Vasculature-linked diseases (VLDs) alter vascular geometry, flow, and blood composition, motivating sensing strategies that can interrogate vascular conditions beyond passive contrast enhancement. This perspective article presents nanoparticle tomography (NPT) as a general sensing framework with the Internet of Bio-Nano Things (IoBNT), which interprets nanoparticle (NP) assisted vascular examination as an inverse problem. In this regard, NPs are treated as transport probes, and disease-related changes are inferred from particle-level or ensemble-level observables, such as arrival time, dispersion, and spatial distribution. Subsequently, various representative NPbased vascular sensing techniques are critically reviewed under the same umbrella of NPT. Furthermore, a benchtop proof-ofconcept is presented, which is based on controlled NP injection, optical tracking, and simplified vascular phantoms, together with simulation-assisted NP signature analysis for stenosis inference. It represents an early-stage NPT prototype under controlled experimental conditions, rather than a fully developed clinical imaging system. By looking into both the potentials and constraints of transport-based vascular inference, this perspective highlights directions for future NP-enabled diagnosis and sensing.
Molecular communication is redefining information transfer across nano-, micro-, and macroscale regimes by integrating principles from biology and engineering to enable programmable, biologically compatible signaling in environments inaccessible to conventional electromagnetic systems. This survey adopts a device-level perspective by integrating three core dimensions that shape MC research. First, we summarize advances in theoretical foundations, including molecular channel modeling, emerging modulation schemes, and detection strategies. Second, we review experimental testbeds across air-based, liquid-based, and biological platforms, emphasizing practical constraints and the limited experimental validation of existing models. Third, we examine recent biomedical applications of MC, such as neuromodulation, programmable therapeutic delivery, and in-vivo monitoring. By integrating insights across these dimensions, we identify key limitations, knowledge gaps, and open challenges that hinder the realization of deployable, device-level MC systems. Finally, we outline future research directions toward integrated, energy-efficient, biocompatible, and experimentally validated MC devices.
This mini-review covers experimental work mainly carried out by our group aiming to the engineering of chemical communication between micro/nanoparticles and between micro/nanoparticles and cells. We exploit two main types of particle platforms – gated mesoporous silica nanoparticles and giant unilamellar vesicles – which are equipped with information processing capabilities. On the one hand, this work provides fundamental insights and experimental platforms for assembling and testing communication models. Moreover, proof-of-concept applications in the biomedical context are highlighted. We believe that the development of particles with communication capabilities holds great potential for the development of applications at the interface of different disciplines – including information and communications technologies, nanotechnology, biotechnology, and biomedicine.
We are entering an era in which intelligence is no longer scarce—yet wisdom may be. AI is expanding what we can do at breathtaking speed, even as it unsettles what we once thought was stable. Charles Dickens’ line feels newly apt: it is, in many ways, “the best of times” and “the worst of times” at once.
This paper presents a Ku-band multi-combined power amplifier (PA) implemented in 130-nm CMOS SOI technology for LEO satellite communication phased arrays. To overcome CMOS integration challenges while attaining watt-level output, the design incorporates two key techniques: a triple-cascode topology and a low-loss, multi-stage power combiner. The triple-cascode structure utilizes RF-grounded symmetrical stacking to eliminate external gate capacitors, thereby enhancing voltage gain, output power, and robustness against input imbalance. The multi-stage combiner efficiently aggregates power from 32 unit cells by integrating four-way transformers with strip-line and transmission-line networks, achieving low insertion loss within a compact footprint. Experimental results show a 3-dB bandwidth of 10.5-14.5 GHz, a saturated output power (Psat) of 30.8 dBm (1.2 W), and a peak power-added efficiency (PAE) of 19.9%. The proposed PA achieves superior output power among state-of-the-art 8-18 GHz CMOS PAs, demonstrating its strong potential for next-generation space-borne transmitters.
This paper presents a flipped voltage follower (FVF) low-dropout (LDO) regulator with an innovative circuit architecture that significantly expands the input supply range and current sink capability. Conventional FVF LDO designs are typically constrained by restrictive input voltage operating ranges inherent in their control loop architecture, which poses significant challenges for RF energy harvester systems demanding robust performance across varying output voltage conditions. To address this limitation, the proposed design implements critical modifications to the biasing and buffer topology, introducing substantial architectural improvements that extend the input operating range while maintaining stable voltage regulation and preventing sudden regulation collapse. Fabricated in a 40 nm CMOS process with an area of 0.0089 mm(2), the proposed FVF LDO demonstrates exceptional performance characteristics, achieving a significantly widened input supply range and delivering a fast transient settling time of 103 ns for a load current step from 0 mA to 10 mA. The LDO also achieves a low quiescent current of 122 & micro;A. The research contributes a robust voltage regulation solution specifically tailored for energy harvesting applications with demanding operational requirements.
We consider the present performance, design principles, and prospects for further improvement, in THz transistor technologies, addressing how transistor characteristics limit IC performance, and showing several 100-300 GHz IC and systems examples.
Advanced computers and versatile digital devices have dramatically changed the work environment for young generation in 21st Century. Large language model-based artificial intelligence (A.I.) software packages such as ChatGPT and Gemini were introduced in 2022 and 2023, respectively. Teachers and students increasingly rely on A.I. software in teaching and learning processes. How to collaborate with A.I. software but remain high autonomy is very crucial to the young generation. First, education in engineering college is revisited that reveals the key to enable each discipline: civil engineering, mechanical engineering, electrical engineering in semiconductor field, computer science information engineering, and chemical engineering materials science. The key lies in increasing one extra dimension for more alternative solutions. Spectrum of computation ranges from analog processing, via digital computing, human brain processing, toward quantum computation. Artificial intelligence systems have brought significant challenges to young generation: both as a threat and as an opportunity. The students ought to be nurtured to think in higher dimension and to extend thinking from particle space to wave space. Mastering the duality of digital intelligence and human wisdom is the key for young generation to excel in 21st Century.
Photoacoustic imaging, merging the high contrast of optical imaging with the deep penetration of ultrasound, has become an important research tool in the biomedical field. In recent years, Gr & uuml;neisen relaxation photoacoustic technology has garnered widespread attention as an emerging method for functional expansion. The Gr & uuml;neisen parameter is a key physical quantity linking the thermodynamic properties of matter with the photoacoustic effect. Its high sensitivity to temperature provides a unique avenue for developing noninvasive and precise photoacoustic imaging of biological tissues. This review outlines the fundamental physical mechanisms and key technological implementations of the Gruneisen relaxation photoacoustic technique, with a focus on its innovative applications in blood flow measurement, resolution enhancement, and the specific identification of lipid components.
Drug delivery can be improved by incorporating the therapeutic molecules inside nano-sized carriers. This can enable controlled release of the drugs at the site of interest, thus minimizing off-target effects. Recent advances in nanotechnology have led to the development of “smart” nanoparticles, which can release their cargo in response to an external stimulus. Ultrasound is a promising external stimulus, because it is able to safely provide mechanical energy in a tightly focused region deep in soft tissue. In this region, the ultrasound provides pressure changes, heating, and/or shear forces that can facilitate drug release from the nanoparticles. In this review, we highlight recent advances in smart nanoparticles and describe how ultrasound could be used to achieve real-time on-demand drug delivery in situ. We also identify promising areas of future research that could lead to impactful drug delivery strategies.
Photoacoustic imaging, merging the high contrast of optical imaging with the deep penetration of ultrasound, has become an important research tool in the biomedical field. In recent years, Grüneisen relaxation photoacoustic technology has garnered widespread attention as an emerging method for functional expansion. The Grüneisen parameter is a key physical quantity linking the thermodynamic properties of matter with the photoacoustic effect. Its high sensitivity to temperature provides a unique avenue for developing noninvasive and precise photoacoustic imaging of biological tissues. This review outlines the fundamental physical mechanisms and key technological implementations of the Grüneisen relaxation photoacoustic technique, with a focus on its innovative applications in blood flow measurement, resolution enhancement, and the specific identification of lipid components.
Data compression with Huffman codes has been commonly employed to reduce the memory size required for emerging applications with large storage needs, such as Machine Learning (ML). However, memories at the nanoscale can suffer from errors, causing data corruption. This issue is even more severe for memories storing compressed data, because the error can propagate after decompression. This paper proposes an efficient error-resilient data compression scheme applicable to nanoscale memories by employing interleaved data storage and Huffman coding. Based on the evaluation results on protecting two compressed ML models, this scheme reduces the memory overhead by over 99% compared to conventional error protection schemes (such as parity or Hamming codes), while limiting the accuracy loss in the range of 0.26% to 3.27%.
Biological sensors require high sensitivity, specificity, and low limits of detection. Among the most effective sensing modalities are resonators, which employ sensitive resonance and phase change detection techniques. This review article will discuss the design and use of ultrasonic resonators for biological applications. By functionalizing the device substrate surface, resonators can demonstrate high specificity for a biological target of interest. The sensing capabilities of these resonators can be further optimized through design modifications, such as increasing the resonance frequency, improving the quality factor or altering the device configuration. This review article focuses on the two major categories of ultrasonic resonators used as sensors: bulk acoustic wave (BAW) resonators and surface acoustic wave (SAW) resonators. These devices can be further classified based on the excited wave mode, the device layout, and the functionalized layer configuration. Conceptually, these are hybrid pieces of nanotechnology, comprising of chip-scale resonators physically interfaced with functionalized nanofilms that bind biological targets. This review aims to structure the classification of acoustic resonators for biological sensing and compare the most common categories of chip-scale ultrasonic resonators by outlining the advantages and disadvantages for each wave mode and configuration. This comparison will help deduce the optimal design for various biological sensing applications, ultimately supporting the development of more effective biological and biomedical sensors using chip-scale ultrasonics.
Thousands of people worldwide are affected by diseases that cause degenerative vision loss leading to permanent blindness while the crucial cells for sight, retinal ganglion cells (RGCs), remain intact and functioning. Image information may be sent through the functioning RGCs to the visual cortex of the brain by exciting them with ultrasound from an epiretinal implant made from a polymer matrix nanocomposite (PMNC) engineered to provide a laser-induced photoacoustic response. The implant has the geometry of a double layer where the layers consist of a PMNC and a neat polymer (without nanoparticles). The PMNC is made of palladium-doped polydimethylsiloxane produced using a chemical vapor deposition-based process. The effective properties of the PMNC depend on the properties of the nanoparticles (including their size, number density and distribution) along with those of the polymer matrix. In this work, the acoustic output of the PMNC was experimentally captured with a high frequency hydrophone. The temperature rise in the near particle region of the PMNC from a single pulse was estimated to be 890 degrees C/(mJ/mm(2)) based on the adiabatic temperature rise in a particle while the temperature rise in the bulk composite from a pulse train was estimated to be 563 degrees C/(mW) and 69 degrees C/(mW) at the front and back sides of the PMNC, respectively. These established temperature limits are key factors for designing accelerated reliability testing of the implant that is needed to evaluate reliability of the material in its use as a retinal prosthetic.
Laser-generated ultrasound (LGU) has emerged as a transformative technology in biomedicine, offering unique advantages over conventional ultrasound, including non-contact operation, high spatial resolution, and broadband frequency spectra. This review synthesizes two decades of advancements in LGU, highlighting its pivotal role in biomedical imaging, tissue characterization, and therapeutic applications. In imaging, LGU integrates seamlessly with modalities like photoacoustics to enhance diagnostic precision, as demonstrated by studies combining laser-induced ultrasound with classical techniques to improve vascular contrast and subsurface tissue visualization. Innovations such as fiber-optic transducers and carbon nanotube composites have enabled further miniaturization and optimization of LGU systems for clinical uses, resulting in high-resolution intravascular and endoscopic imaging. Beyond diagnostics, LGU excels in tissue characterization, providing non-invasive insights into biomechanical properties through techniques like laser-guided focused ultrasound and quantitative ultrasound visualization. These methods have proven invaluable for assessing bone health and detecting microstructural anomalies without ionizing radiation. Therapeutically, LGU enables precision interventions, such as microbubbles and nanodroplets-mediated thrombolysis, targeted drug delivery, and noninvasive surgery, with minimal collateral damages. Recent developments, including optically generated focused ultrasound for neuromodulation, underscore its potential in neurosurgery and regenerative medicine. Despite its promise, challenges like signal attenuation and clinical scalability persist. However, solutions such as AI-driven image reconstruction and robotic-assisted systems are poised to overcome some existing barriers. By bridging technological innovation with clinical needs, LGU is redefining precision medicine, offering safer, more effective alternatives to traditional ultrasound-based diagnostics and therapeutics.
