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3D-printed digital materials whose mechanical behavior travels between those from thermoplastic to rubbery polymers have become increasingly important. However, their mechanical functionalities have not been fully exploited due to intrinsic…
Advancements in theoretical and algorithmic approaches, workflow engines, and an ever-increasing computational power have enabled a novel paradigm for materials discovery through first-principles high-throughput simulations. A major…
Displacement sensing is a fundamental task in metrology. However, the development of quantum-enhanced sensors that fully utilize the available degrees of freedom in many-body quantum systems remains an outstanding challenge. We propose…
The transient response of model hard sphere glasses is examined during the application of steady rate start-up shear using Brownian Dynamics (BD) simulations, experimental rheology and confocal microscopy. With increasing strain the glass…
Finite element models of the thorax are under development to assist vehicle safety researchers with the design of countermeasures such as advanced restrain systems. Computational models have become more refined with increasing geometrical…
Extensive research has been performed on continuous, non-invasive, cuffless blood pressure (BP) measurement using artificial intelligence algorithms. This approach involves extracting certain features from physiological signals like ECG,…
Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that machine learning, combined with multi-labeled datasets, can…
High throughput screening of compounds (chemicals) is an essential part of drug discovery [7], involving thousands to millions of compounds, with the purpose of identifying candidate hits. Most statistical tools, including the industry…
The first experiments in dynamic rotational diamond anvil cell (dRDAC) on severe plastic deformation (SPD) and BCC<->HCP phase transformation (PT) at pressure up to 27.6 GPa, rotation rates up to 1,500 RPM, and strain rates up to 2,094 /s…
Mechanical vibrations in buildings are ubiquitous. Such vibrations limit the performance of sensitive instruments used, for example, for high-precision manufacturing, nanofabrication, metrology, medical systems, or microscopy. For improved…
Shock compression plate impact experiments conventionally rely on point-wise velocimetry measurements based on laser-based interferometric techniques. This study presents an experimental methodology to measure the free surface full-field…
The increasing demand for accelerated scientific discovery, driven by global challenges, highlights the need for advanced AI-driven robotics. Deploying robotic chemists in human-centric labs is key for the next horizon of autonomous…
Characterising materials at pressures of several megabar and temperatures of a few thousand Kelvin is critical for the understanding of the Warm Dense Matter regime and to improve planetary models as these conditions are typical of planets'…
Hierarchical Bayesian Poisson regression models (HBPRMs) provide a flexible modeling approach of the relationship between predictors and count response variables. The applications of HBPRMs to large-scale datasets require efficient…
Deciding how to optimally deploy sensors in a large, complex, and spatially extended structure is critical to ensure that the surface pressure field is accurately captured for subsequent analysis and design. In some cases, reconstruction of…
The presented study aims to estimate blood pressure (BP) using photoplethysmogram (PPG) signals while employing multiple machine learning models. The study proposes a novel algorithm for signal reconstruction, which utilizes the…
This paper describes the automation of a laser heating arrangement for synthesizing and studying materials at high pressures (up to ~ 1 Mbar) and high temperatures (up to ~ 5000 K). In this arrangement, a diamond anvil high-pressure cell…
Cold spraying is an increasingly common approach for repairing and manufacturing components due to its solid-state manufacturing capabilities. However, process optimization remains difficult due to many interdependent parameters and the…
The Swift test was originally proposed as a formability test to reproduce the conditions observed in deep drawing operations. This test consists on forming a cylindrical cup from a circular blank, using a flat bottom cylindrical punch and…
Modern compression algorithms exploit complex structures that are present in signals to describe them very efficiently. On the other hand, the field of compressed sensing is built upon the observation that "structured" signals can be…