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This study explores the effect of heat treatment on the microstructural characteristics and corrosion resistance of 316L stainless steels (SSs) produced via laser powder bed fusion (L-PBF), focusing on anisotropic corrosion behavior—a relatively less explored phenomenon in LPBF 316L SSs. By systematically analyzing the effects of varying heat treatment temperatures (500 °C, 750 °C, and 1000 °C), this work uncovers critical correlations between microstructural evolution and corrosion properties. The findings include the identification of anisotropic corrosion resistance between horizontal (XY) and vertical (XZ) planes, with the vertical plane demonstrating higher pitting and repassivation potentials but greater post-repassivation current densities. Furthermore, this study highlights reductions in grain size, dislocation density, and melt pool boundaries with increasing heat treatment temperatures, which collectively diminishes corrosion resistance. These insights advance the understanding of processing–structure–property relationships in additively manufactured metals, providing practical guidelines for optimizing thermal post-processing to enhance material performance in corrosive environments. 

The 70/30 copper–nickel alloy is used mainly in critical parts with more demanding conditions in marine settings. There is a need for innovative methods that offer fast production and cost-effectiveness in order to supplement current copper–nickel alloy manufacturing processes. In this study, we employ wire arc additive manufacturing (WAAM) to fabricate the 70/30 copper–nickel alloy. The as-built microstructure is characterized by columnar grains with prominent dendrites and chemical segregation in the inter-dendritic area. The aspect ratio of the columnar grain increases with increasing travel speed (TS) at the same wire feed speed (WFS). This is in contrast with the equiaxed grain structure, with a more random orientation, of the conventional sample. The sample built with a WFS of 8 m/min, TS of 1000 mm/min, and a track distance of 3.85 mm exhibits superior corrosion properties in the 3.5 wt% NaCl solution when compared with the conventional sample, as evidenced by a higher film resistance and breakdown potential, along with a lower passive current density of the WAAM sample. The corrosion morphology reveals the critical roles played by the nickel element that is unevenly distributed between the dendrite core and inter-dendritic area. 

Abstract Wire-arc directed energy deposition (DED) processed Inconel (IN) 718 is known to have coarse columnar grains, strong texture, and significant chemical and microstructural inhomogeneity in the as-fabricated condition. Homogenization treatment is commonly used prior to aging to eliminate the inhomogeneity and detrimental precipitation for better mechanical properties. In this study, however, direct aging (DA) at 700 °C without homogenization has resulted in room-temperature yield strength, ultimate tensile strength (UTS), and elongation that are comparable to wrought condition and among the highest reported properties for wire-arc DED IN718. The DA samples at between 650 and 750 °C aging also demonstrates remarkable ductility when deformed at elevated temperatures. In addition, when aged below 750 °C the DA IN718 possesses significantly higher UTS compared to those with homogenization treatment. These superior mechanical properties are highly likely due to the non-uniform and hierarchical precipitation consisting of disk-shaped γ″ in diameter from a few to tens of nm in the dendritic core area and micron-sized Laves phase and carbides in the inter-dendritic region. 

Abstract A multiphysics phase field framework for coupled electrochemical and elastoplastic behaviors is presented, where the evolution of complex solid-electrolyte is described by the variation of the phase field variable with time. The solid-electrolyte interface kinetics nonlinearly depends on the thermodynamic driving force and can be accelerated by mechanical straining according to the film rupture-dissolution mechanism. A number of examples in two- and three- dimensions are demonstrated based on the finite element-based MOOSE framework. The model successfully captures the pit-to-crack transition under simultaneous electrochemical and mechanical effects. The crack initiation and growth has been demonstrated to depend on a variety of materials properties. The coupled corrosion and crystal plasticity framework also predict the crack initiation away from the perpendicular to the loading direction. 

Statistical analysis is a crucial component of many data science analytic pipelines, and preparing data for such analysis is a large part of the data ingestion step. This task is generally accomplished by writing transformation scripts in languages such as SPSS, Stata, SAS, R, Python (Pandas) etc. The disparate data models, language representations and transformation operations supported by these tools make it hard for end users to understand and document the transformations performed, and for developers to port transformation code across languages. Tackling these challenges, we present a formal paradigm for statistical data transformation called SDTA and embody in a language called SDTL. Experiments with real statistical transformations on socio-economic data show that SDTL can successfully represent 86.1% and 91.6% respectively of 4,185 commands in SAS and 9,087 commands in SPSS obtained from a repository. We illustrate how SDTA/SDTL could assist with the documentation of statistical data transformation, an important aspect often neglected in metadata of datasets. We propose a system called C2Metadata that automatically captures the transformation and provenance information in SDTL as a part of the metadata. Moreover, given the conversion mechanism from a source statistical language to SDTA/SDTL, we show how a data transformation program could be converted to other functionally equivalent programs, permitting code reuse and result reproducibility. We also illustrate the possibility of using SDTA to optimize SDTL transformations using rule-based rewrites similar to SQL optimizations. 

Agriculture’s global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture’s environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil erosion, accelerating the growth and expanding the range of crop diseases and pests, and increasing land clearing. We identify multiple pathways through which climate change intensifies agricultural greenhouse gas emissions, creating a potentially powerful climate change–reinforcing feedback loop. The challenges raised by climate change underscore the urgent need to transition to sustainable, climate-resilient agricultural systems. This requires investments that both accelerate adoption of proven solutions that provide multiple benefits, and that discover and scale new beneficial processes and food products.