Search

Your search keyword '"Riley, Brian J."' showing total 249 results
Start Over Author "Riley, Brian J." Language english
249 results on '"Riley, Brian J."'

19. Evaluation of GlassNet for physics‐informed machine learning of glass stability and glass‐forming ability.

Author

Allec, Sarah I., Lu, Xiaonan, Cassar, Daniel R., Nguyen, Xuan T., Hegde, Vinay I., Mahadevan, Thiruvillamalai, Peterson, Miroslava, Du, Jincheng, Riley, Brian J., Vienna, John D., and Saal, James E.

Subjects
ARTIFICIAL neural networks, PHOSPHATE glass, GLASS construction, OPTICAL fibers, TERNARY system, BOROSILICATES, RADIOACTIVE wastes
Abstract

Glassy materials form the basis of many modern applications, including nuclear waste immobilization, touch‐screen displays, and optical fibers, and also hold great potential for future medical and environmental applications. However, their structural complexity and large composition space make design and optimization challenging for certain applications. Of particular importance for glass processing and design is an estimate of a given composition's glass‐forming ability (GFA). However, there remain many open questions regarding the underlying physical mechanisms of glass formation, especially in oxide glasses. It is apparent that a proxy for GFA would be highly useful in glass processing and design, but identifying such a surrogate property has proven itself to be difficult. While glass stability (GS) parameters have historically been used as a GFA surrogate, recent research has demonstrated that most of these parameters are not accurate predictors of the GFA of oxide glasses. Here, we explore the application of an open‐source pre‐trained neural network model, GlassNet, that can predict the characteristic temperatures necessary to compute GS with reasonable performance and assess the feasibility of using these physics‐informed machine learning (PIML)‐predicted GS parameters to estimate GFA. In doing so, we track the uncertainties at each step of the computation—from the original ML prediction errors to the compounding of errors during GS estimation, and finally to the final estimation of GFA. While GlassNet exhibits reasonable accuracy on all individual properties, we observe a large compounding of error in the combination of these individual predictions for the PIML prediction of GS, finding that random forest models offer similar accuracy to GlassNet. We also break down the performance of GlassNet on different glass families and find that the error in GS prediction is correlated with the error in crystallization peak temperature prediction. Lastly, we utilize this finding to assess the relationship between top‐performing GS parameters and GFA for two ternary glass systems: sodium borosilicate and sodium iron phosphate glasses. We conclude that to obtain true ML predictive capability of GFA, significantly more data needs to be collected. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

21. Analytical capabilities for iodine detection: Review of possibilities for different applications.

Author

Riley, Brian J., Beck, Chelsie L., Evarts, Jonathan S., Chong, Saehwa, Lines, Amanda M., Felmy, Heather M., McFarlane, Joanna, Andrews, Hunter B., Bryan, Samuel A., McHugh, Kelly C., Cunningham, Heather S., Asmussen, R. Matthew, Dhas, Jeffrey A., Zhu, Zihua, Crum, Jarrod V., Shen, Steve D., McCloy, John S., and Heiden, Zachariah M.

Subjects
*IODINE isotopes, *PHASES of matter, *THYROID cancer, *IODINE, *ACQUISITION of data
Abstract

This Review summarizes a range of analytical techniques that can be used to detect, quantify, and/or distinguish between isotopes of iodine (e.g., long-lived 129I, short-lived 131I, stable 127I). One reason this is of interest is that understanding potential radioiodine release from nuclear processes is crucial to prevent environmental contamination and to protect human health as it can incorporate into the thyroid leading to cancer. It is also of interest for evaluating iodine retention performances of next-generation iodine off-gas capture materials and long-term waste forms for immobilizing radioiodine for disposal in geologic repositories. Depending upon the form of iodine (e.g., molecules, elemental, and ionic) and the matter state (i.e., solid, liquid, and gaseous), the available options can vary. In addition, several other key parameters vary between the methods discussed herein, including the destructive vs nondestructive nature of the measurement process (including in situ vs ex situ measurement options), the analytical data collection times, and the amount of sample required for analysis. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

22. Static iodine loading comparisons between activated carbon, zeolite, alumina, aerogel, and xerogel sorbents.

Author

Chong, Saehwa, Riley, Brian J., Baskaran, Karthikeyan, Sullivan, Sean, El Khoury, Luke, Carlson, Krista, Asmussen, R. Matthew, and Fountain, Matthew S.

Subjects
*ACTIVATED carbon, *DEAD loads (Mechanics), *SORBENTS, *CARBON foams, *AEROGELS, *CATALYTIC cracking
Abstract

Different sorbents, including activated carbons, an Ag-aerogel, Ag-xerogels, an Ag-alumina, an Ag-zeolite, a Ag2S-polyacrylonitrile composite, and a carbon foam were investigated for static I2(g) loading at 71 °C for 56 d followed by 4.7 d of desorption. The iodine loadings were 630–1249 mg g−1 for activated carbons and 87–744 mg g−1 for other sorbents. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

34. Glass structure and crystallization in boro-alumino-silicate glasses containing rare earth and transition metal cations: a US-UK collaborative program

Author

McCloy, John S., Marcial, José, Patil, Deepak, Saleh, Muad, Ahmadzadeh, Mostafa, Chen, Hua, Crum, Jarrod V., Riley, Brian J., Kamat, Hrishikesh, Bréhault, Antoine, Goel, Ashutosh, Barnsley, Kristian E., Hanna, John V., Rajbhandari, Prashant, Corkhill, Claire L., Hand, Russell J., and Hyatt, Neil C.

Published
2019
Full Text
View/download PDF

36. Synthesis of and iodine capture with MSx (Ag2S, Bi2S3, Cu2S)–polyacrylonitrile composites.

Author

Riley, Brian J, Chong, Saehwa, and Canfield, Nathan L.

Subjects
*POLYACRYLONITRILES, *METAL sulfides, *IODINE, *DIMETHYL sulfoxide, *SILVER sulfide
Abstract

Polyacrylonitrile (PAN) composites were produced with metal sulfides (Ag2S, Bi2S3, and Cu2S) using dimethyl sulfoxide as the PAN dissolution medium. Static I2(g) loading experiments at 130 °C show values of 723, 909, and 1095 mg g−1 for 80Ag2S–PAN, 80Bi2S3–PAN, and 80Cu2S–PAN, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results