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1. The Q ₁ Q ₂ Q ₃ Workflow for Statistics and Data Science Collaborations

   https://doi.org/10.1080/26939169.2025.2475775  

   Vance, Eric A; Trumble, Ilana M; Alzen, Jessica L; House, Leanna L (May 2025, Journal of Statistics and Data Science Education)

   We develop, advance, and promote a previously existing framework called the Qualitative-Quantitative-Qualitative workflow (Q1Q2Q3, pronounced “Q-Q-Q”) to systematically guide the content of interdisciplinary collaborations and improve the teaching of statistics and data science. The Q1Q2Q3 workflow is designed to help statisticians and data scientists develop skills and techniques for collaboration to work with domain experts across academic fields, industry sectors, and organizations. The Q1Q2Q3 workflow explicitly emphasizes the importance of the qualitative context of a project, as well as the qualitative interpretation of quantitative findings. We explain Q1Q2Q3 and provide guidance for implementing each stage of the workflow. We describe how we teach Q1Q2Q3 within a statistics and data science collaboration course and present data evaluating its effectiveness. We also describe how Q1Q2Q3 can be useful for educators teaching introductory, projects-based, and technical statistics and data science courses. We believe that the Q1Q2Q3 workflow is an easy-to-implement technique that is beneficial and necessary for statistics and data science education and practice. It can be used to weave ethics into each stage of practice so that statisticians and data scientists can successfully transform evidence into action for the benefit of society. 

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2. Testing the predictive power of theory for Pd _x Ir _(100−x) alloy nanoparticles for the oxygen reduction reaction

   https://doi.org/10.1039/C9TA13711D  

   Guo, Hongyu; Trindell, Jamie A.; Li, Hao; Fernandez, Desiree; Humphrey, Simon M.; Henkelman, Graeme; Crooks, Richard M. (May 2020, Journal of Materials Chemistry A)

   In this report, density functional theory (DFT) calculations of O and OH binding energies on triatomic surface ensembles of Pd x Ir (100−x) nanoalloys successfully predicted the overall trend in experimental oxygen reduction reaction (ORR) activity as a function of nanoparticle (NP) composition. Specifically, triatomic Pd 3 ensembles were found to possess optimal O and OH binding energies and were predicted to be highly active sites for the ORR, rivaling that of Pt(111). However, DFT calculations suggest that the O binding energy increases at active sites containing Ir, thereby decreasing ORR activity. Pd x Ir (100−x) nanoalloys were synthesized using a microwave-assisted method and their activity towards the ORR was tested using rotating disk voltammetry (RDV). As predicted, the bimetallic electrocatalysts exhibited worse catalytic activity than the Pd-only NPs. The strong qualitative correlation between the theoretical and experimental results demonstrates that the activity of individual active sites on the surface of NPs can serve as a proxy for overall activity. This is a particularly useful strategy for applying DFT calculations to electrocatalysts that are too large for true first-principle analysis. 

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3. In ₂ Se ₃ Synthesized by the FWF Method for Neuromorphic Computing

   https://doi.org/10.1002/aelm.202400603  

   Shin, Jaeho; Jang, Jingon; Choi, Chi_Hun; Kim, Jaegyu; Eddy, Lucas; Scotland, Phelecia; Martin, Lane_W; Han, Yimo; Tour, James_M (November 2024, Advanced Electronic Materials)

   Abstract The development of next‐generation in‐memory and neuromorphic computing can be realized with memory transistors based on 2D ferroelectric semiconductors. Among these, In₂Se₃is the interesting since it possesses ferroelectricity in 2D quintuple layers. Synthesis of large amounts of In₂Se₃crystals with the desired phase, however, has not been previously achieved. Here, the gram‐scale synthesis of α‐In₂Se₃crystals using a flash‐within‐flash Joule heating method is demonstrated. This approach allows the synthesis of single‐phase α‐In₂Se₃crystals regardless of the conductance of precursors in the inner tube and enables the synthesis of gram‐scale quantities of α‐In₂Se₃crystals. Then, α‐In₂Se₃flakes are fabricated and used as a 2D ferroelectric semiconductor FET artificial synaptic device platform. By modulating the degree of polarization in α‐In₂Se₃flakes according to the gate electrical pulses, these devices exhibit distinct essential synaptic behaviors. Their synaptic performance shows excellent and robust reliability under repeated electrical pulses. Finally, it is demonstrated that the synaptic devices achieve an estimated learning accuracy of up to ≈87% for Modified National Institute of Standards and Technology patterns in a single‐layer neural network system. 

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4. Manipulating Atomic Structures at the Au/TiO ₂ Interface for O ₂ Activation

   https://doi.org/10.1021/jacs.9b13453  

   Huang, Jiawei; He, Shuai; Goodsell, Justin L.; Mulcahy, Justin R.; Guo, Wenxiao; Angerhofer, Alexander; Wei, Wei David (April 2020, Journal of the American Chemical Society)

   null (Ed.)
5. Dibridged, Monobridged, Vinylidene-Like, and Linear Structures for the Alkaline Earth Dihydrides Be ₂ H ₂ , Mg ₂ H ₂ , Ca ₂ H ₂ , Sr ₂ H ₂ , and Ba ₂ H ₂ . Proposals for Observations

   https://doi.org/10.1021/acs.inorgchem.0c01651  

   Narendrapurapu, Beulah S.; Bowman, Michael C.; Xie, Yaoming; Schaefer, Henry F.; Tkachenko, Nikolay V.; Boldyrev, Alexander I.; Li, Guoliang (August 2020, Inorganic Chemistry)