This paper examines the effects of laser peening on Alloy 22 (UNS N06022), which is the proposed material for use as the outer layer on the spent-fuel nuclear waste canisters to be stored at Yucca Mountain. Stress corrosion cracking (SCC) is a primary concern in the design of these canisters because tensile residual stresses will be left behind by the closure weld. Alloy 22 is a nickel-based material that is particularly resistant to corrosion; however, there is a chance that stress corrosion cracking could develop given the right environmental conditions. Laser peening is an emerging surface treatment technology that has been identified as an effective tool for mitigating tensile redisual stresses in the storage canisters. The results of laser-peening experiments on Alloy 22 base material and a sample 33 mm thick double-V groove butt-weld made with gas tungsten arc welding (GTAW) are presented. Residual stress profiles were measured in Alloy 22 base material using the slitting method (also known as the crack-compliance method), and a full 2D map of longitudinal residual stress was measured in the sample welds using the contour method. Laser peening was found to produce compressive residual stress to a depth of 3.8 mm in 20 mm thick base material coupons. The depth of compressive residual stress was found to have a significant dependence on the number of peening layers and a slight dependence on the level of irradiance. Additionally, laser peening produced compressive residual stresses to a depth of 4.3 mm in the 33 mm thick weld at the center of the weld bead where high levels of tensile stress were initially present.

Gastric cancer (GC) presents high mortality worldwide because of delayed diagnosis. Currently, exosome-based liquid biopsy has been applied in diagnosis and monitoring of diseases including cancers, whereas disease detection based on exosomes at the metabolic level is rarely reported. Herein, the specific aptamer-coupled Au-decorated polymorphic carbon (CoMPC@Au-Apt) is constructed for the capture of urinary exosomes from early GC patients and healthy controls (HCs) and the subsequent exosome metabolic pattern profiling without extra elution process. Combining with machine learning algorithm on all exosome metabolic patterns, the early GC patients are excellently discriminated from HCs, with an accuracy of 100% for both the discovery set and blind test. Ulteriorly, three key metabolic features with clear identities are determined as a biomarker panel, obtaining a more than 90% diagnostic accuracy for early GC in the discovery set and validation set. Moreover, the change law of the key metabolic features along with GC development is revealed through making a comparison among HCs and GC at early stage and advanced stage, manifesting their monitoring ability toward GC. This work illustrates the high specificity of exosomes and the great prospective of exosome metabolic analysis in disease diagnosis and monitoring, which will promote exosome-driven precision medicine toward practical clinical application.

Multiphoton ionization of uranium atoms followed by laser-induced fluorescence detection of uranium ions is used to study the initial electronic state distribution of photon-produced ions and the degree of ionization within the uranium vapor. Our experimental data clearly demonstrate that photoionization of uranium through the 50 701 cm−1 excited even levels using a broad band pulsed dye laser of 5915 Å produces roughly 50% ground state ions and 50% metastably excited (289 cm−1) ions. The effective photoionization cross section is about 4.7×10−17 cm2. The subsequent dispersion of UII after photoionization appears to be caused by ambipolar expansion of ions and electrons in the plasma. The gA values for the 4050 and 3859 Å transitions of UII are measured to be 0.86×108 and 2.8×108 s−1, respectively.