Новини світу мікро- та наноелектроніки

This is my highschool electronics project, made this at around 15 years old it uses Binary adders, counters and cimparators and has alarm and time adjustment submitted by /u/ZephKeks [link] [comments]

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On the photos you can see the display module I made hooked up to my Arduino. I’m working on the boost and MCU board now, this is also my fist PCB design and I’m so proud of it! More infos, pictures and gerber here submitted by /u/Shyne-on [link] [comments]

submitted by /u/External_Asparagus10 [link] [comments]

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The UK has joined the European Union’s ‘Chips Joint Undertaking’ as a participating state, giving British semiconductor researchers and businesses enhanced access to a €1.3bn fund set aside from Horizon Europe (the European Union’s scientific research initiative) to support research in semiconductor technologies over 2021-2027...

Sivers Semiconductors AB of Kista, Sweden (which supplies ICs and modules for communications and sensor solutions) says that its subsidiary Sivers Photonics of Glasgow, Scotland, UK has signed a product development agreement with an undisclosed company, helping to develop photonic laser arrays enabling next-generation artificial intelligence (AI)...

Infineon Technologies AG has announced the integration of its OPTIGA Trust M security controller, with tamper-resistant hardware certified to Common Criteria EAL6+, with the Verified Boot technology by Thistle Technologies, a pioneer of advanced security solutions for connected devices. This integration enables designers to easily defend their devices against firmware tampering and protect the software supply chain integrity. The result is improved end-user security, which is particularly important in industries with high security requirements such as healthcare, automotive and device manufacturing.

Thistle Technologies Verified Boot provides a secured boot process for IoT devices. Enhanced integrity checks cryptographically examine that the device firmware has not been tampered with. The solution supports the needs of a wide range of IoT devices for smart homes, smart cities and smart buildings, among others, enabling easy implementation with minimal development time. By leveraging the robust security features of Infineon’s OPTIGA Trust M, including its hardware-based root-of-trust, the technology offers a high level of protection against unauthorized firmware modifications and sophisticated cyberattacks.

“Since the start of our partnership in January 2023, Thistle has developed a software integration for our OPTIGA Trust M within Linux to extend our hardware capability into the application software domain for Linux-based system architectures,” said Vijayaraghavan Narayanan, Senior Director and Head of Edge Identity & Authentication at Infineon. “The new solution enables our shared customers to quickly enhance the security of their development.”

“Integrating our Verified Boot technology with Infineon’s OPTIGA Trust M is a significant step forward in making it easy to incorporate sophisticated security capabilities into devices quickly,” said Window Snyder, CEO of Thistle Technologies.

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Infineon Technologies AG has filed a lawsuit, through its subsidiary Infineon Technologies Austria AG, against Innoscience (Zhuhai) Technology Company, Ltd., and Innoscience America, Inc. and affiliates (hereinafter: Innoscience). Infineon is seeking a permanent injunction for infringement of a United States patent relating to gallium nitride (GaN) technology owned by Infineon. The patent claims cover core aspects of GaN power semiconductors encompassing innovations that enable the reliability and performance of Infineon’s proprietary GaN devices. The lawsuit was filed in the district court of the Central District of California.

Infineon alleges that Innoscience infringes the Infineon patent mentioned above by making, using, selling, offering to sell and/or importing into the United States various products, including GaN transistors for numerous applications, within automotive, data centres, solar, motor drives, consumer electronics, and related products used in automotive, industrial, and commercial applications.

“The production of gallium nitride power transistors requires completely new semiconductor designs and processes”, said Adam White, President of Infineon’s Power & Sensor Systems Division. “With nearly two decades of GaN experience, Infineon can guarantee the outstanding quality required for the highest performance in the respective end products. We vigorously protect our intellectual property and thus act in the interest of all customers and end users.” Infineon has been investing in R&D, product development and manufacturing expertise related to GaN technology for decades. Infineon continues to defend its intellectual property and protect its investments.

On 24 October 2023, Infineon announced the closing of the acquisition of GaN Systems Inc., becoming a leading GaN powerhouse and further expanding its leading position in power semiconductors. Infineon leads the industry with its GaN patent portfolio, comprising around 350 patent families. Market analysts expect the GaN revenue for power applications to grow by 49% CAGR to approximately US$2 billion by 2028 (source: Yole, Power SiC and GaN Compound Semiconductor Market Monitor Q4 2023). Gallium nitride is a wide bandgap semiconductor with superior switching performance that allows smaller size, higher efficiency and lower-cost power systems.

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Infineon Technologies AG introduces the new CoolSiC MOSFETs 2000 V in the TO-247PLUS-4-HCC package to meet designers’ demand for increased power density without compromising the system’s reliability even under demanding high voltage and switching frequency conditions. The CoolSiC MOSFETs offer a higher DC link voltage so that the power can be increased without increasing the current. It is the first discrete silicon carbide device with a breakdown voltage of 2000 V on the market and comes in a TO-247PLUS-4-HCC package with a creepage distance of 14 mm and a clearance distance of 5.4 mm. With low switching losses, the devices are ideal for solar (e.g. string inverters) as well as energy storage systems and electric vehicle charging applications.

The CoolSiC MOSFET 2000 V product family is ideally suited for high DC link systems with up to 1500 VDC. Compared to 1700 V SiC MOSFETs, the devices also provide a sufficiently high overvoltage margin for 1500 VDC systems. The CoolSiC MOSFETs deliver a benchmark gate threshold voltage of 4.5 V and are equipped with a robust body diode for hard commutation. Due to the .XT connection technology, the components offer first-class thermal performance. They are also highly resistant to humidity.

In addition to the CoolSiC MOSFETs 2000 V, Infineon will soon be launching the matching CoolSiC diodes: The first launch will be the 2000 V diode portfolio in the TO-247PLUS 4-pin package in the third quarter of 2024, followed by the 2000 V CoolSiC diode portfolio in the TO-247-2 package in the final quarter of 2024. These diodes are particularly suitable for solar applications. A matching gate driver portfolio is also available.

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Motor drive applications are taking a leap forward with the launch of the Infineon Technologies AG OptiMOS 6 200 V MOSFET product family. The new portfolio is designed to deliver optimal performance in applications such as e-scooters, micro-EVs, and E-forklifts. The improved conduction losses and switching behaviour for these new MOSFETs reduce the electromagnetic interference (EMI) and switching losses. This benefits various switching applications, including servers, telecom, energy storage systems (ESS), audio, solar and others. Additionally, the combination of a wide safe operating area (SOA) and industry-leading RDS(on) results in a perfect fit for static switching applications such as battery management systems. With the introduction of the new OptiMOS 6 200 V product family, Infineon sets a new industry benchmark with increased power density, efficiency, and system reliability for its customers’ benefit.

The OptiMOS 6 200 V portfolio delivers enhanced technical features compared to its predecessor, the OptiMOS 3. It features a 42 per cent lower RDS(on) that contributes to reduced conduction losses and increased output power. Regarding diode behaviour, the OptiMOS 6 200 V provides a significant increase in softness, more than three times that of the OptiMOS 3. Combined with up to 89 per cent reduction in Qrr(typ), the switching and EMI behaviours are significantly improved. The technology also features improvements in parasitic capacitance linearity (Coss and Crss), which reduces oscillation during switching and lowers voltage overshoot. A tighter VGS(th) spread and lower transconductance aid in MOSFET paralleling and current sharing, leading to more uniform temperatures and reducing the number of paralleled MOSFETs.

The OptiMOS 6 200 V products feature an improved SOA and are classified as MSL 1 according to J-STD-020. These RoHS-compliant, lead-free products align with current industry standards.

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The high-bandwidth memory (HBM) landscape, steadily growing in importance for its critical pairing with artificial intelligence (AI) processors, is ready to move to its next manifestation, HBM3e, increasing data transfer rate and peak memory bandwidth by 44%. Here, SK hynix, which launched the first HBM chip in 2013, is also the first to offer HBM3e validation for Nvidia’s H-200 AI hardware.

HBM is a high-performance memory that stacks chips on top of one another and connects them with through-silicon vias (TSVs) for faster and more energy-efficient data processing. The demand for HBM memory chips has boomed with the growing popularity of generative AI. However, it’s currently facing a supply bottleneck caused by both packaging constraints and the inherently long production cycle of HBM.

Figure 1 SK hynix aims to maintain its lead by releasing an HBM3e device with 16 layers of DRAM and a single-stack speed of up to 1,280 GB/s.

According to TrendForce, 2024 will mark the transition from HBM3 to HBM3e, and SK hynix is leading the pack with HBM3e validation in the first quarter of this year. It’s worth mentioning that SK hynix is currently the primary supplier of HBM3 memory chips for Nvidia’s H100 AI solutions.

Samsung, now fighting back to make up for the lost space, has received certification for AMD’s AMD MI300 series AI accelerators. That’s a significant breakthrough for the Suwon, South Korea-based memory supplier, as AMD’s AI accelerators are expected to scale up later this year.

Micron, which largely missed the HBM opportunity, is also catching up by launching the next iteration, HBM3e, for Nvidia’s H200 GPUs by the end of the first quarter in 2024. Nvidia’s H200 GPUs will start shipping in the second quarter of 2024.

Figure 2 The 8H HBM3e memory offering 24 GB will be part of Nvidia’s H200 Tensor Core GPUs, which will begin shipping in the second quarter of 2024. Source: Micron

It’s important to note that when it comes to HBM technology, SK hynix has remained ahead of its two mega competitors—Micron and Samsung—since 2013, when SK hynix introduced HBM memory in partnership with AMD. It took Samsung two years to challenge its South Korean neighbor when it developed the HBM2 device in late 2015.

But the rivalry between SK hynix and Samsung is more than merely a first-mover advantage. While Samsung chose the conventional non-conductive film (NCF) technology for producing HBM chips, SK hynix switched to the mass reflow molded underfill (MR-MUF) method to address NFC limitations. According to a Reuters report, while SK hynix has secured about 60-70% yield rates for its HBM3 production, Samsung’s HBM3 production yields stand at nearly 10-20%.

The MUF process involves injecting and then hardening liquid material between layers of silicon, which in turn, improves heat dissipation and production yields. Here, SK hynix teamed up with a Japanese materials engineering firm Namics while sourcing MUF materials from Nagase. SK hynix adopted the mass reflow molded underfill technique ahead of others and subsequently became the first vendor to supply HBM3 chips to Nvidia.

Recent trade media reports suggest Samsung is in contact with MUF material suppliers, though the memory supplier has vowed to stick to its NFC technology for the upcoming HBM3e chips. However, industry observers point out that Samsung’s MUF technology will not be ready until 2025 anyway. So, it’s likely that Samsung will use both NFC and MUF techniques to manufacture the latest HBM3 chips.

Both Micron and Samsung are making strides to narrow the gap with SK hynix as the industry moves from HBM3 to HBM3e memory chips. Samsung, for instance, has announced that it has developed an HBM3e device with 12 layers of DRAM chips, and it boasts the industry’s largest capacity of 36 GB.

Figure 3 The HBM3E 12H delivers a bandwidth of up to 1,280 GB/s and a storage capacity of 36 GB. Source: Samsung

Likewise, Idaho-based Micron claims to have started volume production of its 8-layer HBM3e device offering 24-GB capacity. As mentioned earlier, it’ll be part of Nvidia’s H200 Tensor Core units shipping in the second quarter. Still, SK hynix seems to be ahead of the pack when it comes to the most sought-after AI memory: HBM.

It made all the right moves at the right time and won Nvidia as a customer in late 2019 for pairing HBM chips with AI accelerators. No wonder engineers at SK hynix now jokingly call HBM “Hynix’s Best Memory”.

Related Content

• AI, AR Drive Memory Updates
• Conventional Memory Is Key to Ubiquitous AI
• Memory Bottlenecks: Overcoming a Common AI Problem
• HBM memory chips: The unsung hero of the AI revolution
• Generative AI and memory wall: A wakeup call for IC industry

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Offering Drop-in Replacements for Existing Solutions, IrDA-Compliant Devices Feature New In-House IC and Surface Emitter Chip Technology

Vishay Intertechnology, Inc. has announced that it has upgraded its TFBS4xx and TFDU4xx series of infrared (IR) transceiver modules for IrDA applications to offer 20 % longer link distance and improved ESD robustness to 2 kV. With support for data rates up to 115.2 kbit/s (SIR) and link distances of 1 meter, the devices are intended for wireless communication and data transmission in energy meters and monitors, industrial automation controls, mobile phones, and medical equipment. To increase battery life in portable devices, the modules offer low power consumption with an idle supply current of < 70 μA, down to < 1 μA in shutdown mode.

Devices in the Vishay Semiconductors TFBS4xxx and TFDU4xxx series each consist of a PIN photodiode, infrared emitter (IRED), and low-power control IC in a single package. By upgrading the IR transceivers with Vishay’s latest in-house IC and surface emitter chip technology, the company is assuring the long-term availability of IRDC products for its customers. As drop-in replacements for existing devices, the modules help save costs by eliminating the need for PCB redesigns.

Compliant with the latest IrDA physical layer specification, TFBS4xxx and TFDU4xxx series devices are backwards-compatible and are offered in top- and side-view surface-mount packages. The enhanced solutions provide drop-in, plug-and-play replacements for existing devices in the series.

RoHS-compliant, halogen-free, and Vishay Green, the devices are offered in a variety of package sizes and feature a wide operating voltage range from 2.4 V to 5.5 V and an operating temperature range from -25 °C to +85 °C.

Device Specification Table:

Part #	Dimensions (mm)
TFBS4650	1.6 by 6.8 by 2.8
TFBS4652	1.6 by 6.8 by 2.8
TFBS4711	1.9 by 6 by 3
TFDU4101	4 by 9.7 by 4.7
TFDU4301	3.1 by 8.5 by 2.5

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Infinera Corp of San Jose, CA, USA — a vertically integrated manufacturer of digital optical network systems — has announced ICE-D, a new line of high-speed intra-data-center optics based on monolithic indium phosphide (InP) photonic integrated circuit (PIC) technology. ICE-D optics are designed to dramatically lower cost and power per bit while providing intra-data-center connectivity at speeds of 1.6 terabits per second (Tb/s) and greater. The technology enables data-center operators to cost-effectively keep pace with relentless growth in bandwidth, says Infinera...

Featuring 64 Cerebras CS-3 Systems, Condor Galaxy 3 Doubles Performance at Same Power and Cost

Cerebras Systems, the pioneer in accelerating generative AI, and G42, the Abu Dhabi-based leading technology holding group, today announced the build of Condor Galaxy 3 (CG-3), the third cluster of their constellation of AI supercomputers, the Condor Galaxy. Featuring 64 of Cerebras’ newly announced CS-3 systems – all powered by the industry’s fastest AI chip, the Wafer-Scale Engine 3 (WSE-3) – Condor Galaxy 3 will deliver 8 exaFLOPs of AI with 58 million AI-optimized cores.

The Cerebras and G42 strategic partnership already delivered 8 exaFLOPs of AI supercomputing performance via Condor Galaxy 1 and Condor Galaxy 2, each amongst the largest AI supercomputers in the world. Located in Dallas, Texas, Condor Galaxy 3 brings the current total of the Condor Galaxy network to 16 exaFLOPs.

“With Condor Galaxy 3, we continue to achieve our joint vision of transforming the worldwide inventory of AI computing through the development of the world’s largest and fastest AI supercomputers,” said Kiril Evtimov, Group CTO of G42. “The existing Condor Galaxy network has trained some of the leading open-source models in the industry, with tens of thousands of downloads. By doubling the capacity to 16 exaFLOPs, we look forward to seeing the next wave of innovation Condor Galaxy supercomputers can enable.”

At the heart of Condor Galaxy 3 are 64 Cerebras CS-3 Systems. Each CS-3 is powered by the new 4 trillion transistor, 900,000 AI core WSE-3. Manufactured at TSMC at the 5-nanometer node, the WSE-3 delivers twice the performance at the same power and for the same price as the previous generation part. Purpose-built for training the industry’s largest AI models, WSE-3 delivers an astounding 125 petaflops of peak AI performance per chip.

“We are proud that our newly announced CS-3 systems will play a critical role in our pioneering strategic partnership with G42,” said Andrew Feldman, CEO and co-founder of Cerebras. “Condor Galaxy 3 and the follow-on supercomputers, will together deliver tens of exaflops of AI compute This marks a significant milestone in AI computing, providing unparalleled processing power and efficiency.”

Condor Galaxy has trained state-of-the-art industry-leading generative AI models, including Jais-30B, Med42, Crystal-Coder-7B and BTLM-3B-8K. Jais 13B and Jais30B are the best bilingual Arabic models in the world, now available on Azure Cloud. BTLM-3B-8K is the number one leading 3B model on HuggingFace, offering 7B parameter performance in a light 3B parameter model for inference. Med42, developed with M42 and Core42, is a leading clinical LLM, trained on Condor Galaxy 1 in a weekend and surpassing MedPaLM on performance and accuracy.

The post Cerebras and G42 Break Ground on Condor Galaxy 3, an 8 exaFLOPs AI Supercomputer appeared first on ELE Times.

Third Generation 5nm Wafer Scale Engine (WSE-3) Powers Industry’s Most Scalable AI Supercomputers, Up To 256 exaFLOPs via 2048 Nodes

Cerebras Systems, the pioneer in accelerating generative AI, has doubled down on its existing world record of fastest AI chip with the introduction of the Wafer Scale Engine 3. The WSE-3 delivers twice the performance of the previous record-holder, the Cerebras WSE-2, at the same power draw and for the same price. Purpose built for training the industry’s largest AI models, the 5nm-based, 4 trillion transistor WSE-3 powers the Cerebras CS-3 AI supercomputer, delivering 125 petaflops of peak AI performance through 900,000 AI optimized compute cores.

Key Specs:

• 4 trillion transistors
• 900,000 AI cores
• 125 petaflops of peak AI performance
• 44GB on-chip SRAM
• 5nm TSMC process
• External memory: 1.5TB, 12TB, or 1.2PB
• Trains AI models up to 24 trillion parameters
• Cluster size of up to 2048 CS-3 systems

With a huge memory system of up to 1.2 petabytes, the CS-3 is designed to train next generation frontier models 10x larger than GPT-4 and Gemini. 24 trillion parameter models can be stored in a single logical memory space without partitioning or refactoring, dramatically simplifying training workflow and accelerating developer productivity. Training a one-trillion parameter model on the CS-3 is as straightforward as training a one billion parameter model on GPUs.

The CS-3 is built for both enterprise and hyperscale needs. Compact four system configurations can fine tune 70B models in a day while at full scale using 2048 systems, Llama 70B can be trained from scratch in a single day – an unprecedented feat for generative AI.

The latest Cerebras Software Framework provides native support for PyTorch 2.0 and the latest AI models and techniques such as multi-modal models, vision transformers, mixture of experts, and diffusion. Cerebras remains the only platform that provides native hardware acceleration for dynamic and unstructured sparsity, speeding up training by up to 8x.

“When we started on this journey eight years ago, everyone said wafer-scale processors were a pipe dream. We could not be more proud to be introducing the third-generation of our groundbreaking water scale AI chip,” said Andrew Feldman, CEO and co-founder of Cerebras.

“WSE-3 is the fastest AI chip in the world, purpose-built for the latest cutting-edge AI work, from mixture of experts to 24 trillion parameter models. We are thrilled for bring WSE-3 and CS-3 to market to help solve today’s biggest AI challenges.”

Superior Power Efficiency and Software Simplicity

With every component optimized for AI work, CS-3 delivers more compute performance at less space and less power than any other system. While GPUs power consumption is doubling generation to generation, the CS-3 doubles performance but stays within the same power envelope. the CS-3 offers superior ease of use, requiring 97% less code than GPUs for LLMs and the ability to train models ranging from 1B to 24T parameters in purely data parallel mode. A standard implementation of a GPT-3 sized model required just 565 lines of code on Cerebras – an industry record.

Industry Partnerships and Customer Momentum

Cerebras already has a sizeable backlog of orders for CS-3 across enterprise, government and international clouds.

“As a long-time partner of Cerebras, we are excited to see what’s possible with the evolution of wafer-scale engineering. CS-3 and the supercomputers based on this architecture are powering novel scale systems that allow us to explore the limits of frontier AI and science,” said Rick Stevens, Argonne National Laboratory Associate Laboratory Director for Computing, Environment and Life Sciences.  “The audacity of what Cerebras is doing matches our ambition, and it matches how we think about the future.”

“As part of our multi-year strategic collaboration with Cerebras to develop AI models that improve patient outcomes and diagnoses, we are excited to see advancements being made on the technology capabilities to enhance our efforts,” said Dr. Matthew Callstrom, M.D., Mayo Clinic’s medical director for strategy and chair of radiology.

The CS-3 will also play an important role in the pioneering strategic partnership between Cerebras and G42. The Cerebras and G42 partnership has already delivered 8 exaFLOPs of AI supercomputer performance via Condor Galaxy 1 (CG-1) and Condor Galaxy 2 (CG-2). Both CG-1 and CG-2, deployed in California, are among the largest AI supercomputers in the world.

Today, Cerebras and G42 announced that Condor Galaxy 3 is under construction. Condor Galaxy 3 will be built with 64 CS-3 systems, producing 8 exaFLOPs of AI compute, one of the largest AI supercomputers in the world. Condor Galaxy 3 is the third installation in the Condor Galaxy network. The Cerebras G42 strategic partnership is set to deliver tens of exaFLOPs of AI compute. Condor Galaxy has trained some of the industry’s leading open-source models, including Jais-30B, Med42, Crystal-Coder-7B and BTLM-3B-8K.

“Our strategic partnership with Cerebras has been instrumental in propelling innovation at G42, and will contribute to the acceleration of the AI revolution on a global scale,” said Kiril Evtimov, Group CTO of G42.  “Condor Galaxy 3, our next AI supercomputer boasting 8 exaFLOPs, is currently under construction and will soon bring our system’s total production of AI compute to 16 exaFLOPs.”

The post Cerebras Systems Unveils World’s Fastest AI Chip with Whopping 4 Trillion Transistors appeared first on ELE Times.

Details: The wire is NOT a 3rd party product, it is the wire that came from the box. It’s a Surface laptop charging wire. When I plugged the wire into the socket, I saw a bright white flash, all the lights went off in the classroom instantly, and there was a loud cracking sound. No smoke whatsoever. I plugged into the socket *ABOVE * the blackened one. My pinky finger got nicked a bit from the heat, but i didn’t get electrocuted (thank god) as i wasn’t touching the socket itself. (Don’t worry it’s fine now.) The plug is now taken to test, but I do want to know what might have happened. I remember the wire broke off. Could it be a short circuit, overloading or something else? Thank you. submitted by /u/amongus10011 [link] [comments]

Although micro-LEDs exist as single chips and waveguides as fiber-optic cables, the materials required to make them are too heterogenous to integrate these electronics and photonics components onto a single chip. However, a novel etching technique could enable the combining of optoelectronic light sources and photonic fiber optics...

Outfitted with an Arm Cortex-7 core running at up to 600 MHz, ST’s STM32H7R/S MCUs provide the performance, scalability, and security of a microprocessor. They embed 64 kbytes of bootflash and 620 kbytes of SRAM on-chip to speed execution, while fast external memory interfaces support data transfer rates up to 200 MHz.

The STM32H7R and STM32H7S microcontrollers come with powerful security features. They include protection against physical attacks, memory protection, code isolation to protect the application at runtime, and platform authentication. Additionally, STM32H7S devices provide immutable root of trust, debug authentication, and hardware cryptographic accelerators. With these features, the MCUs target safety certifications up to SESIP3 and PSA Level 3.

The lines are further divided into general-purpose MCUs (STM32H7R3/S3) and those with enhanced graphics-handling capabilities (STM32H7R7/S7). With their dedicated NeoChrom GPU, these MCUs deliver rich colors, animation, and 3D-like effects. Developers can share software between the two lines for efficient use of project resources and to achieve faster time-to-market for new products.

STM32H7R/S MCUs are scheduled to enter volume production starting in April 2024. Sample requests and pricing information are available from local ST sales offices. For more information about the STM32H7R/S general-purpose and graphics lines of MCUs, click here.

STMicroelectronics

Find more datasheets on products like this one at Datasheets.com, searchable by category, part #, description, manufacturer, and more.

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An off-the-shelf S-Band low-noise amplifier, the TDLNA2050SEP from Teledyne, tolerates up to 100 krads of total ionizing dose (TID) radiation. This makes the part suitable for use in high-reliability satellite communication systems and phase-array radar.

According to the manufacturer, the MMIC amplifier delivers a gain of 17.5 dB from 2 GHz to 5 GHz, while maintaining a noise figure of less than 0.4 dB and an output power (P1dB) of 19.5 dB. The device should be biased at a VDD of +5.0 V and IDDQ of 60 mA.

The TDLNA2050SEP low-noise amplifier is built on a 90-nm enhancement-mode pHEMT process and is qualified per MIL-PRF-38534 Class K (space) or Class H (military). It comes in a 2×2×0.75-mm, 8-pin plastic DFN packages.

Devices are available from Teledyne e2v HiRel or an authorized distributor.

TDLNA2050SEP product page

Teledyne e2v HiRel Electronics

Find more datasheets on products like this one at Datasheets.com, searchable by category, part #, description, manufacturer, and more.

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