Rapid detection of incipient foil failure and remediation for longevity in repetitively pulsed, electron-beam-pumped excimer lasers for fusion research.

The use of an electron beam to pump an excimer laser has the advantage of being readily scalable to higher laser energies at high efficiency. Typically, a pulsed power driver generates the electron beam in a vacuum diode that consists of an electron emitter and a thin anode foil that holds the vacuum against the atmospheric-pressure laser gas. Even a miniscule leak in the anode foil can lead to an electrical breakdown in the vacuum diode, resulting in the destruction of the foil and evidence of the failure mechanism.

RhizoNet segments plant roots to assess biomass and growth for enabling self-driving labs.

Flatbed scanners are commonly used for root analysis, but typical manual segmentation methods are time-consuming and prone to errors, especially in large-scale, multi-plant studies. Furthermore, the complex nature of root structures combined with noisy backgrounds in images complicates automated analysis. Addressing these challenges, this article introduces RhizoNet, a deep learning-based workflow to semantically segment plant root scans.

High precision control of laser energy for laser-matter interaction studies.

Precise, highly reproducible control of the laser energy is required for high confidence laser-matter interaction research such as in dynamic compression science and high energy density physics. The energy must be adjustable without affecting the pulse shape (time varying intensity) or beam smoothness. We have developed a convenient two-stage energy tuning method for a nominal 100 J, 351 nm (UV) laser.

The case for data science in experimental chemistry: examples and recommendations.

The physical sciences community is increasingly taking advantage of the possibilities offered by modern data science to solve problems in experimental chemistry and potentially to change the way we design, conduct and understand results from experiments. Successfully exploiting these opportunities involves considerable challenges. In this Expert Recommendation, we focus on experimental co-design and its importance to experimental chemistry.

Insights from high-fidelity modeling of industrial rotary bell atomization.

The global automotive industry sprayed over 2.6 billion liters of paint in 2018, much of which through electrostatic rotary bell atomization, a highly complex process involving the fluid mechanics of rapidly rotating thin films tearing apart into micrometer-thin filaments and droplets. Coating operations account for 65% of the energy usage in a typical automotive assembly plant, representing 10,000s of gigawatt-hours each year in the United States alone.