We overview recent developments of 3D${}^{\pm }$ (additive/subtractive) manufacturing/printing from the point of view of laser development, beam delivery tools, applications, and materials. The average power of ultra-short-pulsed lasers has followed a Moore’s scaling trajectory, doubling every two years, for the past 20 years. This requires fast beam scanning solutions and beam delivery control for larger-area applications. New material synthesis with high spatial resolution is provided at the high intensity TW/cm${}^2$-PW/cm${}^2$ exposure site. Net-shape manufacturing with a reduced number of post-processing steps is a practical trait of 3D${}^{\pm }$ printing. With computer numerical control (CNC) optimised using artificial intelligence (AI), the future of 3D${}^{\pm }$ manufacturing is discussed.

Pattern recognition techniques form the heart of most, if not all, incoherent linear shift-invariant systems. When an object is recorded using a camera, the object information is sampled by the point spread function (PSF) of the system, replacing every object point with the PSF in the sensor. The PSF is a sharp Kronecker Delta-like function when the numerical aperture (NA) is large with no aberrations. When the NA is small, and the system has aberrations, the PSF appears blurred. In the case of aberrations, if the PSF is known, then the blurred object image can be deblurred by scanning the PSF over the recorded object intensity pattern and looking for pattern matching conditions through a mathematical process called correlation. Deep learning-based image classification for computer vision applications gained attention in recent years. The classification probability is highly dependent on the quality of images as even a minor blur can significantly alter the image classification results. In this study, a recently developed deblurring method, the Lucy-Richardson-Rosen algorithm (LR²A), was implemented to computationally refocus images recorded in the presence of spatio-spectral aberrations. The performance of LR²A was compared against the parent techniques: Lucy-Richardson algorithm and non-linear reconstruction. LR²A exhibited a superior deblurring capability even in extreme cases of spatio-spectral aberrations. Experimental results of deblurring a picture recorded using high-resolution smartphone cameras are presented. LR²A was implemented to significantly improve the performances of the widely used deep convolutional neural networks for image classification.

The controlled deposition of CoCrFeNiMo${}_{0.2}$ high-entropy alloy (HEA) microparticles was achieved by using laser-induced forward transfer (LIFT). Ultra-short laser pulses of 230 fs of 515 nm wavelength were tightly focused into ∼2.4 μm focal spots on the ∼50-nm thick plasma-sputtered films of CoCrFeNiMo${}_{0.2}$. The morphology of HEA microparticles can be controlled at different fluences. The HEA films were transferred onto glass substrates by magnetron sputtering in a vacuum (${10}^{-8}$ atm) from the thermal spray-coated substrates. The absorption coefficient of CoCrFeNiMo${}_{0.2}$$\alpha \approx 6\times {10}^5$ cm${}^{-1}$ was determined at 600-nm wavelength. The real and imaginary parts of the refractive index $(n+i\kappa )$ of HEA were determined from reflectance and transmittance by using nanofilms.

Axial resolution is one of the most important characteristics of a microscope. In all microscopes, a high axial resolution is desired in order to discriminate information efficiently along the longitudinal direction. However, when studying thick samples that do not contain laterally overlapping information, a low axial resolution is desirable, as information from multiple planes can be recorded simultaneously from a single camera shot instead of plane-by-plane mechanical refocusing. In this study, we increased the focal depth of an infrared microscope non-invasively by introducing a binary axicon fabricated on a barium fluoride substrate close to the sample. Preliminary results of imaging the thick and sparse silk fibers showed an improved focal depth with a slight decrease in lateral resolution and an increase in background noise.

Ultra-short 230 fs laser pulses of 515 nm wavelength were tightly focused into 700 nm focal spots and utilised in opening ∼400 nm nano-holes in a Cr etch mask that was tens-of-nm thick. The ablation threshold was found to be 2.3 nJ/pulse, double that of plain silicon. Nano-holes irradiated with pulse energies below this threshold produced nano-disks, while higher energies produced nano-rings. Both these structures were not removed by either Cr or Si etch solutions. Subtle sub-1 nJ pulse energy control was harnessed to pattern large surface areas with controlled nano-alloying of Si and Cr. This work demonstrates vacuum-free large area patterning of nanolayers by alloying them at distinct locations with sub-diffraction resolution. Such metal masks with nano-hole opening can be used for formation of random patterns of nano-needles with sub-100 nm separation when applied to dry etching of Si.

Polarisation analysis in the mid-infrared fingerprint region was carried out on thin (∼1 $\mathsf{\mu }$m) Si and SiO₂ films evaporated via glancing angle deposition (GLAD) method at ${70}^{\circ }$ to the normal. Synchrotron-based infrared microspectroscopic measurements were carried out on the Infrared Microspectroscopy (IRM) beamline at Australian Synchrotron. Specific absorption bands, particularly Si-O-Si stretching vibration, was found to follow the angular dependence of ∼${cos}^2\theta$, consistent with the absorption anisotropy. This unexpected anisotropy stems from the enhanced absorption in nano-crevices, which have orientation following the ${cos}^2\theta$ angular dependence as revealed by Fourier transforming the image of the surface of 3D columnar films and numerical modeling of light field enhancement by sub-wavelength nano-crevices.