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Courtesy: Onsemi

Every electronic device that is powered from a wall outlet uses some form of offline switch mode power supply (SMPS) that converts the AC grid voltage to a DC voltage used by the device. An offline SMPS is a switched power supply with an isolation transformer and covers power range from a few watts to multi-kilowatt solutions. Offline SMPS is widely deployed and indispensable in providing reliable and safe power to electronic devices in various applications ranging from consumer electronics, industrial power supply, datacenters to telecom base stations.

When designing an offline SMPS there are many factors to be considered for a successful design including power level, voltages, safety requirements, size, and several more.

Understanding Offline SMPS & Popular Topologies

Fundamentally, an online SMPS uses a two-stage conversion. Firstly, the mains grid voltage is rectified and shaped by the first stage – the power factor corrector (PFC). The output voltage of the PFC stage is set to be a bit higher than the expected input peak voltage. For single phase solutions   this is usually around 380-400 VDC. Since the output of the PFC stage is stable and relatively well-regulated DC voltage, the following DC-DC stage can be less complex. In most offline SMPS, the PFC is single-phase, but for higher power units (multi-kilowatt) it can be 3-phase.

Figure 1: Key Elements of an Offline SMPS

The PFC stage aims to improve efficiency by reducing the apparent power in the system. It corrects the phase difference between the current and voltage (the ‘Power Factor’) to maintain as little difference as possible, as well as shaping the current waveform to be as near as it can be to a pure sinusoid, minimizing total harmonic distortion (THD).

The DC-DC stage (often an LLC converter) takes the PFC output and converts this to the desired voltage, bearing in mind there may be several independent outputs. This stage also includes the galvanic isolation transformer that provides safety isolation as well as level shifting the voltage. Due to the transformer’s inability to accommodate direct current, the incoming DC from the PFC stage is converted back into an alternating current and then rectified for the output.

Efficiency (the ratio between the power delivered at the output and the power consumed by the input) is a crucial parameter for any SMPS. It affects the operating cost, but more importantly, it also defines the internal losses that manifest as heat. This, in turn, determines how much cooling is required when the SMPS is operating. The higher the amount of cooling in terms of fans and/or heatsinks is needed, the larger, heavier and more expensive the solution will be.

Advancements in Offline SMPS Technology

Striving for the highest levels of performance, there is ongoing advancement in the technologies used within offline SMPS.

Boost PFC is nowadays commonly used for a wide range of power due to its simple structure and straightforward control strategy. The inductor current is continuous, electromagnetic interference (EMI) is lower, and the current waveform is less distorted, which leads to a better power factor. A single-phase boost PFC will have a regulated DC output of around 380 V, which will then be converted by the DC/DC converter.

Furthermore, LLC converters are becoming increasingly popular for the DC-DC stage. These resonant converters regulate their output by altering the operating frequency of the resonant tank across a relatively narrow range, thereby operating in a soft-switching mode. This improves efficiency and reduces EMI. They operate at higher frequencies compared to allowing the use of smaller passive components.

Figure 2: A Simple LLC Converter

Synchronous or active rectification is a technique for improving efficiency and reducing conduction losses by replacing rectifier diodes with active switches. While semiconductor diodes exhibit a relatively fixed voltage drop (typically 0.5 to 1 V), MOSFET switches act as resistances and therefore can have very low drop. If further improvements are needed, MOSFET switches can be paralleled in order to handle higher output currents. In such a case the conduction losses are reduced, because the RDSON of the paralleled devices is equal to the inverse sum of their respective RDSON.

Semiconductor materials are also evolving as traditional silicon (Si) has reached its limit for further significant performance gains. New wide-bandgap (WBG) materials such as silicon carbide (SiC) are increasingly preferred in power designs for their ability to operate efficiently at higher switching frequencies and higher operating voltages.

WBG devices exhibit lower losses due to better reverse recovery, significantly contributing to enhanced conversion efficiency. As a result, and due to their ability to operate at higher temperatures, thermal mitigation requirements are reduced when using WBG devices.

onsemi Solutions

onsemi has one of the broadest portfolios of solutions for offline SMPS currently available. At the heart of the range are controllers for the PFC and DC/DC converter stages, power MOSFETs, rectifiers, and diodes. This is supported with MOSFET gate drivers (including for synchronous rectification), optocouplers, low dropout (LDO) regulators, and other devices.

Leading the way in modern high-performance devices, the range includes many SiC devices (diodes and MOSFETs) for use in the most challenging offline SMPS applications.

Using the onsemi range (and a few passive components), offline SMPS from a few watts to several kilowatts can be designed. onsemi’s experience in this area assures designers that their solution will have industry-leading performance and reliability.

Conclusion

Offline SMPS are one of the most common sub-systems, present in almost every mains-connected device. However, to create a successful design, safety, and EMI regulations must be met while performance, especially in terms of efficiency, is an ever-increasing requirement.

While several companies manufacture some of the devices necessary for these designs, few (if any) have a comprehensive range that covers all the components (excluding passives) needed to execute a complete design. There are significant benefits to sourcing components from a single supplier, including knowing that devices have been designed and tested to work together.

The post Key Design Considerations for Offline SMPS Applications appeared first on ELE Times.

Courtesy: Nvidia

What is a token? Why is batch size important? And how do they help determine how fast AI computes?

The era of the AI PC is here, and it’s powered by NVIDIA RTX and GeForce RTX technologies. With it comes a new way to evaluate performance for AI-accelerated tasks, and a new language that can be daunting to decipher when choosing between the desktops and laptops available.

While PC gamers understand frames per second (FPS) and similar stats, measuring AI performance requires new metrics.

Coming Out on TOPS

The first baseline is TOPS, or trillions of operations per second. Trillions is the important word here — the processing numbers behind generative AI tasks are absolutely massive. Think of TOPS as a raw performance metric, similar to an engine’s horsepower rating. More is better.

Compare, for example, the recently announced Copilot+ PC lineup by Microsoft, which includes neural processing units (NPUs) able to perform upwards of 40 TOPS. Performing 40 TOPS is sufficient for some light AI-assisted tasks, like asking a local chatbot where yesterday’s notes are.

But many generative AI tasks are more demanding. NVIDIA RTX and GeForce RTX GPUs deliver unprecedented performance across all generative tasks — the GeForce RTX 4090 GPU offers more than 1,300 TOPS. This is the kind of horsepower needed to handle AI-assisted digital content creation, AI super resolution in PC gaming, generating images from text or video, querying local large language models (LLMs) and more.

Insert Tokens to Play

TOPS is only the beginning of the story. LLM performance is measured in the number of tokens generated by the model.

Tokens are the output of the LLM. A token can be a word in a sentence, or even a smaller fragment like punctuation or whitespace. Performance for AI-accelerated tasks can be measured in “tokens per second.”

Another important factor is batch size, or the number of inputs processed simultaneously in a single inference pass. As an LLM will sit at the core of many modern AI systems, the ability to handle multiple inputs (e.g. from a single application or across multiple applications) will be a key differentiator. While larger batch sizes improve performance for concurrent inputs, they also require more memory, especially when combined with larger models.

The more you batch, the more (time) you save.

RTX GPUs are exceptionally well-suited for LLMs due to their large amounts of dedicated video random access memory (VRAM), Tensor Cores and TensorRT-LLM software.

GeForce RTX GPUs offer up to 24GB of high-speed VRAM, and NVIDIA RTX GPUs up to 48GB, which can handle larger models and enable higher batch sizes. RTX GPUs also take advantage of Tensor Cores — dedicated AI accelerators that dramatically speed up the computationally intensive operations required for deep learning and generative AI models. That maximum performance is easily accessed when an application uses the NVIDIA TensorRT software development kit (SDK), which unlocks the highest-performance generative AI on the more than 100 million Windows PCs and workstations powered by RTX GPUs.

The combination of memory, dedicated AI accelerators and optimized software gives RTX GPUs massive throughput gains, especially as batch sizes increase.

Text-to-Image, Faster Than Ever

Measuring image generation speed is another way to evaluate performance. One of the most straightforward ways uses Stable Diffusion, a popular image-based AI model that allows users to easily convert text descriptions into complex visual representations.

With Stable Diffusion, users can quickly create and refine images from text prompts to achieve their desired output. When using an RTX GPU, these results can be generated faster than processing the AI model on a CPU or NPU.

That performance is even higher when using the TensorRT extension for the popular Automatic1111 interface. RTX users can generate images from prompts up to 2x faster with the SDXL Base checkpoint — significantly streamlining Stable Diffusion workflows.

ComfyUI, another popular Stable Diffusion user interface, added TensorRT acceleration last week. RTX users can now generate images from prompts up to 60% faster, and can even convert these images to videos using Stable Video Diffuson up to 70% faster with TensorRT.

TensorRT acceleration can be put to the test in the new UL Procyon AI Image Generation benchmark, which delivers speedups of 50% on a GeForce RTX 4080 SUPER GPU compared with the fastest non-TensorRT implementation.

TensorRT acceleration will soon be released for Stable Diffusion 3 — Stability AI’s new, highly anticipated text-to-image model — boosting performance by 50%. Plus, the new TensorRT-Model Optimizer enables accelerating performance even further. This results in a 70% speedup compared with the non-TensorRT implementation, along with a 50% reduction in memory consumption.

Of course, seeing is believing — the true test is in the real-world use case of iterating on an original prompt. Users can refine image generation by tweaking prompts significantly faster on RTX GPUs, taking seconds per iteration compared with minutes on a Macbook Pro M3 Max. Plus, users get both speed and security with everything remaining private when running locally on an RTX-powered PC or workstation.

The Results Are in and Open Sourced

But don’t just take our word for it. The team of AI researchers and engineers behind the open-source Jan.ai recently integrated TensorRT-LLM into its local chatbot app, then tested these optimizations for themselves.

The researchers tested its implementation of TensorRT-LLM against the open-source llama.cpp inference engine across a variety of GPUs and CPUs used by the community. They found that TensorRT is “30-70% faster than llama.cpp on the same hardware,” as well as more efficient on consecutive processing runs. The team also included its methodology, inviting others to measure generative AI performance for themselves.

From games to generative AI, speed wins. TOPS, images per second, tokens per second and batch size are all considerations when determining performance champs.

The post TOPS of the Class: Decoding AI Performance on RTX AI PCs and Workstations appeared first on ELE Times.

Through ISED (Innovation, Science and Economic Development Canada), the Canadian government is investing $120m into FABrIC (Fabrication of Integrated Components for the Internet’s Edge) network, which is a five-year project totalling over $220m to advance domestic semiconductor manufacturing and commercialization capabilities...

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Luminus Devices Inc of Sunnyvale, CA, USA – which designs and makes LEDs and solid-state technology (SST) light sources for illumination markets – has launched the mid-power MP-5050-240E and MP-5050-810E LEDs, which deliver what is claimed to be unmatched efficacy of 233 lumens per watt at a correlated colour temperature (CCT) of 4000K at 70 CRI (color-rendering index) and 1 Watt, exceeding the standards in outdoor and industrial lighting applications...

Accenture has acquired Cientra, a silicon design and engineering services company, offering custom silicon solutions for global clients. The terms of the acquisition were not disclosed.

Founded in 2015, Cientra is headquartered in New Jersey, U.S. and has offices in Frankfurt, Germany as well as in Bangalore, Hyderabad and New Delhi, India. The company brings consulting expertise in embedded IoT and application-specific integrated circuit design and verification capabilities, which augments Accenture’s silicon design experience and further enhances its ability to help clients accelerate semiconductor innovation required to support growing data computing needs.

“Everything from data center expansion to cloud computing, wireless technologies, edge computing and the proliferation of AI, are driving demand for next-generation silicon products,” said Karthik Narain, group chief executive—Technology at Accenture. “Our acquisition of Cientra is our latest move to expand our silicon design and engineering capabilities and it underscores our commitment to helping our clients maximize value and reinvent themselves in this space.”

Cientra has deep experience in engineering, development and testing across hardware, software and networks, in the automotive, telecommunications and high-tech industries. The company brings approximately 530 experienced engineers and practitioners to Accenture’s Advanced Technology Centers in India.

“Since inception, Cientra has been dedicated to building top talent and fostering continuous innovation, developing product solutions that drive value for our clients,” said Anil Kempanna, CEO, Cientra. “Joining Accenture provides exciting opportunities to expand globally and scale our capabilities to create new avenues of growth for our clients as well as our people.”

This acquisition follows the addition of Excelmax Technologies, a Bangalore, India-based semiconductor design services provider, earlier this week, and XtremeEDA, an Ottawa, Canada-based silicon design services company, in 2022.

The post Accenture Acquires Cientra to Expand Silicon Design Capabilities appeared first on ELE Times.

At the IEEE Nuclear & Space Radiation Effects Conference (NSREC 2024) in Ottawa, Canada (22–26 July), EPC Space LLC of Haverhill, MA, USA is presenting its latest radiation-hardened (rad-hard) gallium nitride (GaN)-on-silicon technology, highlighting solutions designed to meet the rigorous demands of space applications...

E-Fill Electric (EFEV Charging Solutions Pvt. Ltd.), a pioneering name in India’s EV charging sector, has outlined its wish list for the forthcoming Union Budget, emphasizing key actions to promote the adoption and infrastructure development of electric vehicles (EVs) across the country.

Mayank Jain, Founder & CEO of E-Fill Electric, highlighted several key priorities aimed at fostering a robust EV charging ecosystem:

1. Increased Allocation for FAME Scheme: E-Fill Electric urges the government to enhance allocation under the FAME (Faster Adoption and Manufacturing of Electric Vehicles) scheme to accelerate EV adoption and manufacturing capabilities in India.
2. Tax Incentives for EV Charging Businesses: Lowering GST on EV charging equipment and operational costs shall ensure affordability and promote widespread deployment of charging infrastructure.
3. Investment in Skilled Workforce: E-Fill Electric stresses the importance of investing in training programs to develop a skilled workforce proficient in EV charging installation, maintenance, and repair, vital for sustaining the industry’s growth.
4. Streamlined Land Acquisition Procedures: The Company recommends measures to streamline land acquisition procedures for EV charging companies, potentially through designated zones or expedited approvals, to facilitate speedy infrastructure expansion.
5. Public-Private Partnerships: E-Fill Electric advocates for incentivising partnerships between public and private entities to expedite the development and deployment of EV charging infrastructure nationwide.
6. Research and Development Incentives: The budget should incentivise research and development in EV charging technology, including support for indigenous manufacturing of charging equipment to encourage innovation and self-reliance.
7. Subsidies for EV Chargers: E-Fill Electric suggests introducing subsidies or low-interest loan schemes to encourage individuals and businesses to install EV chargers at homes and workplaces, enhancing convenience and accessibility.
8. Grid Modernization: Prioritizing grid modernisation projects is essential to accommodate the increased electricity demand from EVs, ensuring reliable and sustainable power supply.

Mr. Mayank Jain expressed confidence that these measures, if implemented, will not only boost the EV ecosystem but also align with India’s vision of sustainable and inclusive mobility solutions.

The post E-Fill Electric Presents Wish List for EV Charging Industry in the Upcoming Union Budget appeared first on ELE Times.

Provides functions equivalent to a fully digital control power supply with low power consumption

ROHM has established LogiCoA, a power supply solution for small to medium-power industrial and consumer equipment (30W to 1kW class). It provides the same functionality as fully digital control power supplies at low power consumption and cost equivalent to analog power types.

Analog controlled power supplies are commonly used in industrial robotics and semiconductor manufacturing equipment that operate in the medium power range. However, in recent years these power supplies are also required to provide a high level of reliability and precise control that make it difficult to meet market demands with analog-only configurations. On the other hand, while fully digitally controlled power supplies enable fine control and settings, they are not widely adopted in the small to medium power range due to the high power consumption and cost of the digital controller. To address this issue, ROHM developed the LogiCoA power solution that leverages the strengths of both analog and digital technologies. High-performance low power LogiCoA MCUs are utilized to facilitate control of a variety of power supply topologies.

The LogiCoA brand embodies a design philosophy of fusing digital elements to maximize the performance of analog circuits. ROHM’s LogiCoA power solution is the industry’s first* “analog-digital fusion control” power supply that combines a digital control block centered around the LogiCoA MCU with analog circuitry comprised of silicon MOSFETs and other power devices.

In a fully digital control power supply, the functions handled by digital controllers such as high-speed CPUs or DSPs can be processed by low-bit MCUs, making it possible to achieve increased functionality that is difficult to realize with an analog control power supply at low power consumption and cost. This solution allows for the correction of performance variations in peripheral components according to the power supply circuit by storing various settings such as current and voltage values in the LogiCoA MCU. As a result, there is no need to consider design margins unlike with analog control power supplies, contributing to smaller power supplies that provide greater reliability. On top, as operation log data can be recorded in the MCU’s nonvolatile memory, it is ideal for power supplies in industrial equipment that require logging as a backup in case of malfunction.

The evaluation reference design REF66009 allows users to experience the LogiCoA power supply solution in a non-isolated buck converter circuit. Various tools necessary for evaluation are also offered, including circuit diagrams, PCB layouts, parts lists, sample software, and support documents, while actual device evaluation is possible using the optional LogiCoA001-EVK-001 evaluation board.

Going forward, ROHM will continue to develop LogiCoA MCUs to support various power supply topologies, contributing to achieving a sustainable society by making the power supply block (which accounts for the majority of power loss in applications) more energy-efficient and compact.

LogiCoA Brand

LogiCoA is a brand that embodies a design philosophy of fusing digital elements to maximize the performance of analog circuits. By combining the advantages of analog circuitry with those of digital control, it is possible to maximize the potential of circuit topologies, contributing to more efficient power utilization. As LogiCoA is a design concept that can be applied not only to the power supply field, but also to power solutions as a whole, ROHM is considering its application in future products and solutions.

Details of the LogiCoA Power Supply Reference Design

The REF66009 evaluation reference design offered on ROHM’s website allows users to verify the functionality of the LogiCoA MCU along with the basic operation of the LogiCoA power supply solution using a non-isolated 12V buck converter circuit. Sample software available on the reference design page makes it possible to confirm the sequence control of execution tasks and the monitoring of various parameters in the actual set using the LogiCoA001-EVK-001 reference board. For more information on the reference board, please contact a sales representative or the contact page on ROHM’s website.

Application Examples

• Industrial robots
• Semiconductor manufacturing equipment
• Gaming applications

Supports mounting in a wide range of general industrial equipment and consumer devices (30W to 1kW).

About the LogiCoA MCU

ROHM is developing LogiCoA MCUs optimized for integrated analog-digital control such as LogiCoA power supply solutions. Features include a built-in 3ch analog comparator that can be linked to a timer and D/A converter that enables digital control of various parameters to support different power supply topologies.

■ LogiCoA MCU Specifications (Tentative)

Availability: Now (LogiCoA MCU samples)

Terminology

Fully Digital Control Power Supply

A power supply controlled using digital technology. High-speed CPUs and DSPs can be used to precisely monitor and control various parameters such as voltage and current, improving power supply efficiency and reliability. What’s more, functions that are difficult to perform with analog control can be achieved, such as acquiring operation log data. However, CPUs and DSPs are expensive and consume a large amount of power, which can be a bottleneck in terms of costs and energy efficiency.

Analog Control Power Supply

A power supply configuration consisting of analog components. This type has become mainstream for power supplies 1kW and below due to its simplicity and low power consumption. On the other hand, implementing advanced functionality such as setting arbitrary parameters and logging data is difficult, requiring fully digital control that entails high costs and power consumption.

CPU (Central Processing Unit)

Responsible for executing programs and processing data. Handles calculations and processing as well as carrying out instructions according to a program.

DSP

A device that digitizes analog signals and performs operations such as analysis, filtering, and amplification on the converted digital signals. Flexible enough for high-speed processing and various applications, it plays an important role in circuits that handle digital signals, such as audio and image processing in addition to power supplies.

The post ROHM Offers LogiCoA: the Industry’s First* Analog-Digital Fusion Control Power Supply Solution appeared first on ELE Times.

The new topology eliminates the need for a transformer and significantly reduces the number of capacitors in DC-DC converter ICs.

I’ve always had a makeshift workbench all my life, finally own a house with space that is just mine to do what I want with. submitted by /u/dakiller [link] [comments]

The world of electronic manufacturing changes regularly, and as a result – fabricators must select one of two approaches in fabricating electronic components which are the Surface Mount Technology and Through-Hole Assembly methods. Each method brings its own set of advantages and drawbacks wherein you will have the final say on which manufacturing approach is geared to your standards and budget.

In this article, we’ll be taking a look at the nuances between SMT assembly and Through-Hole Assembly and the criteria that you’ll use as a basis to make the right decision on which manufacturing approach you’ll utilize for your project.

Surface Mount Technology (SMT): An Overview Definition of Surface Mount Technology

To begin our discussion, let’s learn what Surface Mount Technology is. SMT assembly is a process wherein electronic components are mounted directly onto a PCB’s surface through assembly machinery which an operator programs. As a result, this facilitates a fast-paced production which allows the creation of many surface-mounted circuit boards in a short timeframe.

Key Traits of SMT Assembly

• Faster production setup – Compared to Through-Hole assembly, SMT assembly’s production setup facilitates fast-paced mass-production of printed circuit boards. This trait is what makes it favorable for factories or facilities that are required to mass-produce PCBs for different clients from different niches.

• High component density, small board size – Printed circuit boards that are made through this method of assembly are far smaller than their through-hole-made counterparts. That’s because the circuit board’s surfaces contain a very high density of electronic components which maximizes the use of the allotted space of the printed circuit boards

• Flexible application – Compared to through-hole boards, SMT-assembled PCBs are quite ubiquitous as they are utilized in most applications – usually in domestic devices or consumer goods. These items where SMT-assembled circuit boards are integrated into can range from kitchen appliances to your phone.

• Can facilitate more connections – Aside from their density, SMT-assembled boards are also known for their capability to accommodate more connections as components can be placed on both the front and back sides of the printed circuit board. As a result, there are more connections possible for every printed circuit board that works as intended.

• Requires specialized tools and expert-leveled operators – SMT-assembled PCBs will require more care in the process of manufacturing them due to the compact sizes of the printed circuits requiring more attention to ensure that the end product isn’t defective. To ensure that outcome, SMT assembly factories will be required to invest in specialized tools for manufacturing, assembly, and repairing, as well as hiring expert operators who will oversee the manufacturing process.

Through-Hole Assembly: An Overview Definition of Through-Hole Assembly

Before we delve into selecting the ideal assembly method for your project, let’s understand what

is through-hole assembly first. The through-hole method of assembling printed circuit boards involves drilling holes into the board’s surface. Once the holes are set, leads are inserted into the drilled holes before the components are installed and soldered on them. This method of assembly is significantly slower due to the added steps in installing the components but still has a key niche to fill in the world of electronics.

The Key Characteristics of Through-Hole Assembly

• Provides clients with specialized circuit boards – Despite the limited range of designs that through-hole assembled circuits have compared to SMT assembly-made circuit boards, it fares well in electronic setups that require a PCB that can function in specific conditions – say for example, a through-hole assembled PCB that is meant for use in electrical circuit setups that has a high heat dissipation for use in an industrial configuration.

• Reliable and resilient – Compared to the mass-produced SMT-assembled boards, through-hole assembled PCBs are more reliable due to the components being embedded onto the surface of the board through drilled holes and leads which also keeps the component intact. As a result, through-hole assembled boards have a very robust connection making the PCBs ideal for intense work environments ranging from military and aerospace applications to industrial use. On top of that, through-hole assembled boards sport better durability due to their designs having a high heat and stress tolerance.

• Easier repair time and adjustability – Unlike their SMT assembly counterparts, the PCBs made by through-hole assembly methods are easier to repair or operate manually. That’s because the key components embedded on the PCB are easier to replace or modify their positioning when necessary. In addition to what’s stated, the parts are easy to discern and identify so if a component on the PCB is defective; all it takes is to remove the defective part and replace it with a functioning version.

Factors to Consider in Selecting the Manufacturing Method

Now that we’ve covered the two methods of assembling circuit boards; let’s cover next the factors that you’ll need to consider in selecting which method best suits your project. Listed below are the factors that could play into choosing whether you will settle for SMT assembly or through-hole assembly for your future PCBs:

1. Costs of your Project

The first factor that comes into play in making the right choice for your PCB project is its cost. Are you willing to invest a lot of money for a specialized printed circuit board or will you settle for a PCB that can be applied in a myriad of situations? You should also determine how much is the total costs of the materials and components that will be used in your project.

These factors related to the project’s costs should help whether you should opt for SMT assembly or through-hole assembly.

2. Performance or Quantity

The next factor that comes into play whether you should choose SMT assembly or through-hole assembly is whether you value the quantity or the performance of the printed circuit board. If your goal is to produce as many printed circuit boards to meet the needs of many devices, then you could opt for SMT assembly.

However, if you value performance more – then you can consider aiming for through-hole assembly instead. Keep in mind though, that SMT-assembled circuit boards do still hold a solid performance which we’ll explore that nuance in the next criteria.

3. Choosing Between Flexibility or Specialization

If you’ve factored in the performance of the PCBs for your project, then another layer of nuance comes into play – which is choosing between flexibility or specialization. If your project aims to turn the PCBs into a size-fits-many solution for different devices then you could opt for SMT assembly. As stated earlier, the best example of a flexible-use printed circuit board are domestic and everyday electronic items that we use such as smartphones, televisions, and the like.

However, if your electronic configuration calls for a specific circuit board; say for example – if your work environment favors a resilient PCB that can withstand intense amounts of workloads, mechanical stress, and electrical flow – you would want to settle with through-hole assembly instead of SMT-assembled boards as they could deteriorate fast in these types of working conditions. Notable examples of these intense work conditions where through-hole PCBs see use are automotive factories and industrial plants; aside from military and aerospace applications.

4. The Project’s Intended Application

The last hurdle you’ll need to factor into your project whether you should settle for SMT assembly or through assembly is the intended application of your project. Is your project intended for use in consumer products or everyday items? If that’s the case then SMT assembled PCBs are your best bet.

However, if your project’s intended use is for specific niches or uses – for example; printed circuit boards for use in high-powered lighting, or to power the avionics inside a plane then utilizing through-hole assembled circuit boards could be the way to go.

Make the Right Decisions to Bring Your Project to Reality

To sum up what we’ve covered – there are two ways a printed circuit board is manufactured; namely through SMT assembly or through-hole assembly. To ensure that your project will work as intended for its target niche, you should consider the costs, quantity, or performance, its role whether it is flexible or specialized, and its intended niche.

Putting together the manufacturing methods and the factors that you need to consider will ensure that your electrical project is brought to reality.

The post SMT vs. Through-Hole Assembly: Making the Right Choice for Your Project appeared first on Electronics Lovers ~ Technology We Love.

This article demonstrates the operation of an LTspice shift register and discusses details of its schematic and timing relationships.

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Професору Петру Івановичу Бідюку – 75! Інформація КП ср, 07/10/2024 - 15:10

Photonic chips industry accelerator PhotonDelta of Eindhoven, The Netherlands (which connects and collaborates with an ecosystem of photonic chip technology organizations worldwide), has opened a new office in North America, with the aim of growing the photonic chip industry by promoting collaboration between European and North American organizations...

It has been an exciting year for mobile technology with the advent of AI Smartphones. Each year, like clockwork, I find myself eagerly lining up for the latest smartphone launch, driven by an insatiable curiosity and a bit of a tech addiction. My friends might jest that I switch phones more often than my single malt preferences, but through this annual ritual, I gain a front-row seat to the rapid evolution of technology. Each unboxing becomes a discovery of what’s newly possible at the intersection of hardware and software, particularly as smartphones grow not just smarter but seemingly wiser. The innovation of integrating generative AI in smartphones raises the customer experience bar exponentially.

This fascination isn’t merely about indulging in the latest bells and whistles; it’s about experiencing firsthand how intelligent operating systems are revolutionizing our interactions with mobile devices. As generative AI migrates from vast data centers to the palms of our hands, it transforms smartphones into central hubs of personalized technology and AI-driven companions, reshaping the foundations of mobile user interaction.

At the heart of this revolution is Micron Technology. Our advanced memory and storage products support the immense data demands of generative AI, turning what once seemed like a futuristic vision into today’s reality. These technological advancements are crucial as smartphones begin to transition from passive tools to active personal companions, deeply integrated into the fabric of our daily lives. They offer insightful recommendations and enhance our experiences in ways we are only beginning to imagine.

To truly appreciate the impact of these technologies, one must understand the intricate play between large language models (LLMs) like Llama 2, Google Gemini, and ChatGPT, as well as the advanced hardware that supports them. These AI models, which thrive on billions of parameters, demand unprecedented levels of memory capacity and speed—requirements that Micron’s innovative products are designed to meet. Integrating high-capacity, efficient memory systems is not just an improvement; it’s necessary to support the sophisticated AI functions that modern users will come to expect from their devices.

As we stand on the brink of this new era, our relationship with our devices is set to change profoundly. Smartphones will transition from passive tools to active personal companions, deeply integrated into the fabric of our daily lives, making insightful recommendations and enhancing our experiences in ways we are only beginning to imagine. This blog explores how generative AI is driving this monumental shift, redefining the possibilities of smartphone technology and ensuring that users can enjoy a seamless, intuitive, and highly personalized digital experience.

The generative AI advantage: Unlocking the ultimate smartphone companion experience

Generative AI is revolutionizing the capabilities of smartphones by introducing features that were once the domain of science fiction. At its core, generative AI involves using algorithms and models to generate text, images, and even predictions based on extensive data sets on which they have been trained. This transformative technology is making smartphones, not just tools for consumption but instruments of creation and personal assistance.

One of the key features enabled by generative AI is the ability to generate real-time content directly related to user inputs. For example, through AI-powered apps, users can request the generation of digital artwork or manipulate photos and videos in sophisticated ways that go far beyond the current filters and editing tools. Another significant capability is real-time language translation, which is advancing beyond simple text translation to include voice and even real-time video call translations. This allows for a seamless communication experience with almost no language barrier, effectively shrinking the global divide in personal and professional interactions.

Moreover, generative AI enhances personalized recommendations by analyzing user behaviour, preferences, and previous interactions. This data-driven approach allows smartphones to anticipate needs and offer suggestions for everything from daily tasks to complex decision-making processes. It can also guide users through interactive educational content, adapting to their learning pace and style, thus personalizing the educational experience more effectively than ever before.

These features, powered by generative AI, require advanced computational power and significant memory and storage capabilities. The processing occurs on the device itself to ensure responsiveness and data privacy. As these technologies continue to evolve, they promise to enhance how users interact with their devices further, making each smartphone a truly personalized digital companion that learns and grows with its user.

Smartphones that care: How AI is humanizing the mobile experience

The future of AI-enabled smartphones promises a landscape where the line between digital and physical realities blurs, ushering in a new era of interactive and immersive experiences that are currently difficult to imagine. As generative AI continues to evolve, the potential for creating features that transform everyday activities and expand our capabilities is immense.

One of the most exciting prospects is developing extended reality (XR) and spatial computing which is integrated seamlessly with AI. Future smartphones could leverage XR to overlay digital information onto the physical world in real time. Imagine pointing your smartphone at a restaurant and seeing menu recommendations tailored to your taste and dietary preferences pop up in your vision or looking at a piece of furniture and seeing how it would look in your home, configured to your space and color scheme instantly.

Health monitoring is another area ripe for transformation. Future AI smartphones could become proactive health advisors, tracking physical activity and health metrics and predicting potential health issues before they arise. These devices could use advanced sensors and AI-driven analytics to monitor changes in voice tone, breathing patterns, and even eye movements to provide early warnings about health risks such as heart disease or diabetic changes, potentially coordinating directly with medical professionals to provide timely interventions.

Moreover, integrating AI could redefine mobile security, transforming smartphones into highly secure devices that use biometric data like facial recognition, retinal scans, and even behavioural patterns to ensure that access to the device and its applications is intensely personal and completely secure. This could eliminate the need for passwords or traditional security measures, which are vulnerable to breaches.

The concept of an AI companion will likely mature into a fully interactive assistant capable of sophisticated conversation and decision-making assistance. This companion could manage schedules, suggest content, handle mundane tasks, and even offer psychological support, learning continuously from interactions to become more effective and personalized. Furthermore, as generative AI capabilities grow, so will the ability to create and simulate complex virtual environments directly from the device, allowing users to interact with virtual spaces for entertainment, education, or social interaction in unprecedented ways.

Now what does it mean to smartphones’ memory and storage capacities? And what does a phone need to take full advantage of AI applications? As generative AI grows, it becomes even more of a primary innovation driver in the mobile ecosystem. And to support flagships phone’s advanced sensors, cameras, and form factors, high capacity and bandwidth memory and storage is critical. Data is collected and stored on the handset memory and storage, calculated, and processed on the edge (not in the cloud) and translated to valuable and predictive insights.

The future of smartphones equipped with AI technologies offers enhancements of current features and a revolution in how we perceive and interact with our environment. This future is not only about technological advancements but about significantly enhancing human capabilities and experiences, making life more convenient, connected, and healthy. These developments, while complex, require the continued advancement of AI technology paired with significant improvements in hardware, like those provided by Micron, to make these unimagined features a reality.

Memory matters: How Micron’s solutions are unlocking the full potential of AI smartphones and super companions

Micron is at the forefront of defining the future capabilities of AI smartphones, leveraging its leading-edge UFS 4.0 and LPDDR5X DRAM technologies. These innovations are vital for meeting the increasingly complex demands of on-device AI applications, pushing the boundaries of what smartphones can achieve.

The UFS 4.0 technology introduced by Micron sets new standards for storage performance, essential for the fast processing speeds required by AI-driven applications. It achieves a remarkable 4300 megabytes per second (MBps) in sequential read and 4000 MBps in sequential write speeds, doubling the performance of the previous UFS 3.1 standards. This significant increase in data throughput ensures that AI applications can access and process large datasets much faster, reducing latency and enhancing overall device responsiveness​​.

Additionally, Micron’s UFS 4.0 features a compact design with a footprint of just 9×13 millimeters, supporting the development of slimmer and more aesthetically pleasing smartphone designs without compromising performance. The storage solution also includes innovative features like the One-button Refresh, which helps maintain long-term device performance by automating data defragmentation, ensuring that the storage performance remains like-new even after extended use​​.

On the memory side, Micron’s LPDDR5X DRAM is engineered to meet the requirements of advanced AI processing by delivering top speeds of up to 9600 megabits per second (Mbps), which is crucial for handling AI’s extensive computational demands. This speed enhancement, combined with the high-density packaging that allows for increased memory capacity within the same form factor, is critical for AI applications that require rapid access to large volumes of data. ​ It also features 13% Gain with faster Peak Bandwidth and up to 27% power reduction on day of use.

Micron’s advancements enhance smartphones’ raw computational and storage capabilities and enable new AI features by providing the necessary infrastructure to support real-time AI processing on the edge. This strategic focus on developing high-performance and efficient memory and storage solutions firmly positions Micron as a key enabler in the rapidly evolving landscape of AI mobile technology, facilitating the emergence of smartphones that can perform complex AI tasks directly on the device without relying on cloud processing.

The ethical compass: Navigating the moral landscape of AI smartphones

As AI smartphones continue to revolutionize our lives, it’s crucial to acknowledge the ethical considerations that come with these powerful devices. Like a moral compass, we must navigate the complexities of AI technology to ensure it aligns with our values and principles. Privacy and data security are paramount concerns. How will AI smartphones collect, store, and protect our personal information? Transparency and accountability are essential to prevent data breaches and cyber-attacks. Users must be informed about data usage and sharing practices, and measures must be taken to prevent biases and discrimination in AI decision-making. Transparency and explainability are vital in AI-driven processes. Users deserve to understand how AI arrives at its conclusions and make informed decisions. Autonomous decision-making raises questions about free will and moral agency, and AI smartphones must balance user autonomy and AI-driven actions.

The environmental impact of AI smartphones cannot be ignored. Sustainable manufacturing, reduced electronic waste, and energy efficiency are crucial to minimize their ecological footprint. Finally, human-AI collaboration must prioritize human well-being and dignity, enhancing our capabilities without replacing them. By acknowledging these ethical considerations, we can harness the potential of AI smartphones while upholding our values and principles. Like a compass guiding us through uncharted territory, ethical awareness will ensure AI technology serves humanity, not the other way around.

The future in focus: AI smartphones and the dawn of a new era

Imagine this: It’s a crisp Wednesday morning in the not-too-distant future. Your day begins not with a jarring alarm but with a gentle wake-up nudge from your AI-enhanced smartphone, which has analyzed your sleep patterns and knows the exact moment to wake you. As you stir, your phone has already started your coffee maker, selected a nutritious breakfast based on your health goals for the week, and displayed your optimized route to work, avoiding a traffic jam it predicted from historical data and real-time sensors.

While you eat, your smartphone reviews your calendar prioritizes tasks based on urgency and personal productivity patterns and seamlessly integrates your work commitments with personal ones. It reminds you of your daughter’s recital in the evening and schedules a reminder to leave work early. It even suggests a perfect gift for her performance tonight, which you can pick up on your route home—all curated from understanding your past purchases and her current interests.

This scenario isn’t just a futuristic dream; thanks to companies like Micron, it’s on the verge of becoming reality. By advancing AI capabilities through memory and storage solutions innovations like UFS 4.0 and LPDDR5X DRAM, Micron is turning smartphones into personal assistants that manage our digital tasks and enhance our human experiences.

Micron’s vision to “enrich life for all” is deeply embedded in these advancements. With AI on the edge, smartphones are evolving into devices that think, react, predict, and adapt to our needs in more personalized ways. This new generation of smartphones promises to enhance our productivity and leisure, making each interaction more meaningful by staying seamlessly connected to our loved ones and passions while navigating the complexities of our daily lives.

As we embrace these changes, let’s ponder the profound impact of having a device that does more than execute commands—it collaborates, advises, and supports our every decision. With Micron’s commitment to pushing the boundaries of what’s possible, the future is not just about technological advancement but about creating deeper, more meaningful connections with the world around us. How will you harness this power to reshape your day-to-day life? The possibilities are as boundless as your imagination.

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Researchers at Penn State have developed a new 3D-printed material designed to advance soft robotics, skin-integrated electronics, and biomedical devices. This material is soft, stretchable, and self-assembled, overcoming many limitations of previous fabrication methods, such as lower conductivity and device failure. According to Tao Zhou, an assistant professor at Penn State, the challenge of developing highly conductive, stretchable conductors has persisted for nearly a decade. While liquid metal-based conductors offered a solution, they required secondary activation methods—like stretching or laser activation—which complicated fabrication and risked device failure.

Zhou explained that their method removes the necessity for secondary activation to attain conductivity. The innovative approach combines liquid metal, a conductive polymer mixture called PEDOT: PSS, and hydrophilic polyurethane. When printed and heated, the liquid metal particles in the material’s bottom layer self-assemble into a conductive pathway, while the top layer oxidizes in an oxygen-rich environment, forming an insulated surface. This structure ensures efficient data transmission to sensors—such as those used for muscle activity recording and strain sensing—while preventing signal leakage that could compromise data accuracy.

“This materials innovation allows for self-assembly that results in high conductivity without secondary activation,” Zhou added. The ability to 3D print this material also simplifies the fabrication of wearable devices. The research team is exploring various potential applications, focusing on assistive technology for individuals with disabilities.

The research, supported by the National Taipei University of Technology-Penn State Collaborative Seed Grant Program, included contributions from doctoral students Salahuddin Ahmed, Marzia Momin, Jiashu Ren, and Hyunjin Lee.

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Вакансії в НАЗК kpi ср, 07/10/2024 - 14:00

Courtesy: Microchip

Silicon Carbide (SiC) Schottky Barrier Diodes (SBDs) increase efficiency and ruggedness to help create faster and more reliable applications.

Better Efficiency and Reliability Through Silicon Carbide

Silicon Carbide (SiC) Schottky Barrier Diodes (SBDs) increase efficiency and create reliable high-voltage applications. Our rich history and experience allow us to deliver highly reliable SBDs that are designed with high repetitive Unclamped Inductive Switching (UIS) capability at a rated current, which exhibits no degradation. Our mSiC diodes are designed with balanced surge current, forward voltage, thermal resistance and thermal capacitance ratings at low reverse current for lower switching loss to create more efficient power systems.

Because of differences in material properties between SiC and silicon, silicon Schottky diodes are limited to a lower voltage range with higher on-state resistance (RDS(on)) and leakage current. However, SiC Schottky diodes can obtain a much higher breakdown voltage while maintaining low on-resistance and low switching losses, improving ruggedness over traditional silicon Schottky diodes. Our portfolio of mSiC products covers 700V, 1200V, 1700V and 3300V (3.3 kV) SiC Schottky diodes.

In summary, SiC offers the following advantages over silicon:

• Better reverse current capability
• Higher temperature stability
• Higher radiation resistance

Breakdown Voltage

The breakdown voltage of a diode is the voltage at which the diode breaks down and starts conducting current. The breakdown voltage determines the maximum voltage that the diode can withstand before it fails. SiC SBDs exhibit higher breakdown voltages than silicon diodes because of the SiC material’s higher bandgap. This higher breakdown voltage rating allows SiC diodes to withstand higher voltages without damage.

The higher breakdown voltage of SiC diodes is important for several applications including power converters, inverters and motor drives. In these applications, the diodes are often exposed to high voltages. The higher breakdown voltage of SiC diodes allows them to withstand these high voltages without damage, which can lead to improved reliability and performance.

Forward Voltage Drop

The forward voltage drop of a diode is the voltage drop that occurs when the diode is conducting current. This parameter determines the efficiency of the diode. SiC diodes have a lower forward voltage drop than silicon diodes. The higher bandgap means it takes less energy for an electron to move through the material. This lower forward voltage drop allows SiC diodes to be more efficient than silicon.

The lower forward voltage drop is important for several applications including power converters, inverters and motor drives. In these applications, the diodes are often used to convert power from one form to another. The lower forward voltage drop of SiC diodes allows them to be more efficient in these applications, which can lead to reduced costs and improved performance.

Reverse Recovery

Reverse recovery is a phenomenon that occurs when a diode is switched from conducting current to non-conducting current. During reverse recovery, a small amount of current flows in the reverse direction. This current can cause a voltage drop across the diode, which can damage the diode if it is not properly managed.

SiC diodes have a much shorter reverse recovery time, allowing them to switch from conducting current to non-conducting current more quickly, which can reduce the risk of damage. Reverse recovery is an important consideration for any application that uses diodes.

Reverse Current

The reverse current of a diode is the current that flows in the reverse direction when the diode is biased in the reverse direction. This current is a major factor that limits the performance of SiC diodes in high-voltage applications. The reverse current of SiC diodes is typically much higher than that of silicon diodes because the SiC material has a higher bandgap, which causes it to take more energy to break an electron free from its atom. This higher bandgap also means that there are fewer free electrons available to carry current in the reverse direction.

High reverse current can cause several problems in high-voltage applications, causing the diode to overheat and fail. It can also cause the diode to emit noise and interference. There are a few ways to reduce the reverse current of SiC diodes. One way is to use a diode with a higher breakdown voltage. Another way is to use a diode with a lower doping level. However, these techniques can reduce the performance of the diode in other ways.

High Temperature and High Current Stability

High temperature and high current stability are crucial because SiC diodes are often used in a variety of applications that require high currents and temperatures of up to 150°C. The stability of SiC diodes is important for their use in applications with more demanding conditions.

Stability at high temperatures and currents is due to the higher bandgap, which makes SiC more resistant to damage from heat and high current conditions. SiC diodes have a lower concentration of impurities than silicon diodes, making SiC diodes less likely to experience recombination, the process by which an electron and a hole combine to form an atom. Recombination can cause the diode to lose its ability to conduct current, leading to failure.

These attributes make SiC diodes well suited for applications that require high temperatures and currents, such as power converters and inverters, leading to improved reliability and performance in the end equipment.

Start Designing with SiC

Getting started with designing with Silicon Carbide (SiC) involves understanding its benefits and applications. We offer a range of Silicon Carbide (SiC) power products which are the key to faster, more efficient energy solutions.

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