Dr. Jason Griggs Contributions to Science

Much of my effort has been focused on Accelerated Lifetime Testing (ALT) of medical materials and devices. Prostheses and implants should last a long time before failure clinically. However, researchers must conduct lifetime tests much more rapidly than in the clinical case. This is achieved using three strategies: (1) Overstress acceleration in which products are tested under more severe conditions than the clinical case (e.g., heavier bite force). (2) Usage rate acceleration in which products are damaged more frequently than in the clinical case (e.g., around the clock mastication at cycles per second). (3) Specimens are allocated more efficiently to different treatment groups. Strategies (1) and (2) can sometimes alter the mode of failure, losing the clinical relevance of in vitro studies. In addition, some materials experience an interaction between two different mechanisms of subcritical crack growth, and (1) and (2) can alter this interaction. I have shown how and when all three ALT strategies can be used simultaneously to test products more efficiently. I have worked on metal implants, experimental metals intended for implants, ceramic implants, crown and bridge ceramics, and endodontically treated natural teeth. At the beginning of my career, most dental researchers were using Up-and-Down Method, or ‘Staircase Method’, of Dixon & Mood, in which specimens are assigned to stress levels near the 50% reliability point, which is not clinically useful because we do not want 50% failures. Maennig had previously developed the Boundary Technique for assigning specimens to stress levels near the ends of the failure distribution, but his published protocols were vague. I proved that Boundary Technique was more efficient than Staircase Method and determined specific testing parameters to be used. I also used finite element models to predict the maximum overstress acceleration that could be used without altering the crack propagation mechanism in metallic implants. Then, Thompson and the NYU group introduced me to an even more efficient method, the Step-Stress Method of Nelson with a cumulative damage model, in which each specimen can be assigned to multiple levels of overstress acceleration to cause rapid failure. I validated the Step-Stress Method on metallic implants by conducting a head-to-head comparison with Boundary Technique. Then, I added a general log-linear model to the cumulative damage model to allow simultaneous usage rate acceleration and overstress acceleration and to compensate for their interaction. My research team has successfully used our latest method on a variety of ceramic materials and metallic implant designs.

1. Ottoni R, Griggs JA, Corazza PH, Della Bona A, Borba M (2018). Precision of different fatigue methods for predicting glass-ceramic failure. J Mech Beh Biomed Mater 88:497-503.
2. Duan Y, Griggs JA (2018). Effect of loading frequency on cyclic fatigue lifetime of a standard-diameter implant with an internal abutment connection. Dent Mater 34:1711-1716.
3. Duan Y, Gonzalez J, Kulkarni P, Nagy W, Griggs J. Fatigue lifetime prediction of a reduced-diameter dental implant system: numerical and experimental study. Dent Mater 34:1299-1309.
4. Corazza P, Duan Y, Kimpara ET, Griggs JA, Della Bona A (2015). Lifetime comparison of Y-TZP/ porcelain crowns under different loading conditions. J Dent 43:450-457.

Another focus has been the analysis of broken surfaces to determine the conditions that were present at the time of failure and to determine the origin of failure. I have analyzed both clinical and in vitro failures of implant abutments, implant bodies, connector screws, polymer-based denture teeth, polycrystalline ceramics, glass-ceramics, fused layered ceramics, water pipes, and semiconductor wafers. Previous researchers used fractal geometry to characterize broken surfaces but suffered from poor repeatability and unknown accuracy, so I used Monte Carlo simulation to compare the accuracy and precision of six methods of analyzing fractal geometry on computer-generated surfaces with known properties. This allowed me to determine the bias of the methods, a correction factor for each method, and their relative precision. I identified the method with greatest precision and used it to test real surfaces fractured in water versus saliva, showing that testing environment did not affect the result. I also showed that replicas of fracture surfaces made by casting epoxy into polyvinyl siloxane impressions yield the same results as the original surface. We can use fractal analysis to determine ceramic toughness and the stress at failure, as well as the layer in which failure originated for multilayered structures. Regarding traditional failure analysis techniques, I analyzed clinically chipped denture teeth to identify the failure origin and developed a rapid invitro test that produces the same pattern on the fracture surface. The manufacturer used my test to develop a new product with much greater chipping resistance. More recently, I studied FPDs made from lithium disilicate glass-ceramic fused to zirconia and determine that the fusion glass layer was the origin of failures. I also categorized the types of flaws (air abrasion, polishing, and porosity) that lead to failure in zirconia and determined the effect of ALT on their relative frequencies of presenting as strength limiting flaws, and I showed how to use mixed Weibull models for the strength distributions of such systems. Finally, I studied zirconia-core crowns fatigue loaded in vitro using various loading points and motions and determined that a sliding contact is important for reproducing a clinical failure mode.

1. Mecholsky JJ, Hsu SM, Jadaan O, Griggs J, Neal D, Clark AE, Xia X, Esquivel-Upshaw JF (2021). Forensic and Reliability Analyses of Fixed Dental Prostheses. J Biomed Mater Res B doi: 10.1002/jbm.b.34796.
2. Jodha KS, Salazar Marocho SM, Scherrer SS, Griggs JA (2020). Fractal analysis at varying locations of clinically failed zirconia dental implants. Dent Mater 36:1052-1058.
3. Griggs JA (2018). Using fractal geometry to examine failed implants and prostheses. Dent Mater 34:1748-1755.
4. Basso GR, Moraes RR, Borba M, Griggs JA, Della Bona A (2015). Flexural strength and reliability of monolithic and trilayer structures obtained by the CAD-on technique. Dent Mater 31:1453-1459.

The most recent topic that I have focused on is design optimization and efficient screening of design factors using response surface methods and artificial intelligence. A common obstacle when designing improved medical materials and devices is that a large number of possible experimental factors leads to a prohibitive number of test groups for a full-factorial experiment. For example, my research group identified 16 independent design factors for dental implants. Exploring just two levels of each factor using traditional methods would require testing 2¹⁶ = 65,536 designs! I use Taguchi orthogonal arrays to efficiently screen main effects followed by response surfaces to optimize the settings of remaining factors. When the response surface is too convoluted to model using commercially available software, then I train an artificial neural network to fit the surface and use sequential minimal energy design to efficiently explore it and find the global maximum. Another related problem is that sometimes a novel medical material or device needs to perform well in multiple ways. The formulation or design corresponding to maximum dimensional accuracy may be different from the one corresponding to maximum shelf-life, minimum cost, and minimum technique sensitivity. I use the harmonic means of multiple response surfaces to find the design that simultaneously compromises between multiple weighted performance objectives. I used these methods to collaborate with several research groups on the formulation of bone tissue scaffolds, the acid bath mixtures used for anodization of implant surfaces, the scanning and forming methods used to manufacture ceramic dental crowns, the implant-abutment connection of reduced-diameter dental implants, and the formulation of electrospun periodontal membranes.

1. Gurumurthy B, Pal P, Griggs JA, Janorkar AV (2020). Optimization of collagen-elastin-like polypeptide-Bioglass scaffold composition for osteogenic differentiation of adipose-derived stem cells. Materialia 9:100572.
2. Jain S, Williamson RS, Marquart M, Janorkar AV, Griggs JA, Roach MD (2019). Osteoblast response to nanostructured and phosphorus enhanced titanium anodization surfaces. J Biomat App 34:594-603.
3. Ottoni R, Griggs J, Borba M (2019). Design optimization of all-ceramic crowns. Dent Mater 35:e27-e28.
4. Gurumurthy B, Griggs JA, Janorkar AV (2018). Optimization of collagen-elastin-like polypeptide composite tissue engineering scaffolds for response surface methodology. J Mechanical Behavior Biomed Mater 84:116-125.