Computed Axial Lithography (CAL) is a 3D additive manufacturing process that is able to form all points within a geometry simultaneously by delivering a light dose to a photopolymer via tomographic reconstruction. CAL can avoid hydrodynamic rate limitations, allowing for higher-viscosity precursors, and fast manufacturing speeds. Hydrogel Infusion Additive Manufacturing (HIAM) is a recent additive manufacturing process that allows for the production of metallic parts but has only been demonstrated with traditional layer-by-layer additive manufacturing. This research demonstrates a modified HIAM process utilizing CAL, in which a higher-viscosity precursor material with additives is used.
Optical projection system with high numerical apertures (NA) enables high-resolution imaging but also suffers from shorter depth of focus and more pronounced aberrations relative to low NA systems. In microscale volumetric additive manufacturing (VAM), these problems significantly reduce overall optical contrast and geometric fidelity. In this context, holography is a promising 3D imaging method to solve these challenges thanks to its focal point steering and aberration correction capabilities. However, the design of holographic projections for optimal 3D patterning remains a non-trivial ill-posed problem and this design problem is particularly challenging in systems where the material exposure responses from multiple holographic beams are coupled. In this work, we introduce a novel method to co-optimize the phase masks for multiple coupled holographic beams for motionless 3D lithography. We showcase the flexibility of this method through examples of single-shot VAM systems with different modes of response coupling such as photoinhibition and two-photon absorption. Lastly, we discuss how this method can naturally extend to design phase masks for holo-tomographic 3D patterning.
As a recently developed 3D printing technique, tomographic volumetric additive manufacturing (VAM) enables rapid printing of freeform objects by parallelizing photopolymerization through tomographic exposure. In this tomographic exposure process, patterning resolution and conversion accuracy crucially depend on the design of tomographic projections. In this nascent field, there are only a few optimization algorithms and each proposed to cater certain special cases of the general inverse design problem. Yet, there is no comprehensive and rigorous treatment to simultaneously address the larger class of design problems involving a mix of greyscale targets, non-linear material response, spatially variant tolerance, arbitrary tomographic configuration, and complex propagation media. This paper outlines two contributions to the mathematical and computational foundation for volumetric 3D printing, namely, a general band constraint optimization model and a ray-tracing light propagation model. These advancements are crucial for VAM in creating accurate functionally graded objects in heterogeneous media. Beyond 3D printing, the findings in this work are relevant to synthesis of spatiotemporal irradiation profiles in other contexts, such as those in photografting of biological constructs, 3D neural photostimulation, and intensity-modulated radiation therapy (IMRT).
Computed Axial Lithography (CAL) is a promising manufacturing technique for microscale optical elements. CAL would also be attractive for custom macroscopic (centimeter-scale) optical components because of its speed and ability to work with a wide range of photopolymer precursors. However, the imaging performance of lenses printed with CAL is impacted by surface profile errors that are on the order of the projected pixel size. To develop CAL for manufacturing optics, this form error needs to be reduced through further optimization of the delivered light dose distribution and improved control of exposure and postprocessing parameters. Using a plano-convex model geometry, we formulated a simulation model that accurately predicts the height profile of a printed lens surface. We elucidate the important role of the diffusion of oxygen or radical scavengers during polymerization in determining the final shape of a printed lens. We have developed an optimization framework that corrects form errors by harnessing mass transport effects. The framework simulates the form error via an interpolation scheme that tracks a relevant objective function (degree of oxygen depletion or polymerization) at the exact surface points of a lens rather than on the grid points of a voxelized reconstruction. We will demonstrate simulation results of reduced form error at both pixel and sub-pixel sized scale as well as experimental results of improved lenses printed by optimized projection sets. We expect our algorithms will also advance CAL in other precision manufacturing applications and printing for materials with high diffusivity such as hydrogel.
The optical design, computation, and material formulation that support roll-to-roll tomographic volumetric additive manufacturing (VAM), a continuous VAM process, are described. Results from initial printing trials are presented.
The process of computed axial lithography (CAL) has been established as one of the fastest available photopolymer 3D printing methods, offering smooth surfaces (r.m.s. surface roughness as low as 6 nm) and the ability to process high-viscosity precursor materials (100,000 cP demonstrated). Recently we showed successful printing of microscale geometries into dispersions of silica nanoparticles in a refractive-index-matched photopolymer. After exposing the 3D geometry via patterned tomographic illumination the material is debinded and sintered. In this way, external features of 50 µm and internal channels of 150 µm diameter have been achieved. This processing technique offers a promising route to production of 3D glass microfluidic devices and complex monolithic micro-optical devices. We will describe the status of optics fabrication via CAL. We will also consider the influence of light scattering on spatial resolution and possible ways of addressing this effect.
Computed axial lithography (CAL) is an emerging volumetric additive manufacturing technology which presents unique opportunities in layerless ultra-rapid fabrication. However, the required process control places particular demands on computing and delivering the appropriate 3D distribution of optical energy, as well as monitoring the solidifying structure within the photo-resin. For example, continued reaction after tomographic exposure is not currently accounted for and could lead to higher degree-of-conversion than designed and consequent feature dilations. Color Schlieren Tomography (CST) is developed as an in-situ metrology tool to monitor volumetrically the internal refractive index and the forming geometry. Major improvements of CST in real-time computation and processing of 3D reconstruction have enabled event-driven patterning control such as auto-termination. With this technique, we monitored the polymerization process in real-time during and after termination of the exposure period signaled by an index-volume termination criterion. Monitoring of continued polymerization after termination (dark polymerization) shows that the refractive index change can rise to 10 times higher than its value at termination. The time-resolved 3D reconstruction data provided by CST can be used for chemical kinetics modeling and development of compensation schemes.
Computed axial lithography (CAL) is a volumetric additive manufacturing method in which a three-dimensional light dose distribution is constructed in a photopolymer from the superposition of illumination patterns from many different angles. The technique’s advantages over layer-by-layer light printing methods stem from the fact that in CAL hydrodynamic stresses are effectively eliminated from the resin precursor material during printing. This key difference allows a wider range of materials to be processed, including high-viscosity or thermally gelled precursors, and allows polymeric objects to be printed around pre-existing solid objects (‘overprinting’). In this talk we describe some of the current limitations on spatial resolution, printing speed, and mechanical properties in CAL. We also describe a computationally efficient approach to modeling the occlusion of light by objects suspended in the printing volume, which supports the optimization of overprinting processes.
The rapid production of three-dimensional microstructures across areas of many square centimeters, such as in a roll-to-roll printing system, is needed for many applications such as microfluidic channels in diagnostic chips, filters with precisely controlled pore size, and surfaces with self-cleaning properties or structural color. Most current methods for transferring 3D microstructures to large substrates involve either multiple sequential deposition and imprinting steps with sacrificial materials to define voids, or lamination of a series of two-dimensionally patterned layers. These techniques have limited throughput and present significant layer-to-layer registration challenges. We introduce a design for an optical patterning system that has the potential to create 3D microstructures in a photopolymer film with a single patterning step on a roll-to-roll web. The technique builds on the process of Computed Axial Lithography that we have recently introduced. In the proposed technique, time-evolving, projected patterns of collimated light illuminate a photopolymer film on a web where it rotates around a backing cylinder. The rotational motion of the web allows each point in the film to be illuminated from many angles sequentially. During the rotation, therefore, a 3D light dose distribution can be synthesized tomographically, with the ability to define 3D polymerized structures which may include re-entrant and encapsulated features. Here, we describe computational modeling of the expected spatial resolution, geometrical fidelity, and patterning speed with this method for relevant photopolymer materials.
Soft lithography provides a convenient technique for prototyping miniaturized fluidic systems. However, 3D-printing techniques offer shorter lead times and greater three-dimensional design freedom, as well as circumventing the manual alignment and inter-layer bonding challenges of soft lithography. As a result, attention has moved towards additive fabrication solutions.
Fused deposition modelling (FDM), inkjet, and stereolithographic projection-based 3D-printing solutions have demonstrated the possibility of printing master molds as well as encapsulated fluidic networks directly. However, all of these techniques typically require the use of solid support structures when printing overhanging features as are required for encapsulated fluidic channels. This support material is time-consuming or, in some cases, entirely impractical to remove from small-scale, encapsulated channels. Additionally, most existing printing techniques are limited to materials that are orders of magnitude higher in elastic modulus than biological tissue. Finally, process-induced surface roughness makes microscopy challenging.
In contrast, we have introduced a new additive technique, computed axial lithography (CAL), which enables volumetric 3D-printing by illuminating a rotating volume of photosensitive material with a 3D light intensity map constructed from the angular superposition of many 2D projections. The projections are computed via the exponential Radon transform followed by iterative optimization. Oxygen inhibition-induced thresholding of the materials’ dose response enhances patterning contrast. Here, we report the application of CAL to fabricate transparent 3D fluidic networks in highly compliant and resilient methacrylated gelatin hydrogels, as well as in stiffer acrylates. Uncured resin provides mechanical support during printing, so the need for solid support structures is eliminated.
Lower-dimensional photopolymerization based additive manufacturing techniques have several drawbacks that currently limit the applicability and scope of 3D printing, including: topological constraints, the requirement for numerous complex support structures that later need to be removed, long print times for complex geometries, relative motion between the liquid resin and printed part, as well as debilitating mechanical weakness and anisotropy resulting from the inherently layered structure of the parts. We propose and demonstrate a novel volumetric 3D printing technique based on one of the most ubiquitous computational imaging methods in the field: computed axial tomography. Computed axial lithography (CAL) is a vat photopolymerization technique that exposes the entire resin volume by projecting images from a multiplicity of angles. The technique is a physical implementation of the filtered back projection algorithm for tomographic reconstruction. We use constrained non-convex optimization in order to generate images that are projected into the resin in order to sculpt a 3-dimensional energy dose that cures the desired arbitrary geometry. This eliminates the requirement for supports and enables complex and nested structures that were previously challenging or impossible to print. Further, the process is layer-less and does not involve any relative motion between the resin and the printed part, which has positive implications for mechanically isotropic part strength. We demonstrate support-less printing of complex geometries containing 10^8-10^9 voxels in 2-4 minutes, orders of magnitude faster than comparable techniques.
A predominant unsolved challenge in tissue engineering is the need of a robust technique for producing vascular networks, particularly when modeling human brain tissue. The availability of reliable in vitro human brain microvasculature models would advance our understanding of its function and would provide a platform for highthroughput drug screening. Current strategies for modeling vascularized brain tissue suffer from limitations such as (1) culturing non-human cell lines, (2) limited multi-cell co-culture, and (3) the effects of neighboring physiologically unrealistic rigid polymeric surfaces, such as solid membranes. We demonstrate a new micro-engineered platform that can address these shortcomings. Specifically, we have designed and prototyped a molding system to enable the precise casting of ~100μm-diameter coaxial hydrogel structures laden with the requisite cells to mimic a vascular lumen. Here we demonstrate that a fine wire with diameter ~130 μm or a needle with outer diameter ~300 μm can be used as a temporary mold insert, and agarose–collagen composite matrix can be cast around these inserts and thermally gelled. When the wire or needle is retracted under the precise positional control afforded by our system, a microchannel is formed which is then seeded with human microvascular endothelial cells. After seven days of culture these cells produce an apparently confluent monolayer on the channel walls. In principle, this platform could be used to create multilayered cellular structures. By arranging a fine wire and a hollow needle coaxially, three distinct zones could be defined in the model: first, the bulk gel surrounding the needle; then, after needle retraction, a cylindrical shell of matrix; and finally, after retraction of the wire, a lumen. Each zone could be independently cell-seeded. To this end, we have also successfully 3D cultured human astrocytes and SY5Y glial cells in our agarose–collagen matrix. Our approach ultimately promises scalable and repeatable production of vascular structures with physiologically realistic mechanical properties.
KEYWORDS: Nanoimprint lithography, Computer simulations, Ultraviolet radiation, Semiconducting wafers, Monte Carlo methods, Process modeling, Anisotropy, Lithography, Convolution, Algorithm development
Full-field, physically-based simulation of nanoimprint lithography (NIL) is needed to address the throughput-versus-yield challenges that are currently faced by NIL. We demonstrate a simulation framework that can track the spreading and coalescence of tens of thousands of picoliter-volume resin droplets beneath a nanoimprint template, predicting evolution of feature filling and residual layer thickness (RLT) uniformity during the imprinting of geometrically complex designs such as found in solid-state memory. We have used the framework to explore directionality of droplet spreading beneath patterned templates, the role of template curvature in mitigating gas entrapment, and detrimental elastic deflections at wafer-edge partial imprint fields.
Just as the simulation of photolithography has enabled resolution-enhancement through Optical Proximity Correction,
the physical simulation of nanoimprint lithography is needed to guide the design of products that will use this process.
We present an extremely fast method for simulating thermal nanoimprint lithography. The technique encapsulates the
resist's mechanical behavior using an analytical function for its surface deformation when loaded at a single location. It
takes a discretized stamp design and finds resist and stamp deflections in a series of steps. We further accelerate the
simulation of feature-rich patterns by pre-computing dimensionless relationships between the applied pressure, the
resist's mechanical properties, and the residual layer thickness, for stamps patterned with uniform arrays of a variety of
common feature shapes. The approach is fast enough to be used iteratively when selecting processing parameters and
refining layouts. The approach is demonstrated in action with three nanoimprint test-patterns, and describes experimentally measured residual layer thickness variations to within 10-15% or better. Finally, our technique is used to propose nanoimprint-aware design rules.
We describe a highly computationally efficient method for calculating the topography of a thermoplastic
polymeric layer embossed with an arbitrarily patterned stamp. The approach represents the layer at the time of
embossing as a linear-elastic material, an approximation that is argued to be acceptable for the embossing of
thermoplastics in their rubbery regime. We extend the modeling approach to represent the embossing of
layers with thicknesses comparable to the characteristic dimensions of the pattern on the stamp. We present
preliminary experimental data for the embossing of such layers, and show promising agreement between
simulated and measured topographies. Where the thickness of the embossed layer is larger than the
characteristic dimensions of the pattern being embossed, the stamp-layer contact pressure exhibits peaks at
the edges of regions of contact, and material fills stamp cavities with a single central peak. In contrast, when
the layer thickness is smaller than the characteristic dimensions of the features being embossed, contact
pressures are minimal at the edges of contact regions, and material penetrates cavities with separate peaks at
their edges. These two apparently distinct modes of behavior, and mixtures of them, are well described by the
simple and general model presented here.
We present a way to identify distortions of transparent
micro-patterned substrates using a desktop document scanner and
a set of image processing routines. The method requires neither expensive optical equipment nor precise positioning of
the part. It is therefore ideally suited to rapid process monitoring. A 5000-dpi imagesetter is used to print a square
reference grid of lines having a known pitch ~100 μm. This reference pattern is used to produce a hard stamp that is
subsequently embossed into a sheet of thermoplastic polymer. The pattern transferred to the polymer may include
distortions resulting from contraction of the sheet after separation from the stamp. To measure these distortions, the
embossed polymeric part is placed on a document scanner. The reference grid is laid on top of the part and rotated by
hand until moire fringes are seen. At least two scans are made, each with a different relative reference-part rotation. For
each scan, the orientation of the part relative to the reference grid may be arbitrarily chosen within an allowable range of
a few degrees. These orientations may be extracted from the captured images, and, together with the moire fringes'
orientations and spacings, provide enough information to obtain the part's distortions. Estimates of part strains may be
improved, at the expense of measurement time, by capturing more images. The approach can detect isotropic shrinkage
of the part with a strain resolution ~10-3.
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