Industry Showcase

Ce Liu, Baobao Lin and colleagues report a rapid and straightforward nucleic acid screening test requiring no professional training or formal medical setting. The device runs on a novel gamepad-like interface and fully integrates nucleic acid release, amplification, and visualization.

Haruki Okamoto and colleagues demonstrate that tank structure is crucial for large-scale platelet production from cultured immortalized megakaryocyte progenitor cell lines, due to the increase in defective turbulent flow space. These insights could guide the development of new bioreactors with improved production efficiency.

Leendert-Jan W. Ligtenberg and colleagues report an X-ray guided platform for the wireless teleoperation of hemocompatible, untethered magnetic robots. The approach will enable clinicians to reach and treat vascular diseases within the body where alternative tethered flexible surgical instruments offer more limited control.

The increasing complexity of the implementation and operation of deep learning techniques hinders their reproducibility and deployment at scale, especially in healthcare. Pati and colleagues introduce a deep learning framework to analyse healthcare data without requiring extensive computational experience, facilitating the integration of artificial intelligence in clinical workflows.

Alanine aminotransferase (ALT) activity is an important indicator to determine drug induced liver injury. However, its measurement is limited to centralized laboratories. Muratore, Zhou, and colleagues designed an ALT assay biosensor platform using silicon nanowire field effect transistor arrays. The biosensor could monitor ALT enzyme activity electrically, with comparable precision to spectrophotometric detection. This biosensor platform will enable routine liver function monitoring in settings both inside and outside of the clinic.

Pierre-Alexis Mouthuy and colleagues report the actuation of cell-material constructs in flexible bioreactor chambers inserted into musculoskeletal humanoid robots. This opens up the opportunity of applying realistic biomechanical stresses to tissue engineered constructs during culture.

Tommaso Bendinelli and colleagues developed a deep learning method that leverages data from different scanning and spectroscopy modalities to improve gemstone origin determination and treatment detection.

Yunje Cho and colleagues improve the resolution of scanning electron microscopes via high-precision auto-focus and auto-stigmation. Their method operates without pre-existing knowledge about the sample.

Yoshida and colleagues present a technique for sealing bedrock flow paths using concretion-forming resin, which is inspired by the natural process of spheroidal concretion formation in natural calcite. The approach shows high speed and durability, also proving a good performance in withstanding seismic activity.

Alexander Blömeke and colleagues investigate the conditions under which the balancing resistors in battery systems can be used for impedance measurements. This helps to improve state estimation and results in safer and more sustainable battery systems.

Anton Molina and colleagues demonstrate the fabrication of absorbent materials from the drought tolerant plant agave sisalana (sometimes known as sisal). The findings suggest a route toward local production of the absorbent component of menstrual pads in low- and middle-income countries, where there is more limited access to sanitary products.

Oscar Recalde-Benitez and colleagues report a FIB-based sample preparation process to limit current leakage during operando TEM experiments, thus improving the accuracy of device nanocharacterization under operating conditions. The methodology results in leakage currents that are small compared to device currents, which enables the analysis of operating stack devices inside the microscope.

Jan Kloppenborg Møller & Goran Goranović and colleagues introduce a data-driven twin methodology which balances physical knowledge with uncertainty quantifications. The approach makes it suited to application of real world problems with inherent unknowns. They demonstrate its application in the modelling and control of membrane water ultrafiltration

Kevin Wyss and colleagues report the flash synthesis of graphene from end-of-life vehicle plastic waste. A polyurethane/flash graphene composite is also re-flashed back into more graphene. A life cycle assessment suggests environmental benefits compared to other graphene synthetic routes.

Sheng Huang, Xiaohui Huang and colleagues propose a methodology for the optimal power dispatch from the wind farms. Their method relies on local data only and allows iterative convergence.

Mauricio Velazquez Lopez and colleagues fabricate a neuromorphic node with a response time that spans a range of 7 orders of magnitude. Their technology is compatible with complementary metal-oxide semiconductors, which makes it suitable for a variety of machine learning tasks.

Dr Roland Brunner and colleagues demonstrate how acoustic interferometry can be used to conduct a non-destructive and high-resolution failure analysis of through-silicon vias. They analyse the detection of nanometre-scale cracks and discuss how the opening angle of the acoustic lens impacts on performance.

Chul Kim and colleagues show a sensor display which is able to capture biometric data. In one device, they combine fingerprint identification and biomarker estimation while maintaining the same display quality.

Zhenming Liu and colleagues show a SiC microelectromechanical system with both high quality factor and high frequency. They demonstrate the advantage of the device over the traditional Si gyroscopes and batch-fabrication possibility.

Chu and colleagues explore holographic data storage as a replacement for hard disk drives, introducing an energy optimization framework for Fe concentrations in iron-doped lithium niobate. Their approach results in a record-breaking performance in both read and density.

Tomoki Inoue and colleagues report a time-series data clustering algorithm using a quantum-inspired digital annealer technology to improve the clustering performance. The algorithm was implemented to cluster time-series data derived from benchmark problems and flow measurement images.

Costa and co-authors detected an earthquake in Mexico using conventional polarisation optics within a trans-oceanic fibre-optic cable connecting Los Angeles, USA with Valparaiso, Chile. Their approach enables non-invasive monitoring and localization of seismic waves on the seabed.

Yao Xiao and colleagues report a graph-based machine learning algorithm for categorising and then more efficiently distributing code segments across different processing units in heterogeneous hardware platforms. The approach leads to more efficient processing, vital for future developments harnessing AI, for example in fields such as autonomous vehicles and machine vision.

5G network operators need data traffic predictions to plan network expansion schemes. Yuguang Yang and colleagues demonstrate performance improvement over state-of-the-art forecasting tools of a deep learning model, Diviner. They demonstrate detailed months-level forecasting for massive ports with complex flow patterns.

Tong Ye and colleagues use a spectrum analyzer and the probability-maintained noise power ratio method to estimate the performance of nonlinear communications systems. The method is verified in seven different nonlinear mechanism and application scenarios.

Debuisschert and colleagues describe a radio frequency signal analyzer platform utilizing the quantum properties of the nitrogen-vacancy center in single crystal diamond. This platform enables millisecond detection of complex microwave signals over a broad tunable frequency range up to 25 GHz.

Murray and colleagues report strain distributions in Si/SiGe nanosheet heterostructures using synchrotron x-ray nanodiffraction techniques. The observations and underlying mechanisms provide insights for future nanodevice design and performance prediction.

Chengcheng Zhao and co-authors study the potential of battery electric buses and hydrogen polymer electrolyte membrane fuel cell buses. They analyse their usage in urban transport and quantify the environmental impact.

Xin Xiong and colleagues estimate end-of life mass predictions of aerospace and rail vehicles in China and predict waste accumulation between 2000 and 2050. The study will aid in developing and managing effective technological solutions for a circular economy as well as formulating plans for governance.

Analysis of the aircraft structural load needs costly and inefficient ground tests. Chenxi and coworkers report a deep learning based approach to predict aircraft strains and loads by identifying the key flight parameters in the load prediction, providing a more efficient and economical way for aircraft load monitoring.

Over-reliance on automation in transportation systems is known to cause accidents. To address this, here, Tomohiro Nakade and colleagues describe a collaborative strategy for autonomous steering, in which the driver can take over from the automation without its full deactivation.

Roberto Torelli and colleagues propose a numerical framework to characterize fuel injection in internal combustion engines at multiple length and time scales. The approach demonstrates potential for increased fidelity in the flow dynamics by means of an affordable end-to-end methodology that links realistic injection operation to fuel combustion and engine emissions.