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: Develop physics-based, data-driven, and hybrid (physics-informed ML) models of thermal systems to capture dynamic thermal behavior Validate models against experimental data and refine model accuracy and
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responses to warming, drought, and elevated CO2 (e.g., gas exchange, fluorescence, hydraulics, respiration, water potential, thermal tolerance) Trait synthesis at scale (e.g., using trait databases TRY, FRED
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architectural models, system-level simulators, and performance modeling frameworks for QHPC systems, capturing relevant characteristics of quantum processing units, classical HPC resources, interconnects, system
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materials. These systems are instrumented and connected through a unified digital thread platform that captures multimodal, high-frequency data across the full manufacturing lifecycle, from process execution