Lead Investigator: Florence Sanchez (Vanderbilt University)
Additional Investigators: Lesa Brown, Kevin G. Brown, Chen Gruber, and David Kosson (Vanderbilt University)

Project Objectives:

• Develop fiber-reinforced high-performance encapsulation grout formulations that are resistant to aging mechanisms (e.g., carbonation, cracking, autogenous shrinkage);
• Develop grout formulations appropriate for the treatment of tank waste sludges and calcined waste to facilitate disposal as Class C or Greater-Than-Class C (GTCC) Low-Level Radioactive Waste;
• Develop machine learning approaches for determining reaction sets and thermodynamic/kinetic constants for geochemical speciation modeling and enhanced grout formulations; and,
• Characterize ancient and natural analogues cement samples that have been exposed to relevant climate conditions and geologic interfaces to improve confidence in long-term performance modeling.

Significance/Impact:
Grout is used in multiple applications for waste management, including for encapsulation of secondary waste (e.g., HEPA filters, equipment, resins, condensate) at the Hanford Site, and as a primary wasteform (e.g., saltstone) at the Savannah River Site (SRS). The following are specific challenges to be addressed through this project:

Encapsulation grout – High-performance encapsulation grouts have been under development based on using low water: cement ratios and admixtures to control rheology. Applications envisioned include bulk fill surrounding and within contaminated materials and equipment and containment boxes or vaults. In both applications, low porosity and permeability result in high retention of radionuclides. However, material micro- and macro-cracking has been observed in response to material aging. Identified failure mechanisms have included autogenous shrinkage, formation of expansive mineral phases, and carbonation. Objective 1 of this project will overcome these challenges by the use of microfiber reinforcement in conjunction with grout formulations resistant to the identified failure mechanisms. Grout formulations will be designed for bulk fill and additive manufacturing (cement printing).

Grout for Hanford sludge solids and Idaho calcined waste – Both Hanford tank sludge solids and Idaho calcine waste have been considered waste streams for thermal treatment (e.g., vitrification) prior to disposal as high-level waste (HLW). However, thermal treatment followed by disposal as HLW can be challenging because of high cost, material handling challenges, and the absence of a geologic repository. Alternative disposal pathways may be viable in the future as either Class C or GTCC radioactive waste when incorporated in grout wasteforms. However, these waste streams differ in composition and physical-chemical properties from other DOE wastes that are currently grouted. Thus, grout performance objectives and conforming formulations will be developed (Objective 2) to enable further consideration of potential grout disposal pathways.

Geochemical reaction sets and thermodynamic constants – Selection of the mineral assemblage and uncertainty associated with mineral reaction thermodynamic constants are central to geochemical speciation-based reactive transport modeling for long-term grout performance (Durdziński, et al. 2017). These predictions can thus influence (and at times, limit) the formulations used for grout wasteforms (e.g., saltstone, Cast Stone, tank closure grouts) critical to DOE waste management practices. Today, the selection of a mineral assemblage is influenced by the modeler’s theoretical knowledge/background, existing data, and calibration processes for uncertain reaction constants and other parameters that rely on the minimization of errors between predictions and experimental results (Wang et al., 2022; Wang et al. 2023). Automation and machine learning would expedite the mineral assemblage selection process significantly by constructing a rigorous and logical framework that incorporates differing types of information for important families of cement-based materials: physical evidence (XRD); likelihood of mineral phase existence (based on prior knowledge of families of materials – e.g., CaCO₃ in carbonate rocks); and better understanding of kinetic versus thermodynamic phenomena and associated uncertainties. The ability to more accurately and consistently predict the performance of important cement-based materials would build confidence in their use for important waste streams (e.g., Hanford tank wastes). Machine learning techniques can help build such confidence (Li et al., 2022). Outcomes for Objective 3 would be to 1) minimize the arbitrary influence on the mineral assemblage selection process, and 2) provide uncertainty quantification and approaches to resolving gaps between predictions and experimental data.

Characterizing ancient cements – Grout wasteforms and concrete containment structures must be evaluated for a performance period of up to and greater than 1000 years to be fully credited in Performance Assessments (PA). However, actual performance data are available for only a few decades. Performance data for cement systems under exposure conditions relevant to DOE sites is needed to understand long-term aging mechanisms and validate models for cement materials evolution. Ancient and natural analogues cement materials, ranging in age from up to 2,500 years for man-made cements to 50,000 years (natural cements) with well-defined exposure conditions (both arid and temperate in contact with carbonate and loess soils) provides an opportunity to provide geochemical and constituent transport data that can be used to confirm current testing and modeling approaches. Outcomes for Objective 4 will use characterization data from ancient materials to build confidence in the integrated testing and modeling approach used by CRESP to evaluate and predict the long-term behavior of cement materials used for DOE waste management.

Public Benefits:
The development of effective grout formulations for a wide variety of waste streams ensures the safety of communities and mitigates the risks associated with waste storage and disposal. The formulations, data, and models developed during this research will be applicable to other industries and waste streams. The results of this work, including the characterization of ancient materials, will help build public confidence in the long-term performance and prediction of the resulting grout waste forms.

References: (* indicates CRESP publication)

*Branch, J.L., Brown, K.G., Arnold, J.R., van der Sloot, H.A. & Kosson D.S. (2015a) Reactive Transport Modeling and Characterization of Concrete Materials with Fly Ash Replacement under Carbonation Attack – 15477. WM’2015, WMSymposia, Phoenix, Arizona.

*Branch, J.L., Kosson, D.S., Brown, KG, van der Sloot, J.A. & Garrabrants, A.C. (2015b) Characterization and reactive-transport modeling of the changes in the chemical speciation and microstructure of cementitious materials as a result of carbonation. IWWG-ARB 2015 Conference, Shanghai, CHINA.

Brown, L., Allison, P. G., & Sanchez, F. (2018). Use of nanoindentation phase characterization and homogenization to estimate the elastic modulus of heterogeneously decalcified cement pastes. Materials & Design, 142, 308-318. https://doi.org/https://doi.org/10.1016/j.matdes.2018.01.030 

Brown, L., & Sanchez, F. (2016). Influence of carbon nanofiber clustering on the chemo-mechanical behavior of cement pastes. Cement and Concrete Composites, 65, 101-109. https://doi.org/https://doi.org/10.1016/j.cemconcomp.2015.10.008

Brown, L., & Sanchez, F. (2018). Influence of carbon nanofiber clustering in cement pastes exposed to sulfate attack. Construction and Building Materials, 166, 181-187. https://doi.org/https://doi.org/10.1016/j.conbuildmat.2018.01.108

Brown, L., Stephens, C. S., Allison, P. G., & Sanchez, F. (2022). Effect of Carbon Nanofiber Clustering on the Micromechanical Properties of a Cement Paste. Nanomaterials, 12(2).

*Chen, Z., Zhang, P., Brown, K. G., Branch, J. L., van der Sloot, H. A., Meeussen, J. C. L., Delapp, R. C., Um, W., & Kosson, D. S. (2021). Development of a Geochemical Speciation Model for Use in Evaluating Leaching from a Cementitious Radioactive Waste Form. Environmental Science & Technology, 55(13), 8642-8653. https://doi.org/10.1021/acs.est.0c06227

Durdziński, P. T., Ben Haha, M., Zajac, M., & Scrivener, K. L. (2017). Phase assemblage of composite cements. Cement and Concrete Research, 99, 172-182. https://doi.org/https://doi.org/10.1016/j.cemconres.2017.05.009  

*Garrabrants, A.C., Brown, L., Zhang, P., van der Sloot, H.A., Brown, K.G., Gruber, C. & Kosson, D.S. (2019) Experimental and modeling efforts to predict long-term geochemistry of vault concrete – salt waste interfaces at U.S. DOE disposal sites. International Workshop on Mechanisms and Modeling of Waste/Cement Interactions 2019. Karlsruhe, Germany.

*Gruber, C., Steen, M., Brown, K. G., Delapp, R., Matteo, E. N., Klein-BenDavid, O., Bar-Nes, G., Meeussen, J. C. L., Ayers, J. C., Kosson, D. S. (2022). Cement‑carbonate rock interaction under saturated conditions: From laboratory to modeling. Cement and Concrete Research, 160, 899-924. https://doi.org/10.1016/j.cemconres.2022.106899.

Li, Z., Yoon, J., Zhang, R., Rajabipour, F., Srubar Iii, W. V., Dabo, I., & Radlińska, A. (2022). Machine learning in concrete science: applications, challenges, and best practices. npj Computational Materials, 8(1), 127. https://doi.org/10.1038/s41524-022-00810-x

Kosson, M., Brown, L., & Sanchez, F. (2020). Early-Age Performance of 3D Printed Carbon Nanofiber and Carbon Microfiber Cement Composites. Transportation Research Record, 2674(2), 10-20. https://doi.org/10.1177/0361198120902704

Kosson, M., Brown, L., & Sanchez, F. (2023). Nanomechanical characterization of 3D printed cement pastes. Journal of Building Engineering, 66, 105874. https://doi.org/https://doi.org/10.1016/j.jobe.2023.105874

Sanchez, F., & Borwankar, A. (2010). Multi-scale performance of carbon microfiber reinforced cement-based composites exposed to a decalcifying environment. Materials Science and Engineering: A, 527(13), 3151-3158. https://doi.org/https://doi.org/10.1016/j.msea.2010.01.084

Sanchez, F., Borwankar, A & Ince, C. (2009) Effect of decalcification on the performance of carbon microfiber reinforced cement-based materials. In: L’Hostis, V., Gens, R. Gallé, C. (eds) RILEM Proceedings Book related to the NUCPERF 2009 Workshop (Long Term Performance of Cementitious Barriers and Reinforced Concrete in Nuclear Power Plants and Waste Management (EFC Event n°317)). 30 March – 2 April 2009, Cadarache, France. PRO 64 (2009), ISBN: 978-2-31158-072-1

*Sarkar, S., Kosson, D. S., Mahadevan, S., Meeussen, J. C. L., der Sloot, H. v., Arnold, J. R., & Brown, K. G. (2012). Bayesian calibration of thermodynamic parameters for geochemical speciation modeling of cementitious materials. Cement and Concrete Research, 42(7), 889-902. https://doi.org/https://doi.org/10.1016/j.cemconres.2012.02.004

Wang, X., Garrabrants, A. C., van der Sloot, H. A., Chen, Z., Brown, K. G., Hensel, B., & Kosson, D. S. (2023). Leaching and geochemical evaluation of oxyanion partitioning within an active coal ash management unit. Chemical Engineering Journal, 454, 140406. https://doi.org/https://doi.org/10.1016/j.cej.2022.140406

*Wang, X., van der Sloot, H. A., Brown, K. G., Garrabrants, A. C., Chen, Z., Hensel, B., & Kosson, D. S. (2022). Application and uncertainty of a geochemical speciation model for predicting oxyanion leaching from coal fly ash under different controlling mechanisms. Journal of Hazardous Materials, 438, 129518. https://doi.org/10.1016/j.jhazmat.2022.129518