Computed Axial Lithography (CAL), a Volumetric Additive Manufacturing (VAM) technology, enables the rapid, full body i.e. not layer-by-layer, fabrication of freeform geometries within seconds through the superposition of projected light patterns. However, as conventional CAL relies on free radical polymerization (FRP), it is an intrinsically exothermic process (ΔT > 60 °C) that can trigger auto-acceleration, so compromising print fidelity and limiting scalability. By regulating polymer chain length during propagation through reversible chain transfer, Reversible Addition-Fragmentation Chain Transfer (RAFT) maintains steady, controlled reaction kinetics and prevents the sharp viscosity increase characteristic of FRP. In this study, we introduce RAFT polymerization into various (meth)acrylate-based systems within CAL to effectively mitigate heat generation and suppress auto-acceleration during photopolymerization. The success of this approach is confirmed by in-situ thermal monitoring and the suppression of thermally induced buoyancy, revealing a substantial reduction in temperature rise compared to FRP. Furthermore, RAFT chemistry enables post-printing functionalization of the printed objects, expanding CAL's chemical versatility. This study demonstrates that RAFT-mediated CAL allows the fabrication of structures inaccessible via FRP, advancing thermally stable and functionally tunable volumetric additive manufacturing.

Computed Axial Lithography (CAL) represents a significant advancement in the emerging field of Volumetric Additive Manufacturing (VAM). CAL addresses key limitations of traditional photopolymer additive manufacturing technologies, by eliminating the need for layering and support structures. Unlike conventional methods, CAL prints components by illuminating all points within a desired geometry simultaneously, using tomographic reconstruction to form the object in a single step. This unique approach eliminates the relative motion between the object and the precursor material, enabling faster printing speeds and reducing the waste associated with support structures. However, CAL parts require post-processing steps before they can be utilized. CAL's core attributes make it particularly suited for In-Space Manufacturing (ISM), due to its fast fabrication times, wide breadth of materials it can use, and minimized footprint. CAL has been successfully demonstrated in microgravity during parabolic flight experiments. However to fully validate and understand CAL's behaviour in microgravity, all manufacturing and post-processing steps must be integrated. In June 2024, we conducted SpaceCAL Mission 3, testing this entire workflow on a suborbital flight aboard Virgin Galactic's SpaceShipTwo. During similar to 140 s of microgravity, the system autonomously manufactured and post-processed four parts using PEGDA700 resin. Post-flight analysis showed that 2/4 parts were recognisable, while others were distorted due to bubble formation from residual water droplets, off-axis optical aberrations, and non-uniform solvent rinsing. Despite these limitations, this study represents the first integrated CAL workflow in space, providing an initial experimental demonstration and analysis for closed-loop in-space manufacturing.

OpenCAL is a low cost CAL based printing and post processing platform developed using commercial off the shelf (COTS) components and standard rapid prototyping tools. The system incorporates recent advancements in VAM, including Optical Scattering Tomography (OST), and is designed with modularity to support future technological integration. The post processing systems developed include standardized procedures for solvent based removal of uncured resin and a centrifugal cleaning module for enhanced material recovery. To support the continued advancement of this technology, multiple community engagement pathways have been established to foster the collaborative development of the OpenCAL ecosystem. A primary deployment environment for OpenCAL is academic makerspaces, where the system is specifically designed to leverage the rapid prototyping tools typically available in these facilities. OpenCAL not only introduces advanced volumetric additive manufacturing capabilities to makerspaces but also serves as a platform for hands on education in emerging manufacturing technologies, photopolymer science, and computational imaging. By lowering the barriers to entry for volumetric printing research, OpenCAL enables a broader range of students, from undergraduate to graduate levels, to engage directly in experimental research, contribute to the refinement of open source CAL technologies, and participate in interdisciplinary projects spanning materials science, mechanical engineering, and computer science. In doing so, OpenCAL has the potential to significantly expand the technical capabilities of academic makerspaces, transforming them into hubs for next generation manufacturing innovation and research driven learning.

This study evaluates the thermal performance of concrete panels integrated with a phase change material (PCM) using a novel 3D-printed macro-encapsulation technique. The objective is to improve passive thermal management in buildings by embedding paraffin wax within additively manufactured ABS containers placed inside concrete panels. The panels were exposed to a calibrated heat flux of 2500 W/m2 using an infrared setup, simulating peak solar radiation. Surface temperatures were recorded via thermocouples and thermal imaging. To complement experiments, coupled simulations were performed using computational fluid dynamics (CFD) with the enthalpy-porosity method and finite element modeling (FEM) with enthalpy-regularization. The results showed good agreement between simulations and measurements, with surface temperature errors below 8%. The PCM-integrated panel reduced internal surface temperature by 5.06%, demonstrating significant thermal buffering. The study reveals a transition from conduction-dominated to convection-enhanced melting within the PCM domain. Validation using velocity streamlines, Nusselt number (Nu) trends, and Fourier analysis confirms the latent heat dynamics. This integrated CFD-FEM approach enables scalable, data-driven design of PCM-based building elements and supports sustainable construction practices through enhanced energy efficiency.

An innovative approach to 3D printing has been developed in which acoustic vibrations and light control the formation of a solid at an air–liquid interface. The strategy enables fast printing of objects with highly detailed features. Optical and acoustic manipulation of polymers to print objects.

Tomographic volumetric additive manufacturing is a rapidly growing fabrication technology that enables rapid production of 3D objects through a single build step. In this process, the design of projections directly impacts geometric resolution, material properties, and manufacturing yield of the final printed part. Herein, we identify the hidden equivalent operations of three major existing projection optimization schemes and reformulate them into a general loss function where the optimization behavior can be systematically studied, and unique capabilities of the individual schemes can coalesce. The loss function formulation proposed in this study unified the optimization for binary and greyscale targets and generalized problem relaxation strategies with local tolerancing and weighting. Additionally, this formulation offers control on error sparsity and consistent dose response mapping throughout initialization, optimization, and evaluation. A parameter-sweep analysis in this study guides users in tuning optimization parameters for application-specific goals.

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.

Additive manufacturing (AM) has revolutionized the fabrication of devices with precisely controlled optical, fluidic, mechanical, and filtering properties, offering greater design freedom than conventional manufacturing methods. Tomographic volumetric additive manufacturing (TVAM) has many advantages compared to other AM methods including smooth layer-less surfaces, support-free and shear force-free printing, material versatility, and speed of production which are translatable to the microscale and evident in printed microfluidic devices and micro-optical components. However, as the patterning scale is reduced, the depth of field of the optical projection system shrinks much more rapidly and does so roughly with the square of the patterning scale. Consequently, the build volume is substantially reduced as the numerical aperture of the system is increased. Additionally, microscale tomographic VAM is currently limited to batch production, i.e., the photoresist container must be exchanged after the exposure phase is completed. In this work, we introduce roll-to-roll (R2R) TVAM in which these limitations are addressed by "unwrapping" the precursor material into a film enabling continuous production of microstructures with theoretically unlimited length. We elaborate the design of a focus-multiplexed projection optical system that can scan the projection focal plane axially in sync with the refresh cycle of a digital micromirror device. We describe the process of iteratively optimizing and segmenting sinograms to produce long aperiodic microstructures with the focus-tunable optical system. Furthermore, we formulate a thermally reversible organogel photoresist which is deposited onto the substrate in films several millimeters in thickness. Finally, we demonstrate printing of complex lattice structures with length more than 60 cm and minimum feature size of 200 um with the R2R TVAM system.

The capability of holography to project three-dimensional (3D) images and correct for aberrations offers much potential to enhance optical control in light-based 3D printing. Notably, multi-beam multi-wavelength holographic systems represent an important development direction for advanced volumetric additive manufacturing (VAM). Nonetheless, searching for the optimal 3D holographic projection is a challenging ill-posed problem due to the physical constraints involved. This work introduces an optimization framework to search for the optimal set of projection parameters, namely phase modulation values and amplitudes, for multi-beam holographic lithography. The proposed framework is more general than classical phase retrieval algorithms in the sense that it can simultaneously optimize multiple holographic beams and model the coupled non-linear material response created by co-illumination of the holograms. The framework incorporates efficient methods to evaluate holographic light fields, resample quantities across coordinate grids, and compute the coupled exposure effect. The efficacy of this optimization method is tested for a variety of setup configurations that involve multi-wavelength illumination, two-photon absorption, and time-multiplexed scanning beam. A special test case of holo-tomographic patterning optimized 64 holograms simultaneously and achieved the lowest error among all demonstrations. This variant of tomographic VAM shows promises for achieving high-contrast microscale fabrication. All testing results indicate that a fully coupled optimization offers superior solutions relative to a decoupled optimization approach.

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.

The field of additive manufacturing (AM) has advanced considerably over recent decades through the development of novel methods, materials, and systems. However, as the field approaches maturity, it is relevant to investigate the scaling frontiers and fundamental limits of AM in a generalized sense. Here we propose a simplified universal mathematical model that describes the essential process dynamics of many AM hardware platforms. We specifically examine the influence of several key parameters on total manufacturing time, comparing these with performance results obtained from real-world AM systems. We find a inverse-cubic dependency on minimal feature size and a linear dependency on overall structure size. These relationships imply how certain process features such as parallelization and process dimensionality can help move toward the fundamental limits. AM methods that are capable of varying the size of deposited voxels provide one possibility to overcome these limits in the future development of AM. We also propose a new framework for classifying manufacturing processes as "top-down" vs "bottom-up" paradigms, which differs from the conventional usage of such terms, and present considerations for how "bottom-up" manufacturing approaches may surpass the fundamental limits of "top-down" systems.

Multi-beam holographic projection is a promising yet underexplored avenue for advanced volumetric additive manufacturing (VAM) systems to control image focus in 3D, compensate for aberrations, and overcome resolution anisotropy. Nevertheless, there is currently no formal method to jointly optimize multiple holographic projections for maximum reconstruction fidelity of the printed object. This work introduces an optimization framework to search for the optimal set of projection parameters, namely phase modulation values and amplitudes, for multibeam holographic lithography. The proposed framework is more general than classical phase retrieval algorithms in the sense that it can simultaneously optimize multiple holographic beams and model the coupled non-linear material response created by co-illumination of the holograms. The framework incorporates efficient methods to evaluate holographic light fields, resample quantities across coordinate grids, and compute the coupled exposure effect. The efficacy of this optimization method is tested for a variety of setup configurations that involve multi-wavelength illumination and time-multiplexed scanning beams. Among all demonstrations, a special test case of holo-tomographic patterning achieved the lowest error with 128 simultaneously optimized holograms, highlighting its potential in high-contrast microscale fabrication. All testing results indicate that a fully coupled optimization offers superior solutions relative to a decoupled

Computed Axial Lithography (CAL) is a recent advancement in volumetric additive manufacturing (VAM) that delivers a light dose to a photopolymer volume through tomographic reconstruction. The precursor liquid or gel itself generally supports the emerging object, eliminating the need for wasteful dedicated solid supporting structures. A challenge, however, is that desired geometry can shrink or expand during solidification and on Earth, if the precursor material's viscosity is low enough. These effects may result in sinking or floating of the component, which can blur the geometry.In principle, CAL is promising for in-space manufacturing because, unlike layer-based processes, CAL does not require a flat liquid-gas interface to be maintained during printing. With suitable development, CAL is potentially capable of manufacturing parts such as organic tissue, flexible seals, rigid trusses, and microstructures for space exploration, as well as repairing existing tools and parts. 'SpaceCAL' flew on a microgravity parabolic flight in May 2022 to demonstrate the capabilities of CAL and analyse a CAL system in a microgravity. Initial findings show that 0.12 Pa-s low viscosity precursor can be printed in microgravity with less geometric distortion than an Earth-based gravity counterpart.

Bioinspired surfaces have great potential for self‐cleaning, condensation acceleration, and drag reduction. However, manufactured biomimetic surfaces typically feature only one or occasionally two length scales of surface topography and do not fully recapitulate the structure and function of natural textures. Herein, a triple‐hierarchical superhydrophobic surface (TriSS) inspired by water‐repellent lotus leaves is introduced, which consist of arrays of microprotrusions with various sizes, grooves between the protrusions, and a covering of nanoscale hairs. The TriSS surface is manufactured by forming an array of microdomes through photolithography and thermal reflow. These microstructures are transferred, by casting, to an elastomer, which is then augmented with surface wrinkles by the relaxation of biaxial stress in an oxidized surface layer. Conformal growth of a nanoporous zinc oxide film and fluorosilanization adds further surface detail. The TriSS surface achieves a sessile water contact angle up to 174.3 ± 0.3° and contact angle hysteresis down to 9.9 ± 0.3° via the very limited liquid–solid contact enabled by the surface topography. The surface also captures and retains a stable air layer, which resists water impingement even when submersed to 20 cm depth for more than 200 h. The TriSS process offers a scalable route to water repellence in industrial applications.

Liquid photoresists are abundant in the field of light-based additive manufacturing (AM). However, printing unsupported directly into a vat of material in emerging volumetric AM technologies-typically a benefit due to fewer geometric constraints and less material waste-can be a limitation when printing low-viscosity liquid monomers and multimaterial constructs due to part drift or sedimentation. With ethyl cellulose (EC), a thermoplastic soluble in organic liquids, a simple three-component transparent thermoreversible gel photoresist with melting temperature of ≈64 °C is formulated. The physically crosslinked network of the gel leads to storage moduli in the range of 0.1-10 kPa and maximum yield stress of 2.7 kPa for a 10 wt% EC gel photoresist. Nonzero yield stress enables sedimentation-free tomographic volumetric patterning in low-viscosity monomer without additional hardware or modification of apparatus. In addition, objects inserted into the print container can be suspended in the gel material which enables overprinting of multimaterial devices without anchors connecting the object to the printing container. Flexural strength is also improved by 100% compared to the neat monomer for a formulation with 7 wt% EC.

Volumetric additive manufacturing techniques are a promising pathway to ultra-rapid light-based 3D fabrication. Their widespread adoption, however, demands significant improvement in print fidelity. Currently, volumetric additive manufacturing prints suffer from systematic undercuring of fine features, making it impossible to print objects containing a wide range of feature sizes, precluding effective adoption in many applications. Here, we uncover the reason for this limitation: light dose spread in the resin due to chemical diffusion and optical blurring, which becomes significant for features ⪅0.5 mm. We develop a model that quantitatively predicts the variation of print time with feature size and demonstrate a deconvolution method to correct for this error. This enables prints previously beyond the capabilities of volumetric additive manufacturing, such as a complex gyroid structure with variable thickness and a fine-toothed gear. These results position volumetric additive manufacturing as a mature 3D printing method, all but eliminating the gap to industry-standard print fidelity.