The investigation of mould inserts in the injection moulding process using metal epoxy composite (MEC) with pure metal filler particles is gaining popularity among researchers. Therefore, to attain zero emissions, the idea of recycling metal waste from industries and workshops must be investigated (waste free) because metal recycling conserves natural resources while requiring less energy to manufacture new products than virgin raw materials would. The utilisation of metal scrap for rapid tooling (RT) in the injection moulding industry is a fascinating and potentially viable approach. On the other hand, epoxy that can endure high temperatures (>220 °C) is challenging to find and expensive. Meanwhile, industrial scrap from coal-fired power plants can be a precursor to creating geopolymer materials with desired physical and mechanical qualities for RT applications. One intriguing attribute of geopolymer is its ability to endure temperatures up to 1000 °C. Nonetheless, geopolymer has a higher compressive strength of 60-80 MPa (8700-11,600 psi) than epoxy (68.95 MPa) (10,000 psi). Aside from its low cost, geopolymer offers superior resilience to harsh environments and high compressive and flexural strength. This research aims to investigate the possibility of generating a new sustainable material by integrating several types of metals in green geopolymer metal composite (GGMC) mould inserts for RT in the injection moulding process. It is necessary to examine and investigate the optimal formulation of GGMC as mould inserts for RT in the injection moulding process. With less expensive and more ecologically friendly components, the GGMC is expected to be a superior choice as a mould insert for RT. This research substantially impacts environmental preservation, cost reduction, and maintaining and sustaining the metal waste management system. As a result of the lower cost of recycled metals, sectors such as mould-making and machining will profit the most.
The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CERN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140 fb^{-1} for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.