Radiation Damage Mechanisms and Research Status of Radiation-Resistant Optical Fibers: A Review.

In recent years, optical fibers have found extensive use in special environments, including high-energy radiation scenarios like nuclear explosion diagnostics and reactor monitoring. However, radiation exposure, such as X-rays, gamma rays, and neutrons, can compromise fiber safety and reliability. Consequently, researchers worldwide are focusing on radiation-resistant fiber optic technology. This paper examines optical fiber radiation damage mechanisms, encompassing ionization damage, displacement damage, and defect centers. It also surveys the current research on radiation-resistant fiber optic design, including doping and manufacturing process improvements. Ultimately, it summarizes the effectiveness of various approaches and forecasts the future of radiation-resistant optical fibers.

Dissolution of mixed oxide(MOX) fuel in nitric acid:A review.

The fast neutron reactor is an internationally promising fourth-generation reactor. The main fuel for this reactor is a mixed oxide fuel, and its reprocessing is currently one of the technical challenges being tackled by various countries. One of the difficulties in the reprocessing of mixed oxide (MOX) fuel lies in the nitric acid dissolution process. The high Pu content in MOX fuel can lead to issues such as solvent radiolysis, nuclear criticality, increased insoluble residues, and slow dissolution rates during the nitric acid dissolution process. These challenges have yet to be effectively addressed. This article discusses the chemical aspects of nitric acid dissolution of MOX fuel and investigates the impact of fuel manufacturing processes, the addition of metal catalyst ions, hydrofluoric acid addition, fuel plutonium content, dissolution temperature, and ultrasonic assistance on the nitric acid dissolution of MOX fuel. A review of various countries' engineering practices related to MOX fuel dissolution is presented. Based on the research findings and experiences, a potentially feasible future industrial processing route for MOX fuel is proposed, and future research priorities are outlined.

Fault diagnosis method of rolling bearings based on adaptive modified CEEMD and 1DCNN model.

The working environment of rolling bearings is highly complex and often the vibration signal of the bearing is mixed with noise, which makes fault diagnosis challenging. As such, it is imperative to denoise the vibration signal of rolling bearings, extract effective vibration features, and improve classification accuracy. In this research, we propose a rolling bearing fault diagnosis model based on adaptive modified complementary ensemble empirical mode decomposition (AMCEEMD) and a one-dimensional convolutional neural network (1DCNN). Firstly, the AMCEEMD method is proposed. This algorithm is an improved signal processing technique based on CEEMD, which introduces fuzzy entropy and kurtosis values to remove noise and identify impulse signals. The purpose of AMCEEMD is to obtain standard Intrinsic Mode Functions (IMFs) while removing noise. Secondly, we introduce the energy ratio, fuzzy entropy, and kurtosis as selection indices for IMFs. The selection of IMFs is adapted, and the selected IMF features are inputted into 1DCNN for fault classification. Finally, it was validated by two bearing experiments and compared with other classification methods. The classification accuracy of AMCEEMD-1DCNN method in this study is higher than other methods. The effectiveness of the AMCEEMD-1DCNN fault diagnosis model was verified.

Siloxane Molecules: Nonlinear Elastic Behavior and Fracture Characteristics.

Fracture phenomena in soft materials span multiple length and time scales. This poses a major challenge in computational modeling and predictive materials design. To pass quantitatively from molecular to continuum scales, a precise representation of the material response at the molecular level is vital. Here, we derive the nonlinear elastic response and fracture characteristics of individual siloxane molecules using molecular dynamics (MD) studies. For short chains, we find deviations from classical scalings for both the effective stiffness and mean chain rupture times. A simple model of a nonuniform chain of Kuhn segments captures the observed effect and agrees well with MD data. We find that the dominating fracture mechanism depends on the applied force scale in a nonmonotonic fashion. This analysis suggests that common polydimethylsiloxane (PDMS) networks fail at cross-linking points. Our results can be readily lumped into coarse-grained models. Although focusing on PDMS as a model system, our study presents a general procedure to pass beyond the window of accessible rupture times in MD studies employing mean first passage time theory, which can be exploited for arbitrary molecular systems.

Porous Copper-Loaded Zeolites for High-Efficiency Capture of Iodine from Spent Fuel Reprocessing Off-Gas.

Capturing volatile radionuclide iodine produced in the nuclear industry is a crucial environmental issue. In previous studies, the principal efficient adsorbent for iodine capture was silver-containing zeolite. As silver-containing zeolites are expensive, alternate copper-loaded porous zeolites, including CuCl loaded NaY reduced by H2 (denoted as H2CuY) and CO (denoted as COCuY), were studied for iodine adsorption at moderate temperatures. The current work also discusses the influence of copper valency on iodine adsorption. Due to the copper sites and nanosized pore structure, H2CuY and COCuY showed high iodine adsorption capacities of 450 and 219 mg/g, respectively. The iodine adsorption capacity of H2CuY was higher than that of silver-loaded zeolites. Moreover, H2CuY and COCuY adsorbed volatile iodine through a chemical mechanism involving the copper sites of different valencies, and the Cu0 was more effective in adsorbing iodine than Cu+. These copper-loaded zeolites with strong chemical interactions with iodine and high iodine adsorption capacities provided the possibility for iodine adsorption application in the nuclear industry.

Synergetic interactions improve cobalt leaching from lithium cobalt oxide in microbial fuel cells.

Cobalt leaching from lithium cobalt oxide is a promising reduction process for recovery of cobalt and recycle of spent lithium ion batteries, but suffers from consumption of large amount of reductants and energy, and generation of excess secondary polluted sludge. Thus, effective and environmental friendly processes are needed to improve the existing process limitations. Here we reported microbial fuel cells (MFCs) to effectively reduce Co(III) in lithium cobalt oxide with concomitant energy generation. There was a synergetic interaction in MFCs, leading to a more rapid Co(III) leaching at a rate 3.4 times the sum of rates by conventional chemical processes and no-acid controls. External resistor, solid/liquid ratio, solution conductivity, pH and temperature affected system performance. This study provides a new process for recovery of cobalt and recycle of spent lithium ion batteries with concomitant energy generation from MFCs.