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ST offers three antenna-matching companion chips for STM32WL33 wireless MCUs to help streamline the development of IoT, smart metering, and remote monitoring systems. The MLPF-WL-01D3, MLPF-WL-02D3, and MLPF-WL-04D3 integrate impedance matching and harmonic filtering on a single glass substrate to boost RF performance.

By integrating antenna protection, matching, and filtering, the devices simplify RF routing, improve reliability, and reduce BOM cost by replacing multiple discrete components. The three Series 3 chips will be joined by four new variants, supporting radio optimization across high-band (826–958 MHz) and low-band (413–479 MHz) ranges, high-power (16/20 dBm) and low-power (10 dBm) modes, and 2-layer or 4-layer PCB designs.

The MLPF-WL-01D3, MLPF-WL-02D3, and MLPF-WL-04D3 antenna-matching ICs are available now in 5-bump chip-scale packages, priced from $0.15 each in 1000-unit quantities. Release dates for the additional variants were not available at the time of this announcement.

MLPF-WL-0xD3 product page

STMicroelectronics

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The NTAG X DNA from NXP is an ISO/IEC 14443-4 Type 4 NFC tag that enables secure authentication of NFC-enabled mobile devices. It features 16 kB of memory, high-speed data transfer, and Secure Unique NFC (SUN) authentication to protect devices across healthcare, smart home, consumer electronics, and industrial markets.

Supporting device-only, device-to-device, and device-to-cloud authentication, the NTAG X DNA secures data transfer via NFC or I²C interfaces at speeds up to 848 kbps and 1 MHz, respectively. A direct MCU connection enables device diagnostics, while the tag’s memory allows access to stored authentication data—even without power. Sensitive information can also be erased in power-off conditions to protect user privacy.

Designed to combat counterfeits and support Digital Product Passport (DPP) compliance, the NTAG X DNA offers strong security with Common Criteria EAL 6+ certification and PKI-based asymmetric cryptography. It is backed by NXP’s EdgeLock 2GO service for UID and certificate delivery, as well as on-demand certificate generation.

NTAG X DNA product page

NXP Semiconductors 

The post IC safeguards NFC communication appeared first on EDN.

Qorvo’s QPA3311 and QPA3316 hybrid power doubler amplifiers are optimized for DOCSIS 4.0 downstream operations up to 1.8 GHz. They support the transition to Unified DOCSIS and smart amplifier architectures that enhance visibility, efficiency, and adaptability in hybrid fiber-coax (HFC) systems.

Based on a GaAs/GaN die, the devices operate from 45 MHz to 1794 MHz and provide 23 dB of gain. They are well-suited for DOCSIS 4.0 CATV nodes and amplifiers. High total composite power and improved signal integrity reduce cascade requirements and enhance end-of-line performance, helping lower infrastructure costs by eliminating the need for booster amps.

The QPA3311 and QPA3316 power doublers operate from 24-V and 34-V supplies, respectively, with power consumption of 12.5 W and 18 W. At 51 dB CNN, total composite power reaches 74 dBmV for the QPA3311 and over 75 dBmV for the QPA3316.

Both the QPA3311 and QPA3316 power doubler amplifiers are housed in SOT-115J packages and are now in production.

QPA3311 product page

QPA3316 product page 

Qorvo

The post Power doublers enable smooth DOCSIS 4.0 upgrades appeared first on EDN.

Asahi Kasei has developed the Sunfort TA series of dry film photoresist for next-generation semiconductor packages requiring circuit patterns with line/space widths of 2/2 µm or less. The film offers high resolution with conventional stepper and laser direct imaging (LDI) systems—used to transfer circuit patterns onto substrates—enhancing precision in back-end processes.

The TA series supports fine wiring formation in panel-level packages and related applications. It enables patterning with a 1.0-µm resist width using LDI exposure in a 4-µm pitch design, as required for redistribution layer (RDL) formation (Figures a and b). The resulting fine resist pattern can be plated by a semi-additive process, then stripped to yield a 3-µm wide plating pattern within the same 4-µm pitch (Figure c).

Asahi Kasei states that Sunfort dry film photoresist will remain integral to advancing panel-level packaging technology as panel sizes increase. With its ability to achieve finer wiring and improve production efficiency, the TA series addresses the rising demand for advanced semiconductor package substrates and interposers in AI, automotive, communications, and IoT markets.

TA series product page

Asahi Kasei 

The post Dry film photoresist enables fine circuit formation appeared first on EDN.

The typical regulator output network

Many voltage regulator chips, both linear and switching, use the same basic two-resistor network for output voltage programming. Figure 1 illustrates this feature in a typical switching (buck type) regulator, see R1 and R2, where:

Vout = Vsense(R1/R2 + 1) = 0.8v(11.5 + 1) = 10v

Figure 1 A typical regulator output programming network where the Vsense feedback node and values for R1 varies from type to type.

Quantitatively, the Vsense feedback node voltage varies from type to type and recommended values for R1 can vary too, but the topology doesn’t. Most conform faithfully to Figure 1. This de facto uniformity is useful if your application involves PWM control of Vout. 

Wow the engineering world with your unique design: Design Ideas Submission Guide

The three-component PWM-to-regulator solution

Figure 2 shows the simple three-component solution that the above topology makes possible. Note, the PWM duty factor (DF) is from 0 to 1, where:

Vout = Vsense(R1/(R2/DF) + 1) = DF(11.5)0.8 + 0.8 = DF*9.2 + 0.8v

Figure 2 Three parts comprise a circuit for linear regulator programming with PWM.

To introduce linear PWM control to the Figure 1 regulator, all that’s required is to add three discrete components: the PWM switch Q1, and the ripple filter capacitors C1 and C2. Note that Vout will go to Vsense(C1/C2 + 1) = 10v for about 6 ms during power up while C1 and C2 are charging, but that should be okay.

The C2 capacitance required for 1 lsb (0.4%) PWM ripple attenuation is C2 = 2(N-2)/(R1*Fpwm), where N is number of PWM bits, and Fpwm is the PWM frequency (10 kHz illustrated).

Then, to avoid messing with U1’s designed loop gain, possibly reducing stability, C1 = C2*R2/R1. This capacitance ratio also provides protection for U1’s Vsense input, since it ensures that even a sudden short of Vout to ground can’t drive Vsense dangerously negative.

 This combination of time constants yields a first-order 8-bit settling time of T8 = R1C2ln(256) = 37ms. More on this lengthy number shortly.

A cool feature of this simple topology is that, unlike many other schemes for digital power supply control, only the precision of R1, R2, and the regulator’s internal voltage reference matter for regulation accuracy. Precision is therefore independent of external voltage sources, e.g., logic rails. Precision, measured as percentage of Vout, is also independent of Df, and remains equal to Vsense precision (e.g., ±1%) for all output voltages.

Speeding up the settling time

What if a 37-ms settling time is too lengthy for your application? What if you wouldn’t mind investing a couple more parts to speed it up? Figure 3 shows what.

Figure 3 Add R3 and C3 to get analog ripple subtraction, second-order filtering, and a 7-ms settling time. The symbol “*” represents a precision of 1% or better.

First disclosed in EDN Design Idea (DI), “Cancel PWM DAC ripple with analog subtraction,” a thrifty way to implement second-order PWM ripple filtering is through the analog subtraction of the AC component in the logic inverse of the PWM signal from the DC result. Figure 3 shows how that can be accomplished by simply adding R3 and C3 to the Figure 2 topology. Note that the impedance ratios of the added parts are equal to the ratio of the 5-Vpp PWM signal at Q1’s gate to the 0.8-Vpp logic complement at its drain = 5v/0.8v = 6.5.  This is why R3 = 6.5*R2 and C3 = C2/6.5.

In closing: This DI revises an earlier submission, “Three discretes suffice to interface PWM to switching regulators.” My thanks go to commenters oldrev, Ashutosh Sapre, and Val Filimonov for their helpful advice and constructive criticism. And special thanks go to editor Shaukat for her creation of an environment friendly to the DI teamwork that made this possible.

Stephen Woodward’s relationship with EDN’s DI column goes back quite a long way. Over 100 submissions have been accepted since his first contribution back in 1974.

 Related Content

• Three discretes suffice to interface PWM to switching regulators
• Cancel PWM DAC ripple with analog subtraction
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• Tracking preregulator boosts efficiency of PWM power DAC
• Another PWM controls a switching voltage regulator
• Control an LM317T with a PWM signal

The post Revisited: Three discretes suffice to interface PWM to switching regulators appeared first on EDN.

For decades, we heard silicon was the only answer. However, while the world’s largest fabs were busy taping out silicon, the communities of engineers and scientists working on non-silicon technologies continued pushing forward. Compound semiconductors—semiconductors made from two or more periodic table elements—include indium phosphide (InP), silicon nitride (SiN), gallium arsenide (GaAs), germanium (Ge), indium gallium arsenide (InGaAs), cadmium telluride (CdTe), gallium nitride (GaN), and silicon carbide (SiC).

Once Tesla introduced SiC MOSFETs in its EVs in 2018, SiC would no longer go unnoticed. The market has grown to more than $2.5 billion in 2024, and despite the temporary slowdown in 2025, is expected to continue growing at a staggering pace according to Yole and TrendForce.

Most EV electronics suppliers now offer SiC power ICs, creating a new ecosystem of material suppliers, capital equipment, fabless companies, foundries, and outsourced semiconductor assembly and test (OSAT) service suppliers.

Some integrated device manufacturers (IDMs)—including Bosch, Denso, Infineon, onsemi, Rohm, SanAn, STMicroelectronics, and Wolfspeed—went fully vertical starting with the SiC powder and ending with multi-die power modules.

Figure 1 SiC’s bubble size indicates its manufacturing volume and annual growth. Source: Author

Many newcomers got into the substrate business because of the high cost of the raw material. They invested heavily in mergers and acquisitions and organic growth and are now faced with the challenge of returning investment to shareholders. In this highly competitive environment, manufacturers are pushed to new levels in yield, quality, efficiency, and capacity.

Benefits are costly

SiC offers benefits to designers and consumers. Thanks to the material properties, SiC transistors can be operated at much higher voltages with lower resistance, showing less performance degradation with temperature, making SiC electronics appealing for power conversion and charging applications in vehicles and power grid applications.

However, the raw material is substantially more expensive than silicon. Crystal growth is orders of magnitude slower than silicon—its hardness, second only to diamond, makes it hard to slice, polish, and dice. High operating voltages require thick epitaxial layers that exhibit high defectivity. Next, vertical transistor architecture requires substantial wafer backside processing. All this translates to higher defectivity and lower yield with frequent yield excursions.

To the consumer, it’s higher product cost and lower reliability in the field.

Years behind silicon

“SiC is decades behind silicon,” is the common cliché among manufacturers. Here, the dominant wafer size is a good indication of material platform maturity. Historically, as silicon manufacturing matured, the industry transitioned to a larger wafer size, going through 100-, 150-, 200- and 300-millimeter (mm) wafers over the four decades, as shown in the figure below.

Figure 2 Most of the high-volume manufacturing capacity for SiCs is expected to remain on 150-mm wafers. Source: Author

Presently, SiC is made predominantly on 150-mm substrates. Meanwhile, several companies announced a transition to 200-mm substrates. While Chinese substrate supplier SICC demonstrated 300-mm substrate in 2024, use of such a large substrate is beyond the horizon. In the next several years, most of the capacity is expected to remain on 150-mm wafers.

Yes, SiC is 30 years behind silicon, judging by the substrate sizes in volume manufacturing.

Complexity of SiC circuits resembles silicon chips in the 1980s—integration into complex circuits today is at the package level rather than on a monolithic IC as seen in silicon. While the most complex silicon ICs count billions of transistors, SiC ICs are nowhere near such complexity. The reason is simple—die yield scales exponentially with the die area. At high defectivity levels, this becomes detrimental, and the only answer is going with a smaller die, integrating known good die at the package level into a more complex circuit.

However, while SiC seems decades behind silicon, it does not need decades to catch up.

The big data platform

Methodologies developed over the decades in silicon IC manufacturing are now available. One example is a solution that deploys data analytics for silicon utilized to streamline innovation. The benefits are numerous:

• Breaking the silos: The technology cycle from IC design to high-volume manufacturing is long with many players and data silos across operations. That’s where end-to-end big data platforms can connect all data end-to-end and make it available to a broad range of functions.
• Smart factory: Front-end factories are different from their predecessors. Today’s manufacturing ecosystem offers a variety of software capabilities from dozens of suppliers with well-established interoperability.
• Standardization: Thanks to several organizations—including SEMI, Global Semiconductor Alliance (GSA), and Semiconductor Industry Association (SIA)—there is a broad landscape of industry standards covering everything from equipment connectivity to data formats and specifications. Standards enable better interoperability between tools and suppliers, streamlining equipment and software deployments to support yield ramps.
• Material traceability: Whether the need is for tracing wafers in a fab or die in an assembly line, the task is complex and ranges from multiple substrate IDs and rework at different steps to substrate grading to cherry-picking. In an assembly line, it’s a challenge solved with traceability standards.
• Data models: A data model details material data, inline data from the fabs, and assembly and test data from OSATs. It describes physical entities such as equipment, wafers, dies and modules, processes including fab, assembly and test, and their relationships in the context of manufacturing flow.
• Artificial intelligence/machine learning (AI/ML): Decades ago, scientists had to develop analytical relationships between causes and effects, while software developers came up with software specifications. A myriad of data-centric frameworks and the ubiquity of AI/ML now shorten this cycle, eliminating numerous bottlenecks.
• Too much data: Vast amounts of data are generated per wafer throughout the manufacturing operations, though most of that data is never used. At the same time, engineers in the automotive segment are putting more stringent requirements on their chip and module suppliers regarding data collection and retention. The data platform must enable a good mix of storage options allowing tradeoffs between performance and cost and provide the knobs for data caching and aging.

Adopting an industry-standard solution allows manufacturers to improve efficiency and ramp yields faster than the competition.

What’s next

According to Yole, TrendForce, McKinsey and SEMI, growth is forecasted for most compound semiconductor devices, with silicon carbide at the top of that list. Following Gartner’s terminology of the “hype cycle,” it’s past disillusionment. Both silicon and GaN have been carving out more space in the power IC market. This change will push SiC for performance and cost.

At the same time, more suppliers are stepping into the market in each segment—material suppliers, foundries, fabless and IDMs. Competition will intensify, pushing manufacturers for higher yields, faster development cycles, and higher levels of integration.

Under pressure for cost and performance, designers and manufacturers must start adopting big data platforms.

Steve Zamek, director of product management at PDF Solutions Inc., is responsible for manufacturing data analytics solutions for foundries and IDMs. Prior to this, he was with KLA (former KLA-Tencor), where he led advanced technologies in imaging systems, image sensors, and advanced packaging.

Related Content

• The Road to 200-mm SiC Production
• Silicon carbide (SiC) counterviews at APEC 2024
• Wolfspeed to Build 200-mm SiC Wafer Fab in Germany
• Silicon carbide’s wafer cost conundrum and the way forward
• Reducing Costs, Improving Efficiency in SiC Wafer Production with CMP

The post Accelerating silicon carbide (SiC) manufacturing with big data platforms appeared first on EDN.

Interested in DIY a simple electronic impulse relay module? T. K. Hareendran designs an impulse relay circuit that mimics the functions of a conventional electromechanical impulse relay. This module switches the same load from several switching points. He also provides design details of different ICs that can be used in this hobby-level project. That includes pin-by-pin configurations and respective timing steps.

Read the full article at EDN’s sister publication, Planet Analog.

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• Dual-coil relay driver uses only two MOSFETs
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• Relays Are Great, But There’s No Need to Let Them Waste Power

The post Basic considerations for electronic impulse relay DIY appeared first on EDN.

Last week was a biggie for those of you into tech conferences. First and foremost, of course, there was the 2025 iteration of the Silicon Valley-located Embedded Vision Summit, for which I have both personal interest and professional association. In parallel (and in Taiwan), a “little” computer conference called Computex was going on. And from a single-company-sponsored event standpoint, there were two dueling ones: Google with I/O in Mountain View, CA, which I’ll cover in my next post, and Microsoft, with Build in Seattle, WA, which I’ll detail today.

2024 launches

To begin, however, I’ll rewind two weeks further in the past. Revising my previous year’s (2024) Build coverage, you’ll note as I did at the time that this was the first time Microsoft launched new generations of the consumer-tailored versions of its various Surface family mobile computer products that exclusively leveraged Qualcomm’s Snapdragon X Arm-based SoCs.

And equally, if not more notable, last year was also the first time Microsoft added Arm-based variants to its “For Business” Surface product portfolio:

2025 launches

Fast forward to early May 2025 and, for some unknown reason, Microsoft decided to decouple its new-hardware unveilings from the main Build event, releasing the earlier announcements on May 6. Once again there were Arm-only Surface systems for consumer:

and business users:

Although this time, there weren’t any full-generation upticks. Instead, portfolio expansion and cost reduction (the latter aided by broader product line tweaks, albeit tempered by looming tariff-induced potential price increases) came to the fore. The Surface Pro is now available in both legacy 13” and new 12” form factors, while the Surface Laptop now comes in both legacy 13.8” and 15” and a new 13” size. Both newcomers are more svelte than their precursors: 0.61” versus 0.69” and 2.7 lbs. versus 2.96 lbs. for the Surface Laptop, and 0.30” vs 0.37” and 1.5 lbs. vs 1.96 lbs. (in both cases absent the optional keyboard case) for the Surface Pro.

The Surface Laptop’s hardware

I’d argue that the Surface Laptop’s form factor evolution is the more critical of the two from a competitive standpoint, an opinion which factors more generally into the fundamental reason why I’m devoting so much of today’s writeup to hardware. x86-based systems increasingly seem to me to be an afterthought for Microsoft, despite the fact that AMD and Intel have belatedly caught up with Qualcomm from a neural processor core performance standpoint and thereby gained the right to put the Copilot+ marketing moniker on systems containing their CPUs, too. Why is Microsoft becoming increasingly Arm-centric? Because I’d hypothesize, Microsoft is also becoming increasingly Apple-fixated, as the latter company’s half-decade-back announced transition from x86 to Arm-based Apple Silicon systems bears increasingly bountiful fruit.

The new 13” Surface Laptop pretty clearly has Apple’s MacBook Air in its sights, although whether it’ll actually hit its target (and if so, whether mortally or resulting only in a flesh wound) is less clear. For one thing, it’s based on the 8-core variant of the Snapdragon X Plus, versus the 10-core “Plus” and 12-core “Elite” SoCs found in the slightly larger system (that said, all Snapdragon X variants deliver the same level of NPU performance). The SSD is (slower) UFS in interface, versus NVMe, and tops out at 512 GBytes of capacity. There’s only one DRAM option offered: 16 GBytes. And although the display is only slightly smaller, its image quality specs are more notably diminished: 1920×1280 pixels at 60 Hz versus 2304×1536 pixels at 120 Hz.

The Surface Pro’s hardware

The 12” Surface Pro is similarly processor core count, mass storage capacity, and system memory size-encumbered, as is its display, albeit not as badly: IPS-based with 2196×1464 pixels at 90 Hz versus either IPS- or OLED-based 2880×1920 pixels at 120 Hz. That said, I concur with Ars Technica’s Andrew Cunningham; the return of the first few Surface Pro generations’ flimsy keyboard is baffling, especially when it had just been further reinforced with last year’s offering. Both new systems drop the proprietary Surface Connect port in favor of USB-C, curiously dispensing with MagSafe-like magnetic-connector charging capabilities in the process (I’m guessing the European Union might have had a little something to do with that decision).

Big picture, Microsoft is seemingly increasingly confident in Windows 11 Arm64’s Prism x86 code virtualization foundation’s robustness. Nobody (including me, repeatedly) was realistically saying so just a few years ago, but by focusing development attention on 64-bit- and Windows 11-only emulation, the Prism team has made tangible progress since then. I’ve got three Windows 11 Arm64-based systems here, and rarely do I encounter a glitch anymore (that said, I’m not a gamer). Further improving the situation, not only from inherent compatibility but also performance and power consumption standpoints, is the increasing prevalence of Arm64-native application variants (such as Dropbox: yay!). And the “dark cloud” of looming lawsuits between Arm and Qualcomm that I’d mentioned a year ago, thankfully, also dissipated a few months back.

AI-related announcements

Early May wasn’t all about hardware for Microsoft. The company also unveiled a raft of Copilot+-only new and expanded capabilities for Windows 11. And two weeks later, this trend extended even more broadly into Microsoft’s operating system and applications with numerous AI-related announcements at Build. Examples included:

• Web app “hooks” via the Edge browser into on-device deep learning models
• Open-source model support via another set of “hooks”, Windows AI Foundry and its local inference runtime, Windows ML

• Embrace of the Model Context Protocol (MCP), initially unveiled by Anthropic, enabling developers’ AI apps and agents to talk to other apps, web services…even Windows itself

• An AI coding agent offered by Microsoft-owned GitHub
• And even AI “actions” built into File Explorer

Microsoft also revealed a new command-line text editor, an open-source transition for the Windows Subsystem for Linux (WSL), and encryption algorithm enhancements, for example. That said, much of the rest of the keynote (at least; I wasn’t there so can’t speak to the training sessions), was rife with AI technobabble, IMHO, from both Microsoft execs and invited notable guests, complete with innumerable mentions of the “agentic web” and other trendy lingo.

Watch it yourself, or not

See below if you’re up for a slog through the entire 2 hours of oft-tedium:

Conversely, if a 15-minute summary is more to your liking, here’s The Verge’s take:

And with that, having just passed 1,000 words, I won’t force you to slog through any more of my technobabble As always, I’ll end with an invitation to share your thoughts in the comments!

—Brian Dipert is the Editor-in-Chief of the Edge AI and Vision Alliance, and a Senior Analyst at BDTI and Editor-in-Chief of InsideDSP, the company’s online newsletter.

Related Content

• Microsoft’s Build 2024: Silicon and associated systems come to the fore
• Apple on Arm: How did we get here?
• Apple’s spring 2025 part II: Computers, tablets, and a new chip, too
• Microsoft’s Build 2024: Silicon and associated systems come to the fore

The post Microsoft Build 2025: Arm (and AI, of course) thrive appeared first on EDN.

Semiconductor laser diodes (SLDs) are often packaged with a photodiode. The output current from this photodiode can be monitored to regulate the output power intensity of the laser diode. SLDs, however, are prone to pathological drifts, such as temperature variations and mode-hopping, that can alter the output intensity. A popular approach to stabilize the output intensity is to first convert the photodiode current to voltage. This voltage can then be read by a microcontroller, where logic can be programmed to adjust the current supplied to the laser diode. This method is illustrated in Figure 1.

Figure 1 Using a microcontroller to regulate laser diode output power by sensing photodiode current.

Wow the engineering world with your unique design: Design Ideas Submission Guide

Figure 2 provides an alternative implementation that uses a single operational amplifier. When the circuit is powered on, there is initially no photodiode current. The voltage at the positive input of the op-amp is pulled to VCC, and the op-amp powers the laser diode. This induces current in the photodiode, which creates a voltage drop across R1, setting the positive input of the op-amp to: Vcc – Iphotodiode ∗ R1.

Figure 2 A single op-amp solution using negative feedback to provide output power regulation.

The op-amp buffers this voltage and feeds it to the laser diode. The system stabilizes at an operating point determined by:

1. The laser diode’s VI-intensity curve
2. The coupling efficiency between the laser diode and photodiode
3. The current-intensity response of the photodiode
4. R1

Thereafter, negative feedback stabilizes any variations in output intensity. If the laser intensity increases, the photodiode responds by generating a higher current, which in turn creates a larger voltage drop across R1. This reduces the output voltage of the op-amp, subsequently decreasing the laser intensity. The opposite behavior is seen with a drop in laser output power.

This circuit was built on a breadboard using the OPV314 850-nm VCSEL and the OPA551P op-amp from Texas Instruments (Figure 3). R1 was set to 68 kΩ, and VCC was set to 5 V.

Figure 3 Components assembled on a breadboard using the OPV314 850-nm VCSEL and the OPA551P op-amp.

The oscilloscope trace captured from the positive node of the op-amp is shown in Figure 4, demonstrating the stable output from the laser (arbitrary units). R1 can be used to control the output power intensity.

Figure 4 Oscilloscope trace of positive node of op-amp (proxy for output laser intensity).

Anirban Chatterjee is a biomedical engineer with 10 years of experience in the consumer electronics industry. He holds a master’s degree in electrical engineering and is a member of IEEE. He holds a keen interest in biomedical sensors and associated signal processing techniques.

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The post A single op-amp solution to stabilize laser output appeared first on EDN.

Reverse polarity protection is essential in battery-connected automotive systems. So, while reverse polarity is a risky, how do we prevent it? This article delves into reverse polarity protection circuits built around standard and Schottky diodes, as well as high-side P-channel and N-channel MOSFETs. It also offers design ideas on how to implement these protection circuits efficiently.

Read the full article at EDN’s sister publication, Planet Analog.

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The post How reverse polarity protection works to safeguard car battery appeared first on EDN.

At a time when the explosive growth in artificial intelligence (AI), data centers, electric vehicles (EVs), and renewable energy is triggering an unprecedented demand for high-voltage, high-frequency and high-efficiency power devices, the chatter about silicon carbide (SiC) poster child Wolfspeed’s bankruptcy has startled the semiconductors world.

Wolfspeed, which divested its LED and RF businesses to focus on SiC-based power electronics, has been considered a flagbearer in the rapidly emerging SiC semiconductors market. The company pioneered 1-inch, 2-inch, 4-inch and 6-inch SiC wafers, and it was the first outfit to open an 8-inch SiC wafer fab in Mohawk Valley in 2022.

In fact, Wolfspeed is now the only company manufacturing SiC devices on 8-inch wafers in high volume. So, what has gone wrong in Wolfspeed’s SiC fairy tale? For a start, while the word bankruptcy triggers a sense of shock for a company that’s considered the market leader, the truth is that Wolfspeed is restructuring itself to address financial vows and reinforce operational efficiency.

After all, SiC is a new market that is constantly evolving. That inevitably brings growing pains, especially when a new technology like SiC entails higher product development costs while carrying small-volume orders. In other words, Wolfspeed’s situation is more than a company in crisis.

Figure 2 The SiC-based devices promise to transform power electronics in segments ranging from data centers to EVs to renewable energy. Source: Wolfspeed

Why bankruptcy

Now, let’s take a closer look at Wolfspeed’s predicament. First and foremost, a slowdown in EV demand is widely quoted as the cause of Wolfspeed’s current misfortunes. Second, while the SiC substrate business has served as the cash cow for Wolfspeed, the arrival of Chinese players has led to a steep decline in the price of SiC substrates.

According to Yole, the advent of Chinese SiC substrate suppliers has led to a significant capacity expansion and a 30% price drop in 2024. Third, and probably most important, are Wolfspeed’s financial headwinds. It’s carrying $6.5 billion debt while its sales projections seem too optimistic amid the EV slowdown and aggressive push from Chinese players in the SiC market.

So, this bankruptcy news looks more like a bid to establish supply chain discipline, capital flexibility, and policy alignment. The recent change of guards at Wolfspeed in which Gregg Lowe bowed down to make way for Robert Feurle is most likely about setting the stage for this critical transition.

Figure 2 It’s probably no coincidence that Feurle’s appointment precedes the bankruptcy news. Source: Wolfspeed

It’s pretty ironic that Wolfspeed, then known as Cree, made a huge bet on LEDs at a time when the LED market was about to crash. Nearly two decades later, Wolfspeed decided to transform itself into a power electronics device company. Yole calls it an exciting story of business transition.

While the Wolfspeed bankruptcy is most likely coming in weeks, it’s important to put things in perspective. Wolfspeed is still a market leader in SiC materials and is ranked number four in SiC power devices. That said, SiC’s technology and cost challenges leave Wolfspeed with gigantic task of turnaround in a market that demands high CapEx for future development.

Related Content

• Wolfspeed to Build 200-mm SiC Wafer Fab in Germany
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• Wolfspeed at APEC 2025: Jay Cameron on the Growing Role of SiC

The post The truth about Wolfspeed’s bankruptcy chatter appeared first on EDN.

Inductor-inductor-capacitor (LLC) resonant converters have a couple of appealing characteristics for applications requiring an isolated DC/DC converter such as minimal switching losses, no reverse recovery when operating below the resonant frequency and the ability to tolerate large leakage inductance within the transformer.

The challenge

A primary challenge when designing an LLC converter with a wide operating range is the behavior of the gain curve with respect to equivalent load resistance. This is because as the quality factor (Qe), increases, the maximum attainable gain decreases Conversely, the minimum attainable gain increases as Qe decreases. This is shown in Figure 1 below.

Figure 1 LLC gain curves showing that, as Qe increases, the maximum attainable gain decreases. Source: Texas Instruments

This behavior makes it difficult to maintain reasonable root-mean-square (RMS) currents in the power stage and a reasonable switching frequency range. The inductance ratio (Ln) needs to be reduced to reduce the required frequency range; however, a lower inductance ratio increases the magnetizing current in the power stage. This article will discuss five tips for designing an LLC converter with a wide operating range.

Using a reconfigurable rectifier

One potential way to extend an LLC converter’s operating range is to implement a reconfigurable rectifier, as shown in Figure 2.

Figure 2 shows an LLC converter with a reconfigurable rectifier, which can be reconfigured as either a full-bridge or a voltage-doubler. Source: Texas Instruments

In this structure, you can configure the rectifier as a full-bridge or a voltage-doubler rectifier by using a comparator to look at the output voltage to decide the mode of operation. When operating as a full-bridge rectifier, Equation 3 calculates the input-to-output transfer function.

When operating as a voltage doubler rectifier, the input-to-output transfer function is:

Figure 3 shows the switching frequency versus output voltage for an LLC using the above approach to achieve a 140-V to 420-V output voltage range from a fixed 450-V input. This data is collected with an 800-mA load on the output. Notice the jump at 200 V where the comparator switches from full-bridge to voltage-doubler mode.

Figure 3 Switching frequency versus output voltage in LED driver reference design. Source: Texas Instruments

Minimizing winding and rectifier capacitance

If the operating point drops below the minimum gain curve, the LLC controller is forced to operate in burst mode to keep the output voltage in regulation. Burst mode results in higher low-frequency output ripple voltage. This is a concern for applications requiring very low output ripple at light load and at the minimum output voltage.

In such cases, the winding capacitance within the transformer and the output capacitance (Coss) or junction capacitance (Cj) of the rectifiers must be minimized. These parasitic capacitances will cause the gain curve to invert when operating above the resonant frequency. Figure 4 shows the traditional first harmonic approximation (FHA) calculation of an LLC gain curve at light load and the same LLC gain curve when accounting for winding the capacitance and Coss of the rectifiers used in the power stage.

Figure 4 The impact of parasitic capacitance on the LLC gain curve at light load. Source: Texas Instruments

Careful attention to the winding stackup within the transformer and selection of the rectifier components minimizes this gain curve inversion effect. Using wide bandgap devices such as SIC diodes or GaN high electron mobility transistors (HEMTs) as the rectifier can result in considerably lower Coss compared to Si MOSFETs or diodes.

Using LLC controllers with a high-frequency skip mode

A high-frequency skip mode can achieve a lower gain compared to what is achievable with normal switching. Below is an example from a 100-W half-bridge LLC converter with an input range of 70 V to 450 V. In Figure 5, the resonant current is shown in green, and the primary side switch node is shown in blue.

On the right side, the LLC converter is operating in a high-frequency skip mode, omitting every fourth switching cycle. The switching frequency is 260 kHz, but it is sub-modulated at a 77 kHz burst frequency. 

Figure 5 The 100-W LLC converter switching behavior at 70V and 450V inputs with resonant current in green and the primary side switch node in blue. Source: Texas Instruments

 Managing auxiliary bias voltages

Generating the necessary bias voltages for the primary and secondary sides of the power supply can be done by including auxiliary windings on the LLC transformer. For LLC converters with a variable output voltage, the auxiliary winding voltages will change as the output voltage changes. This is especially true for LLC transformers using sectioned bobbins where the auxiliary windings have poor coupling to the secondary windings. When using a simple low-dropout regulator (LDO) structure to regulate the bias voltage, the efficiency will drop as the output voltage increases. It may require a larger physical package to handle the power dissipation.

In Figure 6, Naux1 and Naux2 are sized so that at the lowest output voltage, or the VCC bias voltage, is provided through D1, Q1, and D4. As the output voltage increases, the voltage on C2 is limited to the breakdown voltage of Zener D3 minus the gate-source threshold voltage of Q1. As the output voltage is increased further, the voltage generated by Naux2 becomes high enough to supply VCC, and Q1 is forced off as the gate-source voltage decreases below the turn-off threshold.

Figure 6 Using auxiliary windings along with an LDO structure to generate the necessary bias voltages for the primary and secondary side of the power supply. Source: Texas Instruments

This approach is more efficient than a single winding + LDO but requires two aux windings. An alternative approach that requires only one aux winding is to use a buck converter or boost converter instead of an LDO.

Managing trickle-charging for deeply discharged batteries

LLC converters used as battery chargers must safely recover deeply discharged batteries by applying a small charging current until the battery pack voltage is high enough to safely take the full charging current. LLCs cannot regulate down to a 0-V output with a small output current and therefore struggle to meet this requirement.

This can be managed by including a small constant current circuit with a bypass FET in parallel, as shown in Figure 7. When in trickle-charge mode, the bypass FET turns off, and the output current is supplied by LM317 configured to regulate the output current. This allows the minimum output voltage of the LLC converter to be greater than 0 V, even with an output voltage of 0 V. This approach allows the LLC transformer to generate the necessary bias voltages on the primary and secondary side and avoid needing a separate bias supply when the output voltage is 0 V. Once the battery pack voltage has risen to a high-enough level, a FET with a discrete charge-pump circuit bypasses the constant-current circuit.

Figure 7 LLC with a trickle charging circuit that can safely recover deeply discharged batteries. Source: Texas Instruments

Wide LLC operation

While achieving a wide operating range with an LLC converter may look difficult due the nature of the LLC topology, several strategies exist for obtaining a wide operating range easier to achieve. The five simple tips and tricks listed here are analog-control friendly and do not require more complex, digital-control implementations.

Ben Lough is a Systems Engineer in Texas Instrument’s Power Design Services team focused on power factor correction and isolated DC/DC conversion. He received his MS in Electrical and Computer Engineering from Ohio State University in 2016 and BS in ECE from Ohio State in 2015.

 

Related Content

• Power Tips #117: Measure your LLC resonant tank before testing at full operating conditions
• Power Tips #137: Implementing LLC current-mode control on the secondary side with a digital controller
• Power Tips #84: Think outside the LLC series resonant converter box
• Power Tips #103: LLC design considerations for audio amplifiers

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The smartphone case study

Back in late March, at the end of my coverage of Google’s Pixel 9a smartphone launch:

I mentioned that one of my Pixel 7 phones had started swelling, indicative of a failing battery:

I teased that my fortunate upfront purchase of an extended warranty for it ended up being fortuitous and promised that the “rest of the story” would follow shortly. That time is now, and in this piece, I’ll also contrast my most recent experience with an earlier, less-positive outcome, as a means of more broadly assessing the consumer electronics warranty topic.

First, the Pixel 7. Devices containing swollen batteries can quickly transform into dangerously flammable sources, so I immediately removed the smartphone from its charger and powered it down. I then reactivated my Pixel 6a backup phone, the same one I’d temporarily pressed into service around a year earlier when my other Pixel 7’s rear camera array’s glass cover spontaneously cracked, and swapped the SIM into it. And then, I jumped online with Asurion, reported the issue, paid a (bogus, IMHO) $138.68 “service fee”, was directed to a local repair location (Asurion had bought uBreakiFix in late 2019), dropped the swollen Pixel 7 off, and ~24 hours later had a gift card sitting in my account for the original purchase price!

Let’s do the math:

• I bought the 128 GByte version of the phone in early June 2023 for $499, promotion-bundled (at the time) with a $100 Amazon gift card, for an effective price of $399.
• For the next 20 months (Asurion also auto-refunded my most recent month’s payment, although I had to then manually cancel the overall policy through Amazon, where it was treated as a subscription), I’d been paying $7.83 per month inclusive of tax for extended warranty coverage…a bit irritating, as the phone was redundantly covered by Google’s standard warranty for the first 12 of those months, but…for $156.60 total.
• I paid a $138.68 (once again, ridiculous, but…) “service fee” to process the warranty
• And I ended up getting a $499 gift card.

If my arithmetic is right, I ended up using the phone for nearly 2 years for a total fiscal outlay of $195.28 (plus the cost of the replacement phone, which I’ll mention next). I’m a bit surprised, honestly, that Asurion didn’t just have uBreakiFix swap in a new battery and give it back to me. That said, the display or internals might have gotten stressed by the swelling, so it was likely more straightforward for them from a long-term customer retention standpoint to just give me my money back. And to be clear, considering the burgeoning market for refurbished phones and other consumer electronics devices, they probably went ahead and swapped the battery themselves and then, after running diagnostics on the phone to make sure everything else checked out, resold it on Amazon Renewed, eBay Refurbished, or elsewhere.

Speaking of which, eBay is where I ended up picking up my replacement smartphone. I could have gone with a newer-generation Pixel device (or something else, for that matter), but I already had a bunch of extra Pixel 7-tailored cases, screen protectors and such in storage. And, thanks to Google’s recently expanded five years of software coverage for the Pixel 7 (and my Pixel 6a spare, for that matter), it was now guaranteed to get OS and security updates until October 2027 (versus the original October 2025, i.e. a few months from now as you read these words). I ended up with an eBay Certified Refurbished 128 GByte Pixel 7 in claimed excellent condition, complete with a 1-year bundled warranty, for $198.95 plus tax.

And indeed, when it arrived, it was in excellent condition (reflective of the highly and abundantly rated supplier I’d intentionally, carefully selected), cosmetically at least. It appears to have had a case and screen protector on it for its entire ownership-to-date, both of which I immediately replicated. And functionally, it also seems to be fine, albeit with one characteristic that gave me initial pause. Check out the to-date battery recharge cycle count reported for it:

At first glance, that seemed like a lot, given that Google documents that the Pixel 7 “should retain up to 80% capacity for about 800 charge cycles, after which battery replacement is “recommended,” and particularly given that my other Pixel 7 only has 40 to-date cycles on it:

But I’m an admittedly atypical case study. I work from home, where I also have VoIP, and rarely travel, so my smartphone usage is much lower than the norm. Conversely, given that the Pixel 7 first became available on October 13, 2023, 531 cycles almost exactly match a more typical one-recharge-per-day cadence. Going forward, now in my possession, this phone’s incremental-cycle cadence should dramatically decrease. And to further extend usable life, I’ve belatedly taken the extra step of limiting the peak charge point to 80% of total capacity on both Pixel 7s.

The soundbar case study

So, all good, right? Not exactly…there’s that other case study that I mentioned upfront I wanted to share. Two years back, I told you about my Hisense HS205 soundbar:

 

which I’d recently snagged on sale at Amazon for $34.99 to replace the BÖHM B2 precursor that wouldn’t accept beyond-Red Book Audio digital input streams:

Well…about six months after I bought it, and after very little use, it quit working. It still toggled among the various audio input sources using both the side panel buttons and the remote control:

but nothing came out of the speakers from any of them (and no, it wasn’t in “mute” mode). Given its low price and compact form factor, I assume that the power amplifier fed by all of those inputs via a preamp intermediary was based on inexpensive class D circuitry and had failed.

Good news: although it was beyond the one-month Amazon return period, it was still covered by the one-year factory warranty. Bad news: that warranty was “limited”. Translation: I was responsible for the cost and effort of return shipping to Hisense, including any loss or damage en route, which meant that I’d need to both package it in a bulky/heavily padded/more expensive fashion and pay for optional insurance on it. Further translated: it’d likely cost me as much, if not more, to ship the soundbar back to them as I’d paid for it originally. And I’d probably end up with an already-used replacement, with even more “limited” warranty terms.

Eventually, after I complained long and hard enough, Hisense’s customer support folks relented and emailed me a postpaid shipping label, followed by shipping me a seemingly brand-new replacement soundbar. Candidly, I suspect that although I always try to avoid such “media special treatment,” someone there did an Internet search on my name and figured out I was a “press guy” who should get “handled with kid gloves”. Would the average consumer have accomplished the same outcome, no matter how long and hard they complained? No. Which, again, is why I always strive to maintain anonymity. Sigh.

Similar experiences, good and/or bad? Other thoughts on what I’ve discussed? Sound off in the comments, please!

—Brian Dipert is the Editor-in-Chief of the Edge AI and Vision Alliance, and a Senior Analyst at BDTI and Editor-in-Chief of InsideDSP, the company’s online newsletter.

Related Content

• Google’s Pixel Smartphone Line: Extended and…Distended?
• Battery life management: the software assistant
• Designing for an uncertain future
• Playin’ with Google’s Pixel 7

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How does a hot swap circuit work? What’s the role of a hot swap controller? What are the basic design considerations for selecting a hot swap controller or module? Here is a short tutorial explaining the inner functioning a hot swap device while outlining key design challenges. It also includes hot swap circuit schematics and design examples.

Read the full article at EDN’s sister publication, Planet Analog.

Related Content

• Making the Switch
• Introduction to Hot Swap
• Telecom hardware needs hot swap
• Hot-swap controllers: A programmable approach
• How does hot-swap capability improve isolated I2C interface?

The post Hot swap basics: Controllers, schematics, and design examples appeared first on EDN.

NXP’s OrangeBox 2.0 automotive connectivity domain controller features an upgraded CPU and embedded AI acceleration. This second-generation development platform facilitates secure connectivity between the vehicle’s gateway and its wired and wireless systems in domain- and zonal-based architectures.

Powered by the i.MX 94 applications processor, OrangeBox 2.0 delivers 4× the CPU performance of its predecessor. The processor integrates four Arm Cortex-A55 cores, two Cortex-M7 cores, two Cortex-M33 cores, and the NXP eIQ Neutron NPU. It also adds post-quantum cryptography acceleration along with enhanced AI, safety, and security capabilities. An integrated 2.5-Gbps Ethernet switch enables software-defined networking and supports the shift to software-defined vehicles (SDVs).

OrangeBox 2.0 builds on its predecessor with integrated NXP wireless technologies, including the SAF9100 for software-defined audio and the AW693 for concurrent Wi-Fi 6E and Bluetooth 5.4 to enable secure over-the-air updates. It supports smart car access via NXP’s latest BLE/UWB technology and an automotive-grade secure element.

The OrangeBox 2.0 automotive development platform is expected to be available in the second half of 2025.

OrangeBox 2.0 product page

NXP Semiconductors 

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As Innatera’s first mass-market neuromorphic MCU, Pulsar delivers intelligence at the edge by emulating the brain’s neural networks. It uses Spiking Neural Networks that process only changes in input—enabling real-time decision making with significantly reduced energy and latency. According to Innatera, Pulsar achieves up to 100× lower latency and 500× lower energy consumption compared to conventional AI processors.

The Pulsar chip combines neuromorphic computing with conventional signal processing. In addition to its Spiking Neural Networks (SNNs), it integrates a RISC-V CPU and dedicated accelerators for Convolutional Neural Networks (CNNs) and Fast Fourier Transform (FFT). By processing data intelligently at the sensor level, Pulsar reduces reliance on power-hungry edge processors or cloud infrastructure for interpreting sensor input.

With sub-milliwatt power consumption, Pulsar enables always-on intelligence in power-constrained devices—from sub-millisecond gesture recognition in wearables to energy-efficient object detection in smart home systems. It provides real-time responsiveness with power budgets as low as 600 µW for radar-based presence detection and 400 µW for audio scene classification.

Pulsar is available now, supported by Innatera’s Talamo SDK for neuromorphic application development.

Pulsar product page

Innatera

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Navitas announced a production-ready 12-kW PSU reference design that achieves 97.8% efficiency for hyperscale AI data centers with 120-kW rack densities. The design incorporates three-phase interleaved TP-PFC and FB-LLC stages, implemented using Gen-3 Fast SiC MOSFETs and 4th-generation high-power GaNSafe ICs, respectively. The GaNSafe ICs integrate control, drive, sensing, and essential protection functions, while IntelliWeave digital control enhances overall performance.

IntelliWeave uses a hybrid strategy combining Critical Conduction Mode (CrCM) and Continuous Conduction Mode (CCM) to optimize efficiency from light to full load. This approach simplifies the design, reduces component count, and lowers power losses by 30% compared to conventional CCM-only solutions.

The PSU meets Open Rack v3 (ORv3) and Open Compute Project (OCP) standards, with dimensions of 790×73.5×40 mm. It operates from 180 VAC to 305 VAC and delivers up to 50 VDC, supplying 12 kW above 207 VAC and 10 kW below. Features include active current sharing and protection against overcurrent, overvoltage, undervoltage, and overtemperature. It operates from –5°C to +45°C, provides ≥20 ms hold-up time at 12 kW, and limits inrush current to ≤3× steady-state current for <20 ms. Cooling is provided by an internal fan.

For more information about the 12-kW PSU reference design, click here.

Navitas Semiconductor 

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Toshiba has released four 650-V third-generation SiC MOSFETs in compact 8×8-mm DFN packages. The surface-mount DFN reduces volume by over 90% compared to leaded packages such as TO-247 (3-terminal) and TO-247-4L(X) (4-terminal). It also enables smaller parasitic impedance components, helping to lower switching losses.

The package’s flat, leadless design enables a Kelvin connection for the gate-drive signal-source terminal, minimizing source wire inductance. This improves switching speed and efficiency. For example, the TW054V65C achieves about 55% lower turn-on loss and 25% lower turn-off loss compared to Toshiba’s existing products.

Well-suited for industrial applications, the devices can be used for switch-mode power supplies, EV charging stations, and photovoltaic inverters. Key specifications include:

Toshiba has begun volume shipments of the TW031V65C, TW054V65C, TW092V65C, and TW123V65C 650-V SiC MOSFETs in the 8×8-mm DFN package.

Toshiba Electronic Devices & Storage 

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Powered by the Achronix Speedster 7t1500 FPGA, the VectorPath 815 PCIe accelerator card meets the performance demands of AI and HPC workloads. Speedster FPGAs integrate machine learning processors to deliver a massively parallel architecture, customizable data paths, and efficient processing of sparse and irregular computations.

“The VectorPath 815 card delivers greater than 2000 tokens per second with 10-ms inter-token latency (LLAMA 3.1-8B Instruct) for unmatched generative AI inferencing performance — enabling customers to accelerate bandwidth-intensive, low-latency applications with a greater than 3× total cost of ownership (TCO) advantage vs. competitive GPU solutions,” said Jansher Ashraf, director of AI Solutions Business Development at Achronix.

The Speedster 7t1500 FPGA features 2560 machine learning processors, a 2D network-on-chip, 692k LUTs, and 32 SerDes lanes supporting PCIe Gen5 ×16 and dual 400G Ethernet. The VectorPath 815 card builds on this by integrating 32 GB of GDDR6 memory for 4-Tbps bandwidth, 16 GB of DDR4 memory, dual QSFP-DD ports, and a PCIe Gen5 interface.

VectorPath 815 accelerator cards are now in volume production. 

VectorPath 815 product page

Achronix Semiconductor

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I like to follow energy-harvesting research developments and actual installations, as there are many creative approaches and useful applications. In many cases, harvesting has solved a power-source problem effectively and with reasonable cost versus benefit.

At the same time, however, I see energy harvesting as often being oversold at best and overhyped at worst. There’s a real glow with the concept of getting something for (almost) nothing that is often associated with it, when the harsh reality is you may be getting very little energy for a much higher cost and complexity than what was promoted. That tradeoff may be acceptable if you are desperate or have no viable alternative, but often that is not the case.

Perhaps the strangest non-conventional harvesting scheme I saw was a specialized coating that could be applied as wall paint (see References 1 and 2). That coating used humidity in the air to harvest energy, with the speculative projections that maybe you could power a house using this paint. Of course, beyond the obvious issues of physical-connection wiring, there was the near-trivial actual available output. The power density output of 0.0001-0.05 watts/meter2 was quite modest (to be polite) in both absolute and relative terms and certainly wouldn’t power your house or even a smartphone.

Tailpipe TEG

A good example of a more practical harvesting arrangement is a recent thermoelectric generator (TEG) story I saw in the Wall Street Journal, of all places (Reference 3). A research team at Pennsylvania State University developed a TEG that fits into the exhaust tailpipe of an internal combustion engine (ICE) vehicle and uses the exhaust waste heat to generate up to about 40 watts (Figure 1).

Figure 1 (a) 3D schematic diagram of the TEG system. The geometry of the exhaust gas pipeline can vary. (b) Power (P) and (c) power density (ω) for automobile and high-speed object conditions. Source: Pennsylvania State University

While that’s enough to power or recharge a small electronic device, it’s a fairly modest amount of power in the context of the power of the engine of a car, small airplane, or helicopter. One of their claimed innovations in this implementation is that it is optimized to work better when there is cooling airflow around the moving tailpipe, yielding a larger temperature differential and thus greater output. The design has been modeled, a prototype built and tested, and the collected data is in line with the expectations (Reference 4).

So far, so good. But then it the storyline goes into what I call extrapolation mode, as the “free energy” and “something for almost nothing” aspects start to overtake reality. How much does this harvester cost as a single unit, or perhaps as a mass-produced item? How long will it last in the tailpipe, which is a harsh environment? What’s the effect on engine exhaust flow and back pressure? What’s the developed energy density, by weight and volume?

The WSJ reporter covering this story seemed to be a non-technical journalist who basically repeated what the researchers said—which is certainly a valid starting point—but didn’t ask any follow-up questions. That’s the problem with most energy-harvesting stories, especially the free-heat TEG ones: they are so attractive and feel-good in concept that the realities of the design and installation are not brought up in polite conversation while the benefits are touted.

I’m not saying that this TEG harvesting scheme is of no value. It may, in fact, be useful in specific and well-defined situations. There are many examples of viable waste-heat recovery installations in industrial, commercial, and residential settings to prove that point. But as will all designs, there are hard and soft costs as well as short- and long-term implications that shouldn’t be ignored.

Small-scale TEG

There are also smaller-scale TEG-type harvesting success stories out there. For example, for many decades, gas-fired home water heaters used their own always-pilot light (no longer allowed in many places due to energy mandates) to heat an array of thermocouples. This array then provided power to activate and turn on the gas valve and ignite the gas to heat the water in the tank (Figure 2).

If the pilot light was out for any reason, turning on the gas valve to heat that water would be extremely dangerous. However, the gas-heated thermocouple system is self-protecting and fail-safe: in the absence of that pilot light that ignites the gas and heats the thermocouples, there is no power to actuate the valve, thus the gas flow would be shut off. As an additional benefit, no electrical wiring of any type was needed by the water heater. It was a plumbing-only (water and gas) installation with no external electricity needed.

Figure 2 This schematic of a gas-fired water heater shows the bottom thermocouple assembly whose electrical output controls fail-safe actuation for the gas-flow valve. Source: All Trades Las Vegas

Harvesting hubbub

My sense is that harvesting gets so much favorable attention because it is so relatable and appears to offer no/low-cost benefits with little downside, at least at first glance. There’s little doubt that the multifaceted attraction of TEG and other energy-harvesting approaches attracts a lot of positive attention and media coverage, as this one did. That’s a big plus for these researchers as they look for that next grant.

Engineers know that reality is usually different. When it comes to generating, capturing, and using energy and power, the old cliché that “there’s no such thing as a free lunch” usually applies. The real question is the cost of that lunch.

Have you used TEG-based harvesting in any project? What were the expected and unexpected issues and benefits? Did you stick with it, or do you have to go with another approach?

Bill Schweber is an EE who has written three textbooks, hundreds of technical articles, opinion columns, and product features.

Related Content

• Niche Energy Harvesting: Intriguing, Innovative, Probably Impractical
• Underwater Energy Harvesting with a Data-Link Twist
• Clever harvesting scheme takes a deep dive, literally
• Is triboelectricity the next harvesting source?
• Tilting at MEMS Windmills for Energy Harvesting?
• Energy harvesting gets really personal
• Lightning as an energy harvesting source?

References

1. Nature, “Generic Air-Gen Effect in Nanoporous Materials for Sustainable Energy Harvesting from Air Humidity”
2. Nature, Supplement to “Generic Air-Gen Effect in Nanoporous Materials for Sustainable Energy Harvesting from Air Humidity”
3. The Wall Street Journal, April 18, 2025, “The Heat Coming Out of Your Car’s Tailpipe? Some Can Be Turned Into Electricity”
4. ACS Applied Materials & Interfaces, January 7, 2025, “Thermoelectric Energy Harvesting for Exhaust Waste Heat Recovery: A System Design” (behind paywall, but it is also posted here at ResearchGate)

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