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HoTl is Tetraauricupride structured and crystallizes in the cubic Pm-3m space group. The structure is three-dimensional. Ho is bonded in a body-centered cubic geometry to eight equivalent Tl atoms. All Ho–Tl bond lengths are 3.28 Å. Tl is bonded in a body-centered cubic geometry to eight equivalent Ho atoms.
HoTl(WO4)2 crystallizes in the monoclinic C2/c space group. The structure is three-dimensional. Ho3+ is bonded in a 6-coordinate geometry to six O2- atoms. There are a spread of Ho–O bond distances ranging from 2.27–2.32 Å. W6+ is bonded to six O2- atoms to form a mixture of corner and edge-sharing WO6 octahedra. The corner-sharing octahedral tilt angles are 44°. There are a spread of W–O bond distances ranging from 1.83–2.14 Å. Tl1+ is bonded in a 10-coordinate geometry to ten O2- atoms. There are a spread of Tl–O bond distances ranging from 2.88–3.14 Å. There are four inequivalent O2- sites. In the first O2- site, O2- is bonded in a 4-coordinate geometry to two equivalent W6+ and two equivalent Tl1+ atoms. In the second O2- site, O2- is bonded in a 2-coordinate geometry to one Ho3+, one W6+, and one Tl1+ atom. In the third O2- site, O2- is bonded in a 3-coordinate geometry to one Ho3+, two equivalent W6+, and one Tl1+ atom. In the fourth O2- site, O2- is bonded in a distorted bent 150 degrees geometry to one Ho3+, one W6+, and one Tl1+ atom.
This report examines the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on operations research, private industry, and government sectors, highlighting their applications in automating processes, enhancing decision-making, and optimizing complex systems. AI/ML technologies have revolutionized industries through predictive maintenance, supply chain optimization, and autonomous systems, while also advancing public safety and defense operations. However, challenges such as data integrity, model transparency, and the need for human oversight persist, particularly in high-consequence environments. The report emphasizes the critical role of explainable AI (XAI) and human-computer interaction models like Human-in-the-Loop (HITL) and Human-on-the-Loop (HOTL) in fostering trust and accountability. Balancing automation with ethical responsibility and transparency is essential for the continued successful integration of AI/ML into operational and strategic decision-making frameworks.
The purpose of this project is to estimate the demand for various Urban Air Mobility Concepts (UAM) of Operations and to generate scenarios for use in analysis and simulations. The demand forecast model, previously developed under NASA/NIA Contract No: NNL13AA08B; Task Order No: NNL16AA36T, for an urban on-demand air-taxi commuter concept is the basis for this work.