Green Energy and Emissions Management

Recently, the rising adoption of Internet of Things (IoT) devices and portable electronics has made electronic waste (e-waste) pollution worse, especially when small and low-power IoT devices are single-use only. As such, low-cost and environmentally friendly power sources are in high demand. The technology owner has developed an eco-friendly liquid-activated primary battery for single-use and disposable electronic devices. The battery can be activated by any aqueous liquid and is highly customisable to specific requirements (i.e., shape, size, voltage, power) of each application. This thin and flexible battery can be easily integrated into IoT devices, smart sensors, and medical devices, providing a sustainable energy solution for low-power and single-use applications. The technology owner is keen to do R&D collaboration and IP licensing to industrial partners who intend to use liquid-activated batteries to power the devices.

Mixed plastic waste is an abundant resource containing approximately 7-12 wt.% hydrogen (H2). Traditionally, hydrogen is produced from non-sustainable fossil feedstock, such as natural gas, coal and petroleum oil. This technology offer is a thermo-catalytic process that sustainably recovers hydrogen from plastic waste instead. During hydrogen recovery process, instead of releasing carbon dioxide (CO2) that causes greenhouse gas effect, the technology converts emissions into a form of solid carbon, called carbon nanotubes (CNT). Solid carbon is easier to store and handle compared to the gaseous carbon dioxide. Furthermore, carbon can be sold as an industrial feedstock for manufacturing of polymer composites, batteries, concrete, paints, and coatings. With over 150-190 million tonnes of mixed plastic waste ending up in landfills and our environment annually, the technology offers a sustainable solution for the elimination of plastic waste and decarbonization while providing a clean hydrogen supply.

Platinum group metals (PGM) are critical raw materials (CRM) that are used across multiple industries and in countless applications including but not limited to autocatalytic converters, jewellery, glassware, petrochemical refining, electronics, biomedical, pharmaceuticals, dental implants etc. The primary supply of PGM, through the mining of PGM ores, makes up about 70% of the global supply of PGM. The two dominant producers of PGM are South Africa and Russia, supplying 85% of the mining output of PGM - this leads to a monopoly of the supply chain and price gouging. Recycling PGM-containing waste offers advantages of addressing the supply deficit with less environmental impact compared to mining. However, conventional recycling methods suffer from high energy costs due to high processing temperature of about 1500 oC and requires downstream processing to treat waste which demands higher capital expenditure. Furthermore, the high processing temperatures results in high-value raw materials being burnt in the process and releasing harmful toxins. This technology offer is a novel biorecovery method that incorporates and modifies a series of different biochemical and biological processes in a simple 3-stage process as opposed to the multi-tiered stages of the current conventional methods used in industry. It offers the following advantages over the competition: Consumes 6x less energy 3x cheaper to operate Capable of recovering different PGM simultaneously with high yield even from low-grade waste This technology allows companies to recycle their spent catalyst in a truly green and sustainable manner.

Pre-combustion, post-combustion and oxyfuel combustion capturing from power plants and other industrial scale companies are the three current carbon dioxide (CO2) capture and separation technologies. Unlike liquid and membrane adsorbents, solid adsorbents have a wider temperature range of adsorption and can be safely disposed in the environment. The use of solid adsorbents in industrial exhaust gases has shown to be a successful method of trapping concentrated CO2 for later storage rather than direct emission to the environment. Recent investigations have identified magnesium oxide based (MgO) solid adsorbents as a potential material for CO2 capture at intermediate temperatures. Furthermore, magnesium (Mg) based minerals are nontoxic, abundant materials which can be prepared in large scale at relatively low cost. Even though MgO has a high theoretical CO2 capture capacity (1100 mg CO2/g sorbent), it underperforms in practical applications due to a limiting number of active CO2 capture sites. MgO reacts with CO2 to create MgCO3 in dry, high-temperature circumstances. The formation of such MgCO3 carbonates obstructs additional carbon lattice transit leads which lowers the total CO2 capture efficiency. This technology offer is an anion doping method of MgO at room temperature to prevent the formation of MgCO3. The novel MgO-Mg(OH)2 composite nanomaterial is formed via electrospinning technology and improves the overall efficiency of MgO as a CO2 capture material.

Manufacturing plants constantly seek opportunities to save energy, reduce cost, and be more environmentally sustainable. However, achieving these goals often requires heavy expenditure in the form of hiring teams of experienced engineers, who then perform cost-reduction tasks manually - this method is time-consuming, costly, and prone to inaccuracies due to the risk of human error.  This technology offer provides a no-code Artificial Intelligence (AI) powered platform that monitors energy consumption, carbon dioxide(CO2) emission, and operational expenditures (OPEX) in real-time. The AI engine builds a virtual cognitive model (digital twin) of a physical asset, e.g. a manufacturing plant or a piece of machinary. Simulations are carried out on the model to predict operational inefficiency i.e. high energy usage, equipment breakdown, etc. Upon detection of inefficiencies, the engine is able to suggest the best operating parameters to resolve the inefficiency.

Existing methods for load monitoring typically focus primarily on residential building data, while few look at the effectiveness of such systems for industrial or commercial buildings. Apart from the use of this technology for real-time supply-demand response, such methods can be extended for use in anomaly detection, small-scale load change detection, or an estimation of energy usage, without the associated high costs of sub-metering equipment. The proliferation of neural networks for such demanding tasks solves the computationally expensive problem of traditional methods like Hidden Markov Models (HMM) and fuzzy clustering algorithms. This technology offer is a neural network solution for residential and industrial energy management. It utilises a time-series forecasting tool to predict load, renewable energy generation, and electricity prices, without the need for costly sub-metering equipment. It is based on reinforcement learning algorithms which are trained by rewarding and penalising neural network algorithms for good or bad decisions respectively, the solution is a non-intrusive technique that helps residential and commercial end-users save on energy costs in the open energy market by scheduling their load demand for heating, ventilation, air conditioning (HVAC) systems, washing machines, and charging of their Electric Vehicles (EVs).

To date, the current primary feedstock for plastic production is oil, which accounts for more than 850 million metric tons of greenhouse gases emissions per year. Hence, there has been an increasing demand for green plastics, which are plastic materials produced from renewable sources. This technology offer is a synthesis method of green plastics from carbon dioxide (CO2) and renewable feedstock. The green plastics produced are non-isocyanate polyurethanes (NIPUs) and can be actively tuned to be anionic, cationic, oil-soluble and cross-linkable which enables a wide range of applications. These NIPUs are non-skin irritant, have high bio-content and can possibly be made to be bio-degradable. This technology owner is looking for partners in various industries such as personal and consumer care, coatings and lubricant additives (to name a few) for further co-development of the solution. The technology owner is keen to license this technology as well.