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The rapid expansion of distributed energy resources is heightening uncertainty and variability in distribution system operations, potentially leading to power quality challenges such as voltage magnitude violations and excessive voltage unbalance. Ensuring the dependable and secure operation of distribution grids requires system real-time assessment. However, constraints in sensing, measurement, and communication capabilities within distribution grids result in limited awareness of the system’s state. To achieve better real-time estimates of distribution system security, we propose a real-time security assessment based on data from smart meters, which are already prevalent in most distribution grids. Assuming that it is possible to obtain a limited number of voltage magnitude measurements in real time, we design an iterative algorithm to adaptively identify a subset of smart meters whose real-time measurements allow us to certify that all voltage magnitudes remain within bounds. This algorithm iterates between (i) solving optimization problems to determine the worst possible voltage magnitudes, given a limited set of voltage magnitude measurements, and (ii) leveraging the solutions and sensitivity information from these problems to update the measurement set. Numerical tests on the IEEE 123 bus distribution feeder demonstrate that the proposed algorithm consistently identifies and tracks the nodes with the highest and lowest voltage magnitude, even as the load changes over time. 

Molecules undergo a structural change to minimize the energy of excited states generated via external stimuli such as light. This is particularly problematic for Cu(I) coordination complexes which are an intriguing alternative to the rare and expensive transition metal containing complexes (e.g., Pt, Ir, Ru, etc.) but suffer from short excited state lifetimes due to D2d to D2 distortion and solvent coordination. Here we investigate strategic surface binding as an approach to hinder this distortion and increase the excited state lifetime of Cu(I) polypyridyl complexes. Using transient absorption spectroscopy, we observe a more than 20-fold increase in excited state lifetime, relative to solution, for a Cu(I) complex that can coordinate to the ZrO2 via both carboxylated ligands. In contrast, the Cu(I) complex that coordinates via only one ligand has a less pronounced enhancement upon surface binding and exhibits greater sensitivity to coordinating solvents. A combination of ATR-IR and polarized visible ATR measurements as well as theoretical calculations suggest that the increased lifetime is due to surface binding which decreases the degrees of freedom for molecular distortion (e.g., D2d to D2), with the doubly bound complex exhibiting the most pronounced enhancement. 

Abstract Plant traits can be helpful for understanding grassland ecosystem responses to climate extremes, such as severe drought. However, intercontinental comparisons of how drought affects plant functional traits and ecosystem functioning are rare. The Extreme Drought in Grasslands experiment (EDGE) was established across the major grassland types in East Asia and North America (six sites on each continent) to measure variability in grassland ecosystem sensitivity to extreme, prolonged drought. At all sites, we quantified community‐weighted mean functional composition and functional diversity of two leaf economic traits, specific leaf area and leaf nitrogen content, in response to drought. We found that experimental drought significantly increased community‐weighted means of specific leaf area and leaf nitrogen content at all North American sites and at the wetter East Asian sites, but drought decreased community‐weighted means of these traits at moderate to dry East Asian sites. Drought significantly decreased functional richness but increased functional evenness and dispersion at most East Asian and North American sites. Ecosystem drought sensitivity (percentage reduction in aboveground net primary productivity) positively correlated with community‐weighted means of specific leaf area and leaf nitrogen content and negatively correlated with functional diversity (i.e., richness) on an intercontinental scale, but results differed within regions. These findings highlight both broad generalities but also unique responses to drought of community‐weighted trait means as well as their functional diversity across grassland ecosystems.