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The pages of Design Ideas (DIs) have recently been awash in a veritable cascade of designs for variable frequency oscillators with frequency ranges tunable over multiple decades:

• Self-oscillating sawtooth generator spans 5 decades of frequencies
• 555 VCO revisited
• 5 octave linear(ish)-in-pitch power VCO
• Tune 555 frequency over 4 decades
• Wide-range tunable RC Schmitt trigger oscillator

But despite the size of this crowd, a notable feature missing from all is provision for digital control (e.g., from an MCU GPIO pin) of the oscillation frequency. This DI will address that topic.

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

When starting the design of any digital to analog interface, the first question to be answered is how much resolution (bits) do we need? For the applications listed above, the answer isn’t obvious. That’s because of the extremely wide range  of  the analog quantity (frequency) involved, e.g., 100,000:1 for Christopher Paul’s 5-decade 10 Hz to 1 MHz sawtooth generator.

5 decimal decades = 10ppm and is equivalent to a linear binary resolution of 16.6 bits.  So even if we went with the overkill choice of 16bits (1/65536 = 15ppm), we’d still lose resolution at the bottom end. The first least significant bit (lsbit) increment up from 10 Hz would comprise a 15 ppm of 1 MHz = 15 Hz jump to 25 Hz, nearly trebling the output frequency. 

Figure 1’s circuit takes an approach very different from linear conversion. Working from mere 8bit PWM, it makes lsbit incremental resolution constant and uniformly distributed at ~5% of output.  Here’s how it works.

Figure 1 Antilogarithmic 8-bit PWM gives s constant incremental ~5% per lsbit. Asterisked parts are 1% or better precision (metal film or C0G).

Antilog conversion occurs in a four step ~1ms cycle defined by the combined states of the GPIO PWM bit and D flip/flop decoded by the 4052 analog switch as shown in Figure 2.

Figure 2 Tw = antilog RtCt timeout = 1 to 250 counts = 2 to 500 µs, where
PWM = 1 + 21.63*Ln(Imax/Iout)

The antilog conversion sequence is as follows: 

• BA = 3. duration 12 µs. Timing capacitor Ct charged to Vdd – 1.24 V.
• BA = 2. duration Tw = 2 µs to 500 µs. Ct exponentially discharged toward Vdd with time-constant RtCt = 43.4 µs.
• BA = 1: duration 0 to 498 µs. Ct  residual charge transferred to Csh sample and hold cap.
• BA = 0: duration 2 µs to 500 µs. Ct  residual charge continues to transfer to Csh.

At the end of each 4-step, 1024-µs cycle, Csh will converge toward a charge relative to Vdd between 12 µV and 1.2 V, determined by the antilog of the 2 µs to 500 µs duration of phase 2 of the conversion sequence. The 1-µV typical input offset of the LT2066 makes this adequate for (reasonably) accurate digital to analog conversion. Convergence of Vcsh to 8-bit precision takes a maximum of 8 cycles = 8.2 ms.

Final conversion of the resulting 5-decade current source to a 5-decade frequency output (the point of the exercise) can be done simply (if admittedly kind of crudely) with the circuit in Figure 3.

Figure 3 A minimal 5-decade sawtooth oscillator that enables final conversion of the resulting 5-decade current source to a 5-decade frequency output.

Or it can be done much more precisely with Christopher Paul’s DI by substituting Figure 1 for his original resistor-programmed current source (highlighted in yellow), as shown in Figure 4.

Figure 4 Maximal 5-decade sawtooth oscillator, using Christopher Paul’s DI.

Figure 5 Log (red) and linear (black) plot of source current versus PWM.

Stephen Woodward‘s relationship with EDN’s DI column goes back quite a long way. Over 200 submissions have been accepted since his first contribution back in 1974.  They have included best Design Idea of the year in 1974 and 2001.

 Related Content

• Self-oscillating sawtooth generator spans 5 decades of frequencies
• 555 VCO revisited
• 5 octave linear(ish)-in-pitch power VCO
• Tune 555 frequency over 4 decades
• Wide-range tunable RC Schmitt trigger oscillator

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Fuel cell sensors are electrochemical devices designed for precise measurement. In measurement applications, they have become the gold standard for breath alcohol concentration detection, valued for their ethanol specificity, stability, and courtroom-grade accuracy. Compact and low power, they form the backbone of law enforcement breathalyzers, workplace safety programs, and consumer devices, consistently outperforming semiconductor and infrared (IR) alternatives.

Their proven reliability in complex breath matrices has made them indispensable for safety and compliance, while ongoing innovation is extending their reach into broader analytical domains. And while fuel cells generate clean energy, fuel cell sensors generate precise measurements—a distinction that defines their unique role in modern technology.

Applications and history

Before we get into the basics of how fuel cell sensors work, it’s worth noting their application landscape. While research has explored microbial fuel cell biosensors for environmental monitoring and niche industrial uses, the overwhelming commercial reality today is breath alcohol concentration (BAC) measurement.

Fuel cell sensors have become synonymous with BAC detection because of their unmatched ethanol specificity, stability, and courtroom-grade accuracy. Although BAC formally refers to blood alcohol concentration, in practice it is estimated through breath alcohol analysis. This singular focus has defined their role in law enforcement, workplace safety, and consumer devices, making BAC not just their flagship application but essentially their identity in the marketplace.

Technology itself traces its roots to the 1960s, when early electrochemical cells were adapted to detect ethanol in breath samples. By the late 1970s and early 1980s, law enforcement agencies began adopting fuel cell-based breathalyzers, recognizing their superior specificity compared to semiconductor sensors.

Over time, improvements in miniaturization, catalyst stability, and calibration protocols transformed them from bulky instruments into compact, portable devices. This evolution cemented fuel cell sensors as the trusted backbone of alcohol detection, setting the stage for their enduring role in safety and compliance.

Figure 1 A compact breathalyzer with a fuel cell breath alcohol sensor—Alcotest 4000—simplifies portable BAC measurement. Source: Dräger

As a quick aside, while fuel cells rely on chemical reactions, IR spectroscopy uses light to identify alcohol’s unique spectral fingerprint. By directing an IR beam through a breath sample, the instrument measures the specific wavelengths absorbed by ethanol molecules.

This physics-based method is non-destructive and highly precise, enabling real-time detection of “mouth alcohol” that could otherwise distort results. Because of their sophistication, accuracy, and long-term stability, IR units are reserved as definitive, desktop-based instruments in police stations, providing the courtroom-grade evidence required for testimony.

Fuel cell breath alcohol sensors

Now is the time for a gentle dive into a bit of theory and practice. At their core, these sensors operate on an electrochemical principle: ethanol molecules in exhaled breath are oxidized at a platinum electrode, producing an electrical current directly proportional to concentration. This reaction is simple yet elegant, converting chemical energy into a measurable signal that reflects blood alcohol concentration (BAC).

In practice, this design delivers a combination of portability, stability, and specificity that has made fuel cell sensors the dominant choice for breath alcohol testing. Unlike semiconductor sensors, which can be affected by other volatile compounds, fuel cells respond almost exclusively to ethanol.

Their compact form factor allows integration into handheld devices, while their long-term consistency ensures reliable results in roadside, workplace, and consumer contexts. This balance of theory and application explains why fuel cell sensors remain the benchmark technology for BAC measurement today.

In a nutshell, a fuel cell breath alcohol sensor is essentially a pair of platinum electrodes immersed in a dilute acid electrolyte. When a trace amount of ethanol from exhaled breath reaches the electrodes, it undergoes oxidation, releasing electrons that flow as current. The magnitude of this current is directly proportional to ethanol concentration, providing a simple yet highly reliable way to quantify blood alcohol concentration.

And fundamentally, the fuel cell breath alcohol sensor consists of a porous, chemically inert layer coated on both sides with finely divided platinum black. The porous layer is impregnated with an acidic electrolyte solution, and platinum wire connections are attached to the platinum black surfaces. The assembly is mounted in a plastic case with a gas inlet for introducing a breath sample. While manufacturers add proprietary refinements to this design, the basic configuration is shown in Figure 2.

Figure 2 Drawing illustrates the basic construction of a fuel cell breath alcohol sensor. Source: Author

Hands-on with fuel cell alcohol detection

For those eager to explore fuel cell alcohol sensors, the FS00702 electrochemical ethanol content module offers a robust solution. This fuel cell–type sensor operates through oxidation and reduction reactions at the working and counter electrodes, generating charges that form a measurable current. Current’s magnitude is directly proportional to alcohol concentration, in accordance with Faraday’s law, enabling accurate determination of ethanol levels.

Equipped with a high-stability gas sensor and a high-performance microprocessor, the module supports both UART and analog signal outputs for seamless integration. Its precise automatic calibration and advanced detection systems minimize human interference, ensuring consistent accuracy and reliability in large-scale production environments.

Figure 3 Highlighting FS00702 key specs: enabling makers to detect ethanol with precision, rapid updates, and easy microcontroller integration. Source: Henan Fosen Electronics Technology

As a side note worth mentioning, ethanol is one specific type of alcohol—the compound found in beverages and fuels—whereas “alcohol” broadly refers to a family of related molecules such as methanol, propanol, and isopropanol.

Fuel cell sensors like FS00702 are calibrated for ethanol detection since it’s the relevant analyte for intoxication measurement and fuel monitoring. While the sensor may respond to other alcohols, its accuracy is optimized for ethanol, making precise terminology important in technical contexts.

Practically speaking, sourcing high-quality fuel cell alcohol sensors for hobbyist projects is challenging, since most manufacturers prioritize finished breathalyzer units or bulk industrial modules.

Still, there are accessible alternatives to FS00702 for makers who value the accuracy and specificity of fuel cell technology. The Dart Sensors 2-Electrode fuel cell is considered a gold standard for precision, though it requires a custom amplifier circuit.

Fosensor’s FS00701 provides a smaller footprint than FS00702, ideal for portable builds. Meanwhile, FS00702 itself remains versatile, offering both raw analog output for custom conditioning and a built-in UART option for straightforward microcontroller integration.

Winsen’s ZE321 automotive alcohol module offers a compact design with a convenient UART interface, making it more user-friendly for DIY integration. The ZE321 module operates on the fuel cell electrochemical principle. When the built-in pressure sensor detects exhaled air flowing through the sampling tube at the required rate, the solenoid valve quickly opens to admit a measured volume of breath.

Within the sensor, alcohol and oxygen undergo a redox reaction, generating an electrical current proportional to ethanol concentration. The module’s circuitry measures this current and, after algorithmic processing, outputs an accurate determination of breath alcohol content.

Figure 4 The ZE321 automotive alcohol module monitors exhaled breath flow, samples a fixed volume of gas, and actively detects alcohol content through its fuel cell electrochemical reaction. The onboard circuitry processes the resulting current signal to deliver accurate breath alcohol measurements. Source: Winsen

Accuracy today, innovation ahead

In practical terms, fuel cell–based alcohol testing devices deliver the highest accuracy in measuring breath alcohol content, leaving little room for error. Even so, it’s wise to allow for a small margin of discrepancy. When evaluating any alcohol detection instrument—whether for personal safety, workplace compliance, or automotive use—the sensor type is critical. If precision matters most, fuel cell sensor technology remains the benchmark to aim for.

For makers and engineers, the challenge is clear: fuel cell sensors are not confined to alcohol testing; they are gateways to precision sensing, sustainable energy, and inventive applications across domains. Experiment boldly, share your builds, and push the boundaries of what these devices can achieve. The next breakthrough could start on your workbench.

T. K. Hareendran is a self-taught electronics enthusiast with a strong passion for innovative circuit design and hands-on technology. He develops both experimental and practical electronic projects, documenting and sharing his work to support fellow tinkerers and learners. Beyond the workbench, he dedicates time to technical writing and hardware evaluations to contribute meaningfully to the maker community.

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• Hydrogen Fuel-Cell Vehicles
• Paper-Based Biofuel Cells Power Disposable Electronics
• xEVs Opening New Opportunities for Sensor Development
• Designing a portable system for in situ failure prediction in fuel cells

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Everspin Technologies, a leading developer and manufacturer of magnetoresistive random access memory (MRAM) persistent memory solutions, today announced the UNISYST MRAM family, a new generation of unified memory designed to fundamentally change how embedded systems store and access code and data.

“System designers are running into the physical and performance limits of NOR flash, especially as process nodes move below 40 nanometers and workloads become more demanding,” said Sanjeev Aggarwal, president and CEO of Everspin Technologies. “With UNISYST, we are extending our MRAM roadmap to higher densities while giving customers a practical way to start with PERSYST today and migrate to a code-and-data MRAM architecture as soon as it is available.”

UNISYST is a unified code-and-data MRAM architecture that bridges traditional configuration memory and higher-density persistent storage, extending MRAM into traditional NOR flash applications where superior performance, endurance and reliability are valued. Built as a natural extension of Everspin’s existing PERSYST MRAM platform, UNISYST gives customers a practical, simple migration path from today’s serial MRAM devices to higher-density unified memory without requiring changes to system architecture or software.

Everspin will initially offer the UNISYST family in densities ranging from 128 megabits to 2 gigabits, using a standard xSPI interface operating up to octal SPI at 200MHz. The devices are planned to feature AEC-Q100 Grade 1 qualification and minimum 10-year data retention at extreme temperatures, supporting demanding environments across automotive, aerospace, industrial and edge AI applications.

“As generative AI models move from the cloud to embedded systems, we’re suddenly dealing with assets that are tens or even hundreds of megabytes in size,” said Kwabena W. Agyeman, President and Co-founder of OpenMV. “Storing those models is only part of the challenge — updating them quickly during development and deployment is equally important. High-speed, non-volatile Everspin UNISYST MRAM changes what’s practical for edge AI systems by removing the write bottlenecks associated with traditional flash.”

UNISYST delivers high-bandwidth read and write speeds in a non-volatile memory device, enabling fast boot, rapid updates and predictable performance without the tradeoffs of traditional flash-based designs. By combining high-speed access with persistent storage, UNISYST supports software-defined systems that require frequent reconfiguration while maintaining data integrity across power cycles.

Everspin MRAM has been deployed in mission-critical storage applications for nearly two decades, valued for its endurance and reliability. UNISYST builds on Everspin’s proven MRAM foundation with capabilities designed to support more complex, software-defined systems:

• Code-and-data MRAM architecture designed as a next-generation alternative to other non-volatile memory
• Standard xSPI interface operating up to octal SPI at 200MHz
• Read bandwidth of up to 400 MB/s and write bandwidth of approximately 90 MB/s, over 400 times faster than NOR flash
• Write endurance up to 10 times higher than typical NOR
• AEC-Q100 Grade 1 qualification and minimum 10-year data retention for high-reliability designs

UNISYST is aimed at applications where non-volatile memory must combine high bandwidth, high endurance and predictable behaviour over temperature and time. Target use cases include:

• AI at the edge: Fast AI weight updates, critical storage at the edge, local code-and-data storage for workloads that need fast boot, rapid reconfiguration and non-volatile operation close to the sensor, with the ability to execute in place, removing the need for multiple system memories
• Military and aerospace: Field-programmable gate array (FPGA) configuration and code storage for mission-critical systems, including low-Earth orbit satellites and other platforms that require frequent over-the-air updates
• Automotive: Control, logging and configuration memory in systems that must meet Grade 1 temperature requirements and long-term data retention
• Industrial and casino gaming: High-traffic logging and configuration in environments that demand fast writes, long endurance and persistent storage supporting data logging

The launch of UNISYST represents a platform-level expansion of Everspin’s MRAM portfolio, extending the company’s role from a niche memory supplier to a mainstream memory player serving a multibillion-dollar market. By unifying code storage and data memory, Everspin is addressing the growing demands of software-defined systems that require faster boot times, frequent updates and predictable behaviour over long operating lifetimes.

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Texas Instruments (TI) introduced two new microcontroller (MCU) families with edge artificial intelligence (AI) capabilities, supporting the company’s commitment to enabling edge AI across its entire embedded processing portfolio. The MSPM0G5187 and AM13Ex MCUs integrate TI’s TinyEngine neural processing unit (NPU), a dedicated hardware accelerator for MCUs that optimises deep learning inference operations to reduce latency and improve energy efficiency when processing at the edge.

TI’s embedded processing portfolio is supported by a comprehensive development ecosystem, including the CCStudio integrated development environment (IDE). Its generative AI features allow engineers to use simple language to accelerate code development, system configuration and debugging through industry-standard agents and models paired with TI data. Altogether, TI is accelerating the adoption of edge AI across electronic devices, from real-time monitoring in wearable health monitors and home circuit breakers to physical AI in humanoid robots. These end-to-end innovations are featured in TI’s booth at embedded world 2026, March 10-12, in Nuremberg, Germany.

“TI invented the digital signal processor almost 50 years ago, laying the groundwork for today’s edge AI processing,” said Amichai Ron, senior vice president, Embedded Processing and DLP® Products at TI. “Now TI is leading the next phase of innovation by integrating the TinyEngine NPU across our entire microcontroller portfolio, including general-purpose and high-performance, real-time MCUs. By enabling AI across our software, tools, devices and ecosystem, we are making edge AI accessible and easy to use for every customer and every application.”

“While much of the world has been focused on AI acceleration and NPUs in bigger SoCs, it turns out some of the more interesting and far-reaching applications of AI can be enabled inside smaller chips like microcontrollers,” said Bob O’Donnell, President and Chief Analyst at TECHnalysis Research. “Edge-based applications of AI acceleration can make consumer devices more intelligent and industrial devices more efficient. Plus, if you can combine these chips with software development tools that themselves leverage AI to help build AI features, you bring the power of AI acceleration to a significantly wider audience of engineers and device designers.”

Advanced intelligence at your fingertips

Consumers are always looking for everyday technology to be more intelligent, from fitness wearables to home appliances and electrical systems. However, many engineers believe that AI capabilities are limited to higher-end applications due to high costs, power demands, and coding requirements. TI’s new MSPM0G5187 Arm Cortex-M0+ MSPM0 MCU represents a fundamental shift for embedded designers, who can now bring edge AI to a wide range of simpler, smaller and more cost-effective applications.

With local computation, the TinyEngine NPU executes computations required by neural networks in parallel to the primary CPU running application code. Compared to similar MCUs without an accelerator, this hardware acceleration:

• Minimises the flash memory footprint.
• Lowers latency by up to 90 times per AI inference.
• Reduces energy utilisation by more than 120 times per AI inference.

Such levels of efficiency allow resource-constrained devices – including portable, battery-powered products – to process AI workloads. At under US$1 in 1,000-unit quantities, the MSPM0G5187 MCU reduces system and operating costs by offering an affordable alternative to other MCU or processor architectures.

Real-time control plus AI acceleration for multimotor systems

Motor control applications in appliances, robotics and industrial systems increasingly call for intelligent features such as adaptive control and predictive maintenance, but implementing these capabilities has historically required complex, multi-chip designs. Building on over two decades of motor control leadership through the C2000 real-time MCU portfolio, TI’s new AM13Ex MCUs are the industry’s first to integrate a high-performance Arm Cortex-M33 core, TinyEngine NPU and advanced real-time control architecture into a single chip.

This degree of integration enables designers to implement sophisticated motor control and AI features simultaneously without external components, lowering bill-of-materials costs by up to 30%. Key enhancements include:

• The ability to maintain precise real-time control loops for up to four motors while the TinyEngine NPU runs adaptive control algorithms for load sensing and energy optimisation.
• An integrated trigonometric math accelerator that performs calculations 10 times faster than coordinate rotation digital computer (CORDIC) implementations, delivering more precise, responsive motor-control performance.

Easily train, optimise and deploy AI models

Both MCU families are supported by TI’s CCStudio Edge AI Studio, a free development environment that simplifies model selection, training and deployment across TI’s embedded processing portfolio. This edge AI toolchain gives engineers full flexibility to run AI models on TI MCUs through either hardware or software implementations. Today, there are more than 60 models and application examples available in the tool to help developers start deploying edge AI in any device, with additional tasks and models planned in the future.

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Rohde & Schwarz will participate in EMV 2026, Europe’s premier trade fair and congress dedicated to electromagnetic compatibility, held from March 24-26 in Cologne. At the event, which serves as a crucial platform for industry professionals, the company will show its latest advancements in test & measurement equipment to address the evolving challenges within the EMC landscape.

Rohde & Schwarz will demonstrate a broad portfolio of solutions designed to streamline and optimise EMC testing across diverse sectors, including power electronics, consumer, industrial, automotive, Satcom, military, and wireless communications. EMC testing is evolving to meet the demands of emerging technologies and a crowded radio frequency spectrum. Innovations like AI, 6G, and quantum computing present new challenges for ensuring reliable performance, while widespread electrification and increased bandwidth requirements necessitate testing at higher frequencies. To address these shifts, Rohde & Schwarz is developing scalable and modular test solutions focused on repeatable, reliable measurements – streamlining the path from initial assessment to final certification. A further focus is on bridging the gap between real-world field performance and laboratory testing.

At the show, Rohde & Schwarz will showcase a versatile and adaptable solution for conducted and radiated emission testing with the EMI test receivers R&S EPL1001 and R&S EPL1007 with frequency ranges up to 1 GHz and 7.125 GHz. These receivers provide a scalable approach to EMC testing, allowing users to select the optimal configuration for their needs, whether for efficient pre-compliance measurements or fully CISPR 16-1-1 compliant testing for certification.

Rohde & Schwarz is showcasing a speed-optimised EMI test with its industry-leading R&S ESW test receiver — with ESW-B1000R 970 MHz bandwidth extension — and the automated R&S ELEKTRA software: A live demonstration highlights the system’s capabilities for rapid and detailed device characterisation with 3D emission plots generated by R&S ELEKTRA for a typical commercial EMI test. Complementing this is the R&S HF1444G14 high-gain antenna, extending testing capabilities up to 44 GHz for standards like MIL-STD and FCC.

Rohde & Schwarz will also be expanding its R&S BBA300 family of broadband amplifiers with its new dual-band amplifier series R&S BBA300-CDE/FG for 380 MHz to 13 or 18 GHz and the R&S BBA300-DE1000 with an output power of up to 1000 W in the 1 GHz to 6 GHz range. With high linearity, continuous and very wide frequency bands, and innovative protection concepts for high availability, the R&S BBA300 family meets the requirements for EMC immunity testing today and tomorrow.

Rohde & Schwarz will also show its full vehicle antenna test (FVAT) capabilities at the show. Modern vehicles increasingly rely on multiple antennas – for GNSS, Wi-Fi, cellular services like C-V2X, and more to enable safety, convenience and infotainment features – requiring comprehensive full-vehicle antenna testing. This testing enables vehicle manufacturers and their suppliers to characterise radiation performance, verify RF robustness, ensure co-existence of different wireless technologies and ultimately validate the functions and services enabled by wireless connectivity.

For in-depth signal analysis, Rohde & Schwarz will feature the R&S MXO 3 Series oscilloscope, boasting an unmatched acquisition rate exceeding 4.5 million waveforms per second and featuring up to 8 channels. This advanced oscilloscope also includes powerful standard functions such as a very fast FFT and zone trigger capabilities that empower engineers to quickly and precisely understand complex circuit behaviour, essential for effective EMI troubleshooting and design optimisation.

Rohde & Schwarz will also actively contribute to the congress with technical sessions, workshops and demos focusing on EMI test speed optimisation, EMC for medical products and closed-loop Reverb chamber testing. Attendees can also join a panel discussion exploring the impact of Artificial Intelligence on the EMC landscape, covering its current benefits and potential future challenges. Besides others, a Rohde & Schwarz expert will discuss AI’s role in areas like testing and development, and address concerns about new vulnerabilities.

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