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Ordered L12 γ′ Ni3Al intermetallics are essential strengthening components to maintain the high strength of Ni-based superalloys and recently developed high entropy alloys at elevated temperatures. Under service conditions, structural disorder is usually encountered in these intermetallics, resulting in significant loss of their strengthening functionality. Thus, retaining the degree of order of the L12 intermetallics is vital for their long-term reliability and serviceability. In this study, atomistic simulations and rate equation analysis are employed to highlight a notable enhancement in the reordering ability of L12 intermetallics by incorporating multiple principal elements. Specifically, we examine the effects of Co and Ti addition on the irradiation-induced disordering and kinetic reordering process of L12 intermetallics. Our results reveal that the incorporation of Ti in the Al sublattice can maintain comparable disordering resistance as Ni3Al. Better yet, the introduction of Ti or Co fosters vacancy migration, which accelerates the kinetic reordering rate during the defect diffusion stage. A synergistic effect of Ti and Co in promoting kinetic reordering is also observed. Our work thus suggests a promising approach for designing irradiation-resistant multicomponent intermetallics, which can retain a high degree of structural order under irradiation with chemical disorder contributed by desirable compositions.

Summary: In eukaryotic genomes, rDNA generally resides as a highly repetitive and dynamic structure, making it difficult to study. Here, a synthetic rDNA array on chromosome III in budding yeast was constructed to serve as the sole source of rRNA. Utilizing the loxPsym site within each rDNA repeat and the Cre recombinase, we were able to reduce the copy number to as few as eight copies. Additionally, we constructed strains with two or three rDNA arrays and found that the presence of multiple arrays did not affect the formation of a single nucleolus. Although alteration of the position and number of rDNA arrays did impact the three-dimensional genome structure, the additional rDNA arrays had no deleterious influence on cell growth or transcriptomes. Overall, this study sheds light on the high plasticity of rDNA organization and opens up opportunities for future rDNA engineering.

Multi-principal elemental alloys (MPEAs) exhibit unusual mechanical properties and irradiation resistance. It has been reported that the irradiation tolerance of MPEAs originates from the long-term defect evolution stage rather than the ballistic collision phase. However, understanding the long-term evolution of MPEAs is exceptionally challenging due to intrinsic chemical disorder. In this work, we apply atomistically-informed cluster dynamics to study defect evolution in MPEAs for the first time, which enables us to elucidate the critical features responsible for the irradiation performance of MPEAs. With suitable irradiation parameters, our obtained cluster size distributions are in good agreement with experiments. We further discuss the influences of defect migration energy heterogeneity, cluster geometry, and temperature on the produced defect cluster forms. Our results suggest that the small clusters during the collision phase in MPEAs suppress the formation of large-sized defect clusters in the long term. Contrary to the common belief, a broader migration energy distribution due to chemical disorder cannot reduce the maximal defect cluster size but increase the proportion of small clusters. Our results thus reveal that the major role of chemical complexity in MPEAs is to modify the growth mechanism of clusters by promoting small cluster formation and suppressing overall defect diffusivities.

Multi-principal element alloys (MPEAs), including high entropy alloys, show exceptional mechanical properties and corrosion resistance. These unusual properties are mostly attributed to their particular diffusion behaviors, such as sluggish diffusion. However, this phenomenon is still controversial. Although state-of-the-art simulations report that the percolation effect plays a crucial role in triggering sluggish diffusion in binary alloys, whether this correlation could be generalized to a broad class of MPEAs is unknown. In this work, we combine machine learning (ML) with kinetic Monte Carlo (kMC) to accurately determine the diffusion coefficients in ternary CoCrNi MPEAs. Special care is taken to understand the effects of percolation on diffusion. We find that percolation does not always lead to sluggish diffusion. Instead, the diffusion properties are exclusively governed by the potential energy landscape (PEL) that the diffusing objects experience. By comparing the reduced systems of CoNi and FeNi, we reveal that the percolation effect on triggering the sluggish diffusion strongly depends on the diffusion properties of the slow-diffuser in these systems. These results shed light on the understanding of the complex diffusion behaviors in MPEAs, highlighting the importance of tunning species-dependent PEL in order to tailor their diffusion properties.

L-3-n-butylphthalide (NBP), which is used for treatment of mild and moderate acute ischemic stroke, exerts its effects by modulating the Nrf2 pathway. However, it has not been established whether NBP exerts its preventive effects in high-risk ischemic stroke patients through the Nrf2 pathway. We investigated whether NBP exerts its preventive effects through the Nrf2 pathway in long-term NBP pretreated dMCAO mice models. Nrf2+/+ wild-type and Nrf2−/− knockout mice were randomized into the vehicle group (equal volume vegetable oil), NBP-low-dose group (20 mg/kg) and NBP-high-dose group (60 mg/kg). The drug was administered once daily by gavage for a month. Then, a permanent distal middle cerebral artery occlusion model (dMCAO) was established after pretreatment with NBP. Neurological deficits, cerebral infarct volumes, brain water contents, activities of SOD, GSH-Px and MDA levels were determined. Further, axonal injury and demyelination, expression levels of Nrf2, HO-1 and NQO1 in ischemic brains were determined. Long-term NBP pretreatment significantly improved neurological functions, reduced cerebral infarction volumes, reduced brain water contents, increased SOD, GSH-Px activities, decreased MDA contents, reduced neurological injuries, axonal damage as well as demyelination, while increasing Nrf2, HO-1 and NQO1 mRNA as well as protein expressions in dMCAO mice models.

This work is concerned with the characterization of load-dependent dielectric loss and sensitivity analysis for CNT-based nanocomposite sensors (CNCSs) under AC loading. To this end, an electromechanically coupled microstructural theory is developed from the bottom up to quantitatively predict their overall dielectric loss change ratio and strain-sensitivity factor. In the theory, various categories of load-dependent functional interface effects, such as strain- and filler-dependent electron hopping and dielectric relaxation, are incorporated into it. The electric damage process under mechanical load is characterized through the principle of irreversible thermodynamics. The outcome is a microstructure-based coupled theory whose predictions of AC dielectric loss change ratio can be directly calibrated with the experimental data of MWCNT/PVDF nanocomposite sensor over a broad strain loading range from 0 to 10% and a wide frequency spectrum from 5 kHz to 500 kHz, where PVDF is a shape memory polymer. The theory further demonstrates the advantage of demarcating CNCSs via the dielectric loss over the traditional electric resistance. It can be used to rapidly determine the macroscopic dielectric loss change ratio by choosing a specific CNT volume concentration and AC working frequency, and further simplify the design procedure of highly sensitive strain sensors.