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This technology provides a process for converting non-biodegradable waste plastics, such as low-density polyethylene, high-density polyethylene, and polypropylene, into liquid and gaseous hydrocarbon fuels via catalytic cracking. Utilizing low-cost, bio-renewable rice husk ash, the process uses derived porous silica and chemically modified silica-alumina as effective cracking catalysts. Operating in a two-stage process involving pre-melting at 200–300°C followed by catalytic cracking at 400–500°C in an oxygen-free environment, the system yields high-quality liquid hydrocarbon fuels primarily in the gasoline range (C5–C11) alongside valuable olefinic fuel gases.
This technology relates to a smart vehicle safety and monitoring system for twowheelers designed to mitigate road accidents caused by rider negligence, non-compliance, or impairment. The system integrates two main operational modules: a helmet unit and a vehicle unit that communicate interactively to enforce safety protocols prior to ignition. The helmet unit detects helmet compliance and senses alcohol consumption; if the rider is unhelmeted or under the influence of alcohol, the system automatically disables the vehicle's ignition. Additionally, the vehicle unit incorporates multi-sensor detection— monitoring acceleration, vibration, and tilting angles—to continuously assess vehicle stability and immediately transmit automated emergency alert messages to designated devices in the event of an accident or abnormal riding behavior.
This technology relates to a novel Field Effect Transistor (FET) device and its fabrication method, designed to optimize electron flow and channel control. The structure features a silicon substrate supporting a vertically positioned gate terminal along with one or more C-shaped silicon nanosheets attached to the gate. Each C-shaped nanosheet is enrobed in a high-k hafnium oxide (HfO2) layer to provide robust dielectric insulation. Integrated with source and drain regions situated on adjacent sides of the nanosheets to inject and collect electrons, this dual-channel C-shaped nanosheet architecture significantly enhances gate control, reduces leakage current, and ensures efficient carrier transport across the individual conduction channels.
This technology relates to a High Electron Mobility Transistor (HEMT) field-effect transistor device and its manufacturing method, featuring a novel gate terminal configuration designed to enhance electron mobility. The HEMT structure incorporates a gate material formed into an inverted U-shape positioned on top of a hafnium oxide (HfO2) layer, creating dual contacts across the device. This configuration optimizes the two-dimensional electron gas (2DEG) channel formed at the heterojunction interface between the Aluminum Gallium Nitride (AlGaN) and Gallium Nitride (GaN) layers. By leveraging dual-contact gate control and a high-k dielectric layer, the architecture significantly boosts carrier transport efficiency and switching performance over conventional singlecontact HEMT designs.
This technology relates to a planar Nanosheet MOSFET device designed for the rapid, label-free analysis of water molecules using dielectric permittivity sensing. The device integrates a silicon source region, channel region, and drain region with a gate structure positioned directly over the channel. An embedded nanocavity with optimized dimensions holds the sample water analyte, while a silicon dioxide insulating layer isolates the gate and channel to minimize leakage current and optimize sensitivity. By measuring changes in drain current induced by variations in the dielectric permittivity of water samples (such as differentiating soft snow dynamics), the planar nanosheet architecture delivers an expanded active sensing surface area, enhanced electric field distribution, and effective suppression of short-channel effects.
This technology relates to a sustainable geopolymer concrete block composition and manufacturing method that utilizes industrial by-products to eliminate the need for conventional cement and natural sand. The composition combines copper slag (CS) as a 100% fine aggregate replacement with ground granulated blast furnace slag (GGBS) as the primary binder, activated using an alkaline solution of sodium hydroxide and sodium silicate with controlled water content. Through mechanical dry mixing, liquid activation, vibratory compaction, and ambient-air curing, the geopolymer matrix achieves high early strength and exceptional durability. The resulting eco-friendly paver blocks reduce CO2 emissions, divert heavy industrial waste from landfills, and minimize chemical activator consumption while delivering high-performance structural capabilities suitable for heavy-traffic civil infrastructure.
This Technology relates to a smart miniature circuit breaker (ADAPTIVE MCB) that combines intelligent protection, wireless communication, and real-time analytics for enhanced electrical safety. The system integrates modules for voltage and current protection, fault detection, relay-based load management, RTDenabled thermal trip, and secure over-the-air firmware updates. An STM32 microcontroller processes sensor inputs and executes decision logic to isolate or restore electrical loads, while an ESP8285 Wi-Fi module provides cloud connectivity, remote configuration, and fault alerts. Additional features include lightning strike protection, LCD display with tactile input keys, automatic reconnection, programmable scheduling, and energy data logging for predictive maintenance. The compact design reduces system complexity and supports integration with IoT platforms. Applicable to residential, commercial, and industrial environments, the ADAPTIVE MCB delivers self-healing fault rectification, improved reliability, and intelligent energy automation.
This technology provides a system and method for real-time digital twin simulation of industrial machinery using mixed reality (AR/VR). Operational signals captured from machine sensors (such as temperature, pressure, vibration, and IMU data) are processed by a plant controller and transmitted to a user device, where processing circuitry maps the real-time data onto pre-stored 3D volumetric images or models (such as NeRF, point cloud, or voxel rendering). Utilizing spatial tracking and depth sensing technologies—including LiDAR, SLAM, and structured light projection—the system dynamically aligns and synchronizes the digital twin simulation directly with physical machine geometry. The solution integrates realtime physics-based modeling (CFD, FEA, MBD) alongside machine learning algorithms to superimpose color-coded performance metrics, anomaly highlights, and predictive maintenance insights directly onto the physical asset.
This technology provides an autonomous rover device, system, and method for automated garbage collection and waste sorting. Designed with a dual-frame structure comprising a running frame and a vertical frame, the rover utilizes a motor-driven gear and dual-chain mechanism equipped with sewer blades to sweep and scoop up litter. The system integrates onboard image sensors to locate waste and navigate autonomously—even during communication losses —alongside sorting sensors and an internal moveable triangle frame to categorize and evenly distribute collected garbage within its storage box. Connected via a central server to user devices, terrain sensors, and external surveillance pole cameras, the system dynamically validates coordinates and dispatches nearby rovers for realtime waste clearance.