Across universities, 3D printing has moved well beyond prototyping. In research labs, it is increasingly used to fabricate functional components, experimental devices, and custom tooling that would be impractical – or impossible – to produce using traditional manufacturing methods. As research pushes into smaller scales, softer materials, and more complex geometries, the capabilities of the printing technology itself begin to matter far more than the novelty of additive manufacturing.
For many faculty and graduate researchers, the real value of advanced 3D printing is not that it exists, but that it enables three critical outcomes: faster iteration, higher precision, and material freedom.
In a university research environment, time is rarely abundant. Graduate students balance coursework, teaching responsibilities, and grant-driven research timelines. Waiting hours or days for a single print iteration slows progress and limits how aggressively ideas can be tested.
DLP (Digital Light Processing) 3D printing addresses this challenge by curing an entire layer at once, rather than tracing each feature with a laser or extruding material line by line. In practice, this means print time is largely independent of the number of parts on the build plate. Printing one part or twenty often takes the same amount of time.
For researchers, this enables:
B9Creations’ DLP printers, for example, are capable of printing hundreds of small, high-resolution parts within a typical 8–10-hour workday, and in many cases within a single class or lab period. This speed fundamentally changes how iterative research can be conducted in an academic setting.
As research moves into micro-devices, microfluidics, biomedical interfaces, and advanced materials, nominal resolution specifications are no longer sufficient. What matters is repeatable, effective resolution – the ability to produce the same fine features reliably across prints and across machines.
DLP technology excels here because projected light cures uniform layers with sharp edge definition. B9Creations 3D printers operate at an effective resolution range of approximately 10-50 microns, with validated dimensional tolerances of ±50 microns (±0.002 inches) across fleets of machines. In third-party testing, dimensional variation between printed parts and their CAD models has been measured at scales comparable to a single human cell.
For research, this level of precision means:
Perhaps the most overlooked requirement in university research is material flexibility. Many research projects depend on materials that are not commercially standardized: custom photopolymers, experimental elastomers, or biocompatible resins with specific mechanical properties.
Closed material ecosystems force researchers to compromise their experiments to fit the printer. Open systems allow the printer to adapt to the research.
B9Creations’ platforms are designed to support third-party and custom materials, with software-level control over exposure, curing profiles, and release forces. This capability is particularly important in fields such as biomedical engineering, chemistry, and materials science, where resins may be produced in small batches, cost thousands of dollars per kilogram, or require highly specific curing behavior.
These benefits come together clearly in research conducted at the Weir Biomechatronics Development Lab at the University of Colorado, where doctoral researcher Tyler Currie was developing a neural interface for optogenetics applications in amputees. Optogenetics is a revolutionary neuroscientific technique that uses genetic engineering to introduce light-sensitive proteins (opsins) into specific neurons, allowing researchers to activate or inhibit neural activity with high spatial and temporal precision using light.
University of Colorado researchers were seeking to develop a way to use optogenetics to enable amputees to control a prosthetic hand using the same brain signals we use to control our natural hands. A nerve cuff added to a peripheral nerve and using optogenetics technology would translate neural activity into physical movement.
For the time being, the researchers’ experiments are being carried out on mice. Designing and fabricating this nerve cuff required extreme fabrication precision. The target nerve measured approximately 180 microns in diameter, leaving almost no margin for error. The device also needed to be soft enough to match nerve tissue, flexible enough to allow implantation, and biocompatible for in vivo testing.
Traditional manufacturing methods were quickly ruled out. Early 3D printing attempts introduced their own problems. Some systems could not resolve the fine features. Others over-polymerized soft materials, closing internal channels and compromising function. Variability between prints made it difficult to determine whether failures were caused by the design or the fabrication process.
The research team ultimately transitioned to a DLP system from B9Creations, selected for its ability to reliably produce micro-scale features and support advanced materials.
Using a silicone-based, biocompatible resin, the team was able to print nerve cuffs with:
Equally important, the prints were consistent. Internal features remained open, geometry held from part to part, and post-processing could be refined rather than reinvented with each iteration.
With fabrication stabilized, the research could focus on function. The printed nerve cuffs were implanted onto the vagus nerve in animal models engineered to respond to light. When the light source was activated, researchers observed an immediate and repeatable reduction in heart rate, confirming successful neural stimulation.
The devices were also evaluated over extended implantation periods. After seven days in vivo, there were no signs of tissue damage, weight loss, or adverse biological response. Across multiple trials, the results were consistent, allowing the team to validate the design rather than question the manufacturing process.
At that point, 3D printing had effectively disappeared from the research narrative. It was no longer a variable to manage—it was simply the method that enabled the work.
This example reflects a broader reality across higher education. Many universities already have 3D printing capabilities, often centered in makerspaces or instructional labs. These systems are valuable for teaching and early-stage prototyping. Research environments, however, place fundamentally different demands on fabrication technology.
Advanced research requires:
More than 220 research papers worldwide cite B9Creations technology for applications ranging from microfluidics and biomedical research to materials science and advanced manufacturing, underscoring how these requirements are becoming mainstream rather than exceptional.
The true value of advanced DLP 3D printing in university research is not that it produces parts quickly or with high resolution – though it does both. Its value lies in removing fabrication as a constraint on scientific thinking.
When researchers can trust that a design will print accurately, consistently, and in the right material, they are free to focus on hypotheses, validation, and discovery. In that context, 3D printing stops being a tool to experiment with and becomes infrastructure that accelerates progress.
For universities investing in research-grade additive manufacturing, that distinction is the one that matters most.
Explore select 3D printers from B9Creations, or work with Mission Learning Systems to find the right printer for your research needs.
Electrification is no longer a trend tied to electric vehicles or renewable energy headlines. It is a systems-level transformation reshaping infrastructure, manufacturing, data centers, mobility, and industrial operations. As mechanical systems become electrically driven and electrically driven systems become digitally controlled, technical education must evolve to reflect this shift.
A step-by-step guide for K-12 CTE, technical colleges, and industrial employers building a machining talent pipeline. If you’re building (or
From AI in classrooms to rare earths, GIS, data centers, nuclear, and smart HVAC/R—13 predictions shaping technical education in 2026.
