TECH OFFERS

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.

Enterprises are constantly looking for ways to improve operational efficiency and reduce costs. Traditional automation has limitations, especially when it comes to tasks requiring creativity or complex decision-making. Generative AI has emerged as a transformative technology that addresses a variety of pain-points faced by enterprises across industries. This technology solution offers a seamless integration of large language models (LLMs) and Generative AI fuctions with existing infrastructure, enhancing AI's impact by automating the flow of information and standardizing AI usage within your enterprise. This empowers customer support and operations teams to provide quick and accurate responses, significantly improving service delivery and operational efficiency.    

Issues associated with odor generation present significant challenges in various aspects of daily life, encompassing unpleasant smells from various sources such as toilets, kitchens, pets, tobacco, hospitals, and transportation. These unwanted odors have a detrimental impact on individual well-being, social interactions, and overall environmental quality. Deodorants play a crucial role in addressing these challenges, fostering a more comfortable and hygiene environment. However, conventional deodorants primarily rely on masking the unwanted odors with a strong fragrance, resulting in a slow and ineffective deodorization process, particularly against strong smells. The technology owner has developed a proprietary formulation that offers an effective deodorization approach. Unlike common deodorants, the unique deodorant using the proprietary formulation can remove the sources of unpleasant smells through chemical reactions. It demonstrates remarkable efficiency against a broad spectrum of odors, including those from rotting fish and meat, rotting eggs and milk, rotting vegetable waste, ammonia in toilets, sweat, and body odor. This innovative solution has the potential to revolutionise odor control across diverse scenarios. The technology owner is seeking R&D collaboration with industrial partners who are interested in incorporating this deodorant into their products and applications.

The human skin is the largest organ of the body, capable of extremely sensitive sensing ability and functional characteristics including elasticity, mechanical resistance and self-healing due to different mechano-receptors and sensory nerves. Electronic skin (e-skin) or synthetic skin, is a thin electronic material that stimulate the characteristics of the skin, making it possible for applications in prosthetics, robotics, wearables devices and percutaneous drug delivery systems. This patented technology is an e-skin with tactile, pain and temperature sensing, capable of differentiating various mechanical forces, sensory heat or moisture concurrently. It is a promising technology for healthcare applications. Currently, majority of the sensors in the market for healthcare are in rigid forms and for small application areas, which make it difficult for portable and wearable applications in large surface areas. This thin film flexible electronic skin can detect applied pressure and temperature on it. The skin’s electrical resistance varies with applied pressure and temperature. By measuring the skin’s electrical resistance, the applied pressure and temperature can be derived. The skin can be made stretchable to be covered on irregular curved surfaces. These features complement the drawbacks of rigid sensors for healthcare applications. The technology owner is looking for collaborators in the medical and robotics sectors and potential opportunities outside of healthcare such as beauty and cosmetics.

The proprietary solution is a data acquisition and analytics system that employs non-intrusive clip-on current transformers which are easily installed at electrical distribution boards. This enables AI algorithms to detect subtle changes and patterns in the electrical signature of each connected asset or device. Monitoring electrical assets has traditionally been complex and costly, requiring multiple sensors and expensive systems. This has led to widespread under-monitoring,  resulting in expensive maintenance and significant energy inefficiencies. The solution extracts a proprietary set of deep energy data from electrical devices, assets, and machines, and can be easily installed on both new and existing electrical assets or building infrastructure. It offers real-time monitoring and reporting on important metrics such as real-time power usage effectiveness (PUE) and enables automation of sustainability reporting. The technology offers an industry-changing solution: a non-intrusive cost efficient AI-powered monitoring system that is easy to install. It generates a proprietary data set that fuels machine learning algorithms, enhancing efficiency and reducing total cost of ownership for all connected assets. The technology owner is seeking test-bedding partnerships with real estate businesses, data centre companies or service providers, facility management businesses.

Collagen is a structural protein prevalent in the connective tissues of all organisms, and is the building block of biomaterial that is essential in wound healing and tissue regeneration. Through a patented extraction method, a novel Type I Amphibian collagen has been valorised from discarded skins, an agrifood waste stream and processed into a medical grade collagen biomaterial. The extracted pristine native amphibian collagen possesses unique properties, combining attributes associated with aquatic and land-based collagen sources, giving the extracted collagen more versatility than conventional sources of collagen. The Type I Amphibian collagen possesses a higher biocompatibility and water solubility as compared to mammalian sources of collagen, with a better thermostability profile, than marine sources of collagen. The technology provider has demonstrated the medical application of this extracted collagen by developing a range of specialised wound dressings, specifically designed for the management of chronic wounds. These dressing will significantly improve clinical outcomes and increase the rate of chronic wound closure.  The technology provider is looking for partnerships or collaborations to transform this pristine collagen into medical products. Additionally, with a pristine collagen extract, hydrolysing them into smaller fragments (collagen peptides) that can be customised to the needs of the partnership or collaboration, for the medical/cosmeceutical/nutraceutical industry. 

Despite the remarkable achievements of large language models (LLMs) in various tasks, there remains a linguistic bias that favors high-resource languages, such as English, often at the expense of low-resource and regional languages. To address this imbalance, we introduce SeaLLMs, an innovative series of language models that specifically focuses on Southeast Asian(SEA) languages. SeaLLMs are built upon the Llama-2 model and further advanced through continued pre-training with an extended vocabulary, specialized instruction and alignment tuning to better capture the intricacies of regional languages. This allows them to respect and reflect local cultural norms, customs, stylistic preferences, and legal considerations. Highlights: The models' attunement to local norms and legal stipulations—validated by human evaluations—establishes SeaLLMs as not only a technical breakthrough but also a socially responsiveinnovation. SeaLLM-13b models exhibit superior performance across a wide spectrum of linguistic tasks and assistant-style instruction-following capabilities relative to comparable open-source models. SeaLLMs outperform mainstream commercialized models for some tasks in non-Latin languages spoken in the region, meanwhile, SeaLLMs are efficient, faster, and cost-effective compared to commercialized models.

As rapid global warming accelerates, the need for increased sustainability efforts has become a critical societal challenge. While individual lifestyle changes can contribute, their impact remains limited without broader systemic shifts. This places significant pressure on industries, particularly the fashion & textiles sector, a major contributor to climate change responsible for 10% of global greenhouse gas emissions. Decarbonising this industry is therefore crucial to achieving a sustainable future. This technology enables textiles and fabrics to remove carbon dioxide (CO2) from air. The patent-pending material functionalises textiles to capture CO2 present in air which is sequestered into a harmless mineral during the laundering process. The resultant mineral which is environmentally safe is then washed away, leaving the textile recharged to remove CO2 once more. With this technology, decarbonisation of the textiles industry can be achieved through the decentralised action of consumers utlising functionalised carbon removing products. The technology owner is interested in working with interested companies in the fashion industry value chain to test-bed this new material for carbon removing apparel and fabrics.

3D scanning by employing technologies like LiDAR, laser scans, TOF cameras and photogrammetry is an essential step in the process of making digital twins for the construction and built space sectors. This data is then meticulously processed, often manually, to form the 3D models for integration with Building Information Modeling (BIM) platforms and creation of accurate digital twins. The 3D models, by themselves or in conjunction with the realised Digital Twin, also help in different planning and monitoring tasks during the entire lifecycle of a building from construction to maintenance.  Obtaining the 3D cloud data from scanning and its conversion to a model is an involved process. The technology presented here eases both these processes by providing diverse options for scanning and enabling AI assisted conversion of the data obtained  to a 3D model capable of being used with BIM.