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1. Green light to a green arylation

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   Hossain, Md Mubarak; Gianetti, Thomas L. (July 2022, Trends in Chemistry)
2. From Green to Green: The Environmentalization of Agriculture

   https://doi.org/10.1002/nad.12105  

   Cattelino, Jessica R. (October 2019, Journal for the Anthropology of North America)
3. Galaxy of Green

   https://doi.org/10.2138/gselements.19.3.173  

   First, Emily C; Kremer, Christopher; Telus, Myriam; Trang, David (June 2023, Elements)

   Olivine occurs across the galaxy, from Earth to extraterrestrial bodies including the Moon, Mars, and asteroids, to particles of comet dust and distant debris disks. The mineral is critical to our understanding of early Solar System chronology, planetary formation processes (e.g., magma ocean solidification), crustal evolution (e.g., volcanic eruptions), and surface weathering. Olivine’s ability to shed light on these processes lies in the linkage of small, physical samples and satellite-derived data. Laboratory spectra become the basis for olivine detection and compositional interpretation in remotely sensed spectra ranging from high-resolution planetary maps to single extra-solar datapoints. In turn, petrologic studies of olivine underpin the geologic interpretations of these spectral datasets. Finally, olivine chemistry records Solar System formation conditions and relative chronology. Olivine is our bridge across time and space. 

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4. Green multigrid network

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5. Green Bin Packing

   https://doi.org/10.1145/3788093  

   Bibbens, Jackson; Sigrist, Cooper; Sun, Bo; Kamali, Shahin; Hajiesmaili, Mohammad (March 2026, Proceedings of the ACM on Measurement and Analysis of Computing Systems)

   The online bin packing problem and its variants are regularly used to model server allocation problems. Modern concerns surrounding sustainability and overcommitment in cloud computing motivate bin packing models that capture costs associated with highly utilized servers. In this work, we introduce thegreen bin packingproblem, an online variant with a linear cost β for filling above a fixed levelG. For a given instance, the goal is to minimize the sum of the number of opened bins and the linear cost. We show that when β ≤ 1/G, classical online bin packing algorithms such as FirstFit or Harmonic perform well, and can achieve competitive ratios lower than in the classic setting. However, when β > 1/G, new algorithmic solutions can improve both worst-case and typical performance. We introduce variants of classic online bin packing algorithms and establish theoretical bounds, as well as test their empirical performance. 

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