<section id="isPasted">The combination of light-based and electronic components on a single computer chip would have many benefits for our computing needs. Chips would be faster and consume less energy when using light. However, the problem with current silicon-based technologies is that they cannot emit light. TU/e full professor Erik Bakkers has big plans to change that, though. Along with colleagues at TU Munich and the University of Twente, the research team has just been awarded a €14 million ERC Synergy grant. €5 million will be used to back groundbreaking research at TU/e, with Bakkers coordinating the international project.</section><section tabindex="-1">“Light-emitting chips is the holy grail of future computing technologies – the realization of these chips could revolutionize computing technologies.”That’s how&nbsp;<a href="https://www.tue.nl/en/research/researchers/erik-bakkers" target="_blank">Erik Bakkers</a> – Full Professor at the Department of Applied Physics and Science Education – views the promise of light-emitting microchips.<h3>SiGe holds the key</h3>To get to the promised land, though, a fundamental property of the materials used to make our microchips needs to change.“We must change how atoms are arranged relative to each other. In technical terms, we need to move away from the natural cubic structure of many materials to one that is based on the hexagonal arrangement of atoms. If we achieve this, the materials will be able to emit light.”This is the central goal of the project ‘Bright Chips’, a collaboration between Bakkers, Professor Floris Zwanenburg from the University of Twente, and Professor Jonathan Finley from the Technical University of Munich. The project has just received significant funding to the tune of €14 million as part of the ERC Synergy grant initiative.The material of choice for the ‘Bright Chips’ project is silicon germanium (SiGe) – an alloy that has been shown in recent years to have the suitable properties to emit light.<h3>Three’s not a crowd</h3>“We want to understand how and why SiGe emits light, both from a classical and quantum physics perspectives,” says Bakkers. “Our project is a truly multidisciplinary project which combines the worlds of materials science, photonics, and electronics. And each member of the ‘Bright Chips’ project team will focus on one of these three topics.”At TU/e, the Bakkers’ team will fabricate a new material system based on hexagonal SiGe. Thereafter, the team at TU Munich led by Jonathan Finley will characterize the new SiGe material, and using the material, they plan to demonstrate single photon emitters and lasers.Finally, at the University of Twente, Floris Zwanenburg’s group will fabricate and measure the performance of electronic devices that incorporate the SiGe light-emitting components.“A major milestone or goal for Bright Chips is to study optically-connected SiGe-spin qubits. These can be quickly changed, upscaled, and they are expected to be long-lived due to the unique properties of the materials we will work with,” says Bakkers. “We’re excited to get started with the project!”<h3 id="isPasted">Making blood cells</h3>The second project with TU/e involvement to get an ERC Synergy grant is ‘MakingBlood’.&nbsp;<a href="https://www.tue.nl/en/research/researchers/cecilia-sahlgren" target="_blank">Cecilia Sahlgren</a>, a part-time Full Professor at the Department of Biomedical Engineering and mainly based at Åbo Akademi University in Finland, is one of the four principal investigators on the project.“MakingBlood is seeking to make human blood stem cells (also known as hematopoietic stem cells) using human pluripotent stem cells,” says Sahlgren. “At present, blood stem cells are collected from donors.”“However, too often, a suitable stem cell donor cannot be found. We will explore the cellular, molecular, and physical features that are important for the generation of blood stem cells. Lessons learned here will be used to make blood cells in the lab using a dedicated&nbsp;in vitro setup.”TU/e will play two roles in the project. First, researchers will manufacture a high throughput approach to control flow with magnetic cilia, which will be used to build the embryonic niches that are important for the formation of blood stem cells in the human embryo.This will be done in collaboration with&nbsp;<a href="https://research.tue.nl/en/persons/ye-wang" target="_blank" rel="noreferrer">Ye Wang</a>, who is based in the group of Jaap den Toonder at the Department of Mechanical Engineering.Second, researchers will create&nbsp;in vitro models of the embryonic niches where blood stem cells are formed in the embryo. The ‘MakingBlood’ project is coordinated by the Hospital del Mar Research Institute in Barcelona, Spain, by Professor Anna Bigas.The other principal investigators are Gerald de Haan, Research Director of Sanquin, the Dutch Blood Bank, and Dr Cristina Pina, Senior Lecturer in Biomedical Sciences at Brunel University.<hr><h3 id="isPasted">About the ERC Synergy Grant</h3>A group of two to a maximum of four Principal Investigators (PIs) working together and bringing different skills and resources to tackle ambitious research problems. &nbsp;One will be designated as the corresponding PI (cPI).No specific eligibility criteria regarding the academic training&nbsp;are foreseen for ERC Synergy Grants.PI’s must present a competitive track record that is appropriate to their career stage. Proposals are evaluated on the sole criterion of scientific excellence , which takes on the additional meaning of outstanding intrinsic synergetic effect.</section>

Nemea computer chip with light coming out of it. Image: Created by Jason Jung using Midjourney v4

The first project is developing light-based chips to bridge the gap between photonics and electronics. The second project plans to make blood cells using blood stem cells. The two projects are the first ERC Synergy grants for TU/e.

ERC Synergy grants for cutting-edge light-based chips and for blood cells

Thin film deposition applies material layers at the atomic/molecular level, vital for advancing electronics, energy, and aerospace. Key methods like CVD, PVD, and ALD enhance material properties, driving innovations in semiconductors, solar cells, and precision tech.

Thin Film Deposition Technologies: Transforming Electronics, Energy, and Aerospace

An overview of Flip chip technology, its inception, manufacturing process, advancements and performance optimization techniques.

Flip Chip Technology: Advanced Semiconductor Packaging for Next-Generation Electronics

<section id="isPasted">Modern computing infrastructures in data centers or distributed computing systems contribute significantly to global electricity use. The increasing demand for electricity in these systems poses problems, as the need for electricity could potentially exceed the world's energy production in the near future.&nbsp;To combat this problem, the&nbsp;<a href="https://new.nsf.gov/news/nsf-awards-42-4m-new-grants-support-future-semiconductors" rel="noopener" target="_blank">National Science Foundation has awarded Future of Semiconductor grants totaling $42.4 million to further research on semiconductors.</a> Part of this effort will be led by Dr. Yuxuan 'Cosmi' Lin, assistant professor in the Department of Materials Science and Engineering at Texas A&amp;M University. His team has received $1.8 million to support a collaborative research project on new designs of interconnect technologies to reduce their power consumption and boost the overall performance of microchips.Microchips contain interconnects — layers of metal conductors with nanoscale to microscale dimensions that connect different electronic devices in a computer chip. About 20-40% of power in microchips is consumed by its interconnects. Copper is the standard material for interconnects due to its abundance, offering low costs and good electrical conductivity. &nbsp;However, when its dimensions are reduced below 10 nanometers, its resistivity increases dramatically, increasing power consumption and heat generation.&nbsp;"First, electrons in ultrathin copper nanowires can no longer move freely due to structure and property changes," said Lin. "Second, the surface of copper nanowires must be encapsulated with an insulating layer to make the structure more stable, but this further reduces charge transport."&nbsp;</section><blockquote>This project offers potential pathways for integrating these new interconnect technologies with silicon integrated circuit chips, paving the way for upscaling such as an emerging industrial development and manufacturing technology.<cite>- Dr. Yuxuan 'Cosmi' Lin</cite></blockquote><section>Throughout this three-year project, the team will develop a new way to synthesize copper nanowires and design effective encapsulation layers based on two-dimensional materials. These break the paradigm, limiting current interconnect technology and enabling next-generation high-performance and energy-efficient computer chips."This project offers potential pathways for integrating these new interconnect technologies with silicon integrated circuit chips, paving the way for upscaling such as an emerging industrial development and manufacturing technology," said Lin.&nbsp;The proposed research, education, and workforce development efforts will be conducted among five interdisciplinary research groups across three universities, including Texas A&amp;M, University of Texas at Austin, and Purdue University. New research initiatives and semiconductor workforce development activities will be coordinated across the three campuses. This will enhance the technological leadership and broader societal impact of Texas A&amp;M in microelectronics, which is one of the critical technologies of national interest as outlined by the CHIPS &amp; Science Act and the Texas CHIPS Act."New domain knowledge will be established at the forefront of the electronic materials area in materials science and engineering throughout this project," said Lin. "Additionally, the project seeks to engage students at all levels, providing training in physics, materials science, and nanoelectronics to prepare students for industry. "&nbsp;Besides Dr. Lin’s group, contributors to the research include the four research groups: Dr. Yuanyue Liu's group and Dr. Jamie Warner's group at UT Austin, as well as Dr. Zhihong Chen's group and Dr. Sumeet Gupta's group at Purdue University.&nbsp;</section>

A research team at Texas A&M has received a $1.8M National Science Foundation Future of Semiconductor grant to develop new energy-efficient interconnect technologies for microchips.

New Energy-efficient Interconnect Technologies for Microchips

Embedded system designs all have one thing in common: a microprocessor and controller. These can be as sparse as 4-bit wide controllers with less than 1K of code space or as big as a multicore multi-GHz processing supercomputer with Gis of code space. But, modern IoT-based embedded system designs also have another typical requirement. Many designs will be mixed signals, so almost every design will include wireless communications.Herein lies a challenge. Will a designer choose an overkill all-in open processor with much more performance, peripherals, memory, and processing power than is needed just to have a single integrated processor or dedicated functional processors to handle dedicated and specific tasks?Both approaches may have merit depending on a variety of design constraints. Is time to market the driving force? Is cost the critical constraint? What about size or power efficiency? There are many factors and microcontrollers/microprocessors to choose from, especially as embedded systems invade our living space and become more prevalent. Nearly every place is now an intelligent environment.<h2>Wireless Protocols</h2>Every wireless device uses some sort of protocol to establish and maintain communications. While higher-cost, higher-end cellular protocols can be used for home and building communications, this carries the cost of a recurring monthly cellular fee. Modern 4G and 5G systems fall into this category, utilizing a range of wireless protocols for enhanced connectivity.Wi-Fi® is popular for media-based streaming and high-speed connectivity within a facility. Many Wi-Fi ICs and modules are readily available for designers in their embedded design. Still, many designs don't require the multi-Gbit/sec data rates or have higher power budgets to justify the more sophisticated and costly Wi-Fi medium.Zigbee,&nbsp;Bluetooth®, and LTE are the more power-friendly wireless protocols for room or building use. These require much less firmware, memory, and current, making them suitable for remote controls, lighting systems, media systems, temperature sensors, smoke/fire detectors, heating/cooling systems, and more.What makes these protocols even more desirable is the topological flexibility they offer. In addition to point-to-point, these protocols can offer star, mesh, peer-to-peer, and client-server architectures. Star networks require each node to be in closer proximity to the star center, which is usually an aggregator. Peer-to-peer and mesh networks can “pass the baton” from node to node and cover longer distances since packets propagate along a routing path. This can also help preserve battery life since not a lot of transmission power is needed. Eventually, packets that are necessary for connecting to the World Wide Web will need to be routed to an access point. In all cases, security should be used.<h2>Security</h2>Sometimes, a security breach can be just an annoyance, like if someone hacks into your smart TV and changes channels. Other cases can be more serious, though, such as someone hacking into a home medical system. Handling these threats can be tackled in a few ways, but the most common strategy is encryption.Many encryption algorithms and standards exist—some simple and some very complex. Wireless protocols like Zigbee and BLE have various methods of providing encryption protection. ZigBee uses 128-bit AES keys and is effective at applications layers as well as MAC layers. Bluetooth Low Energy (BLE) allows four layers of security:<ul><li>Level 1:No Security<ul><li>Used for scenarios where data confidentiality is not a concern.</li></ul></li><li>Level 2:Unauthenticated Pairing with Encryption<ul><li>Basic level of security, encrypting data transmission without verifying the identity of the connecting device.</li></ul></li><li>Level 3:Authenticated Pairing with Encryption<ul><li>Enhances security with a method of authentication, such as a PIN, before establishing an encrypted connection.</li></ul></li><li>Level 4: Authenticated LE Secure Connections<ul><li>The highest level of security in BLE, which uses an advanced encryption algorithm for authenticated pairing and secure connections.</li></ul></li></ul>Hardware-accelerated security functions can offload security functions from firmware and make processors much more desirable. Hardware encryption, decryption, hash code generation, pseudo-random sequence generators, and other blocks operate at lightning speed in hardware but take longer to implement in software. This adds latency time and requires the programmer to generate and debug more code.In addition to runtime data protection, another layer of security needs to be in place, which is called a secure boot. With secure boot, boot loader firmware is protected and locked, preventing anyone from rewriting this critical code and redirecting its functionality. Normally, unprotected firmware feeds a processor when it boots. If it is replaced in flash somehow, the system is compromised. Secure boot takes advantage of strongly encrypted initial boot instructions, which then use digital signatures to authenticate the next layer of startup code.<h2>A Dream Come True</h2>Realizing the tightrope that designers have to walk when choosing an ideal microcontroller/microprocessor, many device makers are providing microcontrollers/microprocessors targeting this massive market for IoT, building automation, automotive, and industrial control. These applications need more than a simple processor but don't need a super processor. While development time needs to be quick, cost and size are generally high on the list of constraints.One of the best ways to get the processors and peripherals you need is to use a system-on-chip (SoC) solution. These modular units can be made by an OEM for small quantity runs or used to prototype your own higher volume custom version.The key is the 64MHz&nbsp;<a href="https://www.mouser.com/new/microchip/microchip-pic32cx-advanced-security-mcus/" target="_blank">PIC32CX-BZ3</a> family of processors based on the 32-bit Cortex MF4 Arm. This processor brings a multitude of peripherals and its secure boot ROM checks integrity and authenticity before executing to ensure system root trust. There are also eight protected memory zones and a final fuse that makes it impenetrable.The WBZ351 (Figure 1) drives the <a href="https://www.mouser.com/new/microchip/microchip-pic32x-bz3-wbz351-modules/" target="_blank">WBZ35x modules</a>, which feature a fully compliant Bluetooth Low Energy 5.2 transceiver. The transceiver is also Zigbee 3.0 certified with software stacks built around the robust MPLAB Harmony v3 framework.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzI4ODc2NjAyNDc2LVdCWjM1MSBQb3dlciBNb2R1bGUgQmxvY2sgRGlhZ3JhbS53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 1: The peripheral-packed WBZ351 requires few external devices to implement the entire IoT or wireless design. (Source: Microchip Technology)Also important are the hardware-based security accelerator and public critical hardware (Figure 2). The AES security encryption and HASH code generator are also included to create a secure execution environment. Anti-rollback and firmware readable life cycle encounters offer even more levels of protection.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzI4ODc2NjM4MzI3LVdCWjM1eCBNb2R1bGUgQmxvY2sgRGlhZ3JhbS53ZWJwIiwiZWRpdHMiOnsicmVzaXplIjp7IndpZHRoIjo5NTAsImZpdCI6ImNvdmVyIn19fQ==" style="width: 100%px;" class="fr-fic fr-dib">Figure 2: The WBZ351 module contains all the processing horsepower and peripherals needed to support smart homes and buildings, industrial control and monitoring, and wireless IoT applications. (Source: Microchip Technology)<h2 id="isPasted">Conclusion</h2>When it comes to the IoT and smart environments, designers have a big job. They must integrate&nbsp;<iframe id="66cd9b889131b2a7b5d24384" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/arduino-akx00069-plug-make-kit?iframe=true" frameborder="0" scrolling="no" data-lf-form-tracking-inspected-kn9eq4roawkarlvp="true" data-lf-yt-playback-inspected-kn9eq4roawkarlvp="true" data-lf-vimeo-playback-inspected-kn9eq4roawkarlvp="true"></iframe> wireless connectivity with strict security measures. That’s where Bluetooth Low Energy and Zigbee come in. These solutions can cover large areas with mesh networks while consuming less power. By incorporating secure boot and capacitive touch functionalities, designers can accelerate concept-to-market and allow designers to meet the demands for security and user interaction in today’s IoT devices.The PIC32CX-BZ3 family of processors packs everything needed into one place, including advanced connectivity options and hardware-based security features. By leveraging powerful solutions, designers can navigate complex modern IoT ecosystems to ensure smart environments are intelligent, secure, and user-friendly.

When it comes to the IoT and smart environments, designers have a big job. They must integrate wireless connectivity with strict security measures. 

Wireless IoT Designs Just Got Easier

<section id="isPasted">Dr. Yuxuan Cosmi Lin, assistant professor in the Department of Materials Science and Engineering at Texas A&amp;M University, and a team of researchers are studying the potential applications and unique physical properties of semi-metals in electronic devices. &nbsp;&nbsp;This study was recently published in&nbsp;<a href="https://www.nature.com/articles/s44287-024-00068-z" rel="noopener" target="_blank">Nature Reviews Electrical Engineering</a>. &nbsp;&nbsp;&nbsp;Traditionally, microelectronics and electronic materials can be made of three types of material: semiconductors for computing, metals for transducing power and signals, and insulators to isolate different electrical components. &nbsp;&nbsp;A fourth kind of material, semi-metals, may offer a better alternative than the industry standard. Semi-metals are a special kind of material whose properties are in between metals and semiconductors. These materials are significant due to their favorable properties, such as widely tunable electronic energy states, electrical conductivity, and their unique topological properties, which help control the flow of electronic devices like transistors and microchips.&nbsp;&nbsp;Semi-metals are essential components for modern microchip technologies, and semi-metal-based device technologies may offer exceptional computing performance and orders of magnitude reduction in power consumption.&nbsp;&nbsp;In his review article, Lin summarizes and analyzes the potential applications of semi-metals in electronic devices, providing researchers with a comprehensive knowledge resource that guides future research and promotes interdisciplinary collaboration.</section><blockquote>This review helps identify current challenges, suggests potential solutions, serves as an educational resource and an industrial reference, lays a solid foundation for further exploration of semi-metallic technologies, and promotes the development and marketability of new products.<cite>Dr. Yuxuan Cosmi Lin</cite></blockquote><section>“This review summarizes all the research on semi-metals so far, and we have redefined the concept of semi-metals from the definition, classified them, and summarized their applications in electronics according to the classification,” said Lin. “The review article provides a solid foundation and direction for all subsequent research on semi-metals.”&nbsp;&nbsp;According to Lin, these metals can be used in new devices such as transistors, non-volatile memories (memory that can keep power even when power is removed), and on-chip interconnects made with semi-metals and their interfaces with other materials. It also addresses the current issues with semimetals, such as determining how to scale up the processing technologies and how to converge this technology with mainstream silicon technologies, while also detailing the difficulties in finding new semimetals with desired properties in high throughput.&nbsp;&nbsp;“This review helps identify current challenges, suggests potential solutions, serves as an educational resource and an industrial reference, lays a solid foundation for further exploration of semi-metallic technologies, and promotes the development and marketability of new products,” said Lin. &nbsp;&nbsp;Enzi Zhai, a materials science and engineering graduate student, led the effort for this review article. The project was a cross-university effort with Dr. Cong Su’s group at Yale University and Dr. Qiming Shao’s group at Hong Kong University of Science and Technology. The three groups have a long-term collaboration, and each has significantly contributed to different aspects of semi-metal electronics.&nbsp;&nbsp;“This is a great opportunity for us, as well as for the entire research community, to look at the problems from a broader perspective and try better to shape future research areas and technology development targets,” said Lin. “It not only provides a centralized source of knowledge for researchers but also introduces a new material option to those who do not study semi-metals but work on electronic devices while summarizing directions for basic research on semi-metals for their applications in electronics.”&nbsp;</section>

Dr. Yuxuan Cosmi Lin and a team of researchers are studying the advantages of using semi-metals in different applications. 

The Future of Semi-Metal Electronics

Imagine how a phone call works: Your voice is converted into electronic signals, shifted up to higher frequencies, transmitted over long distances, and then shifted back down so it can be heard clearly on the other end. The process enabling this shifting of signal frequencies is called frequency mixing, and it is essential for communication technologies like radio and Wi-Fi. Frequency mixers are vital components in many electronic devices and typically operate using frequencies that oscillate billions (GHz, gigahertz) to trillions (THz, terahertz) of times per second.&nbsp;Now imagine a frequency mixer that works at a quadrillion (PHz, petahertz) times per second — up to a million times faster. This frequency range corresponds to the oscillations of the electric and magnetic fields that make up light waves.&nbsp;Petahertz-frequency mixers would allow us to shift signals up to optical frequencies and then back down to more conventional electronic frequencies, enabling the transmission and processing of vastly larger amounts of information at many times higher speeds. This leap in speed isn’t just about doing things faster; it’s about enabling entirely new capabilities.Lightwave electronics (or petahertz electronics) is an emerging field that aims to integrate optical and electronic systems at incredibly high speeds, leveraging the ultrafast oscillations of light fields. The key idea is to harness the electric field of light waves, which oscillate on sub-femtosecond (10-15&nbsp;seconds) timescales, to directly drive electronic processes. This allows for the processing and manipulation of information at speeds far beyond what is possible with current electronic technologies. In combination with other petahertz electronic circuitry, a petahertz electronic mixer would allow us to process and analyze vast amounts of information in real time and transfer larger amounts of data over the air at unprecedented speeds. The MIT team’s demonstration of a lightwave-electronic mixer at petahertz-scale frequencies is a first step toward making communication technology faster, and progresses research toward developing new, miniaturized lightwave electronic circuitry capable of handling optical signals directly at the nanoscale.In the 1970s, scientists began exploring ways to extend electronic frequency mixing into the terahertz range using diodes. While these early efforts showed promise, progress stalled for decades. Recently, however, advances in nanotechnology have reignited this area of research. Researchers discovered that tiny structures like nanometer-length-scale needle tips and plasmonic antennas could function similarly to those early diodes but at much higher frequencies.A recent open-access&nbsp;<a href="https://www.science.org/doi/10.1126/sciadv.adq0642" target="_blank">study published in&nbsp;Science Advances</a> by Matthew Yeung, Lu-Ting Chou, Marco Turchetti, Felix Ritzkowsky, Karl K. Berggren, and Phillip D. Keathley at MIT has demonstrated a significant step forward. They developed an electronic frequency mixer for signal detection that operates beyond 0.350 PHz using tiny nanoantennae. These nanoantennae can mix different frequencies of light, enabling analysis of signals oscillating orders of magnitude faster than the fastest accessible to conventional electronics. Such petahertz electronic devices could enable developments that ultimately revolutionize fields that require precise analysis of extremely fast optical signals, such as spectroscopy and imaging, where capturing femtosecond-scale dynamics is crucial (a femtosecond is one-millionth of one-billionth of a second).The team’s study highlights the use of nanoantenna networks to create a broadband, on-chip electronic optical frequency mixer. This innovative approach allows for the accurate readout of optical wave forms spanning more than one octave of bandwidth. Importantly, this process worked using a commercial turnkey laser that can be purchased off the shelf, rather than a highly customized laser.While optical frequency mixing is possible using nonlinear materials, the process is purely optical (that is, it converts light input to light output at a new frequency). Furthermore, the materials have to be many wavelengths in thickness, limiting the device size to the micrometer scale (a micrometer is one-millionth of a meter). &nbsp;In contrast, the lightwave-electronic method demonstrated by the authors uses a light-driven tunneling mechanism that offers high nonlinearities for frequency mixing and direct electronic output using nanometer-scale devices (a nanometer is one-billionth of a meter).While this study focused on characterizing light pulses of different frequencies, the researchers envision that similar devices will enable one to construct circuits using light waves. This device, with bandwidths spanning multiple octaves, could provide new ways to investigate ultrafast light-matter interactions, accelerating advancements in ultrafast source technologies.&nbsp;This work not only pushes the boundaries of what is possible in optical signal processing but also bridges the gap between the fields of electronics and optics. By connecting these two important areas of research, this study paves the way for new technologies and applications in fields like spectroscopy, imaging, and communications, ultimately advancing our ability to explore and manipulate the ultrafast dynamics of light.The research was initially supported by the U.S. Air Force Office of Scientific Research. Ongoing research into harmonic mixing is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. Matthew Yeung acknowledges fellowship support from MathWorks, the U.S. National Science Foundation Graduate Research Fellowship Program, and MPS-Ascend Postdoctoral Research Fellowship. Lu-Ting Chou acknowledges financial support from the China's Ministry of Education for the Overseas Internship Program from the Chinese National Science and Technology Council for the doctoral fellowship program. This work was carried out, in part, through the use of MIT.nano.

The demonstration of a lightwave-electronic mixer at petahertz-scale frquencies is a first step toward making communication technology faster and progresses research toward developing new, miniaturized lightwave electronic circuitry capable of handling optical signals directly at the nanoscale. Image: Sampson Wilcox/Research Laboratory of Electronics

Lightwave electronics aim to integrate optical and electronic systems at incredibly high speeds, leveraging the ultrafast oscillations of light fields.

Nanostructures enable on-chip lightwave-electronic frequency mixer

Brain-machine interfaces (BMIs) have emerged as a promising solution for restoring communication and control to individuals with severe motor impairments. Traditionally, these systems have been bulky, power-intensive, and limited in their practical applications. Researchers at EPFL have developed the first high-performance, Miniaturized Brain-Machine Interface (MiBMI), offering an extremely small, low-power, highly accurate, and versatile solution. Published in <a href="https://ieeexplore.ieee.org/document/10643873" target="_blank" rel="noopener">the latest issue of the IEEE Journal of Solid-State Circuits</a> and presented at the International Solid-State Circuits Conference, the MiBMI not only enhances the efficiency and scalability of brain-machine interfaces but also paves the way for practical, fully implantable devices. This technology holds the potential to significantly improve the quality of life for patients with conditions such as amyotrophic lateral sclerosis (ALS) and spinal cord injuries.<blockquote>This advancement brings us closer to practical, implantable solutions.<footer>Mahsa Shoaran</footer></blockquote>The MiBMI's small size and low power are key features, making the system suitable for implantable applications. Its minimal invasiveness ensures safety and practicality for use in clinical and real-life settings. It is also a fully integrated system, meaning that the recording and processing are done on two extremely small chips with a total area of 8mm2. Thisis the latest in a new class of low-power BMI devices developed at Mahsa Shoaran’s Integrated Neurotechnologies Laboratory (<a href="https://www.epfl.ch/labs/inl/" target="_blank">INL</a>) at EPFL’s IEM and Neuro X institutes.<img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzI1NTgzMDExNzczLTI4ODE1MWE4LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width: 100%px;" class="fr-fic fr-dib">Miniaturized Brain-Machine Interface (MiBMI) - 2024 EPFL / Lundi13 - CC-BY-SA 4.0“MiBMI allows us to convert intricate neural activity into readable text with high accuracy and low power consumption. This advancement brings us closer to practical, implantable solutions that can significantly enhance communication abilities for individuals with severe motor impairments,” says Shoaran.<h3 skip="true">Brain-to-text conversion involves decoding neural signals generated when a person imagines writing letters or words. In this process, electrodes implanted in the brain record neural activity associated with the motor actions of handwriting. The MiBMI chipset then processes these signals in real-time, translating the brain’s intended hand movements into corresponding digital text. This technology allows individuals, especially those with locked-in syndrome and other severe motor impairments, to communicate by simply thinking about writing, with the interface converting their thoughts into readable text on a screen.</h3><blockquote id="isPasted">The chip converts handwriting activity into text with an impressive 91% accuracy.<footer>Mohammed Ali Shaeri</footer></blockquote>“While the chip has not yet been integrated into a working BMI, it has processed data from previous live recordings, such as those from the Shenoy lab at Stanford, converting handwriting activity into text with an impressive 91% accuracy,” says lead author Mohammed Ali Shaeri. The chip can currently decode up to 31 different characters, an achievement unmatched by any other integrated systems. “We are confident that we can decode up to 100 characters, but a handwriting dataset with more characters is not yet available,” adds Shaeri.Current BMIs record the data from electrodes implanted in the brain and then send these signals to a separate computer to do the decoding. The MiBMI chips records the data but also processes the information in real time—integrating a 192-channel neural recording system with a 512-channel neural decoder. This neurotechnological breakthrough is a feat of extreme miniaturization that combines expertise in integrated circuits, neural engineering, and artificial intelligence. This innovation is particularly exciting in the emerging era of neurotech startups in the BMI domain, where integration and miniaturization are key focuses. EPFL's MiBMI offers promising insights and potential for the future of the field.<blockquote>Our goal is to develop a versatile BMI that can be tailored to various neurological disorders, providing a broader range of solutions for patients.<footer>Mahsa Shoaran</footer></blockquote>To be able to process the massive amount of information picked up by the electrodes on the miniaturized BMI, the researchers had to take a completely different approach to data analysis. They discovered that the brain activity for each letter, when the patient imagines writing it by hand, contains very specific markers, which the researchers have named distinctive neural codes (DNCs). Instead of processing thousands of bytes of data for each letter, the microchip only needs to process the DNCs, which are around a hundred bytes. This makes the system fast, accurate, and with low-power consumption. This breakthrough also allows for faster training times, making learning how to use the BMI easier and more accessible.Collaborations with other teams at EPFL’s Neuro-X and IEM Institutes, such as with the laboratories of Grégoire Courtine, Silvestro Micera, Stéphanie Lacour, and David Atienza promise to create the next generation of integrated BMI systems. Shoaran, Shaeri and their team are exploring various applications for the MiBMI system beyond handwriting recognition. “We are collaborating with other research groups to test the system in different contexts, such as speech decoding and movement control. Our goal is to develop a versatile BMI that can be tailored to various neurological disorders, providing a broader range of solutions for patients,” says Shoaran.<hr>ReferencesM. A. Shaeri, U. Shin, A. Yadav, R. Caramellino, G. Rainer and M. Shoaran, "MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes," 2024 IEEE International Solid-State Circuits Conference (ISSCC), San Francisco, CA, USA, 2024, pp. 546-548,&nbsp;<a href="https://ieeexplore.ieee.org/document/10643873/" target="_blank" rel="noopener">doi: 10.1109/ISSCC49657.2024.10454533</a>.M. A. Shaeri, U. Shin, A. Yadav, R. Caramellino, G. Rainer, M. Shoaran, “A 2.46mm2 Miniaturized Brain-Machine Interface (MiBMI) Enabling 31-Class Brain-to-Text Decoding”, in IEEE Journal of Solid-State Circuits (JSSC), 2024,&nbsp;<a href="https://ieeexplore.ieee.org/document/10643873" target="_blank" rel="noopener">doi: 10.1109/JSSC.2024.3443254</a>

Researchers from EPFL have developed a next-generation miniaturized brain-machine interface - 2024 EPFL / Lundi13 - CC-BY-SA 4.0

Researchers from EPFL have developed a next-generation miniaturized brain-machine interface capable of direct brain-to-text communication on tiny silicon chips.

An entire brain-machine interface on a chip

CMOS and CCD sensors both convert light into electronic signals, with CMOS using pixel-level transistors for faster, energy-efficient processing, while CCD transfers charge across the chip for superior image quality but with slower speed and higher power consumption.

CCD vs CMOS Image Sensors: A Comprehensive Guide for Engineering Professionals

Optical Micro-Electro-Mechanical Systems (MEMS) Sensor 

This article delves deeper into the microscopic world of MEMS sensors, exploring their operating principles, diverse applications, and the cutting-edge advancements propelling them into the future.

MEMS Sensors: Miniature Marvels Revolutionizing Modern Technology

<section id="isPasted">Staying up-to-date with the latest electronics engineering trends, design insights, and project innovations is crucial for engineers and serious hobbyists alike. That's where the "Circuit Break" podcast steps in as your indispensable resource.Hosted by Parker Dillmann and Stephen Kraig, seasoned electrical engineers in manufacturing and electronic design, Circuit Break explores all aspects of electrical engineering, from groundbreaking technologies to practical design tips. Whether you're troubleshooting your latest project or exploring new horizons in your career, each episode will ignite your curiosity and enhance your expertise. As a welcome to our community of listeners, we've curated a top 10 list of our podcast episodes. Every selection here represents our mission: to educate, inspire, and entertain electrical engineers at every stage of their journey. Enjoy these handpicked episodes designed to spark your imagination and fuel your passion for electronics. They are not in any particular order, so enjoy them however you like.<h2>Bill Herd - Back Into the Storm</h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1720015431285-1720015431284.png" alt="1dimfkjg" class="fr-fic fr-dii">Bil Herd, one of the early engineers of Home Computers, takes part in a podcast episode entitled&nbsp;<a href="https://www.macrofab.com/podcasts/bil-herd-back-into-the-storm/" target="_blank">Back Into the Storm</a>. The conversation takes an intriguing turn toward the intricacies of Design for Manufacturability (DFM) and the assembly process, drawing from Bil Herd's rich history of designing the Commodore C128 during the era of through-hole components. The episode investigates the transformative impact of the advent of Surface Mount Technology (SMT) on electronic design, comparing and contrasting it with the traditional through-hole method that dominated earlier periods. Bil Herd shares his insights on why through-hole components are still relevant today, alongside common pitfalls that modern engineers and designers face when opting for through-hole technology in contemporary projects.A fascinating discussion emerges around the necessity of "green wire" fixes—quick, manual modifications made to circuit boards during the development phase—and their prevalence in the production of past and present electronic devices. This episode of Circuit Break not only enlightens listeners with historical perspectives but also equips them with practical knowledge on navigating the challenges of DFM and assembly in today's fast-evolving technological landscape. It’s a must-listen for anyone interested in the art and science behind creating durable, efficient, and manufacturable electronic designs.<h2>CHIPS Can't Dip</h2>In an enlightening episode, David Schild, Executive Director of the Printed Circuit Board Association of America (PCBAA), shares his expertise on the crucial role of public policy in supporting the U.S. microelectronics industry.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1720015431966-1720015431966.png" alt="2mgiughrjkfd" class="fr-fic fr-dii">With over 20 years of experience in political involvement and advocacy, Schild discusses the significance of the CHIPS Act and the PCBS Act in addressing challenges like globalization and the need for reshoring manufacturing to ensure a resilient supply chain. He emphasizes the CHIPS Act's strategic importance, with its $52 billion funding aimed at revitalizing American manufacturing and the necessity of aligning private investment with public initiatives to foster innovation and production within the country. The conversation underscores the imperative of making PCB production a national priority, suggesting that while current legislative efforts are commendable, a more comprehensive approach is required to fully leverage America's potential in inventing and manufacturing critical technologies. Listen to <a href="https://www.macrofab.com/podcasts/chips-cant-dip/" target="_blank">CHIPS Can’t Dip now</a>.<h2>Mislabeled Levels of Hell</h2>This episode dives into the unique intersection of engineering and summer fun with a discussion on the feasibility of cooking food using a car’s engine, aptly titled “Manifold Destiny: Cooking on a Car Engine.” This episode explores the intriguing idea of turning your car into a BBQ, noting that exhaust pipes can reach temperatures up to 1200°F–hot enough to cook an egg–and looks at how stainless steel changes color when it’s heated, which is important for cooking on the go.In addition, Stephen shares a project update on his CNC (computer numerical control) endeavors, providing listeners with useful tips on how to use electrical tape properly, maintain tidy wiring, and the benefits of upgrading to a larger 3D printer for expanded project capabilities.Additionally, it humorously addresses a universal frustration that you may not expect: the chaos caused by misplaced hardware and fasteners at stores. Listen to <a href="https://www.macrofab.com/podcasts/mislabeled-levels-of-hell/" target="_blank">Mislabeled Levels of Hell</a> now.<h2>Product of Many Imaginations</h2>This episode features MacroFab’s own Misha Govshteyn and Chris Church as they join hosts Parker and Stephen to dissect the complexities of supply chains, digital manufacturing, and the shift toward nearshoring and reshoring. Using their extensive experience, which was highlighted in their previous podcast appearances, they examine the importance of digital manufacturing, its impact on the industry, the success of various business models, and how investments drive innovation and expansion within the industry.This discussion extends to the practical considerations and enthusiasm surrounding reshoring, questioning the depth of the industry’s commitment to bringing manufacturing back home.The episode also offers a reflective journey through MacroFab’s history, from its inception to its strategic pivots and future aspirations, encapsulated by Chris Church’s “Rules for Start-Up Names.”As the conversation unfolds, it reveals the challenges and opportunities that lie ahead for MacroFab, including the move to new headquarters, underscoring the company’s resilience and adaptive strategies as the manufacturing and technology landscape evolves. <a href="https://www.macrofab.com/podcasts/product-of-many-imaginations/" target="_blank">The Product of Many Imaginations</a> episode not only provides a glimpse into the inner workings of MacroFab but also ignites a dialogue on manufacturing in the 21st century.<h2>IdeaFab - Does This Podcast Change The World?</h2>This is the 3rd collaboration between the Ideatank podcast and Circuit Break podcast where Scott Hansen and Eric Benzenhoefer are idea men who, not humbly, seek to change the world through sharing their million-dollar ideas, but humbly, seek to make podcast episodes talking about their ideas.The <a href="https://www.macrofab.com/podcasts/ideafab-does-this-podcast-change-the-world/" target="_blank">Does This Podcast Change</a> the World episode covers a variety of innovative proposals, from Eric’s vision of perfect feedback rating systems to Scott’s bold ambition of sending people into space, demonstrating that there are a wide range of ideas out there, from practical to futuristic.Stephen also introduces “The College of Above Average Joes,” aiming to redefine education, while Parker presents “The Otter-Matic 2000” and “Friendcoin,” blending technology with social connectivity. Each idea, unique in its own right, sparks discussions about feasibility, impact, and change potential.<h2>Rogue Gerbers – Jerry McDaniel of Customer Care at MacroFab</h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1720015432074-1720015432074.png" alt="Jerry mcdaniel headshot" class="fr-fic fr-dii">In this episode, we spotlight Jerry McDaniel, a seasoned veteran at MacroFab. As the current Director of Care, Jerry brings a wealth of experience from his previous roles, including a pivotal stint as the CTO/CFO of Litigation Records Services in Texas, where he managed litigation records for attorneys on both sides of the courtroom. Additionally, his extensive background in application support at Presensoft Inc. for nearly 11 years has honed his expertise in handling complex customer service scenarios.The <a href="https://www.macrofab.com/podcasts/rogue-gerbers-jerry-mcdaniel-of-customer-care-at-macrofab/" target="_blank">Rogue Gerbers</a> episode follows the philosophy and practices behind customer success at MacroFab. Jerry shares invaluable insights on understanding customer behavior, offering practical advice to engineers on how to anticipate and meet client needs effectively. He emphasizes the importance of empathy, proactive communication, and the ability to adapt to each customer’s unique requirements.One of the highlights of the discussion is Jerry’s recounting of the weirdest customer interaction he’s ever experienced, providing a light-hearted glimpse into the unpredictable world of customer service. Through his stories and advice, listeners gain a comprehensive view of what it takes to excel in customer success, especially in the tech and engineering sectors.This episode is not just a look into Jerry McDaniel’s impressive career but also a masterclass in cultivating meaningful and successful customer relationships.<h2>Your Toaster is Toast</h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1720015432192-1720015432192.png" alt="Toaster toast" class="fr-fic fr-dii">Part shortages and obsolescence got you down? Parker and Stephen have some tips and tricks to help your design stay ahead of the end-of-life (EOL) game.<a href="https://www.macrofab.com/podcasts/your-toaster-is-toast/" target="_blank">Your Toaster is Toast</a> unpacks how many engineers and product designers now face abrupt end-of-life situations without warning. The discussion reveals how foundries, overwhelmed with demand, are now booked years in advance, prioritizing their most profitable lines and fulfilling long-standing orders. This situation is exacerbated by the fact that new semiconductor fabrication plants are not investing in outdated wafer equipment, choosing instead to produce newer parts<h2>Hyperspace Part Packages</h2>Delve into a nuanced debate of whether the electronics industry should shift from the traditional ‘pin one’ marking to a more inclusive ‘indicator mark’ convention for component labeling. This discussion explores the potential benefits and implications of such a change, emphasizing the need for clarity and uniformity in component identification, particularly as it pertains to enhancing the manufacturing process and minimizing errors in assembly.<a href="https://www.macrofab.com/podcasts/hyperspace-part-packages/" target="_blank">Hyperspace Part Packages</a> covers the importance of component marking from a manufacturer’s perspective, debating the placement of indicator marks both inside and outside the footprint, the utility of including diode symbols directly on the board for clarity, and the use of vias and numbering for precise marking. Parker and Stephen advocate for designers to “own” their designs and the importance of being prepared to support them, highlighting the critical role of detailed and accurate documentation to be successful in electronic product design.<h2>Datasheet Lore</h2><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1720015432239-1720015432239.png" alt="Pick right part" class="fr-fic fr-dii">Find out what’s hidden in component datasheets and how they influence the selection of electrical components for design projects.<a href="https://www.macrofab.com/podcasts/datasheet-lore/" target="_blank">Datasheet Lore</a> explores risk management and the strategic considerations behind part selection, giving listeners an inside look at the mind of an experienced engineer navigating the vast sea of electronic components. Parker and Stephen share their approaches to picking parts for a design, emphasizing the importance of balancing performance specifications, cost, availability, and compatibility with the broader system architecture.<h2>Chickens and Tea Leaves, Al’s Simulation Recipe</h2>Al Williams, a figure synonymous with the Hackaday community, and an expert whose extensive experience ranges from underwater explorations to contributions to the International Space Station, returns for the fourth time on the podcast to discuss the pivotal role circuit simulation plays in engineering. The author of numerous books on technology and electronics, as well as a ham radio operator, Williams shares his insights.The conversation kicks off with Williams’ perspective on the value of circuit simulation in both analog and digital circuits, underscoring its significance in validating designs, predicting system behaviors, and identifying potential issues before physical prototypes are developed. The discussion navigates through various simulation software, from the widely used LTSpice to specialized tools like Xyce from Sandia, TINA from Texas Instruments, KiCad’s integrated spice, Microcap 12, EasyEDA, and the educational FALSTAD simulator.The episode discusses situations where simulated or logical performance diverges from real-world behavior, emphasizing the need to understand the limitations and assumptions underlying simulation models. Through this discussion, Williams, Stephen, and Parker illuminate the crucial balance between theoretical simulation and empirical testing, offering listeners a comprehensive view of how simulation tools can augment the engineering design process, reduce development time and costs, and foster a deeper understanding of electronic systems. Listen to <a href="https://www.macrofab.com/podcasts/chickens-and-tea-leaves-als-simulation-recipe/" target="_blank">Chickens and Tea Leaves</a> now.</section><h4>Want More Podcast Episodes?</h4>Each week, Parker and Stephen explore topics in engineering and hardware with guests, DIY electronic devices, and industry news.<a href="https://www.macrofab.com/podcasts/" target="_blank">LISTEN TO CIRCUIT BREAK NOW</a><section><h5> </h5></section>

Need something new to listen to?  Try these 10 Circuit Break Podcasts. 

For Electronics Engineers: Top 10 Circuit Break Podcast Shows

This article delves into the significance of PCB inspection, exploring the latest advancements, challenges, and various inspection techniques employed to safeguard the integrity and functionality of PCBs.

PCB Inspection: Ensuring Quality and Reliability in Electronics Manufacturing

This article provides a detailed understanding of microprocessor vs integrated circuit, their basics, key differences, future trends, challenges, and how they synergize to form the backbone of our digital systems.

Microprocessor vs Integrated Circuit: Unveiling the Core of Modern Technology

The new hardware reimagines AI chips for modern workloads and can run powerful AI systems using much less energy than today’s most advanced semiconductors, according to&nbsp;<a href="https://ece.princeton.edu/people/naveen-verma" target="_blank">Naveen Verma</a>, professor of electrical and computer engineering. Verma, who will lead the project, said the advances break through key barriers that have stymied chips for AI, including size, efficiency and scalability.Chips that require less energy can be deployed to run AI in more dynamic environments, from laptops and phones to hospitals and highways to low-Earth orbit and beyond. The kinds of chips that power today’s most advanced models are too bulky and inefficient to run on small devices, and are primarily constrained to server racks and large data centers.Now, the Defense Advanced Research Projects Agency, or DARPA, has <a href="https://www.linkedin.com/feed/update/urn:li:activity:7162915986004762624/" target="_blank" rel="noopener">announced</a> it will support Verma’s work, based on a suite of key inventions from his lab, with an $18.6 million grant. The DARPA funding will drive an exploration into how fast, compact and power-efficient the new chip can get.“There’s a pretty important limitation with the best AI available just being in the data center,” Verma said. “You unlock it from that and the ways in which we can get value from AI, I think, explode.”The announcement came as part of a broader effort by DARPA to fund “revolutionary advances in science, devices and systems” for the next generation of AI computing. The program, called OPTIMA, includes projects across multiple universities and companies. The program’s call for proposals estimated total funding at $78 million, although DARPA has not disclosed the full list of institutions or the total amount of funding the program has awarded to date.In the Princeton-led project, researchers will collaborate with Verma’s startup,&nbsp;<a href="https://www.enchargeai.com/" target="_blank" rel="noopener">EnCharge AI</a>. Based in Santa Clara, Calif., EnCharge AI is commercializing technologies based on discoveries from Verma’s lab, including several key papers he co-wrote with electrical engineering graduate students going back as far as 2016.Encharge AI “brings leadership in the development and execution of robust and scalable mixed-signal computing architectures,” according to the project proposal. Verma&nbsp;<a href="https://engineering.princeton.edu/news/2023/01/27/encharge-ai-reimagines-computing-meet-needs-cutting-edge-ai" target="_blank">co-founded the company</a> in 2022 with Kailash Gopalakrishnan, a former IBM Fellow, and Echere Iroaga, a leader in semiconductor systems design.Gopalakrishnan said that innovation within existing computing architectures, as well as improvements in silicon technology, began slowing at exactly the time when AI began creating massive new demands for computation power and efficiency. Not even the best graphics processing unit (GPU), used to run today’s AI systems, can mitigate the bottlenecks in memory and computing energy facing the industry.“While GPUs are the best available tool today,” he said, “we concluded that a new type of chip will be needed to unlock the potential of AI.”<h3>The needs are real</h3>Between 2012 and 2022, the amount of computing power required by AI models grew by about 1 million percent, according to Verma, who is also director of the&nbsp;<a href="https://kellercenter.princeton.edu/" target="_blank">Keller Center for Innovation in Engineering Education</a> at Princeton University. To meet demand, the latest chips pack in tens of billions of transistors, each separated by the width of a small virus. And yet the chips still are not dense enough in their computing power for modern needs.Today’s leading models, which combine large language models with computer vision and other approaches to machine learning, were developed using more than&nbsp;<a href="https://cmte.ieee.org/futuredirections/2023/11/14/llms-hitting-2-trillions-parameters/" target="_blank">a trillion variables</a> each. The Nvidia-designed GPUs that have fueled the AI boom have become so valuable, major companies reportedly transport them via armored car. The backlogs to buy or lease these chips stretch to the vanishing point.When Nvidia became only the third company ever to reach a $2 trillion valuation, the Wall Street Journal&nbsp;<a href="https://www.wsj.com/tech/ai/how-a-shifting-ai-chip-market-will-shape-nvidias-future-f0c256b1" target="_blank">reported</a> that a rapidly increasing share of the company’s rising revenue came not through the development of the models, called training, but in chips that enable the use of AI systems once they are already trained. Technologists refer to this deployment stage as inference. And inference is where Verma says his research will have the most impact in the near-to-medium term.“This is all about decentralizing AI, unleashing it from the data center,” he said. “It’s got to move out of the data center into places where we and the processes that matter to us can access computing the most, and that’s phones, laptops, factories, those kinds of things.”<h3>Freeing AI from the cloud</h3>To create chips that can handle modern AI workloads in compact or energy-constrained environments, the researchers had to completely reimagine the physics of computing while designing and packaging hardware that can be manufactured with existing fabrication techniques and that can work well with existing computing technologies, such as a central processing unit.“AI models have exploded in their size,” Verma said, “and that means two things.” AI chips need to become much more efficient at doing math and much more efficient at managing and moving data.Their approach has three key parts.The core architecture of virtually every digital computer has followed a deceptively simple pattern first developed in the 1940s: store data in one place, do computation in another. That means shuttling information between memory cells and the processor. Over the past decade, Verma has pioneered research into an updated approach where the computation is done directly in memory cells, called in-memory computing. That’s part one. The promise is that in-memory computing will reduce the time and energy it costs to move and process large amounts of data.But so far, digital approaches to in-memory computing have been highly limited. Verma and his team turned to an alternate approach: analog computation. That’s part two.“In the special case of in-memory computing, you not only need to do compute efficiently,” Verma said, “you also need to do it with very high density because now it needs to fit inside these very tiny memory cells.” Rather than encoding information in a series of 0s and 1s, and processing that information using traditional logic circuits, analog computers leverage the richer physics of the devices. The curvature of a gear. The ability of a wire to hold electrical charge.Digital signals began replacing analog signals in the 1940s primarily because binary code scaled better with the exponential growth of computing. But digital signals don’t tap deeply into the physics of devices, and as a result they can require more data storage and management. They are less efficient in that way. Analog gets its efficiency from processing finer signals using the intrinsic physics of the devices. But that can come with a tradeoff in precision.“The key is in finding the right physics for the job in a device that can be controlled exceedingly well and manufactured at scale,” Verma said.His team found a way to do highly accurate computation using the analog signal generated by capacitors specially designed to switch on and off with exacting precision. That’s part three. Unlike semiconductor devices such as transistors, the electrical energy moving through capacitors doesn’t depend on variable conditions like temperature and electron mobility in a material.“They only depend on geometry,” Verma said. “They depend on the space between one metal wire and the other metal wire.” And geometry is one thing that today’s most advanced semiconductor manufacturing techniques can control extremely well.

Princeton researchers have totally reimagined the physics of computing to build a chip for modern AI workloads, and with new U.S. government backing they will see how fast, compact and power-efficient this chip can get. An early prototype is pictured above. Photo by Photo by Hongyang Jia/Princeton University

The Defense Department’s largest research organization has partnered with a Princeton-led effort to develop advanced microchips for artificial intelligence.

Built for AI, this chip moves beyond transistors for huge computational gains

The OKdo Nano C100 Developer Kit presents an innovative approach to medical diagnostics, particularly in leveraging AI for leukemia detection. Its affordability and compatibility with the NVIDIA ecosystem democratizes access to AI technologies. The kit is powered by the NVIDIA® Jetson Nano Module, equipping it to handle complex AI workloads efficiently. This makes it an excellent choice for processing-intensive tasks, especially in medical AI applications.1In this article, we will explore the technical specifications of the OKdo Nano C100 Developer Kit and its potential in medical AI applications, focusing on leukemia classification. We will highlight how its cost-effectiveness and robust processing capabilities make it a game-changer in medical diagnostics, offering a power-efficient solution for advanced healthcare technology.<h2 dir="ltr">The OKdo Nano C100 Developer Kit: An Overview</h2>The NVIDIA® Jetson Nano module powers the OKdo Nano C100 Developer Kit. This module is central to the kit's capabilities, featuring a 128-core NVIDIA® Maxwell GPU and a Quad-core ARM A57 CPU, supported by 4 GB of 64-bit LPDDR4 memory. These components deliver robust processing power, crucial for handling sophisticated AI algorithms and workloads.The OKdo Nano C100 boasts extensive input/output capabilities regarding connectivity and integration. It includes a range of ports and connectors, such as USB 3.0 Type A, USB 2.0 Micro-B, HDMI/DisplayPort, M.2 Key E, Gigabit Ethernet, GPIOs, I2C, I2S, SPI, UART, 2x MIPI-CSI camera connector, a Micro SD card slot, and a fan connector. This array of I/O options significantly enhances its versatility, allowing for the integration of various sensors and devices, which is essential in diverse AI applications, including medical imaging and diagnostics.3Another standout feature of the OKdo Nano C100 is its power efficiency. The kit can be powered by a micro-USB 5V 2A or a DC power adapter 5V 4A, consuming as little as 5 watts. This efficient power usage is particularly beneficial for sustained operations in data-intensive tasks.Furthermore, the Developer Kit is supported by NVIDIA® JetPack, a comprehensive suite with a board support package (BSP), Linux OS, and essential software libraries like NVIDIA® CUDA, cuDNN, and TensorRT. These libraries are integral for deep learning, computer vision, GPU computing, and multimedia processing. The support provided by NVIDIA® JetPack simplifies the development process, reducing complexity and enhancing the kit's capability to handle advanced AI workloads, such as those required for leukemia classification.4For more detailed information about the technical specifications and capabilities of the OKdo Nano C100 Developer Kit, please visit their official <a href="https://www.okdo.com/p/okdo-nano-c100-developer-kit-powered-by-nvidia-jetson-nano-module/" target="_blank">website</a>.&lt;image&gt;<h2 dir="ltr" id="isPasted">Building a Leukemia Classification System with the OKdo Nano C100</h2>Building a leukemia classification system using the OKdo Nano C100 Developer Kit involves several key steps, focusing on integrating AI frameworks and models specific to medical imaging.&nbsp;We will discuss how to start with the OKdo Nano C100 developer kit and integrate it with AI frameworks to build a system. Here's a step-by-step guide:<ol><li dir="ltr">Initial Setup: Begin by unboxing the OKdo C100 Nano Developer Kit. Connect it to an HDMI monitor, a USB keyboard, and a mouse. An Ethernet connection is required for OS updates. Optionally, you can fit an M.2 E key wireless module for WiFi support. Connect a quality 5V/4A power supply, but do not power on.5</li><li dir="ltr">Camera Integration: The Nano C100 has two MIPI-CSI camera ports, supporting cameras based on imx219 and imx477 sensors. For the leukemia classification project, attach one or two compatible camera modules, such as the Raspberry Pi V2 camera, by sliding the ribbon cable into the connector with the blue marking facing away from the heat sink.5</li><li dir="ltr">Software Installation: The NVIDIA Jetson Nano module in the C100 comes with 16GB onboard eMMC storage. For development, it’s recommended to flash the system image to a microSD card (32GB or larger, Speed Class 10, A1 rated) and boot from there. Use BalenaEtcher to flash the official OKdo Nano C100 Developer Kit OS image, available on the OKdo Software &amp; Downloads hub.5</li><li dir="ltr">4.&nbsp;First Boot and Configuration: You'll follow a setup sequence, including accepting the NVIDIA end-user license agreement (EULA) upon initial boot. Set up the system language, keyboard layout, time zone, username, password, and computer name. Choose the maximum software partition size and configure the module in MAX power mode.5</li><li dir="ltr">Leveraging NVIDIA JetPack: The kit is supported by NVIDIA JetPack, which includes a board support package (BSP), Linux OS, NVIDIA CUDA, cuDNN, and TensorRT software libraries. This suite is vital for deep learning, computer vision, GPU computing, multimedia processing, and more. It simplifies the development process for AI applications.</li><li dir="ltr">AI Framework Integration: Integrate AI frameworks and models suitable for medical imaging. Leverage NVIDIA JetPack’s support for CUDA and deep learning libraries to build and train models for image classification, object detection, and segmentation.</li><li dir="ltr">Utilize Dual MIPI-CSI Camera Connectors: The dual MIPI-CSI camera connectors and the kit's support for AI video processing are crucial for medical imaging applications. They allow for integrating high-quality imaging sensors essential for accurate leukemia classification.</li></ol>The OKdo Nano C100's support for AI video processing is critical to the leukemia classification problem. This feature enables the Developer Kit to handle real-time video data, a capability essential for medical applications where dynamic imaging (like blood flow or cell movement) may be involved. The system can identify and analyze moving leukemia cells by processing video data, providing a more comprehensive understanding of the disease. This real-time processing capability, combined with the high-performance GPU and CPU of the OKdo Nano C100, makes it a powerful tool for advanced medical imaging and analysis tasks.3<h2 dir="ltr">Educational Implications: A Tool for University Students</h2>The OKdo Nano C100 Developer Kit is well-suited for educational purposes, especially for university students studying AI, machine learning, and medical imaging. With its NVIDIA Jetson Nano module, this kit offers an accessible yet powerful platform for developing and testing AI applications. It supports full desktop Linux and is compatible with peripherals that support 4K, including Ethernet, USB, and HDMI, making it a versatile tool for learning and experimentation.The kit's 128-core NVIDIA Maxwell GPU allows students to engage in various AI applications such as image classification, object detection, segmentation, and speech processing. This feature-rich environment is ideal for hands-on learning in AI and machine learning courses. It also uses NVIDIA’s Deepstream SDK, offering a comprehensive toolkit for AI-based video and image understanding, which is crucial for advanced studies in these fields.In terms of ease of use, the OKdo Nano C100 is designed for simplicity and accessibility. Its platform is built for easy use, running on as little as 5 watts, which is advantageous in an educational setting where resources and technical support might be limited. The Jetson developer kits are primarily intended for developing and testing software in a pre-production environment. They are suitable for educational projects emphasizing real-world applications and practical learning.Overall, the OKdo Nano C100 Developer Kit is a practical, accessible, and powerful tool that can significantly enhance the learning experience of university students in AI and related fields.<h2 dir="ltr">Future Outlook in Healthcare AI with OKdo Nano C100</h2>With its advanced AI capabilities, the OKdo Nano C100 Developer Kit is poised to impact future medical AI developments significantly. Its robust features, including a 128-core NVIDIA Maxwell GPU, Quad-core ARM A57 CPU, and extensive I/O capabilities, make it an ideal tool for complex AI workloads.In healthcare, the potential impact of the OKdo Nano C100 on quality and diagnostics is substantial. Its ability to run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing can revolutionize medical imaging and diagnostics. For instance, its capability to process and analyze complex medical images in leukemia classification can lead to more accurate and faster diagnoses, improving patient outcomes. Additionally, its suitability for various AI applications means it can adapt to various healthcare needs, from drug discovery to patient monitoring, enhancing overall healthcare quality and efficiency.<h2 dir="ltr">Conclusion</h2>The OKdo Nano C100 Developer Kit is a significant technological advancement, particularly in on-premise AI systems. Its high computing capabilities, efficient power usage, and comprehensive software support make it an ideal platform for developing sophisticated AI models. This is especially relevant in medical diagnostics, where its application in leukemia classification demonstrates its potential to transform healthcare practices.&nbsp;By enabling more accurate and quicker diagnoses, the OKdo Nano C100 advances the technology behind healthcare AI and directly contributes to improved patient care and outcomes. As AI continues to evolve, tools like the OKdo Nano C100 will undoubtedly play a pivotal role in shaping the future of healthcare and medical diagnostics.<h2 dir="ltr">References</h2><ol><li dir="ltr"><a href="https://www.okdo.com/p/okdo-nano-c100-developer-kit-powered-by-nvidia-jetson-nano-module/" target="_blank">https://www.okdo.com/p/okdo-nano-c100-developer-kit-powered-by-nvidia-jetson-nano-module/</a></li><li dir="ltr"><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365109/" target="_blank">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10365109/</a></li><li dir="ltr"><a href="https://www.okdo.com/p/okdo-nano-c100-developer-kit/" target="_blank">OKdo Nano C100 Developer Kit - OKdo</a></li><li dir="ltr"><a href="https://www.siliconhighwaydirect.com/OKdo-Nano-C100-Developer-Kit-2520055-p/2520055.htm" target="_blank">OKdo Nano C100 Developer Kit - 2520055 - Silicon Highway Direct</a></li><li dir="ltr"><a href="https://www.okdo.com/getting-started/get-started-with-the-c100-nano-csi-cameras/" target="_blank">https://www.okdo.com/getting-started/get-started-with-the-c100-nano-csi-cameras/</a></li></ol>