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Record W4383616382 · doi:10.2172/1973396

Development of High-efficiency and Cost-effective Forged Ingot Niobium Technology for Science Frontiers and Accelerator Applications

2021· article· en· W4383616382 on OpenAlexaboutno aff
Ganapati Rao Myneni, Gianluigi Ciovati, Pashupati Dhakal, Hani E. Elsayed-Ali, A. Fajardo, Md Obidul Islam, B. Khanal, N. Lannoy, F. Marhouser, P.M. O'Larey, Robert Rimmer, T. Saeki, Masashi YAMANAKA, T. Dohmae, Kensei Umemori, Akira Yamamoto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSuperconducting Materials and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsIngotNiobiumComputer scienceMaterials scienceMetallurgy

Abstract

fetched live from OpenAlex

Development of Forged Ingot Niobium Technology: Worlds science frontier programs and SRF accelerator applications demand high performance and cost-effective SRF accelerator technology [1-8]. Fine-grain (FG) and Large-grain (LG) ingot niobium technologies have been very well developed and implemented in all the present-day accelerator projects. However, forged ingot niobium technology which is the focus of this development proposal will be much more cost-effective and expected to have several technical advantages. FG niobium sheet production is very complex involving more than ten processing steps making them prone to contamination. As a result, they are very expensive to produce and require stringent QA procedure to be ready for SRF cavity production. The accelerating cavity process steps are also numerous and require strict procedures in order to achieve high accelerating gradients and quality factors needed for science frontier programs. LG niobium disc production, directly sliced from the ingot, is relatively simple and straight forward to keep surface cleanness. The disc production cost is significantly low compared to FG niobium sheet production. However, there are (some) draw backs due to non-homogeneity of the grain boundary distribution, resulting in non-uniform mechanical properties and complex cavity fabrication, although the LG cavities achieve the expected high-gradient performance goals with lower cost. Medium-grain (MG) niobium disk production may be realized with a new approach/process, the disc directly sliced from the forged ingot, involves a simpler process steps contributing major production cost reduction [9]. These discs are expected to be superior as they tend to be homogenous with uniform sub millimeter grains and mechanical properties. We are eagerly looking forward to developing the forged ingot niobium SRF accelerator technology for the benefit of the world-wide science frontier programs, green energy subcritical nuclear energy systems and a wide variety of industrial applications including the production of radio isotopes and nuclear transmutation applications. Measurement of thermal characteristics of the forged ingot niobium: Measurement of the thermal diffusivity, D, of superconducting MG niobium is important to be understood in comparison with FG sheet and LG disc, as well as that of advanced composite material of Nb3Sn film sputtered on forged ingot Nb, which will be determined using transient pump-probe thermo-modulation [10,11]. Transient thermo-modulation is based on using an ultrafast laser pulse to heat the superconducting materials by a few K, then a synchronized laser pulse probes the reflectance of the heated material. For thin films on a substrate (e.g, 100-nm Nb3Sn on Nb), it takes <100 ps for the heat to reach the substrate by diffusion. Therefore, an ultrafast method is needed to probe D of the studied material. D will be measured from room temperature to liquid helium temperatures. Fundamental Research: The increase of rf loss in SRF cavities is related to trapping of residual magnetic field during the cavity cool-down. The study suggested that the micro structure plays the role in flux trapping sensitivity. The research includes the flux trapping and expulsion study as forged ingot niobium goes through several mechanical deformations, crystallization leading to the optimal SRF cavity performance. Furthermore, the cavity made from FG, MG, and LG sheet/disc will be compared to understand the optimal re-crystallization temperature that cavity needed to be heat treated which minimize the flux trapping and increase SRF cavity performance. References: 1. S. Belomestnykh, Overview of recent SRF developments for ERLs, presented at the SRF 2015, Whistler, BC, Canada (2015). 2. A. Yamamoto, M. Yamanaka and G. Myneni, Ingot Nb based SRF Technology for the International Linear Collider, in Science and Technology of Ingot Niobium for Superconducting Radio Frequency Applications, AIP Conf. Proc. 1687, 030005-1 ? 03005-6, 2015 3. Report of the Workshop on Energy and Environmental Applications of Accelerators, DOE Workshop Report. https://science.osti.gov/-/media/hep/pdf/Reports/2020/CASM_WorkshopReport.pdf? la=en&hash=AEB0B318ED0436B1C5FF4EE0FDD6DEB84C2F15B2 4. G. Ciovati, et al., Design of a cw, low-energy, high-power superconducting linac for environmental applications, Phys. Rev. Accel. Beams 21, 091601 (2018). 5. P. Dhakal, et al., Effect of high temperature heat treatments on the quality factor of a large-grain superconducting radio-frequency niobium cavity, Phys. Rev. ST Accel. Beams 16, 042001 (2013). 6. P. Kneisel et al., Review of ingot niobium as a material for superconducting radio frequency accelerating cavities, Nuclear Instruments and Methods in Physics Research A 774, 133 (2015). 7. G. Ciovati, P. Dhakal, and G. R, Myneni, Superconducting radio-frequency cavities made from medium and low-purity niobium ingots, Supercond. Sci. Technol. 29, 064002 (2016). 8. M. Drury et al., commissioning of the prototype C75 cavities in a CEBAF cryomodule, in Proc. of IPAC 2018, Vancouver, BC, Canada (2018) 9. Feasibility of forged-ingot niobium disc and SRF cavity fabrication technology recently demonstrated in cooperation of ATI, BSCE, and KEK (2020). 10. Hani E. Elsayed-Ali, ?Measurements of heat transport in thin films by ultrafast laser-based techniques,? 3rd International Conference on Thermal Issues in Emerging Technologies Theory and Applications, Cairo, Egypt, pp. 347 ? 350 (2010). DOI: 10.1109/ThETA17616.2010 11. W. M. G. Ibrahim, H. E. Elsayed-Ali, M. Schinn, and C. A. Bonner, Jr., ?Ultrafast investigation of electron dynamics in multilayer metals,? Int. J. Heat and Mass Transfer, 47(10?11), 2261?2268 (2004).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.245
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
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