TECH OFFERS

Recent advances in soft robotics revolutionize the way robots interact with the environment, empowering robots to undertake complex tasks using soft and compliant grippers. Compared to traditional rigid structures. Soft grippers have excellent adaptability for a variety of objects and tasks. However, the existing gripper systems faces some challenges, such as handling delicate, wet, and slippery items, the risk of damaging valuable items, and high production cost. Based on pneumatic jamming of 3D-printed fabrics, the technology owner has developed a variable-stiffness soft pneumatic gripper that can apply small forces for pinching and pick-up heavy objects via stiffening. The invented grippers are soft and adaptive to handle delicate items with various shapes and weights, minimising the damaging risk of items during the gripping process. In addition, such gripper with adjustable stiffness could handle heavy and bulky items by increasing its gripping strength. These benefits make the gripper more versatile and adaptable to various applications in agriculture, food processing, packaging, manufacturing, and human-robot interaction (HRI). The technology owner is seeking to do R&D collaboration, IP licensing, and test-bedding with industrial partners intending to integrate variable-stiffness gripper in their applications. 

A microfluidic chip-based mechanism has been developed as a Point-of-Care Testing (POCT) device to replace Lateral Flow Assays (LFA) for fast and convenient blood analysis. The microchip system utilises the principle of immunoassays but with high accuracy and compatibility to different signalling tags, providing a quantitative readout. Conventional immunoassays involve multistep procedure and long process time. While LFAs are fast and convenient, they are qualitative. The device demonstrated a one-step assay that can achieve equal or higher sensitivities than standard methods within significantly shorter total processing time. In a microfluidic device, the sample flows in precisely defined microchannels, which allow better control of fluid behaviour and higher consistency in testing results compared to LFA in which the sample flows by wicking through the porous paper-based material. This technology resides in the assembly of components and materials to immobilise antibodies or antigens onto the chip which can be easily scaled for commercial production. The technology owner is seeking collaborations with manufacturers of IVD devices or Medtech companies to out-license the technology and expand the range of antibodies targets for the microchip.

The technology consists in a new type of neural networks, providing explainable, verifiable, compact and private AI solutions. Explainability: the technology provides precise global explanations and the exact rules learned by the AI model, even with large datasets. We transform clients' raw data and/or models into meaningful results through high-quality visual analytics, empowering them to enhance the model based on these explanations. Formal Verification: the technology allows the client to formally verify certain properties of the model, such as its robustness to adversarial attacks, its fairness according to certain features, etc.

Neurological diseases are the second leading cause of death. CT scans have been used as the primary modality to diagnose brain abnormalities such as Intracranial Haemorrhage (ICH) and neurodegeneration. Radiologists usually have to deal with an overwhelming scan backlog and writing radiology reports is a time consuming process. Manual segmentation of lesions is tedious and existing heuristics have been shown to overestimate lesion volumes. Clinicians are also wary of the ‘black box’ nature of deep learning models. Hence, an automated tool in the workflow could substantially improve clinical productivity and interpretability is crucial to build trust with clinical stakeholders. Our proposed technology is an AI solution that automates ICH detection and brain tissue segmentation on CT scans, producing accurate volumetric information to assist triaging. Our technology also comes with a set of tools to interact with the AI models and generate reports easily. Moreover, we strengthen our AI transparency with interpretable models. Our platform also focuses on model robustness tests to assure AI safety.  

Digitalisation is a global trend with digital twin technology increasingly adopted in various industrial segments including smart factories and plants, digital facility management and operation & maintenance, building and construction, etc. Rapid generation of digital twin of physically existing is desired. Conventionally, digital twin is mainly generated using design software which requires professional modellers to spend substantial design time pending on the complexity of the physical twin (to be constructed) and the manpower available. Building information modelling (BIM) is increasingly used as a representation for the digital twin. For existing environments, scan to BIM technology and authoring software products are used for the process of reconstructing of BIM models from LiDAR scanned point clouds. This manual process is typically time consuming, tedious and error prone. Often, meshed models are used for visualization purpose of the digital twin.

Coronary artery disease (CAD) is the leading cause of death worldwide. Computed Tomography Coronary Angiography (CTCA), as a non-invasive alternative to invasive catheterized coronary angiography, has emerged as a recommended first-line investigation for CAD. However, the current practice of generating reports involves a time-intensive process, with CT specialists spending 3-6 hours annotating scans. Furthermore, there is a lack of effective tools for analysing coronary calcium scores, stenosis severity, and plaque characterization. This AI driven platform is for CT data processing that provides a streamlined 'one-stop' solution spanning from diagnosis to clinical management and prognosis. Its key features include: AI-driven platform for CTCA, catering to clinical, research, and industrial applications. Large, shareable, de-identified, Personal Data Protection Act-compliant real-world CT data. Precision toolkits for anonymization, coronary calcium scoring, epicardial adipose tissue (EAT), stenosis severity assessment, plaque quantification, CT fractional flow reserve (FFR), and reporting. The platform’s highly automated features assist physicians in interpreting and synthesizing large volumes of CT data, while minimizing bias, increasing reproducibility, and providing numerical insights in a graphical manner. It offers a comprehensive ‘one-stop’ solution for diagnosis and clinical management of CAD.

A Digital Twin is a digital representation of a physical object or system, often used in various industries for simulation, analysis, and monitoring. In the built environment, which encompasses everything from buildings and infrastructure to urban planning, Digital Twins have a wide range of potential applications that can significantly enhance efficiency, sustainability, and overall quality of life. Digital twins have emerged as a transformative concept in the built environment, revolutionizing how buildings, infrastructure, and cities are designed, constructed, and managed. This innovative technology leverages the power of digital simulations and real-time data to create virtual replicas of physical assets, offering numerous benefits across various sectors within the built environment. The technology owner is seeking co-development partnerships with building owners, facity management companies, smart city or urban planners to adopt their digital twin technology in achieving their sustainability objectives.

For many years, gas detection applications in industries have predominantly relied on single point detectors, which are applicable in many industries covering a wide market sector.   Starting from the year 2010 and onwards, open path line detectors have gained significant recognition and popularity due to their cost-effectiveness and ability to cover larger areas, thereby enhancing safety measures.  More device options are now on the market.   However, all of these devices have the inherent problems of false alarms due to environmental interference, such as rain and snow. A waveform matching technology – multi order laser emitting spectrum (MOLES) was invented. This cutting-edge technology ensures specific gas detection, it only detects when specific gas is detected, and eliminates all false alarms caused by environmental interference.   By gathering industrial inputs and feedbacks, improvements and user-desired features are incorporated into this invention, to enhance its overall performance, reliability and solving many user problems on site, such as no display, alignment problems, and calibration.  This breakthrough innovation will provide a more efficient and reliable gas detection solution for industries, safeguarding their operations and personnel.

Lithium ion (Li-ion) battery is now the dominant energy storage system in portable electronics and electric vehicles (EV). The rapid expanding EV is driving the demand for next generation high-energy batteries. Compared to conventional Li-ion batteries with graphite anode, which has a theoretical capacity of 372 mAh/g, lithium-metal batteries can deliver ten times of specific capacity (3860 mAh/g). Theoretically, anode-free batteries can double the energy density in volume compared to Li-ion batteries at the cell level. However, current anode-free batteries suffer from faster capacity decay due to poor lithium plating on Cu foil. To overcome this challenge, the technology owner has developed a liquid electrolyte comprising lithium difluoro(oxalate)borate (LiDFOB) and a carbonate solvent, enabling reversible lithium plating of anode-free lithium metal batteries. This electrolyte ensures good thermal stability with smooth Li plating of counter electrode on the anodic side even at elevated temperatures. It facilitates a capacity retention of above 80% after 100 cycles for an anode-free battery or 80% after 400 cycles for a battery with a Li metal anode. The technology owner seeks collaboration with industrial partners such as battery developers and manufacturers for further co-development and test-bedding of electrolyte and subsequent licensing of this technology for commercialisation.