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Additively manufactured 316L stainless steels (316L SS) using laser powder bed fusion technique (L-PBF) exhibit an excellent combination of high strength and ductility compared to the conventional counterpart. The outstanding material mechanical properties originate from the sub-grain cellular structures developed during the rapid solidification inherent to L-PBF. These structures consist of elongated cells decorated by high density of dislocations, trapped solute, and fine precipitates at their boundaries. The impact of such cellular structures on corrosion resistances, however, remains incompletely understood. In addition, the L-PBF process leads to high surface roughness and usually around 0.1 to 0.5% of porosity. However, the pitting potential of the L-PBF 316L SS can be an order of magnitude higher than the conventional, well annealed counterpart. In this talk, we will first present a detailed multi-scale characterization of the microstructural features unique to L-PBF 316L SS. In a second part, we will present our experimental-simulation integration approach where we combine surface chemistry mapping and electron and atomic force microscopy with multi-scale simulations to understand the effect of local microstructure variations on pitting and metal dissolution rates in NaCl and HCl environments. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. Authors acknowledge the support of the Laboratory Directed Research and Development (LDRD) program (20-SI-004) at LLNL.

Surfaces of additively manufactured (AM) stainless steel (SS) by fusing metallic powders are known to be much rougher than those produced by conventionally fabrication methods. The measured surface roughness (Sa or Sq) can range from a few to tens of microns depending on the build angle. Recent studies have shown that the large surface roughness associated with printing conditions makes the AM SS surfaces susceptible to localized corrosion and open-circuit corrosion [1, 2]. Sa or Sq have also long been used to characterize the corrosion behavior of traditionally manufactured metals [3]. However, the open-circuit corrosion rate of the traditional metals has been mainly studied in the submicron-scale surface roughness, and some results have showed that changes in the roughness of hundreds of nanometers or more have little effect on the change in the corrosion rate [4]. In addition, when applied to AM materials, no consistent correlation between the pitting breakdown potential (Eb) and surface roughness has been observed. In this study, the dependence of the corrosion behavior on the electrochemically active surface area of AM 316L SS, defined as the total area of the curvilinear surface that is exposed to the electrolyte, has been explored. The localized corrosion susceptibility was evaluated under full immersion in 3.5 wt% NaCl solution through potentiodynamic polarization for testing articles with different surface roughness. While no correlation to Sa or Sq was displayed, the Eb values showed a clear statistical trend with respect to the electrochemically active surface area: the lager the active surface area, the smaller the Eb. The observed correlation fits well with a previously reported stochastic pitting model on metal surfaces [5]. In addition, by normalizing linear polarization resistance and electrochemical impedance spectra with the electrochemically active surface area, it can be confirmed that the as-printed surface roughness of AM 316L SS did not have a significant effect on the change of the open-circuit corrosion phenomenon under static immersion conditions. Our results suggest that electrochemically active surface area is an appropriate parameter to characterize the corrosion behavior of AM metal surfaces. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. References 1. Melia, M.A., et al., How build angle and post-processing impact roughness and corrosion of additively manufactured 316L stainless steel. Npj Materials Degradation, 2020. 4(1). 2. Ni, C., Y. Shi, and J. Liu, Effects of inclination angle on surface roughness and corrosion properties of selective laser melted 316L stainless steel. Materials Research Express, 2019. 6(3). 3. Walter, R. and M.B. Kannan, Influence of surface roughness on the corrosion behaviour of magnesium alloy. Materials & Design, 2011. 32(4): p. 2350-2354. 4. Li, W. and D.Y. Li, Influence of surface morphology on corrosion and electronic behavior. Acta Materialia, 2006. 54(2): p. 445-452. 5. Shibata, T., 1996 W R Whitney Award lecture: Statistical and stochastic approaches to localized corrosion. Corrosion, 1996. 52(11): p. 813-830.

Understanding dissolution kinetics is essential for predicting and mitigating materials corrosion; however, many mechanistic details still remain enigmatic. Examples include the evolution of solvation properties of ions and nature of electron transfer during dissolution. In this work, we integrate high-fidelity first-principles calculations based on grand-canonical density functional theory (DFT) and mesoscale simulations to predict dissolution kinetics of aluminum metal in acidic conditions. First, we show that the inclusion of an explicit solvation shell is crucial for accurately predicting the redox potential of metal dissolution. Second, we show that metal dissolution is governed by two kinetically limited processes, which are associated with the metal-metal bond breaking and ion diffusion within the electric double layer. Interestingly, it is found that kinetics and thermodynamics of these processes can be described with a simple model functionally based on Marcus theory, and their relative importance can be switched, depending on the applied potentials. Third, we show how dissolution kinetics derived from DFT is integrated with mesoscale simulations to elucidate the role of microstructure on the global metal dissolution. Comparison with experimental measurements will also be discussed. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was supported with Laboratory Directed Research and Development funding under Project 20-SI-004.

Flexible electronic skin with features that include sensing, processing, and responding to stimuli have transformed human-robot interactions. However, more advanced capabilities, such as human-like self-protection modalities with a sense of pain, sign of injury, and healing, are more challenging. Herein, a novel, flexible, and robust diffusive memristor based on a copolymer of chlorotrifluoroethylene and vinylidene fluoride (FK-800) as an artificial nociceptor (pain sensor) is reported. Devices composed of Ag/FK-800/Pt have outstanding switching endurance10

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