In a groundbreaking advance at the intersection of bioengineering and microbiology, researchers at Harvard’s John A. Paulson School of Engineering and Applied Sciences have unveiled a pioneering device known as a pico-calorimeter. This remarkable instrument is capable of directly detecting heat signals emanating from minute populations of living cells, a feat that until now has remained technologically elusive due to the vanishingly small scale of these thermal signatures. By enabling real-time metabolic tracking at unprecedented sensitivity, the pico-calorimeter promises to revolutionize our understanding and monitoring of cellular activity, bacterial growth, and antibiotic response.

At the core of this innovation is the principle that living cells, as they metabolize nutrients, grow, divide, and react to external stimuli such as drugs, intrinsically emit heat. This metabolic heat, although incredibly subtle, offers a direct, unmediated insight into the physiological state of cells. Unlike conventional methods that infer cellular metabolism indirectly through oxygen consumption or chemical byproducts, the pico-calorimeter provides a direct calorimetric measurement, offering a more immediate and accurate assay of cellular energetics.

The technical architecture of the device is a marvel of microengineering. It consists of three ultrafine glass capillaries aligned on a delicately micromachined membrane with near-atomic precision. One of these capillaries harbors the biological sample suspended in a liquid growth medium, while the remaining two serve as thermodynamic reference points. As the bacteria or other cells within the sample metabolize and proliferate, they release minute quantities of heat. This thermal flux generates infinitesimal temperature gradients relative to the reference capillaries, which are then transduced into electrical signals by a nearby thermopile—an exquisitely sensitive heat-to-electricity converter capable of resolving fluctuations on the order of picowatts.

A critical enhancement in this iteration of the pico-calorimeter lies in its housing within a vacuum chamber. This vacuum environment thermally isolates the sensor assembly from ambient thermal noise, dramatically amplifying sensitivity by nearly an order of magnitude compared to antecedent designs. The prior versions employed liquid droplets on suspended membranes, which, while innovative, presented operational challenges and limited sensitivity. The current vacuum-sealed, microfluidic integration advances robustness, usability, and measurement fidelity, marking a milestone in the delicate art of thermal detection at the cellular scale.

Demonstrating the device’s prowess, the research team employed the pico-calorimeter to monitor Escherichia coli growth dynamics, beginning with an initial seed population as modest as thirty to forty individual bacterial cells. This capability to detect and analyze such small biological communities unveils immense potential for applications ranging from fundamental microbiology to clinical diagnostics. Notably, the device was employed to examine bacterial metabolic responses upon introduction of antibiotics with varying mechanisms of action—chloramphenicol, rifampicin, and ampicillin—capturing differential heat signatures indicative of altered cellular viability and activity.

These direct calorimetric measurements have revealed metabolic perturbations well in advance of what traditional culture-based microbiological assays could discern. This capability is particularly transformative in clinical scenarios such as sepsis, where detecting and characterizing bacterial populations at extremely low concentrations in blood is vital but presently time-consuming. The pico-calorimeter’s sensitivity could drastically truncate diagnostic timelines from days to hours, allowing more timely and targeted antimicrobial interventions.

Beyond measuring growth and antibiotic susceptibility, the pico-calorimeter enables continuous, real-time monitoring of fundamental cellular parameters including viability, proliferation rate, and stress responses. This temporal resolution offers researchers the invaluable ability to dynamically track cellular states and transitions, capturing metabolic shifts as cells respond to environmental perturbations or pharmacological treatments. Such insights may open new frontiers in cell biology, pharmacodynamics, and personalized medicine.

This breakthrough device represents the culmination of roughly two decades of meticulous research in the Vlassak laboratory, with contributions building from initial exploration of nano-calorimetry techniques aimed at materials science phenomena such as phase transitions in shape memory alloys and metallic glasses. The interdisciplinary bridge extended to biological systems has ushered in ultrasensitive calorimetry methods capable of assessing metabolic heat production in large cells and complex embryonic development processes, laying foundational expertise for this current bio-calorimetric leap.

Technologically, the fabrication of the pico-calorimeter draws upon state-of-the-art micro- and nanofabrication facilities, including the Harvard Center for Nanoscale Systems. The integration of microfluidics and micromachined sensing elements within thermally isolated environments exemplifies the cutting-edge convergence of materials science, electrical engineering, and biological instrumentation. The multidisciplinary synergy underscores the technological sophistication essential for detecting thermal signals billions of times smaller than everyday heat fluxes.

Commercially, the Harvard Technology Development office has filed multiple patents covering the pico-calorimeter and its applications in antimicrobial susceptibility testing. Juanjuan Zheng, a pivotal figure in this research and founder of an innovative startup, is leveraging the technology to deliver practical, label-free, real-time metabolic readouts. These tools hold promise for broad adoption in life sciences research, pharmaceutical development, and clinical diagnostics, harnessing the power of heat measurement to glean functional insights from minute biological samples.

As the research community embraces this transformative platform, interest has surged from a diverse array of scientific domains. The ability to capture direct metabolic information from tiny, dynamic living systems resolves a long-standing challenge in single-cell and small-population analysis. This heralds a new era where functional metabolic data provides early and actionable information on biological states, ranging from cellular growth and stress response to drug efficacy and resistance patterns.

In essence, the Harvard pico-calorimeter transcends conventional bioanalytical tools by transforming infinitesimal heat emissions into a vivid metabolic narrative. This technological breakthrough not only augments our scientific toolkit but also possesses the potential to accelerate biomedical discovery, enhance therapeutic precision, and ultimately improve patient outcomes by enabling rapid, noninvasive interrogation of cellular function. The implications for healthcare, research, and biotechnology are profound, heralding an exciting frontier where the subtle warmth of life becomes an unequivocal signal of cellular health and response.

Subject of Research: Cells
Article Title: A pico-calorimeter for cellular metabolism and antimicrobial susceptibility testing
References: Proceedings of the National Academy of Sciences
Image Credits: Vlassak Group / Harvard SEAS
Keywords: Calorimetry, Chemical analysis, Life sciences, Biophysics, Single cell profiling, Single molecule analysis, Materials science, Physics, Applied sciences and engineering, Applied physics, Engineering, Electrical engineering, Chemical engineering, Mechanical engineering, Health and medicine, Biomedical engineering

In a groundbreaking advancement that could reshape the landscape of bioelectronic medicine, researchers have developed a wirelessly powered, bioresorbable electrical stimulation system with unprecedented programmable control over stimulation waveforms. This innovation integrates tissue-penetrating near-infrared (NIR) light to modulate electrical currents with precision, harnessing a novel bioresorbable silicon phototransistor as the cornerstone of its operation. Pioneering beyond earlier monophasic pulse devices, this technology allows for the delivery of monophasic, biphasic, and polyphasic stimulation patterns, significantly enhancing the versatility and therapeutic potential of implantable electrical stimulators designed to dissolve harmlessly after use.

Traditional electrical stimulators implanted in biological tissues have largely relied on wired connections or bulky batteries, impeding patient mobility and often necessitating additional surgeries for device removal. Bioresorbable devices emerged as a solution to these challenges by safely degrading in the body over time, eliminating the risks associated with permanent implants. However, these earlier systems primarily delivered monophasic pulses, limiting therapeutic precision and adaptability in complex treatments. The innovation reported by Kim, Seo, Wang, and colleagues introduces a new paradigm by integrating wireless power transfer via NIR light and programmable waveform control within a fully bioresorbable platform, thus extending the functional range and easing the clinical management of bioelectronic therapies.

Central to this system is the incorporation of bioresorbable silicon phototransistors engineered to serve as optoelectronic modulators within the electrical circuitry. When illuminated by externally applied near-infrared light that penetrates deep into biological tissues, these phototransistors effectively adjust current flows at critical circuit nodes. This optical modulation capability replaces conventional electronic control elements, which often rely on persistent power sources or invasive wiring, thereby enabling the device to operate autonomously while still allowing fine-tuning of stimulation parameters through non-contact optical inputs.

The adoption of near-infrared light as the wireless power and control mechanism is particularly significant. NIR light possesses the ability to penetrate through several centimeters of tissue without causing damage, providing a safe and efficient transmission channel between the external controller and the implanted device. This feature supports programmability in situ, empowering clinicians to tailor electrical stimulation waveforms dynamically after device implantation. Precisely controlling the shape, amplitude, and timing of the electrical pulses is crucial for optimizing therapeutic outcomes in applications such as neuroregeneration and cardiac pacing.

The research team demonstrated the remarkable versatility of their bioresorbable system by successfully delivering a variety of stimulation waveforms. Monophasic pulses, which are unidirectional current flows, serve as a baseline therapy. More complex biphasic and polyphasic waveforms, which alternate current direction and comprise multiple phases respectively, have been shown to minimize tissue damage and improve efficacy in various biosignaling contexts. The ability to generate these sophisticated patterns expands the therapeutic range of the device, potentially enabling treatments that were previously inaccessible using bioresorbable technologies.

In demonstrating practical utility, the device was tested in both small and large animal models, validating its capacity for clinically relevant electrical stimulation regimes. The system was effectively employed in single- and dual-chamber cardiac pacing, a critical intervention for managing arrhythmias and heart block. Through controlled electrical stimulation, the device could synchronize cardiac contractions, a feat crucial for restoring efficient cardiac output. These trials highlight the translational potential of the technology for future human applications, situating it as a promising alternative to current electronic pacemakers that require permanent implantation and battery replacements.

Further extending the functional scope, the researchers utilized the bioresorbable stimulator to activate phrenic neuromuscular pathways to either induce or block diaphragmatic movements. The phrenic nerve controls diaphragmatic excursion, essential for respiration, and its modulation has significant implications for respiratory therapies, such as in patients with spinal cord injuries or central hypoventilation syndromes. By enabling wireless, programmable neurostimulation of the phrenic nerve, the technology offers a minimally invasive approach to manage life-sustaining respiratory functions, with the added benefit of device degradation after the therapeutic window.

The bioresorbable nature of the silicon phototransistors and associated electronics assures that after fulfilling their therapeutic role, the devices gradually dissolve into biocompatible byproducts. This process circumvents the complications related to device explantation surgeries, reducing patient risk and healthcare costs. Moreover, the materials chosen minimize inflammatory responses and tissue irritation, facilitating seamless integration with host biology during the operational phase.

The engineering behind this system represents an intersection of materials science, optoelectronics, and biomedical engineering. The architecture leverages the semiconducting properties of silicon in thin-film, bioresorbable form, combined with circuit design optimized for minimal power consumption and maximal efficiency during NIR irradiation. These multidisciplinary innovations collectively overcome longstanding barriers in the fabrication of transient electronic implants capable of sophisticated programmable functionality.

Controlling the stimulation waveforms via light permits remote adjustment without physical connections, paving the way for real-time therapeutic modulation responsive to patient status or physiological signals. Future iterations could incorporate feedback mechanisms by integrating bioresorbable sensors that monitor tissue response, creating closed-loop systems for personalized medicine. This dynamic adaptability could be transformative in managing chronic conditions requiring variable and responsive electrical stimulation protocols.

This research also addresses one of the fundamental challenges of implantable devices: power delivery. The optical wireless power transfer circumvents the need for bulky batteries or explant procedures, offering renewed device miniaturization potential. Coupled with programmable phototransistors, these innovations enable multifunctional implants that conform to soft tissues and degrade harmlessly, a trifecta crucial for implantation in sensitive organs like the heart and nervous system.

The ability to deliver polyphasic waveforms through a single bioresorbable receiver unit is particularly noteworthy. Conventionally, generating these complex waveforms requires sophisticated circuitry and stable power sources, neither of which are trivial to implement in resorbable devices. The research showcases how optical control unlocks this capability without sacrificing bioresorbability or wireless operation, representing a paradigm shift in transient biomedical electronics.

The successful application of this device in large animal cardiac models bridges a critical gap toward clinical translation. Such models replicate human physiological scales and complexities far more closely than small animals, validating both the efficacy and safety of the system under conditions analogous to human therapies. This demonstration is an essential milestone on the path toward human clinical trials and eventual regulatory approval.

Moreover, the phrenic nerve stimulation experiments illustrate the broader applicability beyond cardiac pacing. Neuromuscular control via electrical stimulation has vast clinical relevance, from restoring motor function to modulating organ systems. The biodegradable, wireless nature of this system makes it especially suited for temporary therapeutic interventions, such as post-surgical recovery or transient disease states, where permanent implants would be unnecessary or undesirable.

While this work represents a major leap forward, ongoing challenges remain, including further optimization of device longevity relative to treatment durations, refinement of light delivery systems to maximize tissue penetration and minimize off-target effects, and integration with advanced biocompatible materials to tailor resorption timelines. Addressing these will be key to broadening the range of clinical applications and ensuring patient safety across diverse scenarios.

Overall, this wirelessly powered, light-controlled, bioresorbable stimulation system emerges as a versatile platform poised to transform bioelectronic therapies. Its elegant combination of programmable polyphasic waveform delivery, wireless operation via near-infrared light, and full bioresorbability addresses critical limitations of current implantable stimulators. By enabling sophisticated, minimally invasive, and transient electrical stimulation paradigms, this technology advances the frontiers of regenerative medicine, cardiac therapy, and neuromodulation, marking a significant milestone in the evolution of biomedical devices.

Subject of Research: Wireless bioresorbable electrical stimulation device with programmable waveform control using near-infrared light

Article Title: A wirelessly powered, light-controlled, bioresorbable stimulation system with programmable polyphasic waveforms

Article References:
Kim, J.U., Seo, S.G., Wang, H. et al. A wirelessly powered, light-controlled, bioresorbable stimulation system with programmable polyphasic waveforms. Nat Electron (2026). https://doi.org/10.1038/s41928-026-01655-8

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41928-026-01655-8

In a groundbreaking advancement for optoelectronic technology, researchers have unveiled a novel approach harnessing the unique properties of Si₃N₄/n-Si hybrid devices to achieve interface-controlled broadband photodetection. This development promises to revolutionize the efficiency and spectral range of photodetectors, devices integral to a wide array of applications from telecommunications to environmental monitoring. The study, recently published in Scientific Reports, highlights how meticulous control over material interfaces can dramatically enhance device performance, marking a significant leap forward in photodetector design and fabrication.

Photodetectors serve as the eyes of modern electronic systems, converting light into electrical signals that enable everything from digital imaging to fiber optic communication. Traditional photodetectors, however, have long been limited by narrow operational bandwidths and sensitivity constraints, curbing their effectiveness in emerging high-performance applications. By integrating silicon nitride (Si₃N₄) with n-type silicon (n-Si), the researchers have engineered a hybrid platform that deftly overcomes these limitations, exploiting interface phenomena to extend detection capabilities across a broad spectrum of electromagnetic radiation.

At the heart of this innovation lies the strategic manipulation of the Si₃N₄/n-Si interface. Silicon nitride, known for its excellent dielectric properties and chemical stability, acts as both a passivation layer and an optical modulator when interfaced with silicon. This interplay at the atomic and electronic scale shapes charge carrier dynamics, reduces surface recombination losses, and enhances photon absorption efficiency. Such interface engineering ensures that the hybrid device is not only highly sensitive but also capable of operating seamlessly over a wide range of wavelengths, from ultraviolet through visible to near-infrared.

The research team deployed advanced fabrication techniques to precisely control the deposition and interface formation of Si₃N₄ on the n-Si substrate. Utilizing plasma-enhanced chemical vapor deposition (PECVD), they achieved a uniform and defect-minimized nitride layer that adheres perfectly to the silicon surface. This meticulous fabrication step is essential as interface traps, commonly induced by imperfections, can severely degrade photodetector responsiveness and noise levels. By minimizing such imperfections, the hybrid device attains an unprecedented signal-to-noise ratio crucial for sensitive detection tasks.

Optical characterization of the Si₃N₄/n-Si hybrids revealed remarkable broadband responsivity, a parameter quantifying the device’s ability to convert incoming photons across various wavelengths into electric current. The devices demonstrated enhanced photoresponse not only in the visible spectrum but also extended into ultraviolet and infrared regions, surpassing conventional silicon-based photodetectors limited by the bandgap constraints of pure silicon. This broadband sensitivity opens the door to new applications where multispectral light detection is necessary without the need for separate sensors.

One of the pivotal mechanisms for this extended response is the formation of interfacial states that facilitate charge transfer and broaden the spectral detection range. These states effectively lower the energy barriers that typically restrict silicon’s photoresponse, enabling efficient utilization of photons with energies both above and below the traditional silicon bandgap. This effect is modulated by the thickness and stoichiometric composition of the Si₃N₄ layer, parameters finely tuned during device fabrication to optimize performance.

Beyond spectral coverage, the temporal response of these hybrid photodetectors is equally impressive. The devices exhibited fast switching times and low dark currents, essential characteristics for high-speed communications and low-light detection scenarios. Reduced dark current, a measure of unwanted noise in the absence of illumination, directly correlates with enhanced sensitivity, thereby allowing the detection of weak optical signals with unprecedented clarity.

Integration compatibility is another striking advantage of the Si₃N₄/n-Si system. Both materials are well-established in mainstream semiconductor manufacturing, meaning that this innovation can be seamlessly incorporated into existing silicon-based electronic platforms. This compatibility facilitates scaling production while maintaining cost efficiency, a critical factor for commercial adoption in industries such as consumer electronics, healthcare diagnostics, and environmental sensing.

The research also delves into the underlying physics governing the device operation. Through combined experimental and theoretical analyses, the study elucidates charge carrier transport across the interface, the role of interface dipoles, and modulation of the built-in electric field that directs photogenerated carriers. Such detailed understanding offers a roadmap for further improvements, potentially inspiring future hybrid systems with tailored optoelectronic properties suitable for specific industrial applications.

In terms of real-world application, these hybrid photodetectors could significantly enhance the performance of cameras, optical coherence tomography devices, and remote sensing instruments. The broadband detection capability reduces the reliance on multiple sensors, simplifying device architectures and improving reliability. Additionally, their fast response times and stability under various environmental conditions are promising for deployment in harsh or variable environments, including space exploration and autonomous vehicle navigation.

This research marks a notable shift in photodetector technology by emphasizing interface engineering to transcend inherent material limitations. By capitalizing on the complementary properties of Si₃N₄ and n-Si junctions, the study injects fresh momentum into the pursuit of universal photodetectors that excel in speed, sensitivity, and spectral range. The findings underscore the vast potential lying in hybrid material systems, motivating continued exploration into interface-controlled photonic devices.

Looking forward, the researchers suggest exploring further modifications to the Si₃N₄ layer such as doping or introducing nanoscale structuring to tailor the interface behavior. Such advancements may unlock new functionalities like polarization sensitivity or even tunable wavelength selectivity, pushing hybrid photodetectors beyond current performance frontiers. These directions align with the broader scientific quest to develop smarter, more adaptable optoelectronic components for the next generation of information and sensing technologies.

In conclusion, the Si₃N₄/n-Si hybrid photodetector described in this study represents a pivotal development that combines material science innovation with practical engineering to address longstanding challenges in photodetection. Its broadband capability, operational stability, and integration potential poise it as a top candidate for a wide spectrum of applications demanding fast, efficient, and reliable light detection. As industries continue to demand more from photonic devices, such interface-controlled systems stand out as a transformative solution poised to redefine the future of photodetection technology.

Subject of Research: Interface-controlled broadband photodetection in Si₃N₄/n-Si hybrid devices

Article Title: Interface-controlled broadband photodetection in Si₃N₄/n-Si hybrid devices

Article References:
Manfo, T.A., Yıldız, D.E., Bağcı, C. et al. Interface-controlled broadband photodetection in Si₃N₄/n-Si hybrid devices. Sci Rep (2026). https://doi.org/10.1038/s41598-026-57951-y

Image Credits: AI Generated

In a significant milestone for the advancement of intelligent transport systems, representatives from fifteen partner institutions converged in the Swiss city of Winterthur for the General Assembly of the MOVEO project. Spanning two days in early June and hosted collaboratively by the Zurich University of Applied Sciences (ZHAW) alongside the City of Winterthur, this high-level meeting marked a pivotal moment to assess the multifaceted progress achieved in this ambitious European Union-backed initiative. The assembly provided a platform for experts specializing in transport infrastructure, digitalization, and inclusivity to engage in comprehensive dialogues surrounding the integration of cutting-edge technologies across diverse transport environments.

MOVEO stands at the intersection of innovation and real-world application, targeting critical challenges faced by modern transport systems. Over the course of the assembly, attendees delved deeply into advancements across the project’s core technical domains. One focal area involved the enhancement of inspection and monitoring systems designed to surveil transport infrastructure dynamically and track traffic flows in real time. By deploying sophisticated sensors and analytic devices, the project aims to generate actionable data streams that can preemptively identify structural stresses or anomalies, ultimately elevating maintenance efficiency and passenger safety.

Another crucial theme that permeated discussions was the development of intelligent door-to-door mobility solutions catering to both passenger transit and goods logistics. These smart mobility frameworks integrate multimodal transport options, leveraging data-driven route optimization and seamless transfer protocols to facilitate efficient, sustainable travel. The capacity of such systems to adapt dynamically to user needs and traffic conditions represents a paradigm shift from traditional static schedules to responsive, user-centric mobility networks.

In tandem with technological innovation, a significant portion of the dialogue addressed the pursuit of inclusivity and accessibility within transport services and infrastructure. Realizing transport environments that accommodate the full spectrum of user abilities demands rigorous design principles and thoughtful integration of assistive technologies. MOVEO’s commitment to these objectives manifests in both hardware adaptations and software interfaces, ensuring equitable access and enhancing user experience for disabled individuals, elderly passengers, and other traditionally underserved demographics.

Central to MOVEO’s methodology is the concept of a ‘digital twin’—a sophisticated virtual replica of physical assets and operational scenarios. This digital twin platform supports the project’s demonstration sites by enabling detailed simulation, predictive modeling, and real-time monitoring in a highly scalable and flexible manner. The ability to virtually recreate and experiment within these models accelerates technology validation cycles and informs better decision-making, reducing costs and mitigating risks associated with physical trial-and-error processes.

Highlighting the project’s real-world applicability, the partners provided updates on progress across five geographically and climatically diverse demonstration sites. Two are situated in eastern Switzerland, reflecting alpine and temperate conditions, while the others span the historic landscape of Ravenna, Italy; the complex hydrological system of France’s Seine basin; and the strategic maritime hub of Klaipėda port in Lithuania. Each site serves as a living laboratory where varying infrastructure types and life cycle stages are addressed, allowing the consortium to benchmark technologies against multifaceted operational contexts.

During the assembly, a notable field visit to the Leonie-Moser bridge in Winterthur offered tangible insight into the ongoing integration of MOVEO innovations. This upcoming bridge, slated for completion in September 2026, will link the districts of Oberwinterthur and Grüze, facilitating pedestrian and bus transit. Importantly, it forms a key node for sensor installations dedicated to monitoring passenger flows, particularly as commuters transfer between train and bus services. The instrumentation strategy exemplifies how real-time data acquisition enables nuanced understanding of multimodal transport interactions on critical infrastructure.

José Solís Hernández, project coordinator and an expert engineer from Spain’s CEMOSA, underscored the rapid progress being made in technological implementations. Reflecting on the trajectory thus far, Hernández emphasized the consortium’s focus on concluding key installation phases by the upcoming October deadline. This timeline aligns with preparatory activities for the next formal project review, during which minimum viable products (MVPs) must be finalized, demonstrating functional readiness and alignment with strategic objectives.

MOVEO’s expansive consortium harnesses expertise from nine European nations, uniting a comprehensive value chain that spans the entirety of transport and digitalization disciplines. The collective includes specialists in critical areas such as structural inspection, advanced monitoring techniques, logistics optimization, user mobility dynamics, and social inclusiveness. Engaging end-users alongside transport infrastructure managers ensures that developed solutions remain relevant, practical, and attuned to operational realities.

The innovative research underpinning MOVEO crystallizes around five core pillars. Firstly, infrastructure assessment and redesign leverages analytical tools to evaluate existing assets, proposing modifications that enhance resilience and adaptability. Secondly, inspection and monitoring integrate sensor networks and diagnostic technologies to maintain operational integrity. The third pillar, digitalized mobility, focuses on user-centered, data-driven solutions that redefine transit experiences. Smart logistics form the fourth pillar, addressing the efficient movement of goods with a sustainability lens. Finally, inclusiveness and accessibility aim to democratize mobility services, ensuring no user is left behind regardless of physical or cognitive barriers.

Backed by nearly five million euros in funding through the European Union’s Horizon Europe framework, MOVEO is positioned for a 42-month research phase culminating in October 2028. This substantial financial support reflects the high strategic importance assigned to the project, especially amidst rising pressures to modernize transport infrastructure in alignment with environmental, economic, and social objectives. The collaborative approach fosters cross-border innovation, ensuring outcomes deliver broad-reaching impacts for European mobility systems and beyond.

Ultimately, MOVEO exemplifies how integrative, interdisciplinary research can be effectively mobilized to tackle the complexities of future transport demand. By bridging digital technology with physical infrastructure and emphasizing user inclusivity, the project charts a course toward a smarter, safer, and more sustainable mobility ecosystem. As installations near completion and the demonstrator sites become fully operational, MOVEO’s innovations promise to inform policy, guide industry practices, and elevate standards across the entire European transportation landscape.

Subject of Research: Transport infrastructure monitoring, digitalized mobility, and inclusive transport solutions in Europe.

Article Title: (Not provided)

News Publication Date: (Not provided)

Web References: https://mediasvc.eurekalert.org/Api/v1/Multimedia/27a1c0f0-d8a7-487e-97b3-ebce96f60ef7/Rendition/low-res/Content/Public

References: (Not provided)

Image Credits: European Science Communication Institute gGmbH

Keywords: MOVEO project, transport infrastructure, digital twin, sensor monitoring, multimodal mobility, smart logistics, transport inclusiveness, European Union Horizon Europe, infrastructure assessment, pedestrian flow monitoring

The Transient Artifact and Continuous Learning System (TACLS) leverages data from continuously operating satellite networks coupled with machine learning models to help meteorologists at the National Weather Service forecast flash floods more efficiently. This new software is the result of a collaboration between NASA’s Jet Propulsion Laboratory, the University of California, San Diego (UCSD), and the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS).

Created with support from NASA’s Earth Science Technology Office (ESTO), TACLS leverages machine learning to automatically locate evidence (unusual increases in atmospheric moisture) of impending flash flooding that meteorologists may otherwise miss as they analyze large amounts of data. TACLS flags that evidence, indicates where flash flooding could likely occur, and displays that information via a user-friendly visualization for human analysts to interpret. Those analysts can then decide whether to issue a flash flood warning or weather advisory.

This novel framework for tracking extreme weather events and predicting imminent flash floods operates in near real-time, producing forecasts in as little as fifteen minutes.

“That’s really what we wanted to do, to give meteorologists a tool to help decision making for flash flood warnings,” said Yehuda Bock, Distinguished Researcher at the UCSD Scripps Institution of Oceanography and principal investigator for TACLS.

In simulations testing, TACLS used data from diverse severe weather events—including atmospheric rivers, monsoonal convection, and tropical cyclone remnants—between 2017 and 2023 and successfully captured 93% of the issued flash-flood warnings. Meteorologists from the National Weather Service are currently working to incorporate TACLS into their existing systems for forecasting flash floods in Southern California.

This learning system has two main components. First, an analytic back-end software suite uses machine learning algorithms to process satellite data and determine areas at risk for flooding. Second, user-friendly visualization software highlights those areas for further analysis by humans.

The ACLS back-end software analyzes data from satellites in the Global Navigation Satellite System (GNSS), a constellation of satellite networks that drive navigation services around the world. Water vapor in the troposphere delays signals from these satellites as they travel to Earth. This signal delay can be analyzed to calculate the amount of water vapor in the atmosphere over a particular location on Earth.

The TACLS analytic back-end software suite features a machine learning model trained using more than 30 years of past GNSS data. This model is an anomaly detector that tracks unusual increases in atmospheric moisture. The model then carefully examines that atmospheric moisture data and determines whether it’s either an artifact (a false feature or distortion in the data) or a transient (a time-sensitive physical event, like heavy precipitation) that requires interpretation by human analysts.

If TACLS determines the data represents a transient, such as an extreme weather event that warrants a flash flood warning, it will forward that data to the TACLS visualization software (MGViz) for further evaluation by humans. The analysts use their judgement and experience to interpret these events and determine whether the flagged data indicates a flash flood is likely, and, if necessary, issue a flash flood warning.

Several past innovations developed at JPL are leveraged by TACLS to process GNSS data and present the results. The analytic back-end software suite incorporates elements from JPL’s Domain-agnostic Outlier Ranking Algorithms program and the Time-series Forecasting, Evaluation, and Deployment program. The TACLS visualizer is based on the Multi-Mission Geographic Information System, originally developed at JPL for NASA’s Mars missions.

The TACLS software binds all these components within a novel system that enhances existing methods to reduce the amount of time it takes for a human analyst to determine whether to issue a flash flood warning.

Both the TACLS software and the data used to train it will be open-source, allowing scientists to either tailor this model in response to their unique research needs or create their own model from scratch.

For additional details, see the entry for this project on NASA TechPort. 

Project Lead: Dr. Yehuda Bock, University of California, San Diego. 

Sponsoring Organization(s): NASA’s Earth Science Technology Office Advanced Information Systems Technology Program; JPL; NOAA; National Weather Service. 

The Transient Artifact and Continuous Learning System (TACLS) leverages data from continuously operating satellite networks coupled with machine learning models to help meteorologists at the National Weather Service forecast flash floods more efficiently. This new software is the result of a collaboration between NASA’s Jet Propulsion Laboratory, the University of California, San Diego (UCSD), and the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS).

Created with support from NASA’s Earth Science Technology Office (ESTO), TACLS leverages machine learning to automatically locate evidence (unusual increases in atmospheric moisture) of impending flash flooding that meteorologists may otherwise miss as they analyze large amounts of data. TACLS flags that evidence, indicates where flash flooding could likely occur, and displays that information via a user-friendly visualization for human analysts to interpret. Those analysts can then decide whether to issue a flash flood warning or weather advisory.

This novel framework for tracking extreme weather events and predicting imminent flash floods operates in near real-time, producing forecasts in as little as fifteen minutes.

“That’s really what we wanted to do, to give meteorologists a tool to help decision making for flash flood warnings,” said Yehuda Bock, Distinguished Researcher at the UCSD Scripps Institution of Oceanography and principal investigator for TACLS.

In simulations testing, TACLS used data from diverse severe weather events—including atmospheric rivers, monsoonal convection, and tropical cyclone remnants—between 2017 and 2023 and successfully captured 93% of the issued flash-flood warnings. Meteorologists from the National Weather Service are currently working to incorporate TACLS into their existing systems for forecasting flash floods in Southern California.

This learning system has two main components. First, an analytic back-end software suite uses machine learning algorithms to process satellite data and determine areas at risk for flooding. Second, user-friendly visualization software highlights those areas for further analysis by humans.

The ACLS back-end software analyzes data from satellites in the Global Navigation Satellite System (GNSS), a constellation of satellite networks that drive navigation services around the world. Water vapor in the troposphere delays signals from these satellites as they travel to Earth. This signal delay can be analyzed to calculate the amount of water vapor in the atmosphere over a particular location on Earth.

The TACLS analytic back-end software suite features a machine learning model trained using more than 30 years of past GNSS data. This model is an anomaly detector that tracks unusual increases in atmospheric moisture. The model then carefully examines that atmospheric moisture data and determines whether it’s either an artifact (a false feature or distortion in the data) or a transient (a time-sensitive physical event, like heavy precipitation) that requires interpretation by human analysts.

If TACLS determines the data represents a transient, such as an extreme weather event that warrants a flash flood warning, it will forward that data to the TACLS visualization software (MGViz) for further evaluation by humans. The analysts use their judgement and experience to interpret these events and determine whether the flagged data indicates a flash flood is likely, and, if necessary, issue a flash flood warning.

Several past innovations developed at JPL are leveraged by TACLS to process GNSS data and present the results. The analytic back-end software suite incorporates elements from JPL’s Domain-agnostic Outlier Ranking Algorithms program and the Time-series Forecasting, Evaluation, and Deployment program. The TACLS visualizer is based on the Multi-Mission Geographic Information System, originally developed at JPL for NASA’s Mars missions.

The TACLS software binds all these components within a novel system that enhances existing methods to reduce the amount of time it takes for a human analyst to determine whether to issue a flash flood warning.

Both the TACLS software and the data used to train it will be open-source, allowing scientists to either tailor this model in response to their unique research needs or create their own model from scratch.

For additional details, see the entry for this project on NASA TechPort. 

Project Lead: Dr. Yehuda Bock, University of California, San Diego. 

Sponsoring Organization(s): NASA’s Earth Science Technology Office Advanced Information Systems Technology Program; JPL; NOAA; National Weather Service. 

The post NASA Uses Machine Learning to Enhance Flash Flood Warnings appeared first on NASA Science.

In a groundbreaking development addressing one of modern industry’s most persistent environmental challenges, researchers have unveiled an innovative approach to detoxify hydrazine-contaminated wastewater using advanced organic photovoltaic catalysts (OPCs). This pioneering work marries the fields of sustainable energy and environmental remediation, offering a dual benefit of pollutant degradation and clean hydrogen production, all under the benign influence of sunlight without the input of external energy or sacrificial chemicals.

Hydrazine (N₂H₄), a widely used compound in various industrial applications — from rocket propellants to agricultural chemicals — poses severe environmental and health risks due to its high toxicity and resistance to conventional treatment methods. Current remediation technologies often rely heavily on energy-intensive processes or the addition of chemicals that generate secondary pollution, making a sustainable, efficient, and cost-effective solution a critical unmet need. The recent study introduces narrow-bandgap organic photovoltaic catalysts fine-tuned with donor-acceptor heterojunctions that efficiently harness a broader range of the solar spectrum, extending from visible to near-infrared wavelengths.

The crux of the innovation lies in the OPCs’ ability to excite and separate charge carriers with remarkable efficiency, directly translating solar energy into catalytic activity. By facilitating precise and rapid charge transfer, these catalysts enable degradation of hydrazine molecules in wastewater into harmless end products. Remarkably, this photocatalytic process simultaneously generates hydrogen gas, turning a hazardous byproduct into a valuable clean fuel, thus underscoring the approach’s dual environmental and energy implications.

To enhance the practical viability of these materials, the research team incorporated an ultra-thin coating of alumina (Al₂O₃) on OPC nanoparticles. This coating significantly improves the catalysts’ stability and performance, particularly in complex, real-world wastewater matrices, which often contain a plethora of interfering substances. The Al₂O₃ shell protects the active organic components against photodegradation and chemical fouling, enabling sustained catalytic activity without performance loss over multiple cycles.

Delving deeper, the research utilized a combination of density functional theory (DFT) calculations, in situ spectroscopy, and isotope labeling experiments to unravel the underlying catalytic mechanisms. These investigations revealed that proton-coupled electron transfer is the pivotal step driving hydrazine degradation and hydrogen evolution. This insight not only illuminates the fundamental chemical pathways involved but also informs the strategic design of next-generation catalysts that maximize charge utilization and catalytic turnover.

Under simulated sunlight conditions resembling natural AM 1.5 G, 100 mW cm⁻² illumination, the optimized OPC nanoparticles demonstrated exceptional efficacy by reducing hydrazine concentrations from a hazardous 640 ppm to mere trace amounts in just five hours. This level of remediation meets stringent industrial and agricultural discharge standards, marking a significant milestone in wastewater treatment technology. Additionally, the system achieved mass-normalized hydrogen evolution rates as high as 559.3 ± 28.0 mmol h⁻¹ g⁻¹, concurrently producing hydrogen at a scale that could contribute meaningfully to clean energy portfolios.

One of the most compelling features of this work is the catalyst’s recyclability and the absence of any secondary pollution generation. Unlike conventional treatment methods that often result in toxic sludge or require periodic regeneration with hazardous chemicals, the OPCs maintained high activity across multiple uses without discharging any secondary contaminants. This aspect fundamentally redefines the sustainability paradigm for toxic wastewater treatment.

The organic photovoltaic catalysts’ narrow bandgap is a critical enabler of their success. Conventional photocatalysts like titanium dioxide primarily absorb ultraviolet light, which constitutes only a small fraction of solar radiation. By contrast, the OPCs’ tailored bandgap allows efficient absorption of visible and near-infrared light, which make up the majority of the solar spectrum. This increase in solar energy utilization translates directly to enhanced catalytic performance, positioning these materials well ahead of traditional alternatives in terms of solar-to-chemical conversion efficiency.

The donor-acceptor heterojunction architecture engineered in the OPCs plays a central role in overcoming charge recombination issues plaguing many organic materials. By spatially separating electron and hole carriers, these heterojunctions extend carrier lifetimes and facilitate their transfer to reaction sites on the catalyst surface. This strategy drastically improves the quantum efficiency of the photocatalytic process, ensuring more hydrazine molecules are converted per photon absorbed.

Complex industrial wastewaters often contain diverse ionic species, organic contaminants, and fluctuating pH, posing significant challenges to photocatalyst stability. The introduction of the Al₂O₃ shell effectively buffers OPCs against such harsh chemical environments, offering a protective barrier while allowing substrate molecules to access active sites. This protective strategy exemplifies a clever marriage of materials science and catalysis design principles for real-world applicability.

From a mechanistic viewpoint, the proton-coupled electron transfer (PCET) mechanism elucidated by the study provides valuable insights into the synergy between charge carriers and hydrogen ions in driving hydrazine decomposition. This mechanistic clarity opens avenues for rational catalyst tuning, potentially enabling tailored systems for the breakdown of other recalcitrant pollutants beyond hydrazine, thus broadening the technology’s impact.

The dual function of hydrazine degradation coupled with hydrogen evolution not only abates environmental hazards but also tackles energy sustainability by producing a clean, renewable fuel. This convergence of waste remediation and green energy generation is especially significant amidst global efforts to decarbonize industrial processes and promote circular economy principles.

Furthermore, the study demonstrates that the system operates without any external power input, relying solely on passive sunlight, making it exceptionally attractive for applications in remote or off-grid locations. The absence of sacrificial reagents further simplifies operation, reduces operational costs, and eliminates sources of secondary pollution, highly desirable attributes for scalable industrial deployment.

The mass and area-normalized hydrogen evolution rates reported represent a benchmark in the field of photocatalytic wastewater treatment, underscoring the potency and commercial promise of these organic photovoltaic catalysts. Importantly, their synthetic procedures and materials composition suggest compatibility with scalable manufacturing methods, bolstering their potential for rapid translation from laboratory to practice.

In summary, this innovative approach combines advances in organic photovoltaics, surface chemistry, and catalysis to deliver a paradigm shift in the treatment of hydrazine wastewater alongside clean energy production. The research sets a new standard for sustainable, efficient, and highly effective remediation technologies, aligning closely with urgent needs in industrial pollution control and the global hydrogen economy.

As industries worldwide grapple with environmental regulations and increasing demands for sustainability, the emergence of such multifunctional catalytic systems heralds a new era in wastewater treatment. With further refinements and scaling efforts, this technology is poised to transform hazardous waste management and bolster renewable energy initiatives concurrently, illustrating the power of interdisciplinary science in solving complex societal challenges.

This landmark study paves the way for future explorations into organic photovoltaic catalyst systems tailored to diverse environmental contaminants and integrated into smart treatment modules. The ability to couple sunlight-driven pollutant degradation with valuable fuel generation may well inspire a suite of next-generation sustainable technologies tailored for the demands of the 21st century.

Subject of Research:
Advanced photocatalytic treatment of hydrazine-contaminated wastewater using organic photovoltaic catalysts for simultaneous environmental remediation and hydrogen production.

Article Title:
Solar remediation of hydrazine wastewater using efficient narrow-bandgap organic photovoltaic catalysts.

Article References:
Wu, Y., Lee, Y., Zhang, Z. et al. Solar remediation of hydrazine wastewater using efficient narrow-bandgap organic photovoltaic catalysts. Nat Water (2026). https://doi.org/10.1038/s44221-026-00666-1

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s44221-026-00666-1