Tech Offers

A Scalable and Adaptive Model-Predictive Distributed Control of Building HVAC Systems

This technology offers a novel model-predictive distributed control method and a flexible and cost effective IoT implementation architecture for energy saving in building HVAC systems. It is scalable and real-time optimally responsive to changes in a large building that has more than 500 zones via a patented token-based HVAC scheduling strategy. The larger the building, the higher the energy saving potential, due to its novel coordinated HVAC scheduling approach. It is autonomously adaptive to the building operational environment via effective system identification techniques, including machine learning techniques, on real-time data attainable from the proposed IoT infrastructure. It is also occupant-centric, i.e., capable of learning and addressing individual human comfort requirements. The technology is applicable to any new or old VAV (or VRV) HVAC system without any need of major retrofitting on existing HVAC controllers and data acquisition systems, due to its highly flexible plug-and-play implementation architecture. It can also be used to convert an old HVAC system into a highly automated and intelligent one, allowing a building owner to check remotely, via commonly used mobile devices, the status of the building HVAC system and initiate supervisory control for better performance, thus, can enhance the effectiveness of existing BMS and building automation. The technology provider is seeking for industry partners to commercialise the technology.          

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Advanced Functional Fibers and Fabrics

This technology enables the seamless integration of multiple functional components into one flexible fiber with precise control over nanometre-level architecture and composition, at fiber length, uniformity, and cost. This technology also allows an all-in-fiber solution, achieving multiple functionalities, offering a lego-like template to enable the integration of different components into a single flexible fiber. These new fibers and their multi-dimensional fabrics have the ability to see, hear, and sense their surroundings, communicate, store and convert energy, monitor health, control temperature, and many more. This technology also offers industry scale-up capabilities, with kilometer length from one fabrication, to accomplish high production yield and cost-effectiveness.

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Protecting Big Data Privacy Using Randomized Information Dispersal Technology

The way we protect big data privacy is by mathematically decomposing big data into randomized fragments that are un-recognizable, un-linkable, and un-interpretable; these shredded fragments can then be sent over the internet or stored in multiple clouds, servers, or devices with metadata privacy. The attackers would need to search through the sea of big data in order to identify the fragments that belong to a particular record. What we are building is essentially a big data shredder that disperses the information of big data from different software applications into un-recognizable fragments before storing or communicating the data, by doing so, this technology provides the distributed trust in protecting the big data privacy. Big data is protected by different security mechanisms whether they are at rest or in transit using our proposed technology. Hackers will have to gain access to multiple storage locations and communication channels in order to retrieve the shredded fragments and recover the original records. For authorised users, the original data can be reconstructed instantaneously in any software applications, environments, or platforms using the metadata information and the corresponding shredded data fragments. Any security breach to the software application is confined to the amount of metadata loss during the attacks, thus our proposed technology differentiates ourselves from encryption because any loss of encryption keys may lead to massive data loss. As a mathematical technique, our proposed big data privacy solution can be easily integrated and combined with existing privacy-preserving technologies such as anonymization and encryption technology.

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Superlyophobic Materials for Immiscible Liquids Separation

Separation of oil/water mixture using wetting materials has been extensively investigated. However, the wastes released in industrial processes such as multi-phase liquids extraction, food industries or chemical reaction contain more complicated liquids components. The technology presents a novel strategy to prepare a broad range of superlyophobic materials based on polydopamine (PDA) mediated coating. The results demonstrate that the deposition of PDA nanoparticles enhances the growth of silicone microsheets (SMS), which increases trapped air fraction and results in superlyophobicity towards high surface tension liquids and superlyophilicity to liquids with surface tension smaller than 30 mN/m.

Superlyophobic sorbents generated from melamine foam and polyurethane foam can absorb various oils with capacity from 53 g/g to 120 g/g (melamine foam) and from 26.5 g/g to 52.5 g/g (polyurethane foam), depending on the oil type and density. High absorption capacity of porous foams towards oils makes them possible to remove low surface tension liquids from a batch of high surface tension immiscible organic liquids such as formamide or diethylene glycol. On the other hand, superlyophobic membranes fabricated from stainless steel mesh, cotton fabric and filter papers can filter chloroform and carbon tetrachloride from water and formamide with efficiency higher than 96%. All as-prepared superlyphobic materials show excellent regeneration. The preparation of superlyophobic materials introduced in this work opens a general strategy for separation of immicible liquids by both static and continuous methods.

The technology provider is seeking partner for research collaboration, scale-up testing/test-bedding, product co-development, technology licencing or manufacturing.  


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High Flux and Low Fouling Membrane Separation Process

Membrane fouling due to particulates is driven by permeate drag is a key issue that reduces the efficiency of membranes in various applications. To overcome this, a flow-field mitigation of membrane fouling (FMMF) technique has been developed that can potentially reduce the fouling. The technique is based on changing the pattern of the flow of fluids from parallel to an inclined one to counter the permeate drag experienced by the foulants.

Researchers have designed two configurations of FMMF channels and also identified corresponding mechanisms to mitigate fouling, along with confirming the efficacy of FMMF through CFD simulations and experiments. 

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Reinforced Low Energy Membrane and Module for Pressure Driven Water Purification Processes

This technology relates to a reinvention of the structure of spiral wound membrane module to increase productivity and to simplify the membrane fabrication process. Despite undergoing a long history of development, the structure of the spiral wound membrane modules remained the same. Each module is made up of several leaf sets, with each leaf set consisting of feed spacers, flat sheet membranes and a permeate carrier wrapped around the permeate collecting tube.

The technology here involves combining the 3 layers in a leaf set into 2 layers on an industrial-scale casting line such that more membrane can fit into a standard specific volume. By combining the permeate carrier and the membrane into a single sheet, we were able to eliminate the need for the typical non-woven backing for the membrane. As such, the leaf set thickness can be significantly reduced by approximately 10-20%, and hence the theoretical surface area and productivity of the membrane modules can be increased by 30-50%.

The material cost can potentially be reduced by 10-20% and the internal ion concentration polarization (ICP) is expected to be reduced due to less bulky structure. This design also lessen the work required to roll an element due to less sheets per leaf-set. The technology provider is currently seeking joint-venture partners for technology evaluation licensing with research collaboration agreement (RCA) to scale-up and commercialize the technology.

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