Predictive capabilities for laser machining via a neural network.

The interaction between light and matter during laser machining is particularly challenging to model via analytical approaches. Here, we show the application of a statistical approach that constructs a model of the machining process directly from experimental images of the laser machined sample, and hence negating the need for understanding the underlying physical processes. Specifically, we use a neural network to transform a laser spatial intensity profile into an equivalent scanning electron microscope image of the laser-machined target. This approach enables the simulated visualization of the result of laser machining with any laser spatial intensity profile, and hence demonstrates predictive capabilities for laser machining. The trained neural network was found to have encoded functionality that was consistent with the laws of diffraction, hence showing the potential of this approach for discovering physical laws directly from experimental data.

Ultrafast multi-layer subtractive patterning.

Subtractive femtosecond laser machining using multiple pulses with different spatial intensity profiles centred on the same position on a sample has been used to fabricate surface relief structuring. A digital micromirror device was used as an intensity spatial light modulator, with a fixed position relative to the sample, to ensure optimal alignment between successive masks. Up to 50 distinct layers, 335 nm lateral spatial resolution and 2.6 µm maximum depth structures were produced. The lateral dimensions of the structures are approximately 40 µm. Surface relief structuring is shown to match intended depth profiles in a nickel substrate, and highly repeatable stitching of identical features in close proximity is also demonstrated.

Real-time particle pollution sensing using machine learning.

Particle pollution is a global health challenge that is linked to around three million premature deaths per year. There is therefore great interest in the development of sensors capable of precisely quantifying both the number and type of particles. Here, we demonstrate an approach that leverages machine learning in order to identify particulates directly from their scattering patterns. We show the capability for producing a 2D sample map of spherical particles present on a coverslip, and also demonstrate real-time identification of a range of particles including those from diesel combustion.

Single-pulse ablation of multi-depth structures via spatially filtered binary intensity masks.

Digital micromirror devices (DMDs) show great promise for use as intensity spatial light modulators. When used in conjunction with pulsed lasers of a timescale below the DMD pixel switching time, DMDs are generally only used as binary intensity masks (i.e., "on" or "off" intensity for each mask pixel). In this work, we show that by exploiting the numerical aperture of an optical system during the design of binary masks, near-continuous intensity control can be accessed, whilst still maintaining high-precision laser-machining resolution. Complex features with ablation depths up to ∼60 nm, corresponding to grayscale values in bitmap images, are produced in single pulses via ablation with 150 fs laser pulses on nickel substrates, with lateral resolutions of ∼2.5 µm.

Sub-diffraction limit laser ablation via multiple exposures using a digital micromirror device.

We present the use of digital micromirror devices as variable illumination masks for pitch-splitting multiple exposures to laser machine the surfaces of materials. Ultrafast laser pulses of length 150 fs and 800 nm central wavelength were used for the sequential machining of contiguous patterns on the surface of samples in order to build up complex structures with sub-diffraction limit features. Machined patterns of tens to hundreds of micrometers in lateral dimensions with feature separations as low as 270 nm were produced in electroless nickel on an optical setup diffraction limited to 727 nm, showing a reduction factor below the Abbe diffraction limit of ∼2.7×. This was compared to similar patterns in a photoresist optimized for two-photon absorption, which showed a reduction factor of only 2×, demonstrating that multiple exposures via ablation can produce a greater resolution enhancement than via two-photon polymerization.

Rapid bespoke laser ablation of variable period grating structures using a digital micromirror device for multi-colored surface images.

A digital micromirror device has been used to project variable-period grating patterns at high values of demagnification for direct laser ablation on planar surfaces. Femtosecond laser pulses of ∼1 mJ pulse energy at 800 nm wavelength from a Ti:sapphire laser were used to machine complex patterns with areas of up to ∼1 cm2 on thin films of bismuth telluride by dynamically modifying the grating period as the sample was translated beneath the imaged laser pulses. Individual ∼30 by 30 µm gratings were stitched together to form contiguous structures, which had diffractive effects clearly visible to the naked eye. This technique may have applications in marking, coding, and security features.