Study on visible-light-curable polycarprolactone and poly(ethylene glycol) diacrylate for LCD-projected maskless additive manufacturing system

Additive manufacturing (AM) systems present tremendous advantages over the traditional manufacturing systems, particularly for realizing complex shapes and producing custom parts. These advantages, and the rapid growth in the availability of AM systems, have led to a widespread increase in the use of AM. Unfortunately, general design for additive manufacturing (DfAM) tools that predict the engineering performance of AM parts are largely unavailable, and this has forced engineers to rely on engineering judgment and/or data from physical experiments. The data sets reported in the literature that quantify the performance of the existing AM systems provide much needed insight, but the data produced by experiments conducted on specific AM systems are necessarily of limited applicability. Given the large number of AM systems currently in use today, a potentially vast amount of data are needed to fully understand them all, and new AM systems and materials are being developed almost daily. To mitigate this need for an ever-increasing amount of data, this paper proposes the use of an approximation-assisted multi-objective optimization technique to quantify the performance of an AM system for specific design application in a targeted fashion. This general approach uses a limited number of physical experiments to answer a specific DfAM question of interest, and the results can then be used to design functional parts without the need for additional data. The implementation of the proposed approach is demonstrated with a material extrusion case study.

Fiber forming mechanism and reaction kinetics of novel dynamic-crosslinking-spinning for Poly(ethylene glycol) diacrylate fiber fabrication

Designing efficient closed-loop control algorithms is a key issue in Additive Manufacturing (AM), as various aspects of the AM process require continuous monitoring and regulation, with temperature being a particularly significant factor. Here we study closed-loop control for the temperatures in the extruder of a Material Extrusion AM system, specifically a Big Area Additive Manufacturing (BAAM) system. Previous approaches for temperature control in AM either require the knowledge of exact model parameters, or involve discretisation of the state and action spaces to employ traditional data-driven control techniques. On the other hand, modern algorithms that can handle continuous state and action space problems require a large number of hyperparameter tuning to ensure good performance. In this work, we circumvent the above limitations by making use of a state space temperature model while focusing on both model-based and data-driven methods. We adopt the Linear Quadratic Tracking (LQT) framework and utilise the quadratic structure of the value function in the model-based analytical solution to produce a data-driven approximation formula for the optimal controller. We demonstrate these approaches using a simulator of the temperature evolution in the extruder of a BAAM system and perform an in-depth comparison of the performance of these methods. We find that we can learn an effective controller using solely simulated input–output process data. Our approach achieves parity in performance compared to model-based controllers and so lessens the need for estimating a large number of parameters of the often intricate and complicated process model. We believe this result is an important step towards achieving autonomous intelligent manufacturing.

The performance characterization of the manufacturing processes for additive manufacturing (AM) systems is a significant task for their standardization and implementation in the industry. Also, there is a large diversity of materials used in different AM processes. In the present paper, a methodology is proposed to evaluate, in different directions, the performance of an AM process and material characterization in terms of surface quality. This methodology consists of eight steps, based on a new surface inspection artifact and basic artifact orientations. The proposed artifact with several design configurations fits different AM systems sizes and meets the needs of customers. The effects of main factors on the surface roughness of up-facing platens of the artifacts are investigated using the statistical design of experiments. The proposed methodology is validated by a case study focused on PolyJet material jetting technology. Samples are manufactured of photopolymer resins and post-processed. Three factors (i.e., artifact orientation, platen orientation, and finish type) are considered for the investigation. The case study results show that the platen orientation, finish type, and their interaction have a significant influence on the surface roughness (Ra). The best Ra roughness results were obtained for the glossy finish type in the range of 0.5–4 μm.

As part of the cosmos of digital fabrication technology, Additive Manufacturing (AM) systems are able to manufacture three-dimensional components and products directly from raw material and 3D design data. The layer-by-layer operating process of these systems does not require the use of tools, moulds or dies.Technology observers speculate that AM will have a profound economic impact on the manufacturing sector and indeed on wider society. By constructing a model of production cost for two different AM systems used commercially for the manufacture of end-use metal parts, Electron Beam Melting (EBM) and Direct Metal Laser Sintering (DMLS), this paper performs an inter-process comparison of cost performance. High specific costs, measured at £2.39 and £6.18 per cm3 of material deposited respectively, are identified as a central impediment to more widespread technology adoption of such additive systems.The research demonstrates differing levels of system productivity, suggesting that the observed deposition rates are not sufficient for the adoption of EBM and DMLS in high volume manufacturing applications. Despite the absence of amortisable tooling costs, the analysis also reveals that economies of scale are achievable in AM. The results reached are further discussed in the light of the varying strategic requirements posed by the market-pull and technology-push modes of innovation which are both found in the AM industry.

A physical hash for preventing and detecting cyber-physical attacks in additive manufacturing systems

We developed an electroholography unit, which consists of a special-purpose computational chip for holography and a reflective liquid-crystal display (LCD) panel, for a three-dimensional (3D) display. The special-purpose chip can compute a computer-generated hologram of 800x600 grids in size from a 3D object consisting of approximately 400 points in approximately 0.15 seconds. The pixel pitch and resolution of the LCD panel are 12 mum and 800x600 grids, respectively. We implemented the special purpose chip and LCD panel on a printed circuit board of approximately 28cmx13cm in size. After the calculation, the computer-generated hologram produced by the special-purpose chip is displayed on the LCD panel. When we illuminate a reference light to the LCD panel, we can observe a 3D animation of approximately 3cmx3cmx3cm in size. In the present paper, we report the electroholographic display unit together with a simple 3D display system.

Interfacially-mediated oxygen inhibition for precise and continuous poly(ethylene glycol) diacrylate (PEGDA) particle fabrication

At the Johns Hopkins University Applied Physics Laboratory (APL), glass bead-filled polyamide (a.k.a. nylon) (GFN) is being used frequently for functional parts and systems, built using a laser-based powder bed fusion (PBF) additive manufacturing (AM) system. Since these parts have performance requirements, it is important to understand the mechanical properties of the additively-made GFN as a function of build orientation and build parameters. In addition, the performance of the AM system used to manufacture these parts must be evaluated in order to understand its capabilities, especially in order to determine the dimensional precision and repeatability of features built with this system. This paper summarizes recent APL efforts to characterize the GFN powder, the mechanical properties of parts made with GFN, and the performance of the laser PBF machine while running GFN using an AM test artifact.

Synthetic hydrogel polymers were prepared by free radical photopolymerization in aqueous solution of the sodium salt of 2-acrylamido-2-methylpropane sulfonic acid (Na-AMPS). Poly(ethylene glycol) diacrylate (PEGDA) and 4,4′-azo-bis(4-cyanopentanoic acid) were used as the crosslinker and UV-photoinitiator, respectively. The effects of varying the Na-AMPS monomer concentration within the range of 30–50% w/v and the crosslinker concentration within the range of 0.1–1.0% mol (relative to monomer) were studied in terms of their influence on water absorption properties. The hydrogel sheets exhibited extremely high swelling capacities in aqueous media which were dependent on monomer concentration, crosslink density, and the ionic strength and composition of the immersion medium. The effects of varying the number-average molecular weight of the PEGDA crosslinker from = 250 to 700 were also investigated. Interestingly, it was found that increasing the molecular weight and therefore the crosslink length at constant crosslink density decreased both the rate of water absorption and the equilibrium water content. Cytotoxicity testing by the direct contact method with mouse fibroblast L929 cells indicated that the synthesized hydrogels were nontoxic. On the basis of these results, it is considered that photopolymerized Na-AMPS hydrogels crosslinked with PEGDA show considerable potential for biomedical use as dressings for partial thickness burns. This paper describes some structural effects which are relevant to their design as biomaterials for this particular application.

Poly(ethylene glycol) diacrylate (PEGDA) was grafted, through UV-initiated grafting, onto a microporous polypropylene (PP) membrane in order to develop a moisture-sensitive porous structure. Based on the concentration of the PEGDA grafting solution, as well as other variables, the pores of the membrane were filled to varying degrees with cross-linked PEGDA hydrogel, decreasing the pore sizes. This decrease in pore size was highly dependent on the grafting degree (weight add-on of the grafted polymer) that was dependent upon grafting conditions. Grafting with PEGDA resulted in a microporous polypropylene membrane with increased hydrophilicity and moisture-responsive pores. The functional membrane can be used in biological protective materials to limit the transport of liquid-borne pathogens while maintaining moisture transport properties.

PurposeAmong the different methodologies used for performance control in precision manufacturing, the measurement of metrological test artefacts becomes very important for the characterization, optimization and performance evaluation of additive manufacturing (AM) systems. The purpose of this study is to design and manufacture several benchmark artefacts to evaluate the accuracy of the selective laser melting (SLM) manufacturing process.Design/methodology/approachArtefacts consist of different primitive features (planes, cylinders and hemispheres) on sloped planes (0°, 15°, 30°, 45°) and stair-shaped and sloped planes (from 0° to 90°, at 5° intervals), manufactured in 17-4PH stainless steel. The artefacts were measured optically by a structured light scanner to verify the geometric dimensioning and tolerancing of SLM manufacturing.FindingsThe results provide design recommendations for precision SLM manufacturing of 17-4PH parts. Regarding geometrical accuracy, it is recommended to avoid surfaces with 45° negative slopes or higher. On the other hand, the material shrinkage effect can be compensated by resizing features according to X and Y direction.Originality/valueNo previous work has been found that evaluates accuracy when printing inwards (pockets) and outwards (pads) geometries at different manufacturing angles using SLM. The proposed artefacts can be used to determine the manufacturing accuracy of different AM systems by resizing to fit the build envelope of the system to evaluate. Analysis of manufactured benchmark artefacts allows to determine rules for the most suitable design of the desired parts.

Fundamental scaling relationships in additive manufacturing and their implications for future manufacturing and bio-manufacturing systems

In‐cell sensor technology applied in Liquid Crystal Displays (LCDs) panels are investigated to enable adaptive adjustment of screen brightness and color temperature based on ambient light, thereby enhancing the display performance of screens in various environments. By incorporating ambient light sensors (ALS) and color temperature sensors (CTS), which are compatible with the normal manufacturing process of LCD panels, TCL CSOT has achieved a technological upgrade compared to traditional LCDs technology. In‐cell ALS referred to a wide sensing range of 0~10000 lux and high resolution of 1 lux below 50 lux. In‐cell CTS showed an effective range of 3500~9000 K with detection accuracy of 800 K. With these sensors, LCDs panel can adaptively change its brightness and color temperature within different environments, leading to a new feature of TV, monitor and other commercial LCDs.

Porous hydrogels for the adsorption of metals from aqueous solutions were prepared from chitosan nanofibers (CNFs) and poly(ethylene glycol) diacrylate (PEGDA). These hydrogels exhibited high swelling rates and porosities, which were evaluated by a gravimetric method and scanning electron microscopy, respectively. Both factors were influenced by the CNF/PEGDA ratio. The prepared hydrogels adsorbed both transition metals (e.g., copper) and post-transition metals (e.g., tin). The adsorption capacity increased with increasing CNF/PEGDA ratio, indicating synergism between chelation and the enlarged surface area of the porous structure during adsorption. The kinetic data indicated that metal adsorption could be fit to a pseudo-second-order kinetic model, whereas the equilibrium data were fit to the Langmuir isotherm model. Overall, the results revealed that CNF-PEG hydrogels are promising adsorbent materials for metal recovery in environmental applications. Porous hydrogels (CNF-PEG hydrogels) for the adsorption of metals from aqueous solutions were prepared from chitosan nanofibers (CNFs) and poly(ethylene glycol) diacrylate (PEGDA). CNF-PEG hydrogels adsorbed both transition metals (e.g., copper) and post-transition metals (e.g., tin). The adsorption capacity was observed to increase with increasing CNF/PEGDA ratio, indicating that the CNFs exhibit synergism between chelation between metals and chitosan, and the enlarged surface area of the porous structure.