact angle values) within a certain range. Specifically, post-processing of the surface at 120° may provide a static contact angle of the post-processed surface between 45° and 105°, preferably between 50° and 100°, more preferably between 55° and 95°, and most preferably between 60° and 90°.

[0058] Once the part has been manufactured using method 100, depending on the post-processing performed at 120, the surface of the part will have one or more surface roughness parameter values ​​listed at (i) to (x), and optionally surface wettability values ​​listed above.

[0059] The part manufactured using method 100 is an additively manufactured part. The additively manufactured part can be formed from a material such as a polymer (e.g., polypropylene). Furthermore, the additively manufactured part can be formed using layers of powder material that have been thermally bonded together using a process such as PBF (e.g., SLS). This means that the additively manufactured part can include a first region (or a first plurality of regions) where the material has not yet melted and a second region (or a second plurality of regions) where the material has melted and has been re-cured.

[0060] Method 100 allows for the fabrication of additively manufactured parts with surfaces exhibiting low bacterial adhesion susceptibility. Specifically, by adjusting the post-processing applied at 120 to include one or more of the surface roughness parameter values ​​listed above, the additively manufactured part can be validated for low bacterial adhesion susceptibility without requiring inefficient and time-consuming validation methods. Current processes for validating bacterial adhesion to additively manufactured parts involve destructive testing of a number of prototypes, resulting in additional waste and reduced manufacturing efficiency. Specifically, alternative methods for validating bacterial adhesion to additively manufactured parts would involve contaminating a number of prototypes with specific bacteria to determine the extent to which such bacteria adhere to the prototype surfaces over time. Such methods are time-consuming because they require determining bacterial adhesion over time (e.g., 24 hours). Such methods also involve manual work and the possibility of introducing additional contaminants due to manual handling of the selected prototypes being tested. Such methods require fabricating additional parts to be tested and may require testing many parts to provide statistical validity. Each surface also needs to be measured using a profilometer or microscope to determine that the part has low bacterial adhesion susceptibility.

[0061] In contrast, method 100 allows verification that additively manufactured parts produced using method 100 have a low tendency for bacterial adhesion by adjusting the post-processing of the surface of the additively manufactured part to provide one or more surface roughness values ​​that correspond to the surface roughness values ​​of surfaces with a low tendency for bacterial adhesion.

[0062] Given the low susceptibility of bacteria to attach to the surface of a part, the surface of the part can be considered suitable for use in a biological treatment system. Even if the surface has an arithmetic mean height (linear roughness) Ra exceeding the threshold typically used to determine whether a part surface is suitable for use in a biological treatment system, the surface of the part can still be classified as suitable for use in a biological treatment system. For example, if the surface of the part has one or more surface roughness parameter values ​​listed at (i) to (x), then even if the surface Ra value is greater than 0.5 µm, the surface of the part can be classified as suitable for use in a biological treatment system. The value of 0.5 µm is the threshold Ra value currently used in industry to determine whether a part surface is suitable for use in a biological treatment system.

[0063] Figure 2 This is a flowchart of a method 200 for classifying the surfaces of parts to suit their use in a biological treatment system.

[0064] At 210, the part is manufactured. The part includes surfaces intended to be wetted during use. The part can be manufactured using additive manufacturing processes such as powder bed melting (PBF). Manufacturing the part at 210 may also include post-processing of the part.

[0065] At 220, one or more surface roughness parameters of the surface are measured (e.g., from a CLSM image described in reference method 100). The method may include filtering the CLSM image using an appropriate scale range (e.g., filtering the image to remove surface features with wavelengths greater than 54 µm).

[0066] At 230, based on one or more surface roughness parameters measured at 220, it is determined whether the surface has a low tendency for bacterial adhesion.

[0067] If it is determined at 230 that the surface has a low tendency for bacterial adhesion, then method 200 may include classifying the part at 240 as suitable for use in a biological treatment system.

[0068] If it is determined at 230 that the surface does not have a low susceptibility to bacterial adhesion, then method 200 may include modifying the design process related to the surface design at 250. Alternatively or additionally, if it is determined at 230 that the surface does not have a low susceptibility to bacterial adhesion, then the method may include modifying the manufacturing process related to the fabrication of the surface at 260. Modifying the manufacturing process may include incorporating one or more post-processing operations (such as chemical vapor phase smoothing) into the manufacturing process, and / or modifying one or more post-processing operations performed at 210.

[0069] One or more surface roughness parameters measured at 220 may include one or more of the following: valley material ratio Smrk2 (%), valley reduction height Svk (µm), and valley void volume Vvv (µm). 3 µm -2 The maximum pit depth Svkx (µm), arithmetic mean height Sa (µm), maximum pit depth Sv (µm), root mean square height Sq (µm), five-point pit height S5v (µm), material specific height difference Sdc (µm), and maximum height Sz (µm).

[0070] If, after filtering surface features to remove those with wavelengths greater than 54 µm, one or more of the following conditions are met, a surface can be determined to have a low susceptibility to bacterial attachment at 230:

[0071] (i) The reduced valley height Svk of the filtered surface is less than 5 µm, preferably less than 4 µm, more preferably less than 3 µm, more preferably less than 2 µm, and most preferably less than 1 µm.

[0072] (ii) The arithmetic mean height Sa of the filtered surface is less than 2.5 µm, preferably less than 2 µm, more preferably less than 1.5 µm, and most preferably less than 1 µm;

[0073] (iii) The valley void volume Vvv of the filtered surface is less than 0.5 µm. 3 µm -2 More preferably less than 0.4 µm 3 µm -2 More preferably less than 0.3 µm 3 µm -2 More preferably less than 0.2 µm 3 µm -2 And most preferably less than 0.1 µm 3 µm -2 ;

[0074] (iv) The height S5v of the five-point pit on the filtered surface is less than 15 µm, preferably less than 12.5 µm, more preferably less than 10 µm, more preferably less than 7.5 µm, and most preferably less than 5 µm.

[0075] (v) The maximum pit depth Svkx of the filtered surface is less than 20 µm, preferably less than 15 µm, more preferably less than 10 µm, and most preferably less than 5 µm.

[0076] (vi) The valley material ratio of the filtered surface to Smrk2 is between 85% and 95%, preferably between 86% and 93%, and more preferably between 87% and 91%.

[0077] (vii) The root mean square height Sq of the filtered surface is less than 4 µm, preferably less than 3.5 µm, more preferably less than 3 µm, more preferably less than 2.5 µm, and most preferably less than 2 µm.

[0078] (viii) The maximum height Sz of the filtered surface is less than 20 µm, more preferably less than 17.5 µm, more preferably less than 15 µm, and most preferably less than 12.5 µm;

[0079] (ix) The maximum pit depth Sv of the filtered surface is less than 20 µm, preferably less than 15 µm, more preferably less than 10 µm, and most preferably less than 5 µm; and

[0080] (x) The material height difference Sdc of the filtered surface is less than 7 µm, preferably less than 6 µm, more preferably less than 5 µm, more preferably less than 4 µm, and most preferably less than 3 µm.

[0081] If, after filtering the surface features to remove those with wavelengths greater than 54 µm, more than one of the conditions listed at (i) to (x) is met, the surface can be determined to have a low bacterial adhesion tendency at 230. In one instance, if all the conditions listed at (i) to (x) are met, the surface can be determined to have a low bacterial adhesion tendency at 230. As mentioned above, the surface may have an arithmetic mean height Ra value greater than the threshold typically used to classify part surfaces as suitable for use in biological processing systems (e.g., greater than 0.5 µm).

[0082] Method 200 allows for the determination of whether the surface of a part (particularly additively manufactured parts) is suitable for use in a biological processing system due to its low susceptibility to bacterial adhesion. Current processes for determining the susceptibility of bacterial adhesion to additively manufactured parts involve destructive testing of a number of prototypes, resulting in additional waste and reduced manufacturing efficiency. Specifically, alternative methods for determining the susceptibility of bacterial adhesion to additively manufactured parts would involve contaminating a number of prototypes with specific bacteria to determine the extent to which such bacteria adhere to the prototype surfaces over time. Such methods are time-consuming because they require determining bacterial adhesion over time (e.g., 24 hours). These methods also involve manual work and the possibility of introducing additional contaminants due to manual handling of the selected prototypes being tested. Such methods require the fabrication of additional parts to be tested and may require testing many parts to provide statistical validity. Each surface also needs to be measured using a profilometer or microscope to determine if the part has low bacterial adhesion.

[0083] In contrast, Method 200 allows for the determination of whether an additively manufactured part is suitable for use in a biological processing system due to its low bacterial adhesion tendency. This determination is based on measurements of one or more surface roughness values ​​that are most strongly correlated with surfaces exhibiting low bacterial adhesion tendency. This allows for a more efficient verification of the suitability of additively manufactured parts for use in biological processing systems due to their low bacterial adhesion tendency.

[0084] Example

[0085] This embodiment describes a comparison of two types of surfaces, which were identified as highly different in terms of characterization using roughness parameter values. The relevant roughness parameter with the highest degree of difference between the first type of surface (low biofilm development tendency) and the second type of surface (high biofilm development tendency) was determined. Therefore, it is anticipated that post-processing of the surface can provide a surface roughness parameter corresponding to the roughness parameter value of the first type of surface, thereby producing a surface with low biofilm development tendency.

[0086] To study bacterial attachment and biofilm development, individual studs 300 were manufactured. For example... Figure 3 As shown, each stud 300 has a length of 17.8 mm, a top diameter of 4.4 mm, and a surface area of ​​45 mm². 2 As reported by Zaborskyte et al., “Modular 3D-Printed Peg Biofilm Device for Flexible Setup of Surface-Related Biofilm Studies”, Frontiers in Cellular and Infection Microbiology 11 (2022) (the entire contents of which are incorporated herein by reference), biofilm growth mainly occurs at the gas-liquid interface at a depth of 4 mm from the bottom of the stud.

[0087] Reference studs were manufactured using two different methods: for the PP_CNC sample, axial computer numerical control (CNC) milling was performed using a VF-8 milling machine available from Haas Automation Inc. (Oxnard, CA, USA); and for the PP_IM sample, injection molding was performed using an ES 80 / 50 HL machine available from Engel in Schwertberg, Austria. Additively manufactured stud samples were produced via laser-based powder bed melting (PBF-LB / P, or simply “PBF” herein). The layer thickness was 0.1 mm, and the printing tolerance was ±0.3%. The sample orientation during printing was horizontal (0°). Figure 3 It is understandable that for additively manufactured stud samples, the outer surface of the stud includes multiple boundaries between adjacent layers.

[0088] In this embodiment, three grades of polypropylene (PP) were used as is. These three grades are: medical-grade isotactic PP homopolymer (used for reference samples produced using CNC milling, and designated PP_CNC herein), medical-grade ethylene-propylene copolymer (used for reference samples produced using injection molding, and designated PP_IM herein), and industrial-grade ethylene-propylene copolymer (used for samples produced using PBF, and designated PP_PBF herein). Each grade exhibits different characteristics in terms of crystallinity (Xc) and melting point (Tm). The PP grade used for the PP_CNC sample has 43% Xc and a Tm of 164°C; the PP grade used for the PP_IM sample has 36% Xc and a Tm of 151°C; and the PP grade used for the PP_PBF sample has 30% Xc and a Tm of 146°C. PP grades copolymerized with ethylene were used for PP_IM and PP_PBF samples to ensure dimensional stability during processing by reducing the Xc value (because a higher Xc value can lead to increased material shrinkage, which may have a negative impact on dimensional stability during processing).

[0089] Different surface textures of PP_PBF samples were obtained using six different post-processing methods: (i) no post-processing (i.e., PBF samples printed as is), denoted in this paper as PEG_PBF_0h; (ii) PBF samples tumbled for 5 h, denoted in this paper as PEG_PBF_5h; (iii) PBF samples tumbled for 10 h, denoted in this paper as PEG_PBF_10h; (iv) PBF samples tumbled for 15 h, denoted in this paper as PEG_PBF_15h; (v) PBF samples tumbled for 13 h followed by polishing for 3 h, denoted in this paper as PEG_PBF_13h_3P; and (vi) PBF samples post-processed using chemical vapor phase smoothing (CVS), denoted in this paper as PEG_PBF_VS. Reference stud samples are denoted in this paper as PEG_CNC (for CNC milled samples) and PEG_IM (for injection molded samples).

[0090] Post-treatment methods (ii) through (v) involve tumbling surface finishing using abrasive polishing media with coarse grains, a matte finish, and a moderate media abrasion rate. Due to the small size of the samples, the printed specimens are suspended on a porous barrel filled with surface finishing media. This results in a surface finish characterized by a matte appearance. Post-treatment method (v) involves subsequent processing using polishing media with fine grains, a semi-gloss finish, and a very low media abrasion rate, resulting in a surface finish with a semi-gloss appearance. For post-treatment methods (ii) through (v), the detergent concentration and dosage are constant for each experiment, and it does not provide chemical energy to the surface finishing process.

[0091] The post-processing method (vi) involves using a highly volatile solvent, which is evaporated and injected onto the polymer surface of the sample. The solvent partially dissolves the polymer surface, causing the dissolved polymer to flow into surface features such as pores, holes, and crevices. After the solvent evaporates from the surface, this flow of the dissolved polymer reduces surface texture and increases smoothness.

[0092] Figure 4 This is a graph of the static contact angle of the sample under consideration. The static contact angle was measured by dropping a drop of distilled water (e.g., Milli-Q (RTM) water from a Milli-Q (RTM) water purification system available from Merck KGaA in Darmstadt, Germany) onto a Theta Lite optical tensiometer available from Biolin Scientific in Gothenburg, Sweden. The contact angle was calculated using the OneAttension software (version 1.8) available from Biolin Scientific in Gothenburg, Sweden. A 2 µL droplet size was used on the curved surface of the stud. Figure 4 The value shown is the average of three measurements.

[0093] like Figure 4 As shown, the reference samples (PEG_CNC and PEG_IM) and the vapor-smoothed sample (PEG_PBF_VS) exhibited the most hydrophilic behavior, with contact angles of 60°±2°, 82°±3°, and 88°±4°, respectively. The surfaces of the printed originals and the tumbled surfaces, especially those post-treated with abrasive media, showed higher hydrophobicity, with contact angles ranging from 118°±3° (PEG_PBF_0h) to 114°±10° (PEG_PBF_15h). The effect of using polishing media slightly reduced the static contact angle to 111°±4°. The increased surface roughness of the printed original studs and the tumbled studs contributed to the enhanced hydrophobicity, primarily due to trapped air and increased surface area. In contrast, vapor-smoothed surfaces produced smoother surfaces, making the studs more hydrophilic and producing contact angle values ​​similar to the reference samples.

[0094] Preprocessed images derived from surface morphology measurements by CLSM were used for scale-sensitive fractal analysis. Surface texture of the samples was measured using a VK-X1000 confocal laser scanning microscope available from Keyence Corporation in Osaka, Japan. Each surface image measures 275.3 × 206.5 µm. 2The area was measured to be 2048 × 1536 pixels. A total of 12 images were generated using multi-file analyzer software (version 2.1.2.17), with four images per sample and three samples per specimen, taken at 50x magnification and a lateral pixel pitch of 0.134 µm. During image acquisition, each sample was rotated 90° around its axis to capture the surface texture features of the complete stud sample.

[0095] Image preprocessing involves the following steps: (i) topography channel extraction (i.e., extracting relevant channels (topography) from the three channels of the CLSM data), removing outliers, and filling in missing points (if any); (ii) surface denoising by applying a spatial filter with a window size of 5x5 pixels; (iii) forming a removal operation to remove large (i.e., high-wavelength) surface features from the surface; and (iv) leveling the surface using a least-squares plane method (e.g., to reduce any convexity or concavity of the surface).

[0096] Scale-sensitive fractal analysis is then performed on the preprocessed image. Scale-sensitive fractal analysis uses area-scale relationships derived from fractal geometry and based on the assumption that the observed area depends on the observation scale. A "relative area" parameter can be calculated for different observation scales and used for characterization. Relative area describes how much surface area is increased by the roughness of the surface texture. A nominally smooth and flat surface has a relative area of ​​1. If texture is increased, the relative area increases, and this increase will vary depending on the observation scale. The area-scale method is further described in the ISO 25178-2 standard. In this disclosure, one version of the area-scale method is employed, which calculates the surface field parameter Sdr (unfolded area ratio) at different scales. Similar to relative area, Sdr is a measure of how much surface area is increased by the roughness of the surface texture, but it is typically calculated only at the sampling scale. Here, it is calculated at different scales to provide the "Sdr area ratio" as a function of scale. Complexity is a measure of the slope of the Sdr area map at each scale. This measurement captures the complexity of the stud surface at various observation scales, thus contributing to an understanding of surface complexity. In this embodiment, below 150 µm 2 The scale is of interest, assuming that colonies of a few hundred bacterial cells will colonize a triangular region approximating this threshold within hours. 150 µm 2 The triangular region, based on a length of 20 µm and a height of 15 µm, represents a cluster of approximately 100 E. coli cells that adhered to the surface after a 6-hour incubation period. Therefore, the scale of observation is similar to that of standard microorganisms, such as bacteria, present on bioprocessing equipment.

[0097] Figure 5A graph showing the Sdr area ratio (developed interface area ratio) versus scale for each sample is presented. At 0.1 µm... 2 At the 150 µm scale, the PEG_PBF_0h sample had the highest Sdr area ratio, followed by the PEG_PBF_5h, PEG_PBF_10h, PEG_PBF_15h, PEG_PBF_13h_3P, PEG_IM, and PEG_CNC samples, with the PEG_PBF_VS sample being the least common. 2 The threshold at Figure 5 As shown in the figure. For the PEG_CNC, PEG_IM, and PEG_PBF_VS samples, values ​​close to one were observed, indicating that the surface is smooth. As mentioned above, for the PEG_PBF_0h sample, the maximum Sdr area ratio was observed for the range of 0.01 to 150 µm. 2 The scale values ​​range from 2.2 to 1.5. Figure 5 The effect of tumbling surface finishing on the samples is also shown, where a gradually decreasing Sdr area ratio is associated with a longer tumbling surface finishing time.

[0098] Figure 6 A graph showing the complexity versus scale for each sample is presented. At 10 µm 2 At the scale of , the PEG_PBF_0h sample has the highest complexity, followed by the PEG_PBF_5h sample, PEG_PBF_10h sample, PEG_PBF_15h sample, PEG_PBF_13h_3P sample, PEG_IM sample, PEG_CNC sample, and finally the PEG_PBF_VS sample. Figure 6 This helps to distinguish the scale at which different manufacturing processes produce different surface features on the stud surface. The printed studs as is (PEG_PBF_0h) and the tumbled studs (PEG_PBF_5h, PEG_PBF_10h, PEG_PBF_15h) exhibit the highest complexity variation, ranging from near zero at low scales to 150 µm. 2 Values ​​exceeding 80 at low scales. Conversely, CNC (PEG_CNC) and vapor-smoothed (PEG_PBF_VS) samples showed a constant trend at both low and high scales. For IM samples (PEG_IM), complexity remained low at low scales but increased at higher scales, likely due to the presence of weld lines in the surface morphology.

[0099] After determining 150 µm 2 After determining the relevant scale thresholds, use the equation A length of 18 µm was calculated. For the final step of the analysis, the surface was filtered to remove surface features with wavelengths greater than 54 µm (e.g., by using a high-pass robust Gaussian filter of order 1 with a nested exponent of 54 µm). This filter was implemented to achieve the SL-filtered surface for parameter evaluation. The determination of this filter range involved considering a cutoff wavelength three times the previously determined length, which has been found in the literature to provide good results. Finally, a comprehensive set of 85 surface roughness parameters was calculated according to ISO-25178-2:2022. Image preprocessing, area-scale analysis, surface roughness parameter calculation, and 3D image surface filtering were performed using MountainsLab (RTM) Premium surface analysis software (version 9.3.10281), available from Digital Surf in Besançon, France.

[0100] Principal component analysis (PCA) was performed to address the high dimensionality of the initial dataset containing roughness parameters for each sample, aiming to preserve its most critical information. By employing PCA statistical tools, surface roughness information from different manufacturing processes was condensed into a set of three principal components (PCs), thus facilitating a clearer visualization and interpretation of complex data patterns. Figure 7As shown, the score plots of the first principal component (t[1]) and the third principal component (t[3]) indicate the similarity between the PEG_CNC sample (green circles - all between -2.5 and -7.5 on the t[1] axis and between -3 and 4 on the t[3] axis), the PEG_IM sample (gray circles - all between -2.5 and -12.5 on the t[1] axis and between -4 and 4 on the t[3] axis), and the PEG_PBF_VS sample (pink triangles - all between -5 and -12.5 on the t[1] axis and between -4 and 2 on the t[3] axis), while the printed original sample and the tumbled sample are grouped with high dispersion on the right side of the plot (where: the PEG_PBF_0h sample uses the sample located between t[1] and t[3]). The PEG_PBF_5h sample is shown using a maroon triangle between 0 and 10 on the t[1] axis and between -5 and 2 on the t[3] axis; the PEG_PBF_10h sample is shown using a yellow triangle between 0 and 12.5 on the t[1] axis and between -3 and 4 on the t[3] axis; the PEG_PBF_15h sample is shown using a purple triangle between 0 and 10 on the t[1] axis and between -3 and 5 on the t[3] axis; and the PEG_PBF_13P3 sample is shown using a blue triangle between -2.5 and 5 on the t[1] axis and between -2 and 5 on the t[3] axis. Using a confidence ellipse calculated based on Hotelling's T2 with a significance level of 0.05, three outliers (orange triangles) were found in the PEG_PBF_5h sample.

[0101] Using this information, two distinct categories were identified to determine the most relevant surface roughness parameters. The first category encompassed reference samples (PEG_CNC and PEG_IM) and vapor-smoothed surface samples (PEG_PBF_VS), while the second category included the remaining samples (including all tumbled surface finish samples). By performing partial least squares discriminant analysis (PLS-DA), projective importance (VIP) of the variables was plotted, revealing the most significant families of roughness parameters that should be used to describe the differences between the two categories. Figure 8 From the calculation of 85 roughness parameters, ten were selected as the most important for further implementation to describe the surface differences between the two categories. Function (layered surface) and height parameters are the families with the highest importance among the ten selected parameters. The information provided by the parameters among the ten selected parameters is mainly related to the description of the surface valleys. Figure 8 As shown, the ten roughness parameters corresponding to the maximum surface difference between the two categories are: valley material ratio Smrk2 (%), valley height reduction Svk (µm), valley void volume Vvv (µm). 3 µm-2 The maximum pit depth Svkx (µm), arithmetic mean height Sa (µm), maximum pit depth Sv (µm), root mean square height Sq (µm), five-point pit height S5v (µm), material specific height difference Sdc (µm), and maximum height Sz (µm).

[0102] To investigate bacterial attachment, two bacterial models were used: *Escherichia coli* CFT073 (DA47112) and *Staphylococcus aureus* subsp. Rosenbach (DA78720). These are two standard bacterial models widely used in the bioprocessing industry. These Gram-negative and Gram-positive microorganisms are particularly relevant as representatives because they are recommended by regulatory agencies for assessing and controlling bioload impacts in biopharmaceutical manufacturing.

[0103] During the experimental procedures, bacterial cultures were grown in both liquid and solid media. The liquid media used were Luria-Bertani broth (LB) (Sigma Aldrich, USA) and M9 medium with 0.2% glucose. M9 medium consisted of 0.1 mM CaCl2, 1 mM MgSO4, 1x M9 salt (Sigma Aldrich, USA), and 0.2% (w / v) glucose. Solid media consisted of LB agar, high-salt (LA) agar (Sigma Aldrich, USA), and Mueller-Hinton (MH) agar (Beckton Dickinson, USA). Overnight (O / N) liquid cultures (1 ml of medium in a 10 ml tube) were incubated from single colonies with continuous shaking at 180 rpm at 37°C, while cultures used in biofilm experiments were incubated at 37°C without shaking. Agar plates containing bacterial colonies were incubated at 37°C or 30°C without shaking.

[0104] Biofilms were cultured on fabricated peg surfaces using the FlexiPeg biofilm device identified in Zaborskyte et al., “Modular 3D-Printed Peg Biofilm Device for Flexible Setup of Surface-Related Biofilm Studies,” Frontiers in Cellular and Infection Microbiology 11 (2022). O / N bacterial cultures diluted in 200 µl were inoculated into microtiter 96-well plates with flat-bottomed wells (using Nunc (RTM) 96-well plates available from Thermo Fisher Scientific (Waltham, MA, USA). For experiments using LB or M9 medium, the O / N cultures were diluted 100,000-fold (approximately 2–4 × 10⁻⁶ per well) in the appropriate medium prior to inoculation. 4 (bacteria). For experiments in phosphate-buffered saline (PBS), O / N cultures were diluted only 10,000 times in PBS (approximately 2-4 × 10⁶ bacteria per well). 5Cover the wells with a sterile (autoclaved) cap containing the inserted pins and place the cap in a plastic box to prevent culture medium evaporation. Before harvesting the biofilm from the pins, place the box in a 37°C incubator without shaking for the set time. Allow the pins in LB or M9 medium to grow for 4 h or 48 h (replace the medium after 24 h), and allow the pins in PBS to grow for 4 h, 6 h, 16 h, or 24 h. After removing the device from the incubator, wash all pins in PBS by immersing all pins in a new microtiter plate (flat bottom) containing 240 µl PBS / well for 1 minute. Repeat the washing step 3 times, changing the PBS between each wash. Push the washed pins into a glass tube containing 600 µl PBS (using sterile forceps) and vortex (Vortex-Genie 2T, 230V, available from Scientific Industries, Inc. (Bohemia, NY, USA)) for 2 minutes to disperse all bacterial cells attached to the pins. To measure the number of bacteria growing on the pins, the extracted bacteria in PBS were diluted 10, 100, 1,000, 10,000, 100,000, and 1,000,000x, and 5 µl droplets from each dilution were transferred to MH agar plates (LA, Sigma-Aldrich), dried, and grown overnight at 30°C. If a low colony-forming unit (CFU) count was expected, 50 µl of undiluted sample was plated on one half of a plate with a sterile inoculation loop and grown overnight at 37°C. The colonies formed were then counted, the CFU / pin ratio was calculated, and plotted in a graph.

[0105] Biomass quantification of the biofilm was performed using crystal violet staining (CVS). To achieve this, the biofilm was grown in LB medium for 4 h and 48 h, with the medium replaced after 24 h. Alternatively, the biofilm was also grown in PBS for 24 h as described above. After incubation at 37°C, the stapes were thoroughly washed three times by transferring the stapes caps to 96-well plates containing 240 µl of PBS. The caps containing the washed stapes were inverted, transferred to tissue paper, and dried at 37°C for approximately 30 min. To stain the dried stapes, they were inserted into microtiter wells containing 250 µl of 0.05% (w / v) CV solution and incubated at room temperature for 15 min. After the incubation period, the CV solution was discarded, and the stapes were washed three times in 250 µl of PBS for 1 min each time. The washed stapes were air-dried for 10 min, and the presence of the biofilm was visually examined. To decolorize the studs, they were transferred to a new microtiter plate containing 200 µl of 10% (v / v) acetic acid. The absorbance of the well containing acetic acid and CV from the studs was measured at 540 nm using a Multiskan (RTM) FC microplate spectrophotometer (available from Thermo Fisher Scientific (Waltham, MA, USA)).

[0106] Eight biological replicates were performed, and for each replicate, the mean absorbance value of control pins grown under the same culture medium and conditions in the absence of any bacteria was determined. These control pins underwent the same staining, dissolution, and measurement procedures as the biological samples. To account for any background signal or nonspecific absorbance, the mean absorbance value of the control pins was subtracted from the absorbance value obtained from the biological samples.

[0107] Figures 9a through 9e illustrate the attachment and biofilm growth of *E. coli* and *S. aureus* on the surfaces of the reference and additively manufactured samples. Figure 9a shows the viable cell count of *E. coli* in LB medium after 48 h, Figure 9b shows the viable cell count of *S. aureus* in LB medium after 48 h, Figure 9c shows the viable cell count of *E. coli* in LB medium after 4 h, and Figure 9d shows the viable cell count of *S. aureus* in LB medium after 4 h. In Figures 9a through 9d, the y-axis represents the colony-forming units (CFU) per stud on a logarithmic scale, while the x-axis shows the different types of stud samples. Results from two independent experiments are presented, with a total of eight biological replicates. The median is visually represented as a black line. Statistical analysis was performed by Brown-Forsythe and Welch ANOVA, followed by Dunnett's T3 multiple comparisons. The symbol “ns” indicates a p-value greater than 0.0332, the symbol “*” indicates a p-value between 0.0021 and 0.0332, and the symbol “**” indicates a p-value between 0.0002 and 0.0021. Figure 9e shows representative images of biofilms grown on different emboli for 48 h and stained with 0.1% crystal violet.

[0108] As shown in Figures 9c and 9d, after a 4-hour interval, significant differences were observed between Class I and Class II surfaces in the reverse side of colony-forming units per pin for both bacterial models. Specifically, Class I pins exhibited relatively low cell counts, typically in the tens, while the printed, unprinted pins showed significantly higher cell counts. In the case of *E. coli*, this range was 1,000 to 10,000 cells, while for *Staphylococcus aureus*, it ranged from 100 to 1,000 cells.

[0109] For Class II studs, the use of abrasive media at different times (5 h, 10 h, and 15 h) had a negligible effect on reducing the cell count per stud (Figs. 9c and 9d). However, studs post-treated with polishing media for 3 hours showed a reduction in cell count, although this was not statistically significant. Interestingly, vapor-smoothed studs exhibited a significant reduction in CFU / stud ratio, showing lower values ​​for both *E. coli* and *Staphylococcus aureus* than reference studs processed by injection molding.

[0110] CV staining was used as a method for quantifying biofilm biomass. Initial assessments were performed for both bacteria at 4 and 48 hours in LB and 24 hours in PBS. While this assay does not directly measure functional aspects of the biofilm, it provides valuable insights into the overall biofilm structure and biomass. Specifically, CV staining facilitates the visualization and quantification of live and dead cells within the biofilm, as well as the presence of extracellular matrix (ECM) components. Of particular interest was the observation that measurable biofilms were produced by CV staining in experiments performed solely in LB for 48 hours. This assessment was based on absorbance measurements at 540 nm obtained after dissolving CV in acetic acid. Subsequently, the remaining post-processed pins were prepared using both *E. coli* and *S. aureus* under these specific conditions. Visual evidence revealed clear stained biomass rings around all pins at the gas-liquid interface, as shown in Figure 9e. Interestingly, biofilms on PEG_IM with *E. coli* and PEG_PBF_VS with *S. aureus* exhibited small circular patterns, while more uniform rings formed on the remaining samples.

[0111] Although the CFU / pin counts were comparable across all surfaces after 48 hours in LB, a significant difference emerged in biomass presence between Class I and Class II pin surfaces, with a difference of approximately 5-fold. For example, the crystal violet absorbance of CNC and IM pins was 0.110 and 0.090, respectively, while the PEG_PBF_0h pin showed a significantly higher value of 0.559 for *E. coli*. Combined with visual inspection, it can be inferred that a more evolved biofilm with higher ECM content formed on the unprinted pins. Furthermore, tumbling with abrasive media for 5, 10, and 15 hours revealed comparable *E. coli* biofilm growth compared to the unprinted pins. However, an additional 3-hour treatment with polishing media resulted in a significant 70% reduction in crystal violet absorbance. Moreover, *Staphylococcus aureus* samples post-treated with abrasive media showed values ​​2–4 times higher than those on the unprinted pins, while PEG_PBF_13hP3h showed values ​​similar to PEG_PBF_0h. Based on the CFU / pendant results, PEG_PBF_VS showed comparable results to the reference pendant, with absorbances of 0.042 and 0.059 for Escherichia coli and Staphylococcus aureus, respectively. Therefore, these findings provide valuable insights into biofilm development on different pendant surfaces and the impact of post-treatment techniques on biofilm formation, thus contributing to a better understanding of the interaction between surface properties and bacterial attachment in bioprocessing equipment.

[0112] Furthermore, to elucidate biofilm differentiation and gain a deeper understanding of observed surface differences, biofilms grown on LB medium for 48 hours were imaged using FE-SEM. Specifically, the surface morphology of the scaffolds was analyzed using an FE-SEM (JSM 7400F, JEOL, Japan). Filamentous samples were sputtered using a chromium-coated (~10 nm) stencil (SC7640, Polaron, United Kingdom) and then imaged at 1 kV. Images were acquired for both Escherichia coli and Staphylococcus aureus, focusing on both type I and type II emboli.

[0113] Figure 10 Field emission scanning electron microscopy (FE-SEM) images of *E. coli* biofilms on CNC-milled studs (PEG_CNC) in Luria-Bertani broth (LB) medium for 48 h are shown at magnifications of (a) x1000, (b) x2200, (c) x5000, and (d) x10000. Other FE-SEM images of *E. coli* biofilms on injection-molded studs (PEG_IM) in LB medium are shown at magnifications of (e) x1000, (f) x2200, (g) x5000, and (h) x10000. Finally, FE-SEM images of *E. coli* biofilms on vapor-smoothed studs (PEG_PBF_VS) in LB medium are shown at magnifications of (i) x1000, (j) x2200, and (k). Field emission scanning electron microscope images imaged at magnifications of x5000 and (k) x10000.

[0114] Figure 11Field emission scanning electron microscopy (FE-SEM) images of *E. coli* biofilms on molten powder bed studs (PEG_PBF_0h) after printing for 4 h in Luria-Bertani broth (LB) medium, imaged at (a) x1000, (b) x2200, (c) x5000, and (d) x10000 magnifications; *E. coli* biofilms on PBF studs (PEG_PBF_5h) treated with abrasive media for 5 h in LB medium, imaged at (e) x1000, (f) x2200, and (g) x5000 magnifications; and *E. coli* biofilms on PBF studs (PEG_PBF_10h) treated with abrasive media for 10 h in LB medium, imaged at (h) x1000, (i) x2200, and (g) x5000 magnifications. Field emission scanning electron microscope (FESEM) images at (j) x2200 magnification and (j) x5000 magnification; Escherichia coli biofilm on PBF studs (PEG_PBF_15h) treated with abrasive media for 15 h in LB medium and imaged at (k) x1000 magnification, (l) x2200 magnification, (m) x5000 magnification, and (n) x10000 magnification; and Escherichia coli biofilm on PBF studs (PEG_PBF_13hP3h) treated with abrasive media for 13 h (including a three-hour polishing step) in LB medium and imaged at (o) x1000 magnification, (p) x2200 magnification, and (q) x5000 magnification.

[0115] Figure 12 Field emission scanning electron microscopy (FE-SEM) images of Staphylococcus aureus biofilms on CNC-milled pins (PEG_CNC) in Luria-Bertani broth (LB) medium for 48 h are shown, imaged at (a) x1000, (b) x2200, and (c) x5000 magnifications; FE-SEM images of Staphylococcus aureus biofilms on injection-molded pins (PEG_IM) in LB medium, imaged at (d) x1000, (e) x2200, and (f) x5000 magnifications; and FE-SEM images of Staphylococcus aureus biofilms on vapor-smoothed pins (PEG_PBF_VS) in LB medium, imaged at (g) x1000, (h) x2200, and (i) x5000 magnifications. Figure 13 Field emission scanning electron microscopy (FE-SEM) images of Staphylococcus aureus biofilm on molten powder bed studs (PEG_PBF_0h) after printing for 48 h in Luria-Bertani broth (LB) medium, imaged at (a) x1000, (b) x2200, and (c) x5000 magnification; Staphylococcus aureus biofilm on PBF studs (PEG_PBF_5h) treated with abrasive media for 5 h in LB medium, imaged at (d) x1000, (e) x2200, and (f) x5000 magnification; and Staphylococcus aureus biofilm on PBF studs (PEG_PBF_10h) treated with abrasive media for 10 h in LB medium, imaged at (g) x1000, (h) x2200, and (i) x2200. Field emission scanning electron microscope (FESEM) images at (k) x5000 magnification; Staphylococcus aureus biofilm on PBF studs (PEG_PBF_15h) treated with abrasive media for 15 h in LB medium and imaged at (k) x1000 magnification, (k) x2200 magnification, and (l) x5000 magnification; and Staphylococcus aureus biofilm on PBF studs (PEG_PBF_13hP3h) treated with abrasive media for 13 h (including a three-hour polishing step) in LB medium and imaged at (m) x1000 magnification, (n) x2200 magnification, and (o) x5000 magnification.

[0116] Reference studs produced by CNC milling ( Figure 10 a and Figure 10 b) Exhibits a uniform surface with visible lines produced by the cutting tool. Additionally, samples incubated with *E. coli* form localized and dispersed thin layers of cell colonies, with a higher density observed on surface features generated during manufacturing. Figure 10 c and Figure 10 d). No 3D structures or EPS were found. Similarly, samples incubated with Staphylococcus aureus showed isolated cells and small colonies of 20-30 cells dispersed on the surface. Figure 12 a, Figure 12 b and Figure 12 c). In contrast, studs manufactured using IM exhibit the smoothest surface of all surfaces, thus revealing only the presence of weld lines ( Figure 10 e and Figure 10f). Furthermore, these surfaces exhibited the greatest variation between the two bacterial strains. Large, round colonies formed on the smooth, plug-topped surfaces after incubation with *E. coli*. Figure 10 e Figure 10 f、 Figure 10 g and Figure 10 h), while Staphylococcus aureus exhibits a preference for adhering along the weld line, thus forming a continuous flow of cells, with only a small number of scattered colonies on the remaining surface area (h). Figure 12 d、 Figure 12 e and Figure 12 f). Furthermore, the vapor-smoothed surfaces also exhibited a high degree of smoothness compared to the original printed surfaces. However, their surfaces also displayed a "volcano-like" structure formed during post-processing. In the case of bacterial adhesion, *E. coli* was observed (…). Figure 10 i、 Figure 10 j、 Figure 10 k and Figure 10 l) Cells exhibit a dispersed distribution, thus occupying smooth surfaces and displaying a "volcano" characteristic. Conversely, Staphylococcus aureus cells exhibit a significantly higher attachment density, uniformly colonizing the surface regardless of surface features ( Figure 12 g、 Figure 12 h and Figure 12 i). In summary, surface morphology analysis of the Class I pin samples revealed distinct characteristics in terms of surface texture and bacterial adhesion behavior. CNC pins exhibited a uniform surface with visible cut lines, while IM and VS pins were the smoothest, but they displayed surface features resembling weld lines and volcano-like structures, respectively. *E. coli* and *S. aureus* cells showed the highest adhesion on IM pins, while *E. coli* adhered only to surface features on both CNC and VS surfaces. Conversely, *S. aureus* cells densely adhered to the VS surface, and only small colonies were found on the CNC samples.

[0117] Type II studs were incubated under the same conditions as Type I studs. These Type II studs included stud samples printed as is and stud samples that underwent surface tumbling with abrasive and polishing media at different tumbling times. Figure 11 and Figure 13 As previously mentioned, the PEG_PBF_0h (printed as is) studs exhibited a highly rough surface with adhered PP powder particles (ranging in size from 20 µm to 100 µm) fused to the exterior of the stud surface, a phenomenon known as the necking phenomenon. Biofilm studies revealed the presence of E. coli (…). Figure 11 a, Figure 11 b、 Figure 11 c and Figure 11 d) and Staphylococcus aureus ( Figure 13 a, Figure 13 b and Figure 13c) The cells are hidden within the gaps between powder particles, making them imperceptible on the outer surface. The presence of crevices, pores, and irregularities provides favorable attachment sites for these cells. However, their ability to colonize and generate large-area biofilm patches (similar to what was observed in Class I samples) is limited.

[0118] The effects of tumbling the surface with abrasive media for 5, 10, and 15 hours resulted in a slight reduction in the initial roughness of the printed stud samples. This surface treatment revealed the presence of some smoother areas on the surface, but overall, they remained comparable to the PEG_PBF_0h sample. Subsequent analysis of the PEG_PBF_5h sample revealed Escherichia coli (E. coli) Figure 11 e Figure 11 f and Figure 11 g) and Staphylococcus aureus ( Figure 13 e Figure 13 f and Figure 13 g) cells appeared as scattered small colonies. However, with increasing post-treatment time, smoothness improved, resulting in pins with denser and larger cell patches for both bacterial species. Figure 11 h、 Figure 11 i、 Figure 11 j、 Figure 11 k、 Figure 11 l、 Figure 11 m、 Figure 11 n、 Figure 13 g、 Figure 13 h、 Figure 13 i、 Figure 13 j、 Figure 13 k and Figure 13 l). The application of the polishing medium provided the highest smoothness for the surface-milled samples, and patches of potential biofilm were also found at the intersections between particles and smooth areas. Figure 11 o、 Figure 11 p、 Figure 11 q、 Figure 13 m、 Figure 13 n and Figure 13 o).

[0119] To assess the impact of surface texture on bacterial growth and adhesion, a series of experiments were conducted using PBS as the culture medium. PBS was chosen because it provides a nutrient-free environment, allowing focus solely on the effects of surface texture without confounding the availability of nutrients. Experiments were performed with two bacteria (Escherichia coli and Staphylococcus aureus) at four time points (4, 6, 16, and 24 hours). Figure 14 a and Figure 14 b).

[0120] Figure 14Escherichia coli and Staphylococcus aureus attachment and biofilm growth are shown on the surfaces of reference studs (PEG_CNC and PEG_IM) and additively manufactured studs (PEG_PBF_0h, PEG_PBF_5h, PEG_PBF_10h, PEG_PBF_15h, PEG_PBF_13hP3h and PEG_PBF_VS). Figure 14 a shows the viable cell counts of *E. coli* in PBS at 4, 6, 16, and 24 hours. The y-axis represents colony-forming units (CFU) per stump on a logarithmic scale, while the x-axis shows the different time points. Results from two independent experiments are presented, with a total of eight biological replicates. The median for all conditions is shown as a sign. At 24 h, the values ​​(in ascending order) correspond to: PEG_IM, PEG_CNC, PEG_PBF_VS, PEG_PBF_5h, PEG_PBF_15h, PEG_PBF_13h_3P, PEG_PBF_0h, and PEG_PBF_10h.

[0121] Figure 14 b shows the viable cell counts of Staphylococcus aureus in PBS at 4, 6, 16, and 24 hours. The y-axis represents colony-forming units (CFU) per pin on a logarithmic scale, while the x-axis shows the different time points. Results from two independent experiments are presented, with a total of eight biological replicates. The median for all conditions is shown as a sign.

[0122] In the E. coli PBS experiment ( Figure 14 a) Regarding bacterial attachment, different behaviors were observed in Class I and Class II samples. Class I samples exhibited a maximum threshold of 100 CFU / pendant, beyond which cell attachment increased significantly at each time point. Regardless of the abrasive medium used and the time points considered, post-printed pendants and surface-rolled pendants showed similar levels of E. coli attachment. No substantial differences were observed in these samples. Consistent with previous findings, only PEG_PBF_VS pendants demonstrated the ability to reduce bacterial attachment at each time point. As expected, the reference pendants (CNC and IM) also exhibited the lowest CFU number per pendant at each time point. Furthermore, E. coli cell attachment on the pendants reached saturation at 6 hours, and no significant change in CFU was observed until 24 hours.

[0123] Staphylococcus aureus experiment ( Figure 14(b) Different trends were observed, with a decrease in bacterial attachment observed for all samples at 16 hours. The saturation point for Staphylococcus aureus appeared earlier, at 4 hours, where the CFU per pin remained relatively constant, before experiencing a significant decrease at 16 hours. These findings elucidate the contrasting behavior of Gram-positive and Gram-negative bacteria attaching to various pin samples over time. The results highlight the importance of surface features and properties in influencing bacterial attachment dynamics.

[0124] Figure 15 shows the... Figure 8 The values ​​of relevant roughness parameters were obtained from the variable projection importance (VIP) plot. These roughness parameters describe the valley regions of the stud sample. Figure 15a The valley material ratio (Smrk2) is shown. Figure 15b The reduced pit depth (Svk) is shown. Figure 15c The maximum pit depth (Svkx) is shown. Figure 15d The arithmetic mean height (Sa) is shown. Figure 15e The root mean square height (Sq) is shown. Figure 15f The maximum pit depth (Sv) is shown. Figure 15g The maximum height is shown. Figure 15h The valley void volume (Vvv) is shown. Figure 15i The depth of the five-point pit (S5v) is shown, and Figure 15j The material-to-height difference (Sdc) is shown. The calculated average value is derived from a set of 12 samples for each stud sample. Figures 15a to 15c The functional parameters of the layered surface are shown. Figures 15d to 15g The height parameter is shown. Figure 15h The volume-based functional parameters are shown. Figure 15i The characteristic parameters are shown, and Figure 15j The functional parameters are shown.

[0125] Visual inspection, including FE-SEM imaging of the stud surface, revealed significant differences in surface morphology. Surfaces produced by conventional methods (CNC and IM) exhibited low-valley roughness parameters. Figure 10 , Figure 12 (and Figure 15). Conversely, the AM-generated samples exhibit a rough surface characterized by molten powder particles, thus producing a large number of surface features ideal for cell adhesion (and Figure 15). Figure 11 and Figure 13 Post-treatment with abrasive media showed minimal impact on relevant roughness parameters, thus keeping the valley areas of the stud surface largely unchanged (Fig. 15). Excellent results were obtained using polishing media, but this effect was uneven, showing both smooth areas and areas with no discernible effect. Figure 11 and Figure 13Only gas-phase smoothing produces a significant surface transition, resulting in a smooth surface scattered with residual "volcanic" surface features. Figure 10 and Figure 12 Several explanations exist for this phenomenon; however, further research is needed to determine the primary cause.

[0126] Subsequent characterization steps involved in-depth surface texture analysis, focusing on various relevant roughness parameters. Robust correlations were established between specific surface roughness parameters and the adhesion of *E. coli* and *Staphylococcus aureus* during the first bacterial attachment phase (4 hours) in LB medium (Figs. 9c and 9d, and Fig. 15). Significant differences on the surfaces of different studs were described by parameters from different families, including hierarchical surface parameters (Smrk2, Svk, Svkx), highly correlated parameters (Sa, Sq, Sv, Sz), volumetric function parameters (Vvv), feature-specific parameters (S5v), and functional parameters (Sdc). Furthermore, surfaces belonging to class I studs exhibited the highest hydrophilicity (e.g., ...). Figure 4 (As shown) showed the lowest bacterial attachment after 4 hours.

[0127] Focusing on these roughness parameter groups, it is clear that valley regions have a more significant impact than their peak and hill counterparts. In Class I pins, encompassing PEG_CNC, PEG_IM, and PEG_PBF_VS, both reduced pit height and maximum pit depth exhibit identifiable lower values, as shown in Figure 15. In this classification, vapor-smoothed pins clearly show the lowest values. This trend persists across all examined parameters, confirming the significance of valley regions in mediating bacterial attachment. Furthermore, this is confirmed by analysis of the S5v parameter, which quantifies the average of the five most prominent pit depths (…). Figure 15i Type I studs exhibited an average pit depth of less than 5 µm, in stark contrast to the 35 to 46 µm range observed in Type II studs.

[0128] Extending the analysis to include surface roughness, the effectiveness of culture surfaces characterized by shallow features and non-deep pits in mitigating the adhesion of *E. coli* and *Staphylococcus aureus* is evident. As demonstrated in Figures 9c and 9d, this effect is significant in the initial hours of bacterial attachment. However, as shown in Figures 9a and 9b, regardless of the specific surface properties of the studs, after a 48-hour period, the CFU count per stud significantly increases to approximately 10. 7 One. It can be envisioned that the extended incubation period will result in even greater biomass accumulation.

[0129] Related to the findings on surface roughness, static contact angles measured on type I studs, compared to type II studs, indicated higher hydrophilicity (e.g., ...). Figure 4 (As shown). Specifically, those manufactured using CNC milling exhibit the lowest degree of hydrophobicity, with values ​​of 60º ± 2º. In the field of biological treatment, the use of highly hydrophobic surfaces is important for avoiding water adhesion within equipment interiors with complex geometries and unstable flows. However, conflicting results regarding the initial adhesion of bacteria based on surface wettability have been reported in the literature. Generally, it is recognized that superhydrophobic and superhydrophilic surfaces tend to reduce bacterial adhesion, while there is no consensus on surfaces with moderate wettability. This disclosure reveals that hydrophilic stud surfaces (Type I studs) exhibit lower bacterial adhesion, while hydrophobic stud surfaces (Type II studs) exhibit higher bacterial adhesion for Escherichia coli and Staphylococcus aureus. Figure 4 This illustrates how the surface texture of the stud affects the contact angle results measured using an optical tensiometer.

[0130] As previously mentioned, CFU / pendant differentiation was evident in the 4-hour LB experiment, with pendants exhibiting 100-fold more adherent cells compared to type I pendants (Figs. 9c and 9d). For pendants post-treated with grinding and polishing media, an intermediate value between the reference pendant and the post-printed pendant was observed for both bacterial models (Figs. 9c and 9d). Nevertheless, only pendants treated with vapor phase smoothing showed a significant change in bacterial adhesion compared to PEG_PBF_0h. In contrast, all samples treated with tumbling showed similar E. coli counts and higher Staphylococcus aureus counts when compared to their post-printed counterparts. FE-SEM imaging was performed after 4 hours of incubation with both cell types in LB medium, as this adhesion time revealed relevant differences in CFU / pendant adhesion on different surfaces.

[0131] The next step involved employing PBS-based experiments to simulate real-world conditions in biological treatment environments where culture media typically lack essential nutrients. Analyses were performed at multiple time points (4, 6, 16, and 24 hours), and the expected trend of increasing CFU / embolic attachment over time did not match the observed data pattern. Figure 14 However, compared to type II samples, type I studs exhibited a lower number of attached E. coli cells, as previously observed in LB medium analysis.

[0132] To observe the significant differences between different surfaces, bacterial adhesion of *E. coli* on LB medium was assessed for each sample after 48 hours. Except for samples with smooth gas phase, the results shifted towards a state of equilibrium with comparable CFU / pile values ​​(Figure 9a). This observation suggests that bacteria in nutrient-rich media eventually adhere to and proliferate on a variety of surfaces.

[0133] In biofilm analysis using crystal violet staining, type II pins (high valley roughness parameter) showed greater biomass accumulation. Compared to reference pins, these pins reached equilibrium earlier and exhibited enhanced ECM generation capacity, leading to the formation of more mature biofilms (Fig. 9e). Furthermore, crystal violet staining revealed significant biomass accumulation at the gas-liquid interface, forming characteristic rings around the pins.

[0134] Within a 48-hour timeframe, including cases with a bacterial load exceeding 10... 6 FE-SEM studies of the studs (CFU / stud) confirmed varying degrees of bacterial attachment on the surfaces of different studs. The highest level of E. coli cell attachment was observed on the IM studs, characterized by the presence of numerous, round cell colonies distributed along the smooth areas of the studs. Figure 10 e Figure 10 f、 Figure 10 g and Figure 10 h). Conversely, in the case of Staphylococcus aureus, denser attachments were observed along the weld line of the stud (h). Figure 12 d、 Figure 12 e and Figure 12 f). In the latter case, a layered bacterial layer was observed, involving cell division and abundant attachment to the surface. For the printed, unmodified studs, PEG_PBF_0h, the opposite was observed, in which dispersed E. coli and Staphylococcus aureus cells were found (f). Figure 11 b、 Figure 11 c. Figure 13 b and Figure 13 c). Meanwhile, the remaining stud samples, characterized by low-valley roughness parameters (CNC and VS), exhibited dispersed cell clusters scattered in random patterns on the surface. VS studs showed increased Staphylococcus aureus cell density ( Figure 12 g、 Figure 12 h and Figure 12 i). Contrary to the results of crystal violet staining, SEM images showed that pins with high valley roughness parameters presented greater difficulties for bacterial attachment. On smooth surfaces, once attachment occurred, bacteria experienced less resistance and proliferated more easily due to the lack of surface constraints. However, for pins tumbled with abrasive media, the most mature biofilms with ECMs were observed, obtained from crystal violet staining, and correlated with the characterization of high valley roughness parameters.

[0135] Therefore, it can be understood from the above analysis that the ten relevant surface roughness parameters (in) Figure 8Adjusting the values ​​(indicated by the Chinese identifier) ​​to those associated with Class I studs (shown in Figure 15) can be expected to produce surfaces with low bacterial adhesion tendency (i.e., consistent with the findings in Figures 9c and 9d). Specifically, a low bacterial adhesion tendency can be expected if the surface of the post-processed additively manufactured part has one or more of the following surface roughness parameter values, which are generated by filtering surface features to remove surface features with long wavelengths (e.g., greater than 54 µm):

[0136] (i) a reduced valley height Svk less than 5 µm, preferably less than 4 µm, more preferably less than 3 µm, more preferably less than 2 µm, and most preferably less than 1 µm (e.g.) Figure 15b As shown, the Svk value for PEG_CNC is 0.8 µm, the Svk value for PEG_IM is 1.1 µm, and the Svk value for PEG_PBF_VS is 0.1 µm, which contrasts with the value greater than 17 µm for Class II surfaces.

[0137] (ii) an arithmetic mean height Sa less than 2.5 µm, preferably less than 2 µm, more preferably less than 1.5 µm, and most preferably less than 1 µm (e.g.) Figure 15d As shown, the Sa value of PEG_CNC is 1.0 µm, the Sa value of PEG_IM is 0.5 µm, and the Svk value of PEG_PBF_VS is 0.1 µm, which contrasts with the value of greater than 4.5 µm for Class II surfaces.

[0138] (iii) Less than 0.5 µm 3 µm -2 More preferably less than 0.4 µm 3 µm -2 More preferably less than 0.3 µm 3 µm -2 More preferably less than 0.2 µm 3 µm -2 And most preferably less than 0.1 µm 3 µm -2 The valley void volume Vvv (e.g.) Figure 15h As shown, the Vvv value of PEG_CNC is 0.06 µm. 3 µm -2 The Vvv value of PEG_IM is 0.08 µm. 3 µm -2 And the Vvv value of PEG_PBF_VS is 0.01 µm. 3 µm -2 , compared to Class II surfaces greater than 1.7 µm 3 µm-2 (to form a comparison of values)

[0139] (iv) The height S5v of the five-point indentation is less than 15 µm, preferably less than 12.5 µm, more preferably less than 10 µm, more preferably less than 7.5 µm, and most preferably less than 5 µm (e.g. Figure 15i As shown, the S5v value of PEG_CNC is 2.8 µm, the S5v value of PEG_IM is 4.2 µm, and the S5v value of PEG_PBF_VS is 0.6 µm, which contrasts with the value of greater than 35 µm for Class II surfaces.

[0140] (v) The maximum pit depth Svkx is less than 20 µm, preferably less than 15 µm, more preferably less than 10 µm, and most preferably less than 5 µm (e.g. Figure 15c As shown, the Svkx value of PEG_CNC is 2.7 µm, the Svkx value of PEG_IM is 4.4 µm, and the Svkx value of PEG_PBF_VS is 0.8 µm, which contrasts with the value of greater than 41 µm for Class II surfaces.

[0141] (vi) Valley material ratio between 85% and 95%, preferably between 86% and 93%, and more preferably between 87% and 91% (e.g., Smrk2) Figure 15a As shown, the Smrk2 value of PEG_CNC is 90.4%, the Smrk2 value of PEG_IM is 87.9%, and the Smrk2 value of PEG_PBF_VS is 87.8%, which contrasts with the value of less than 79% for Class II surfaces.

[0142] (vii) A root mean square height Sq less than 4 µm, preferably less than 3.5 µm, more preferably less than 3 µm, more preferably less than 2.5 µm, and most preferably less than 2 µm (e.g.) Figure 15e As shown, the Sq value of PEG_CNC is 1.4 µm, the Sq value of PEG_IM is 1.2 µm, and the Sq value of PEG_PBF_VS is 0.1 µm, which contrasts with the values ​​greater than 7 µm for Class II surfaces.

[0143] (viii) A maximum height Sz less than 20 µm, more preferably less than 17.5 µm, more preferably less than 15 µm, and most preferably less than 12.5 µm (e.g.) Figure 15g As shown, the Sz value of PEG_CNC is 11.8 µm, the Sz value of PEG_IM is 12.9 µm, and the Sz value of PEG_PBF_VS is 1.5 µm, which contrasts with the value of greater than 68 µm for Class II surfaces.

[0144] (ix) The maximum pit depth Sv is less than 20 µm, preferably less than 15 µm, more preferably less than 10 µm, and most preferably less than 5 µm (e.g. Figure 15f As shown, the Sv value of PEG_CNC is 3.6 µm, the Sv value of PEG_IM is 4.8 µm, and the Sv value of PEG_PBF_VS is 0.8 µm, in contrast to the value greater than 41 µm for Class II surfaces); and

[0145] (x) material height difference Sdc less than 7 µm, preferably less than 6 µm, more preferably less than 5 µm, more preferably less than 4 µm and most preferably less than 3 µm (e.g. Figure 15j As shown, the Sdc value of PEG_CNC is 3.0 µm, the Sdc value of PEG_IM is 0.7 µm, and the Sdc value of PEG_PBF_VS is 0.2 µm, which contrasts with the value of greater than 14 µm for Class II surfaces.

[0146] If the static contact angle of such post-treated surfaces is between 45 and 105 degrees, preferably between 50 and 100 degrees, more preferably between 55 and 95 degrees, and most preferably between 60 and 90 degrees, then such post-treated surfaces can also be expected to have a low tendency for bacterial adhesion (e.g., Figure 4 As shown, the static contact angle value of PEG_CNC is 60 degrees, that of PEG_IM is 82 degrees, and that of PEG_PBF_VS is 88 degrees, which contrasts with the static contact angle value of Class II surfaces, which is higher than 110 degrees.

[0147] The following paragraphs describe the changes or modifications to the systems and methods described in this paper.

[0148] It should also be understood that the methods described herein are not limited to the evaluation of the surfaces of parts produced by PBF, and can also be applied to the surfaces of parts produced by other AM technologies. Furthermore, it should be understood that the methods described herein are not actually limited to the evaluation of the surfaces of parts produced by AM technologies, and can alternatively or additionally be applied to the surfaces of parts produced using other manufacturing technologies.

[0149] Furthermore, the methods described herein are not limited to the evaluation of stud-shaped surfaces. Specifically, Figure 2 The method can be used to verify the tendency of bacteria to attach to other features of manufactured parts, such as pockets, cavities, and corners. The findings described herein are particularly applicable to surfaces including the boundaries between adjacent layers of additively manufactured parts.

[0150] The described methods can be implemented using computer-executable instructions. A computer program product or computer-readable medium may include or store computer-executable instructions. A computer program product or computer-readable medium may include hard disk drives, flash memory, read-only memory (ROM), CDs, DVDs, caches, random access memory (RAM), and / or any other storage medium in which information is stored for any duration (e.g., for extended periods, permanently, briefly, temporarily buffered, and / or cached information). A computer program may include computer-executable instructions. A computer-readable medium may be a tangible or non-transitory computer-readable medium. The term "computer-readable" encompasses "machine-readable."

[0151] The singular terms “a” and “an” should not be considered as meaning “one / a kind and only one / a kind”. Rather, unless otherwise stated, they should be considered as meaning “at least one” or “one or more”. The word “comprising” and its derivatives, including “comprises” and “comprise”, include each of the stated features, but do not exclude the inclusion of one or more other features.

[0152] The specific embodiments described above have been illustrated by way of example only, and are to be considered in all respects as illustrative rather than restrictive. It should be understood that variations may be made to the described embodiments without departing from the scope of the invention. It will also be apparent that many variations exist that are not described but fall within the scope of the appended claims.

Claims

1. A method (100) for producing a part (300) for use in a biological treatment system, the method comprising: The part (300) described in (110) is manufactured using an additive manufacturing process. as well as The surface of the part (300) is post-treated (120), wherein the surface is intended to be wetted during use; The post-processed surface has one or more of the following surface roughness parameter values ​​(optionally measured according to ISO 25178-2:2022), and said one or more surface roughness parameter values ​​are measured on the surface after filtering the surface to remove surface features with long wavelengths: The reduced valley height Svk is less than approximately 5 µm; The arithmetic mean height Sa is less than approximately 2.5 µm; Less than approximately 0.5 µm 3 µm -2 The valley void volume Vvv; and / or The height of the five-point pit is less than approximately 15 µm, S5v.

2. The method (100) according to claim 1, wherein the surface comprises a plurality of boundaries between adjacent layers of the part (300).

3. The method (100) according to claim 1 or claim 2, wherein the part (300) is manufactured using powder bed melting.

4. The method (100) according to any one of claims 1 to 3, wherein post-treatment of the surface includes chemical vapor phase surface smoothing of the surface.

5. The method (100) according to any one of claims 1 to 4, wherein the height of the reduced valley Svk of the post-treated surface is less than about 4 µm, preferably less than about 3 µm, more preferably less than about 2 µm, and most preferably less than about 1 µm.

6. The method (100) according to any one of claims 1 to 5, wherein the arithmetic mean height Sa of the post-processed surface is less than about 2 µm, preferably less than about 1.5 µm, and more preferably less than about 1 µm.

7. The method (100) according to any one of claims 1 to 6, wherein the valley void volume Vvv of the post-treated surface is less than about 0.4 µm. 3 µm -2 Preferably less than about 0.3 µm 3 µm -2 More preferably less than about 0.2 µm 3 µm -2 And most preferably less than about 0.1 µm 3 µm -2 .

8. The method (100) according to any one of claims 1 to 7, wherein the height S5v of the five-point pit on the post-treated surface is less than about 12.5 µm, preferably less than about 10 µm, more preferably less than about 7.5 µm, and most preferably less than about 5 µm.

9. The method (100) according to any one of claims 1 to 8, wherein the post-processed surface has a maximum pit depth Svkx, optionally less than about 20 µm, preferably less than about 15 µm, more preferably less than about 10 µm and most preferably less than about 5 µm, as measured according to ISO 25178-2:2022, wherein the maximum pit depth Svkx is measured for the surface after filtering the surface to remove surface features with long wavelengths.

10. The method (100) according to any one of claims 1 to 9, wherein the post-processed surface has a valley material ratio Smrk2, optionally measured according to ISO 25178-2:2022, between about 85% and 95%, preferably between about 86% and 93%, and more preferably between about 87% and 91%, wherein the valley material ratio Smrk2 is measured for the surface after filtering the surface to remove surface features having long wavelengths.

11. The method (100) according to any one of claims 1 to 10, wherein the post-processed surface has a root mean square height Sq, optionally less than about 4 µm, preferably less than about 3.5 µm, more preferably less than about 3 µm, more preferably less than about 2.5 µm and most preferably less than about 2 µm, as measured according to ISO 25178-2:2022, wherein the root mean square height Sq is measured for the surface after filtering the surface to remove surface features with long wavelengths.

12. The method (100) according to any one of claims 1 to 11, wherein the post-processed surface has a maximum height Sz of less than about 20 µm, more preferably less than about 17.5 µm, more preferably less than about 15 µm and most preferably less than about 12.5 µm, as measured according to ISO 25178-2:2022, wherein the maximum height Sz is measured for the surface after filtering the surface to remove surface features with long wavelengths.

13. The method (100) according to any one of claims 1 to 12, wherein the post-processed surface has a maximum pit depth Sv that is optionally less than about 20 µm, preferably less than about 15 µm, more preferably less than about 10 µm and most preferably less than about 5 µm, as measured according to ISO 25178-2:2022, wherein the maximum pit depth Sv is measured for the surface after filtering the surface to remove surface features having long wavelengths.

14. The method (100) according to any one of claims 1 to 13, wherein the post-processed surface has a material specific height difference Sdc of less than about 7 µm, preferably less than about 6 µm, more preferably less than about 5 µm, more preferably less than about 4 µm and most preferably less than about 3 µm, as measured according to ISO 25178-2:2022, wherein the material specific height difference Sdc is measured for the surface after filtering the surface to remove surface features having long wavelengths.

15. The method (100) according to any one of claims 1 to 14, wherein the static contact angle of the post-treated surface is between about 45 degrees and 105 degrees, preferably between about 50 degrees and 100 degrees, more preferably between about 55 degrees and 95 degrees, and most preferably between about 60 degrees and 90 degrees.

16. The method (100) according to any one of claims 1 to 15, wherein the part (300) is formed of polypropylene.

17. The method (100) according to any one of claims 1 to 16, wherein the arithmetic mean height Ra along the surface is greater than about 0.5 µm.

18. An additively manufactured part (300) for use in a biological processing system, wherein the additively manufactured part (300) includes a surface intended to be wetted in use, wherein the surface has one or more of the following surface roughness parameter values, optionally measured according to ISO 25178-2:2022, wherein the one or more surface roughness parameter values ​​are measured for the surface after filtering the surface to remove surface features having long wavelengths: The reduced valley height Svk is less than approximately 5 µm; The arithmetic mean height Sa is less than approximately 2.5 µm; Less than approximately 0.5 µm 3 µm -2 The valley void volume Vvv; and / or The height of the five-point pit is less than approximately 15 µm, S5v.

19. The part (300) of claim 18, wherein the surface includes a plurality of boundaries between adjacent layers of the part (300).

20. The part (300) according to claim 18 or claim 19, wherein the height of the reduced valley Svk of the surface is less than about 4 µm, preferably less than about 3 µm, more preferably less than about 2 µm, and most preferably less than about 1 µm.

21. The part (300) according to any one of claims 18 to 20, wherein the arithmetic mean height Sa of the surface is less than about 2 µm, preferably less than about 1.5 µm, and more preferably less than about 1 µm.

22. The part (300) according to any one of claims 18 to 21, wherein the valley void volume Vvv of said surface is less than about 0.4 µm 3 µm -2 Preferably less than about 0.3 µm 3 µm -2 More preferably less than about 0.2 µm 3 µm -2 And most preferably less than about 0.1 µm 3 µm -2 .

23. The part (300) according to any one of claims 18 to 22, wherein the height S5v of the five-point recess on the surface is less than about 12.5 µm, preferably less than about 10 µm, more preferably less than about 7.5 µm, and most preferably less than about 5 µm.

24. The part (300) according to any one of claims 18 to 23, wherein the part (300) is formed of polypropylene.

25. The part (300) according to any one of claims 18 to 24, wherein the arithmetic mean height Ra along the surface is greater than about 0.5 µm.

26. A method (200) for classifying the surface of a part (300) for use in a biological treatment system, the method comprising: Manufacturing (210) the part (300), wherein the part (300) includes a surface intended to be wetted in use; as well as One or more of the following: After filtering the surface to remove surface features with long wavelengths, the reduced valley height Svk of the surface is measured (220), and if the reduced valley height Svk of the surface is less than about 5 µm, the surface is classified as suitable for use in the biological treatment system. After filtering the surface to remove surface features with long wavelengths, the arithmetic mean height Sa of the surface is measured (220), and if the arithmetic mean height Sa of the surface is less than about 2.5 µm, the surface is classified as suitable for use in the biological treatment system. After filtering the surface to remove surface features with long wavelengths, the valley void volume Vvv of the surface is measured (220), and if the valley void volume Vvv of the surface is less than about 0.5 µm... 3 µm -2 The surface is then classified as suitable for use in the biological treatment system; and After filtering the surface to remove surface features with long wavelengths, the five-point pit height S5v of the surface is measured (220), and if the five-point pit height S5v of the surface is less than about 15 µm, the surface is classified as suitable for use in the biological treatment system.

27. The method (100, 200) or part (300) according to any of the preceding claims, wherein the long wavelength is: greater than about 10 µm; greater than about 20 µm; greater than about 30 µm; greater than about 40 µm; greater than about 50 µm; greater than 54 µm; greater than about 54 µm; greater than about 55 µm; greater than about 60 µm; greater than about 70 µm; greater than about 80 µm; greater than about 90 µm; or greater than about 100 µm.

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