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A Cold Atmospheric Plasma (CAP) apparatus was designed and developed for SARS-CoV-2 killing as evaluated by pseudotyped viral infectivity assays. The reactive species generated by the plasma system was fully characterized by using Optical Emission Spectroscopy (OES) measurement under given conditions such as plasma power, flow rate, and treatment time. A variety of reactive oxygen species (ROS) and reactive nitrogen species (RNS) were identified from plasma plume with energies of 15–72 eV in the frequency range between 500–1000 nm. Systematic virus killing experiments were carried out, and the efficacy of CAP treatment in reducing SARS-CoV-2 viral infectivity was significant following treatment for 8 s, with further enhancement of killing upon longer exposures of 15–120 s. We correlated killing efficacy with the reactive species in terms of type, intensity, energy, and frequency. These experimental results demonstrate effective cold plasma virus killing via ROS and RNS under ambient conditions. 

Molecular dynamics (MD) simulations are invoked to simulate the diffusion process and microstructural evolution at the solid–liquid, cast-rolled Al–Cu interfaces. K-Means clustering algorithm is used to identify the formation and composition of two types of nanostructural features in the Al-rich and Cu-rich regions of the interface (i.e., the intermetallic Al2Cu near the Al-rich interface and the intermetallic Al4Cu9 near the Cu-rich interface). MD simulations are also used to assess the effects of annealing temperature on the evolution of the compositionally graded microstructural features at the Al–Cu interfaces and to characterize the mechanical strength of the Al–Cu interfaces. It is found that the failure of the Al–Cu interface takes place at the Al-rich side of the interface (Al2Cu–Al) which is mechanically weaker than the Cu-rich side of the interface (Cu–Al4Cu9), which is also verified by the nanoindentation studies of the interfaces. Centrosymmetry parameter analyses and dislocation analyses are used to understand the microstructural features that influence deformation behavior leading to the failure of the Al–Cu interfaces. Increasing the annealing temperature reduces the stacking fault density at the Al–Cu interface, suppresses the generation of nanovoids which are precursors for the initiation of fracture at the Al-rich interface, and increases the strength of the interface. 

In practice, differentially private data releases are designed to support a variety of applications. A data release is fit for use if it meets target accuracy requirements for each application. In this paper, we consider the problem of answering linear queries under differential privacy subject to per-query accuracy constraints. Existing practical frameworks like the matrix mechanism do not provide such fine-grained control (they optimize total error, which allows some query answers to be more accurate than necessary, at the expense of other queries that become no longer useful). Thus, we design a fitness-for-use strategy that adds privacy-preserving Gaussian noise to query answers. The covariance structure of the noise is optimized to meet the fine-grained accuracy requirements while minimizing the cost to privacy.