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🎓 Зимовий вступ 2026 у КПІ: нульовий курс «Відкритий шлях до вищої освіти» kpi ср, 01/07/2026 - 12:00

Union Electronics and IT Minister Ashwini Vaishnaw predicted that ‘Bharat’ will become a major player in the entire electronics stack, in terms of design, manufacturing, operating system, applications, materials, and equipment.

In an X post, the Union Minister drew attention to a major milestone for Prime Minister Narendra Modi’s ‘Make in India’ initiative and making India a major producer economy since Apple shipped $50 billion worth of mobile phones in 2025.

“Electronics production has increased six times in the last 11 years. And electronics exports have grown 8 times under PM Modi’s focused leadership. This progress has propelled electronics products among the top three exported items,” Vaishnaw noted.

He further informed that 46 component manufacturing projects, laptop, server, and hearable manufacturers had added to the ecosystem, which are making electronics manufacturing a major driver of the manufacturing economy.

“Four semiconductor plants will start commercial production this year. Total jobs in electronics manufacturing are now 25 lakh, with many factories employing more than 5,000 employees in a single location. Some plants employ as many as 40,000 employees in a single location,” the minister informed, adding that “this is just the beginning”.

Last week, the industry welcomed the approval of 22 new proposals under the third tranche of the Electronics Components Manufacturing Scheme (ECMS) by the government, saying that it marks a decisive inflexion point in India’s journey towards deep manufacturing and the creation of globally competitive Indian champions in electronics components.

With this, the total number of ECMS-approved projects rises to 46, taking cumulative approved investments to over Rs 54,500 crore. Earlier tranches saw seven projects worth Rs 5,532 crore approved on October 22 and 17 projects amounting to Rs 7,172 crore on November 17. The rapid scale-up across tranches underscores the strong industry response and the growing confidence in India’s components manufacturing vision.

According to the IT Ministry, the 22 projects approved in the third tranche are expected to generate production worth Rs 2,58,152 crore and create 33,791 direct jobs.

The post “‘Bharat’ will become a major player in entire electronics stack…”, Predicts Union Minister, Ashwini Vaishnaw appeared first on ELE Times.

EDOM Technology announced the introduction of the NVIDIA Jetson T4000 edge AI module, addressing the growing demand from system integrators, equipment manufacturers, and enterprise customers for balanced performance, power efficiency, and deployment flexibility. With powerful inference capability and a lightweight design, NVIDIA Jetson T4000 enables faster implementation of practical physical AI applications.

Powered by NVIDIA Blackwell architecture, NVIDIA Jetson T4000 supports Transformer Engine and Multi-Instance GPU (MIG) technologies. The module integrates a 12-core Arm Neoverse-V3AE CPU, three 25GbE network interfaces, and a wide range of I/O options, making it well-suited for low-latency, multi-sensor, and real-time computing requirements. In addition, Jetson T4000 features a third-generation programmable vision accelerator (PVA), dual encoders and decoders, and an optical flow accelerator. These dedicated hardware engines allow stable AI inference even under constrained compute and power budgets, making the platform particularly suitable for mid-range models and real-time edge applications.

For system integrators (SIs), the modular architecture of Jetson T4000, combined with NVIDIA’s mature software ecosystem, enables rapid integration of vision, sensing, and control systems. This significantly shortens development and validation cycles while improving project delivery efficiency, especially for multi-site and scalable edge AI deployments.

For equipment manufacturers, Jetson T4000’s compact form factor and low-power design allow flexible integration into a wide range of end devices, including advanced robotics, industrial equipment, smart terminals, machine vision systems, and edge controllers. These capabilities help manufacturers bring stable AI inference into products with limited space and power budgets, accelerating intelligent product upgrades.

Enterprise users can deploy Jetson T4000 across diverse scenarios such as smart factories, smart retail, security, and edge sensor data processing. By performing inference and data pre-processing at the edge, organisations can reduce system latency, lower cloud workloads, and improve overall operational efficiency—while maintaining system stability and deployment flexibility.

In robotics and automation applications, Jetson T4000 features low power consumption, high-speed I/O and a compact footprint, making it an ideal platform for small mobile robots, educational robots, and autonomous inspection systems, delivering efficient and reliable AI computing for a wide range of automation use cases.

NVIDIA Jetson product lineup spans from lightweight to high-performance modules, including Jetson T4000 and T5000, addressing diverse requirements ranging from compact edge devices and industrial control systems to higher-performance inference applications. With NVIDIA’s comprehensive AI development tools and SDKs, developers can rapidly port models, optimise inference performance, and seamlessly integrate AI capabilities into existing system architectures.

Beyond supplying Jetson T4000 modules, EDOM Technology leverages its extensive ecosystem of partners across chips, modules, system integration, and application development. Based on the specific development stages and requirements of system integrators, equipment manufacturers, and enterprise customers, EDOM provides end-to-end support—from early-stage planning and technical consulting to ecosystem enablement. By sharing ecosystem expertise and practical experience, EDOM helps both existing customers and new entrants to the edge AI domain quickly build application capabilities and deploy edge AI solutions tailored to real-world scenarios.

The post NVIDIA’s Jetson T4000 for Lightweight & Stable Edge AI Unveiled by EDOM appeared first on ELE Times.

Anritsu Corporation will exhibit Battery Cycler and Emulation Test System RZ-X2-100K-HG, planned for sale in the North American market as an evaluation solution for eMobility, at CES 2026 (Consumer Electronics Show), one of the world’s largest technology exhibitions to be held in Las Vegas, USA, from January 6 to January 9, 2026.

The launch of the RZ-X2-100K-HG in the North American market represents the first step in the global expansion efforts of TAKASAGO, LTD., which holds a significant share in the domestic EV development market, and it is an important measure looking ahead to future global market growth.

At CES 2026, a concept exhibition will showcase the Power HIL evaluation system combining the RZ-X2-100K-HG with dSPACE’s HIL simulator, demonstrating a new direction for the EV evaluation process.

Additionally, the power measurement solutions from DEWETRON, which joined the Anritsu Group in October 2025, will also be exhibited. Using a three-phase motor performance evaluation demonstration, we will present example applications.

About the RZ-X2-100K-HG

The RZ-X2-100K-HG is a test system developed by TAKASAGO, LTD. of the Anritsu Group, equipped with functions for charge-discharge testing and battery emulation that support high voltage and large current. It is a model based on the RZ-X2-100K-H, which has a proven track record in Japan, adapted to comply with the United States safety standards and input power specifications. This system is expected to be used for testing the performance, durability, and safety of automotive batteries and powertrain devices in North America.

About Power HIL

Power HIL (Power Hardware-in-the-Loop) is an extended simulation technology that combines virtual and real elements by adding a “real power supply function” to HIL (Hardware-in-the-Loop). Power HIL creates a virtual vehicle environment with real power, reproducing EV driving tests and charging tests compatible with multiple charging standards under conditions close to reality. This allows for high-precision and efficient evaluation of battery performance, safety, and charging compatibility without using an actual vehicle.

Terminology Explanation

[*] Battery Emulation Test System

A technology that simulates the behaviour of real batteries (voltage, current, internal resistance, etc.) using a power supply device to evaluate how in-vehicle equipment operates.

The post Anritsu to Bring the Future of Electrification Testing at CES 2026 appeared first on ELE Times.

Keysight Technologies, Inc. introduced Keysight AI Software Integrity Builder, a new software solution designed to transform how AI-enabled systems are validated and maintained to ensure trustworthiness. As regulatory scrutiny increases and AI development becomes increasingly complex, the solution delivers transparent, adaptable, and data-driven AI assurance for safety-critical environments such as automotive.

AI systems operate as complex, dynamic entities, yet their internal decision processes often remain opaque. This lack of transparency creates significant challenges for industries, such as automotive, that must demonstrate safety, reliability, and regulatory compliance. Developers struggle to diagnose dataset or model limitations, while emerging standards — such as ISO/PAS 8800 for automotive and the EU AI Act- mandate explainability and validation without prescribing clear methods. Fragmented toolchains further complicate engineering workflows and heighten the risk of conformance gaps.

Keysight AI Software Integrity Builder introduces a unified, lifecycle-based framework that answers the critical question: “What is happening inside the AI system, and how do I ensure it behaves safely in deployment?” The solution equips engineering teams with the evidence needed for regulatory conformance and enables continuous improvement of AI models. Unlike fragmented toolchains that address isolated aspects of AI testing, Keysight’s integrated approach spans dataset analysis, model validation, real-world inference testing, and continuous monitoring.

Core capabilities of Keysight AI Software Integrity Builder include:

• Dataset Analysis: Analyse data quality using statistical methods to uncover biases, gaps, and inconsistencies that may affect model performance.
• Model-Based Validation: Explains model decisions and uncovers hidden correlations, enabling developers to understand the patterns and limitations of an AI system.
• Inference-Based Testing: Evaluates how models behave under real-world conditions, detects deviations from training behaviour, and recommends improvements for future iterations.

While open-source tools and vendor solutions typically address only isolated aspects of AI testing, Keysight closes the gap between training and deployment. The solution not only validates what a model has learned, but also how it performs in operational scenarios — an essential requirement for high-risk applications such as autonomous driving.

Thomas Goetzl, Vice President and General Manager of Keysight’s Automotive & Energy Solutions, said: “AI assurance and functional safety of AI in vehicles are becoming critical challenges. Standards and regulatory frameworks define the objectives, but not the path to achieving a reliable and trustworthy AI deployment. By combining our deep expertise in test and measurement with advanced AI validation capabilities, Keysight provides customers with the tools to build trustworthy AI systems backed by safety evidence and aligned with regulatory requirements.”

With AI Software Integrity Builder, Keysight empowers engineering teams to move from fragmented testing to a unified AI assurance strategy, enabling them to deploy AI systems that are not only performant but also transparent, auditable, and compliant by design.

The post Keysight’s Software Solution for Reliable AI Deployment in Safety-Critical Environments appeared first on ELE Times.

Courtesy: Orbit & Skyline

In the semiconductor ecosystem, we are familiar with the chips that go into our devices. Of course, they do not start as chips but are made into the familiar form once the process is complete. It is easy to imagine how to arrive at that end in silicon-based technology, but things are far more interesting in the III-V tech world. Here, we must first achieve the said III-V film using a thin-film deposition method. It is obvious that this would form the bedrock of the device, and quality is critical. Minimal defects, highest mobility, and a plethora of demands following the advent of technology have made this aspect extremely important in today’s world.

In this blog, we will cover how Molecular Beam Epitaxy (MBE) enables the growth of GaAs-based devices, its history, advantages, challenges, and the wide range of optoelectronic applications it supports. Looking to optimise thin-film growth or improve device yield? Explore our Semiconductor FAB Solutions for end-to-end support across Equipment, Process, and Material Supply.

What Is Molecular Beam Epitaxy (MBE)?

Molecular Beam Epitaxy (MBE) is a well-known thin-film growth technique developed in the 1960s. Using ultra-high vacuum (UHV) conditions, it grows high-purity thin films with atomic-level control over the thickness and doping concentration of the layers. This provides excellent control to tune device properties and, in the case of III–V films, bandgap engineering. Such sought-after features make MBE widely renowned for producing the best-quality films, which currently lead device performance in applications such as LEDs, solar cells, sensors, detectors, and power electronics.

However, its major drawbacks include high costs and slow growth rates, limiting large-scale industry adoption. Need support with MBE tool installation, calibration, or fab floor setup? Our Global Field Engineering and Fab Facility Solutions teams can help.

A Brief History of MBE Technology

The concept of Molecular Beam Epitaxy was first introduced by K.G. Günther in a 1958 publication. Even though his films were not epitaxial—being deposited on glass, John Davey and Titus Pankey expanded his ideas to demonstrate the now-familiar MBE process for depositing GaAs epitaxial films on single-crystal GaAs substrates in 1968.

The final version of the technology was given by Arthur and Cho in the late 1960s, observing the MBE process using a Reflection High Energy Electron Diffraction (RHEED) in-situ process. If you work with legacy MBE platforms or require upgrade support, our Legacy Tool Management Services ensure continuity and extended tool life.

Why GaAs? The First Semiconductor Grown by MBE

The first semiconductor material to be grown using MBE, gallium arsenide or GaAs for short, is one of the leading III-V semiconductors in high-performance optoelectronics such as solar cells, photodetectors, lasers, etc. Due to its several interesting properties, such as a high band gap of 1.43 eV, high mobility, high absorption coefficient, and radiation hardness, it finds use in sophisticated applications such as space photovoltaics as well as infrared detectors and next-generation quantum devices.

Since GaAs was the first material to be studied using the MBE method, it is far better understood with decades of research on devices. The efficiency of heterojunction solar cells grown on substrates such as Ge was as high as 15-20% in the 1980s. Although the current numbers are the best in the industry, using MBE for growing GaAs solar cells comes with its own set of challenges and advantages:

• Throughput and cost: Commercially, it is not as viable as some of the other vapor phase growth techniques since it is a slow and expensive process. Growth rates of MBE films are usually in the range of ~1.0 μm/h, which are far behind the CVD achieved rates of up to ~200 μm/h.
• Thickness and uniformity: Solar cell structures require absorber layers with thicknesses of the order of several microns. Maintaining uniformity over such a range is not trivial.
• Defect management: Thin films are beset with a range of defects such as dislocations, antisite defects, point defects, background impurities and so on. Optoelectronic devices suffer heavily due to the presence of defects as carrier lifetimes reduce and consequently open circuit voltage and fill factor. Therefore, multiple factors such as substrate quality, interface sharpness, and growth conditions are mandatory.
• Doping and alloy incorporation: MBE is one of the best techniques to dope and make alloys, especially when it comes to III-V compounds. Band gap engineering to expand the available bandwidth for solar absorption is one of the most important advantages of using MBE. When making multiple junctions or tandem cells, several growth challenges, such as phase separation, strain, and exact control of the composition of each layer, are challenging.
• Surface and interface quality: Interfacial strain is one of the major causes of loss of carriers due to recombination. When making solar cell stacks, there are multiple layers where interfaces are required, such as window layers, tunnel junctions, and passivation layers. MBE is excellent at providing abrupt interfaces due to its fast shutter speed and ultra-high vacuum conditions, resulting in high-performance devices.

A lot of the advantages of MBE are nullified due to its challenges, which makes it more of a hybrid technique when it comes to industrial applications. This has resulted in the usage of higher throughput methods, such as MOVPE/MOCVD, along with hybrid attempts to improve efficiency.

Other Optoelectronic Devices Grown Using MBE

In III-V materials and beyond, MBE has excelled in growing device-quality layers of several other types of optoelectronic structures:

• LASERs and VCSELs: One of the most grown stacks by MBE is of AlGaAs/GaAs heterostructure for quantum well lasers and vertical cavity surface emitting lasers (VCSELs). AlGaAs/GaAs multi-quantum well VCSELs with distributed Bragg reflectors (DBRs) have been successfully demonstrated with threshold currents, continuous wave operations at elevated temperatures, GHz modulation speeds, etc.
• Quantum Cascade LASERs (QCLs): The same GaAs/AlGaAs heterostructures have been fabricated for application in mid-infrared QCLs using MBE. Its specialty in producing abrupt interfaces and controlled doping is used in growth methods to reduce interface roughness and improve performance.
• Infrared Photodetectors: A leading IR photodetector currently is HgCdTe (MCT), which has been grown using MBE on GaAs substrates. GaSb-based nBn detectors are also grown using superlattices of InAs/GaSb, which reduces lattice mismatch due to buffer layers.
• High mobility 2D electron gas heterostructures: One of the most important discoveries of the last couple of decades has been that of 2-dimensional electron gas, which has led to applications such as high electron mobility transistor (HEMT). AlGaAs/GaAs heterostructures support the formation of this 2DEG, where the purity of the source material is critical. MBE grown films have shown mobilities as high as ~ 35 x 106 cm2/V.s.

Conclusion

MBE is a complex, slow process that has largely been confined to R&D labs traditionally. However, the quality of the deposited layers is unparalleled and has helped in improving and discovering new devices. In the last decade or so, there has been partial adoption of MBE in the industry due to the ability of the tool to provide cutting-edge device quality. However, mass adoption is unlikely due to the low quantity of wafers that are possible to grow at a time, and so we remain content with discovering the next generation of devices.

The post Molecular Beam Epitaxy (MBE) Growth of GaAs-Based Devices appeared first on ELE Times.

Fabless firm Cambridge GaN Devices Ltd (CGD) — which was spun out of the University of Cambridge in 2016 to design, develop and commercialize power transistors and ICs that use GaN-on-silicon substrates — has appointed Fabio Necco as chief executive officer. The move is designed to drive forward CGD’s entry into key markets...

This is an SoC Camera sensor and controller from an old webcam likely manufactured in the early 2000s hence that chip is manufactured in 2004 (the year i was born in lol) i found this camera in my grandparents house a decade ago i grapped it as a kid and thought it was cool and disassembled it and through it in a big plastic bag along with my cool junk collection. A decade later i found it's pcb (the shell is no where to be found lol) and desoldered it's components and found that SoC chip that i thought it's pretty cool! submitted by /u/inevitable_47 [link] [comments]