Single-frame 3D lensless microscopic imaging via deep learning.

Since the pollen of different species varies in shape and size, visualizing the 3-dimensional structure of a pollen grain can aid in its characterization. Lensless sensing is useful for reducing both optics footprint and cost, while the capability to image pollen grains in 3-dimensions using such a technique could be truly disruptive in the palynology, bioaerosol sensing, and ecology sectors. Here, we show the ability to employ deep learning to generate 3-dimensional images of pollen grains using a series of 2-dimensional images created from 2-dimensional scattering patterns.

Motion control for laser machining via reinforcement learning.

Laser processing techniques such as laser machining, marking, cutting, welding, polishing and sintering have become important tools in modern manufacturing. A key step in these processes is to take the intended design and convert it into coordinates or toolpaths that are useable by the motion control hardware and result in efficient processing with a sufficiently high quality of finish. Toolpath design can require considerable amounts of skilled manual labor even when assisted by proprietary software.

A light-guiding urinary catheter for the inhibition of biofilm formation.

Catheter-associated urinary tract infection (CAUTI) is a leading cause of hospital-acquired infections worldwide causing debilitating illness for patients as well as a significant financial and treatment burden on health services. CAUTI is linked with the build-up of biofilms on catheter surfaces which act as a reservoir for infection. Additionally, urease-producing bacteria such as Gram-negative (), can form crystalline biofilms which encrust catheter surfaces ultimately leading to blockages which require immediate removal of the catheter.

Optimization of flow path parameters for enhanced sensitivity lateral flow devices.

Lateral flow devices (LFDs) or lateral flow tests (LFTs) are one of the most widely used biosensor platforms for point-of-care (POC) diagnostics. The basic LFD design has remained largely unchanged since its first appearance, and this has limited LFD use in clinical applications due to a general lack of analytical sensitivity. We report here a comprehensive study of the use of laser-patterned geometric control barriers that influence the flow dynamics within an LFD, with the specific aim of enhancing LFD sensitivity and lowering the limit of detection (LOD).

Single step phase optimisation for coherent beam combination using deep learning.

Coherent beam combination of multiple fibres can be used to overcome limitations such as the power handling capability of single fibre configurations. In such a scheme, the focal intensity profile is critically dependent upon the relative phase of each fibre and so precise control over the phase of each fibre channel is essential. Determining the required phase compensations from the focal intensity profile alone (as measured via a camera) is extremely challenging with a large number of fibres as the phase information is obfuscated.

Deep-Learning-Assisted Focused Ion Beam Nanofabrication.

Focused ion beam (FIB) milling is an important rapid prototyping tool for micro- and nanofabrication and device and materials characterization. It allows for the manufacturing of arbitrary structures in a wide variety of materials, but establishing the process parameters for a given task is a multidimensional optimization challenge, usually addressed through time-consuming, iterative trial-and-error. Here, we show that deep learning from prior experience of manufacturing can predict the postfabrication appearance of structures manufactured by focused ion beam (FIB) milling with >96% accuracy over a range of ion beam parameters, taking account of instrument- and target-specific artifacts.

Semi-quantitative detection of inflammatory biomarkers using a laser-patterned multiplexed lateral flow device.

Inflammatory markers including C-reactive protein (CRP) and procalcitonin (PCT) have been shown to be useful biomarkers to improve triage speed and prevent the inappropriate use of antibiotics for infections such as pneumonia. Here, we present a novel and exciting solution to guide the administration of antibiotic treatment via rapid, semi-quantitative and multiplexed detection of CRP and PCT using an advanced lateral flow device (LFD) designed to have multiple parallel flow-paths, produced via the precise laser-based partitioning of the single flow-path of a standard LFD. Each flow-path within this multiplexed LFD has a unique detection capability which permits tailored detection of CRP within a predefined cut-off range (20 μg/mL - 100 μg/mL) and PCT above a pre-defined threshold (0.

A SARS-CoV-2 nucleocapsid ELISA represents a low-cost alternative to lateral flow testing for community screening in LMI countries.

Background Controlling the spread of SARS-CoV-2 is problematic because of transmission driven by asymptomatic and pre-symptomatic individuals. Community screening can help identify these individuals but is often too expensive for countries with limited health care resources. Low-cost ELISA assays may address this problem, but their use has not yet been widely reported.

The future of bone regeneration: integrating AI into tissue engineering.

Tissue engineering is a branch of regenerative medicine that harnesses biomaterial and stem cell research to utilise the body's natural healing responses to regenerate tissue and organs. There remain many unanswered questions in tissue engineering, with optimal biomaterial designs still to be developed and a lack of adequate stem cell knowledge limiting successful application. Advances in artificial intelligence (AI), and deep learning specifically, offer the potential to improve both scientific understanding and clinical outcomes in regenerative medicine.

Modeling adult skeletal stem cell response to laser-machined topographies through deep learning.

The response of adult human bone marrow stromal stem cells to surface topographies generated through femtosecond laser machining can be predicted by a deep neural network. The network is capable of predicting cell response to a statistically significant level, including positioning predictions with a probability P < 0.001, and therefore can be used as a model to determine the minimum line separation required for cell alignment, with implications for tissue structure development and tissue engineering.

Laser-patterned paper-based sensors for rapid point-of-care detection and antibiotic-resistance testing of bacterial infections.

Antimicrobial resistance (AMR) has been identified by the World Health Organisation as a global threat that currently claims at least 25,000 deaths each year in Europe and 700,000 globally; the number is projected to reach 10 million per year between 2015 and 2050. Therefore, there is an urgent need for low-cost but reliable point-of-care diagnostics for early screening of infections especially in developing countries lacking in basic infrastructure and trained personnel. This work is aimed at developing such a device, a paper-based microfluidic device for infection testing by an unskilled user in a low resource setting.

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.

Rapid Multiplexed Detection on Lateral-Flow Devices Using a Laser Direct-Write Technique.

Paper-based lateral flow devices (LFDs) are regarded as ideal low-cost diagnostic solutions for point-of-care (POC) scenarios that allow rapid detection of a single analyte within a fluidic sample, and have been in common use for a decade. In recent years, there has been an increasing need for rapid and simultaneous detection of multiple analytes present within a single sample and to facilitate this, we report here a novel solution-detection using a multi-path LFD created via the precise partitioning of the single flow-path of a standard LFD using our previously reported laser direct-write (LDW) technique. The multiple flow-paths allow the simultaneous detection of the different analytes individually within each of the parallel channels without any cross-reactivity.

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.

Improved sensitivity and limit-of-detection of lateral flow devices using spatial constrictions of the flow-path.

We report on the use of a laser-direct write (LDW) technique that allows the fabrication of lateral flow devices with enhanced sensitivity and limit of detection. This manufacturing technique comprises the dispensing of a liquid photopolymer at specific regions of a nitrocellulose membrane and its subsequent photopolymerisation to create impermeable walls inside the volume of the membrane. These polymerised structures are intentionally designed to create fluidic channels which are constricted over a specific length that spans the test zone within which the sample interacts with pre-deposited reagents.

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.

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.

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.

Pulsed laser deposited diode-pumped 7.4 W Yb:Lu₂O₃ planar waveguide laser.

Fabrication, characterization, and laser performance of an Yb:Lu₂O₃ planar waveguide laser are reported. Pulsed laser deposition was employed to grow an 8 µm-thick Yb-doped lutetia waveguide on a YAG substrate. X-ray diffraction was used to determine the crystallinity, and spectroscopic characterization showed the absorption and emission cross-sections were indistinguishable from those reported for bulk material.

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  cm 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.

Laser-based patterning for fluidic devices in nitrocellulose.

In this report, we demonstrate a simple and low cost method that can be reproducibly used for fabrication of microfluidic devices in nitrocellulose. The fluidic patterns are created via a laser-based direct-write technique that induces polymerisation of a photo-polymer previously impregnated in the nitrocellulose. The resulting structures form hydrophobic barriers that extend through the thickness of the nitrocellulose and define an interconnected hydrophilic fluidic-flow pattern.

456-mW graphene Q-switched Yb:yttria waveguide laser by evanescent-field interaction.

In this Letter, we present a passively Q-switched Yb:Y2O3 waveguide laser using evanescent-field interaction with an atmospheric-pressure-chemical-vapor-deposited graphene saturable absorber. The waveguide, pumped by a broad area diode laser, produced an average output power of 456 mW at an absorbed power of 4.1 W.

Diode-end-pumped 1.2 W Yb:Y₂O₃ planar waveguide laser.

Fabrication, characterization and laser performance of a Watt-level ytterbium-doped yttria waveguide laser is presented. The waveguide was grown onto a YAG substrate by pulsed laser deposition and features a 6 µm thick ytterbium-doped yttria layer sandwiched between two 3 µm undoped yttria layers. The laser deposited film was characterized by X-ray diffraction, showing a high degree of crystallinity and analyzed spectroscopically, showing performance indistinguishable from previously reported bulk material.

Q-switched operation of a pulsed-laser-deposited Yb:Y(2)O(3) waveguide using graphene as a saturable absorber.

The first, to the best of our knowledge, Q-switched operation of a pulsed-laser-deposited waveguide laser is presented. A clad Yb:Y(2)O(3) waveguide was Q-switched using an output coupling mirror coated with a single layer of graphene deposited by atmospheric pressure chemical vapor deposition. During continuous-wave operation, a maximum power of 83 mW at a slope efficiency of 25% was obtained.