TS-072175 — The Need Modern industrial and energy systems are increasingly complex, making timely fault detection and discrimination critical for safety, reliability, and cost control. Existing fault diagnosis methods often struggle with transient states, require extensive historical data, or lack interpretabil…

TS-071386 — The Need The search for sustainable, high-performance battery materials is hindered by reliance on finite metal-based resources and slow, trial-and-error development cycles. Organic electrode materials (OEMs), composed of earth-abundant elements, offer a more sustainable path but present challenges …

TS-071385 — The Need Open source software is foundational to modern development, yet it introduces significant security risks due to outdated dependencies and inaccurate vulnerability advisories. Public databases often fail to identify all affected versions of software, leaving organizations exposed. With vulne…

TS-071267 — The Need Modeling solvent effects on catalytic surfaces is critical for designing industrial processes like biomass conversion, fuel synthesis, and electrocatalysis. Traditional multiscale simulations combining density functional theory (DFT) and molecular dynamics (MD) offer accuracy but are comp…

TS-070971 — The Need Modern gas turbines and compressors rely on bladed disks, which are highly sensitive to mistuning caused by manufacturing tolerances, wear, or damage. Existing modeling tools are fragmented, complex, and often limited to specific mistuning types. Industry will greatly benefit from a unified…

TS-070954 — The Need Intersections are among the most dangerous areas on U.S. roadways, accounting for approximately 25% of traffic fatalities and nearly half of all injuries annually. Vulnerable Road Users (VRUs), including pedestrians and cyclists, face increasing risk due to complex traffic dynamics and limi…

TS-069654 — Technology bundle containing T2025-148 and T2024-150.

TS-069523 — The Need In many scientific and industrial fields, there is a critical need for interpretable and accurate models that can be derived from complex datasets. Traditional machine learning methods often produce black-box models that lack transparency and interpretability, making it difficult to unders…

TS-068440 — Accurate measurement of physical attributes, such as dimensions, alignments, and surface features, is essential for ensuring quality and consistency across industries. Traditional measurement methods, often reliant on manual tools and human oversight, are time-intensive, prone to errors, and lac…

TS-067792 — A software tool for optimizing the manufacturing process for metal alloys.