The research team, led by Neha Sharma of the University Hospital Basel and Duke-NUS Medical School together with colleagues at the University of Basel, Iuliu Hatieganu University of Medicine and Pharmacy in Romania, and the University Center for Dental Medicine Basel, set out to answer a deceptively simple question: what happens to the dimensional accuracy and mechanical strength of modern 3D-printed photopolymer resins when they are exposed to clinically realistic sterilization cycles? The stakes are higher than they might appear. Standard steam autoclaving runs at 121 degrees Celsius, but prion inactivation protocols demanded by infection-control authorities require an extended cycle holding a searing 134 degrees Celsius for at least 18 minutes. That thermal assault had never been systematically evaluated on the contemporary biocompatible resins now flowing through hospital 3D print labs.

To close that gap, the investigators selected four commercially available biocompatible photopolymer resins: P pro Surgical Guide Clear, ProArt Print Splint, BioMed Clear Resin, and BioMed Amber Resin. Two additive manufacturing platforms were represented, stereolithography, which cures liquid resin with a precisely steered ultraviolet laser, and digital light processing, which cures entire layers at once using a projected light pattern. The experimental design deliberately worked at two scales. First, the team printed 240 standardized ISO specimens for rigorous benchtop testing of dimensional accuracy and flexural strength, the classic three-point bending measure of how much load a material can carry before fracturing. Second, they printed 72 clinically relevant patient-specific guides representing two real surgical scenarios: cranial resection guides and oral implantology guides. This dual approach ensured the findings would speak both to materials scientists and to surgeons.

The specimens were randomly allocated to three experimental groups. A baseline group remained non-sterilized, a steam group underwent the extended prion-inactivation autoclave cycle at 134 degrees Celsius for 18 minutes, and a plasma group was treated with low-temperature hydrogen peroxide plasma sterilization at a gentle 55 degrees Celsius for 19 minutes. Dimensional accuracy was quantified using root mean square deviation analysis, a method that compares the printed object against its digital design point by point and expresses mismatch as a single deviation value in micrometers. Statistical evaluation relied on two-way analyses of variance followed by Bonferroni post-hoc testing, with the significance threshold set at 0.05.

The accuracy results told a nuanced story. Across the board, deviation was lowest for the simple ISO specimens, averaging 61 plus or minus 24 micrometers, followed by the cranial guides at 119 plus or minus 29 micrometers and the oral implantology guides at 147 plus or minus 45 micrometers. Geometry, in other words, matters: the more complex and curved the anatomy a guide must capture, the harder it is to print true. Material selection proved equally decisive. The ProArt Print Splint and P pro Surgical Guide Clear resins delivered significantly higher dimensional accuracy than the two BioMed resins across every geometry tested, with the difference reaching statistical significance at p less than 0.001. Sterilization method also significantly shifted dimensional accuracy overall, although the magnitude and direction of the change depended on the shape of the object, confirming that there is no single sterilization penalty that applies uniformly to every printed device.

The mechanical findings delivered the study’s most dramatic surprise. Counterintuitively, steam sterilization increased the flexural strength of the ISO specimens to 41 plus or minus 16 megapascals, compared with a baseline of 33 plus or minus 19 megapascals, while plasma sterilization reduced strength to 29 plus or minus 16 megapascals, a statistically significant divergence at p less than 0.001. The likely explanation lies in polymer physics: the intense heat of autoclaving drives additional post-cure crosslinking within the photopolymer network, effectively finishing a polymerization reaction that room-temperature light curing had left incomplete. Steam exposure, in effect, acts as an aggressive post-cure. But that apparent strengthening came with a catastrophic catch that standardized specimens alone could never have revealed.

When the researchers turned to the clinically relevant patient-specific guides, the picture darkened. Every single steam-sterilized guide printed from BioMed Clear and BioMed Amber resins developed visible cracks across its structure. These were not hairline cosmetic flaws; they were structural failures that rendered the devices clinically unusable, undermining exactly the geometric fidelity that makes surgical guides worth printing in the first place. The thinner, anatomically contoured walls of the guides behave differently from the stocky ISO bars, concentrating thermal stresses from rapid heating and cooling into fracture lines. The lesson is one the field is learning repeatedly as additive manufacturing enters medicine: benchtop material data cannot be extrapolated naively to real device geometries. A resin that tests beautifully in standard specimens can fail in the operating room.

Plasma sterilization told a more cautious tale. The low-temperature hydrogen peroxide treatment avoided crack formation entirely; all plasma-treated guides remained structurally intact. Yet the method exacted its own price in reduced flexural strength of the specimens, and the authors flag a further unresolved regulatory and microbiological question: hydrogen peroxide clearance, the ability of the sterilant to penetrate the device and then dissipate without leaving cytotoxic residues, has not been validated for these particular resins. The researchers therefore stop short of endorsing plasma sterilization as a default substitute for autoclaving. An intact guide is worthless if residual oxidant could compromise tissue healing, and the data simply do not yet exist to rule that risk out.

The study’s central conclusion is a shift in how surgical 3D printing workflows should be conceived. Material and sterilization method, the authors argue, must be selected and validated as a pair, matched both to the specific sterilization cycle available at the point of care and to the mechanical and accuracy demands of the intended procedure. A high-accuracy resin paired with an incompatible sterilization cycle is not a workflow; it is a latent failure waiting to reach the operating theater. For hospital print labs producing guides under time pressure, the practical message is to consult validated material-sterilization combinations before a case, not after a guide emerges from the autoclave visibly fractured on the morning of surgery.

Beyond the immediate clinical implications, the work resonates with a broader trend in biomedical additive manufacturing. As regulators, including those administering the European Union Medical Device Regulation, scrutinize hospital-produced devices ever more closely, standardized evidence of how fabrication variables interact with post-processing steps becomes essential. This study provides exactly that kind of evidence for the prion-inactivation steam cycle, an extreme but legally mandated condition that most prior research ignored. It also highlights the enduring value of testing devices and specimens side by side. The 61 micrometer accuracy of an ISO bar, the 147 micrometer deviation of an implantology guide, the crosslinking that strengthens a specimen while splitting a guide apart: these are the granular, quantitative facts on which the safety of point-of-care 3D printing will ultimately rest. As hospital printers multiply from Basel to Bangkok, the pairing of resin and sterilization cycle may prove to be one of the most consequential choices a surgical team never knew it was making.

Subject of Research: Effects of steam and plasma sterilization on the accuracy and strength of 3D-printed surgical guide resins

Article Title: Dimensional accuracy and flexural strength of 3D-printed photopolymer resins for point-of-care surgical guides after steam and plasma sterilization: an in-vitro comparative study

Article References: Sharma, N., Burde, A. V., Manea, A., Fischer, J., Thieringer, F. M., & Rohr, N. (2026). Dimensional accuracy and flexural strength of 3D-printed photopolymer resins for point-of-care surgical guides after steam and plasma sterilization: an in-vitro comparative study. 3D Printing in Medicine. https://doi.org/10.1186/s41205-026-00352-8

Image Credits: AI Generated

DOI: 10.1186/s41205-026-00352-8

Keywords: 3D printing, surgical guides, sterilization, photopolymer resins, dimensional accuracy, flexural strength, steam sterilization, plasma sterilization, craniomaxillofacial surgery, dental implants, point-of-care manufacturing, biomaterials

Investment casting is one of metallurgy’s oldest processes, with roots stretching back to early weapons, jewelry, and religious art. It remains prized today for aerospace turbine blades and biomedical components because it delivers exceptional surface finish, dimensional accuracy, and the ability to reproduce complex shapes. In Nepal, the technique has been used since at least the sixth century A.D. to produce the bronze and gilded deities that fill temples and monasteries across the Himalayas. The process is intensely manual: a sculptor first carves a detailed wax master pattern, which is encased in a rubber mold from which multiple wax replicas can be made. These replicas are assembled with gating systems, dipped in a traditional slurry of cow dung and clay, reinforced with metal wires, dewaxed, preheated, and finally filled with molten metal. After cooling, each piece demands hours of filing, chiseling, and hand-applied gold plating.

That artisanal character comes at a cost. Defect rates in Nepali sculpture casting hover around thirty percent, and sculptures can take anywhere from one month to two years to complete depending on size. Because global economic shifts and advancing technology are squeezing demand for Nepali cast sculptures, improving casting design, modeling, and production efficiency has become essential for the industry’s survival. The research team, led by Zenisha Shrestha with Abhishek Pandey and Bijendra Prajapati, set out to determine whether systematic parameter optimization, never before applied to this traditional setting, could meaningfully improve dimensional accuracy in gilding metal, an alloy of ninety percent copper and ten percent zinc that is the most widely used sculpture material in Nepal.

The researchers chose a sword as their test specimen, selected for its cultural relevance in Nepali society and its relatively simple geometry, which makes dimensional analysis tractable. The design was modeled in SOLIDWORKS, with the gating system developed through the modulus method to reflect designs typical of sculpture manufacturing. From an Ishikawa cause-and-effect analysis of casting stability, the team identified three controllable parameters: the number of slurry coating layers, the mold preheat temperature, and the metal pouring temperature. Factors such as wax composition, alloy composition, slurry composition, cooling methods, and environmental conditions were treated as noise parameters that could not be easily controlled in the workshop.

The experimental design followed a Taguchi L9 orthogonal array, allowing nine carefully chosen experiments to explore the parameter space efficiently. Slurry coatings ranged from two to four layers, preheat temperatures spanned 500 to 600 degrees Celsius, and pouring temperatures covered the 1150 to 1200 degree Celsius range typical of Nepali sculpture foundries. Each coating choice involves a trade-off: thin shells save material and time but risk bulging and leaking under the metallostatic pressure of pouring, while thicker coatings prevent defects and improve heat retention at the cost of longer processing. Preheating the mold reduces thermal shock and premature freezing of the melt, improving fill of thin sections, though excessive preheat can accelerate mold-metal reactions and increase surface-connected porosity. Higher pouring temperatures superheat the metal above its melting point, preventing unfilled sections in intricate features.

Four response variables were measured for each casting: weight, length, breadth, and thickness. Before optimization, the team verified data quality through normality testing with probability plots and the Anderson-Darling test, confirming that all responses followed normal distributions. Pareto tests and analysis of variance at a 95 percent confidence level then established that all three process parameters significantly influenced every response variable. The number of coatings emerged as the dominant factor, contributing 44.42 percent of the variance in weight, 48.01 percent in length, 58.81 percent in breadth, and 41.82 percent in thickness. Pouring temperature exerted its greatest influence on weight at 39.31 percent and length at 31.38 percent, while preheat temperature most strongly affected breadth and thickness. Residual plots showed randomly distributed errors, confirming the reliability of the statistical model.

Because dimensional accuracy depends on optimizing all four responses simultaneously, the researchers turned to multi-response optimization. Grey relational analysis, a technique designed for systems with limited information, converts multiple responses into a single grey relational grade by normalizing the data and calculating correlation coefficients, using an identification coefficient of 0.5 consistent with prior studies. The innovation here was the coupling of grey relational analysis with principal component analysis, which uses eigenvectors to derive objective weights for each response rather than assuming they matter equally. The first principal component captured 81.9 percent of the data’s variance and identified length as the most significant response. Experiment 3, combining a 500 degree Celsius preheat, a 1200 degree Celsius pour, and four coating layers, ranked highest under both the standard and PCA-weighted grades, and both methods converged on the same optimal setting, strengthening confidence in the result.

The confirmatory experiment delivered striking improvements. The weighted grey relational grade rose from 0.357 under initial conditions to 0.966 under optimal conditions, closely matching the predicted value of 0.9677. Weight deficit fell from 3.160 percent to 0.682 percent, length shrinkage dropped from 4.860 percent to 0.545 percent, breadth shrinkage plummeted from 6.156 percent to 1.067 percent, and thickness shrinkage declined from 4.200 percent to 1.800 percent. In practical terms, a cast sword produced under the optimized parameters now deviates from its wax pattern by barely one percent in its principal dimensions, meaning far less manual filing and correction before gold plating. Given that finishing work is among the most labor-intensive stages of sculpture production, even modest dimensional improvements translate into significant reductions in lead time and cost.

The implications extend well beyond Nepal’s foundries. The authors note that the GRA-PCA methodology can be adapted to any complex manufacturing process where multiple conflicting objectives must be balanced, including precision casting of aerospace turbine blades, biomedical device manufacturing where dimensional control is critical, and automotive component casting where strength, weight, and tolerances compete. For Nepal, the study represents the first application of advanced multi-response optimization to traditional sculpture casting, and it arrives at a pivotal moment for an industry whose economic viability depends on competing with industrialized producers. Future work, the researchers suggest, could examine surface roughness, mechanical properties, and additional process parameters. But the central message is already clear: fourteen centuries of artisanal wisdom and twenty-first-century statistical rigor are not adversaries. When the number of coatings, the preheat temperature, and the pouring temperature are tuned together, the ancient art of Himalayan metal sculpture can achieve a precision its original masters could scarcely have imagined, preserving both a cultural heritage and the livelihoods of the craftsmen who sustain it.

Subject of Research: Multi-response optimization of investment casting parameters to improve the dimensional accuracy of gilding metal sculptures in traditional Nepali manufacturing.

Article Title: Improvement of dimensional accuracy in gilding metal sculpture manufacturing using grey relational analysis coupled with principal component analysis

Article References: Shrestha, Z., Pandey, A., & Prajapati, B. (2026). Improvement of dimensional accuracy in gilding metal sculpture manufacturing using grey relational analysis coupled with principal component analysis. Heliyon, 12(14), Article e45412. https://doi.org/10.1016/j.heliyon.2026.e45412

Image Credits: AI Generated

DOI: Not provided

Keywords: investment casting, grey relational analysis, principal component analysis, Taguchi method, dimensional accuracy, gilding metal, Nepal sculpture manufacturing, shrinkage reduction, ANOVA, multi-response optimization, Kathmandu Valley, metal casting