The workshop’s third panel, moderated by planning committee member Teresa Clement, Raytheon, dealt with post-additive processes, with a specific focus on dimensional accuracy, part quality, and ...

This workshop will explore opportunities to use statistical and data-driven methods for additive manufacturing qualification, including approaches that enhance dimensional accuracy and recent advances ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Demonstrating the applicability of αη across a diverse range of systems. These include a canonical dynamical system (Rössler attractor), simulation data for slow earthquakes (spring-slider system), a ...

Synthetic data generation has emerged as a crucial technique for addressing various challenges, including data privacy, scarcity and bias. By creating artificial data that mimics real-world datasets, ...

All humans need clean water to live. However, purifying water can be energy-intensive, so there is great interest in improving this process. Researchers at Tohoku University have reported a strategy ...

Researchers tested a strategy for developing single-atom catalysts that may help us develop more efficient methods for water purification. All humans need clean water to live. However, purifying water ...

Data-driven science represents a transformative paradigm in materials science. Both data-driven materials science and informatics encompass systematic knowledge extraction from materials datasets.

As the demand for faster and more affordable mobile connectivity grows, so does the challenge of ensuring that networks can keep up – both in performance and profitability. A new technical paper ...