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TECH OFFERS

Discover new technologies by our partners

Leveraging our wide network of partners, we have curated numerous enabling technologies available for licensing and commercialisation across different industries and domains. Enterprises interested in these technology offers and collaborating with partners of complementary technological capabilities can reach out for co-innovation opportunities.

Efficient Green Method to Process Poultry Feather into Hydrolysable Protein
Current extraction methods requires treatment that is not only non-environmental friendly but also destroys some of the nutrients in the keratin. The current state of the art for extracting protein from feather meal are through physical treatment involving high temperature and/or high-pressure steam to hydrolyze the feathers for animal feed production. However, the nutritional value of such feather meal is low because excess thermal degradation denatures certain amino acids such as lysine and tryptophan. In addition, high temperature cause the formation of non-nutritive amino acids such as lysinoalanine.  Chemical treatment is also commonly used to hydrolyze feathers. For example, mercapto-acetate and sodium tetrathionate can dissolve feathers completely but they are highly toxic. Biological treatment involves application of keratinolytic microorganisms and their enzymes (keratinase) for feathers hydrolysis. However, application in industry is limited because it is a time-consuming process. This technology is an efficient extraction method which uses less harsh chemicals and optimizes the yield of keratin within a relatively short period of time. This method has been tested with chicken feathers recovering amino acids and keratin. The extracted compound derived could also serve as an alternative protein for fish and pet feed. The technology provider is keen to work with a commercial partner who would be interested in using this technology for commercialization or partners who like to formulate this upcycled protein into pet and animal feed. The partner could also help in running some trials and eventually license this technology.
Autonomous UAV System Using Multi-Modality Sensor Fusion
The proposed technology is a fully integrated navigation solution for urban structure inspection. The system is built on a visual-inertial-range-and-LIDAR (VIRAL) fusion-based simultaneous localization and mapping system (SLAM). The VIRAL SLAM algorithm can work both indoor and outdoor in all lighting conditions. The team has developed some prototype devices with all the necessary sensors and codes and are compatible with popular drones. In urban navigation, the GPS is likely to suffer from a multi-path effect. The drone is prone to perception noises that lead to crashes. The proposed system can effectively solve the aforementioned problem and can achieve mm-level accuracy. The target users are drone or robotics service providers or other 3rd-party developers that create new onboard devices for autonomous operations. The partnership model can be technology license transfer, research collaboration, and technology further development contracts.
Emergency Incident Detection and Fall Prevention Solution
More than 70,000 elderly live alone and are cared for by over 400 social welfare organisations in Singapore. As the population's average age continues to rise and the healthcare manpower continues to shrink, this particularly vulnerable group of individuals require quick access to the right care at the right time. Technology that gives caregivers the ability to respond to incidents promptly is highly crucial in such situations.  This technology offers a combination of analytics and hardware devices that detect falls, abnormal sounds, and bed-exit events to prevent falls. Applied for emergency monitoring, it can detect falls and differentiate real screams and ambient environmental audio for real-time detection of emergencies in sensitive areas, e.g. washrooms and high traffic areas such as communal rooms, providing caregivers with the assurance that their charges are continuously monitored. This solution also prevents falls by detecting bed-exit events. Should such incidents occur, caregivers can rapidly verify the validity of the incident and respond accordingly within seconds.
Plant-Derived Nano-delivery Technology to Improve Bioavailability of Actives
This technology uses plant-derived nanoparticles (PDNPs) and nanofibers (PDNFs) which are isolated from sour cherries. The PDNPs and PDNFs transport high quantities of biologically active payloads into living cells of plants, animals and humans. The nanoparticles bind to and protect actives from degradation and can transport them into cells. The nanoparticles bind wells to any type of material for delivery, e.g. hydrophobic and hydrophilic materials. The technology owner is open to conduct R&D for clients who are looking to develop a product for specific intended use. They are developing a manufacturing protocol for companies who wish to license their technology.
Vanadium Redox Flow Battery for Enhanced Energy Storage Solution
Today, the cost of energy generated by renewable sources is less than conventional energy. However, current energy storage solutions (e.g. Lithium-ion battery etc.) used to harness energy from renewables are expensive, unsafe and unreliable which has severely impeded the adoption and development of such renewable sources. Hence, there is a need for a cost efficient, safe, environmentally friendly and reliable energy storage system (ESS) to address these existing issues. This technology offer is a vanadium redox flow battery (VRFB) as a promising ESS. Unlike lithium-ion and lead acid batteries, VRFB has the flexibility to design and customise its power and energy density independently. This results in enhanced performance in terms of round-trip efficiency, energy density and thermal window as well as lowered levelised cost of storage when benchmarket against lithium-ion battery based ESS for long discharge duration. The VRFB also uses a unique stack design and an organic additive mixture on the electrolyte that improves the thermal stability and allows for 25% increase in energy efficiency when compared to other VRFB solutions.It also reduces safety risks related to over-charging, discharging and thermal runaways. This VRFB ESS is stable for up to 25 years with no electrolyte degradation and is made with environemtally friendly materials. The technology owner is seeking partner and collaborators especially those in renewable energy, large scale utility and microgrid projects to test bed their technology.
Recycling of Spent Lithium-ion Battery Materials
Lithium-ion batteries (LIBs) have been the preferred portable energy source in recent decades. However, disposal of these spent LIBs causes serious environmental problems because the batteries are made of hazardous components such as heavy metals and electrolytes. Current recycling method for LIBs are energy intensive, costly, generate harmful emissions while having poor recovery rate of the valuable metals. Therefore, there is a need for a low cost, environmentally friendly recovery method that can achieve high yield for the critical battery materials. This technology offer is a highly versatile recycling method for LIBs that directly converts crushed LIBs material (black mass) into ready-to-use battery-grade cathode materials. This direct conversion is based on proprietary hydrometallurgical co-precipitation method and allows for the skipping of the production of mixed precious metal salts and immediately produces reusable battery-grade cathode materials. Furthermore, there is no need for pre-sorting and a mixture of LIBs materials with different chemistries can be processed in a single batch. These includes lithium cobalt oxide (LCO), lithium manganese oxide (LMO), lithium nickel manganese cobalt oxide (NMC) and lithium nickel cobalt aluminium oxide (NCA). The production outputs are battery-grade NMC hydroxides (622/532/111/811), and the by-products may include lithium carbonate and sodium sulphate. Lastly, adoption of this technology allows for up to 4x increment in recycling profits and a cost recovery period of <1 year. The technology owner is seeking industry partners to license and adopt the technology, preferably companies with an interest to invest in or build a LIB recycling plant.
Low-latency Digital Twin for Industrial Applications
In this modern age of data, many systems and Internet-of-Things (IoT) information sources are independent and scattered, resulting in the increased complexity of processing heterogeneous data for visualisation purposes. Digital twins can help to mirror their physical, real-world equivalents in three-dimensional (3D) space to improve spatial perception and are ideally suited for high-risk environments that are physically inaccessible by humans. In such cases, IoT sensors are put in place to support real-time remote fault identification, operation, training, maintenance, and synchronise with various types of management dashboards to facilitate decision-making processes. This technology offer is a one-stop platform that empowers enterprises to create digital twins (or a one-to-one reproduction of physical real-world objects/building/machinery) - where next-generation spatial hardware e.g. Augmented Reality/Virtual Reality (AR/VR) headsets or smart glasses can be used to interact with contextual, real-time information in a fully rendered 3D environment that blends the digital information (sensor data and digital mapping) and physical (real-world) layers for a range of industrial applications including continuous monitoring and predictive maintenance.  The technology owner is keen to collaborate with companies in the Port, Manufacturing, and Property (facility management, building management, energy management, security management) industries for test-bedding of existing use-cases on a project basis, leading up to product R&D collaboration and eventually licensing.
Universal Hardware and Platform for Real-time Data Analysis
Real-time manufacturing data can help to predict the condition of production machines and peripheral equipment. However, not every machine has the system to collect and analyse the condition of a machine. Furthermore, it is hard to gain data from non-networked devices, especially from old ones, as well as to integrate different types of manufacturing equipment. This technology offer is a SaaS and hardware solution for real-time data collection and analysis. The modular hardware provides an interface for communication channels and protocols of all industrial equipment. Hence, it makes every type of new or old production and peripheral equipment integrable. Upon the data collection from the universal hardware, the platform will analyse the data using deep-learning algorithm, generating detailed production information. The technology owner is keen to out-license its solution and looking for collaboration with partners in plastics manufacturing (especially for injection moulding), textile industry, and IHLs for further applications. 
Gamified Data Annotation Platform for Supervised Machine Learning
Machine Learning (ML) is a sub-field of Artificial Intelligence (AI) where a machine is able to learn without being explicitly programmed. However, before a machine can effectively perform even the simplest AI tasks, e.g. differentiating between images containing an elephant or a tiger, it has to be trained on images containing both animals. To be useful in supervised learning, training data needs to be properly labelled or annotated by a human for the machine to extract the relevant features and produce an ML model that serves its intended purpose. This highlights the important role that data annotation plays in producing robust, accurate ML algorithms in video analytics, natural language processing, and audio processing. However, many organisations that want to embark on their supervised learning journey often face difficulties gaining access to high-quality labelled datasets, known as ground truth data, due to the abundance of low-quality, expensive and unstructured data. This technology offer is a mobile application-based data platform that enables companies to obtain high-quality annotated data. It de-centralises data collection and data annotation tasks into manageable bite-sized chunks for optimal annotation performance and crowd/out-sources the annotation task to a pool of data taggers via a mobile application. Labelling quality is established through a gamification system and a series of built-in verification procedures, including AI-assisted pre-filtering and collective human quality control.