CyberSec Research

The built-in potential of p-n junctions plays a critical role in charge separation, which is fundamental to the photovoltaic effect. However, the conventional classical theory of photovoltaic effect in p-n junctions typically does not account for the quantitative influence of the built-in potential. In this study, we revisit the classical theory and propose an improved analytic expression of photocurrent by applying more accurate boundary conditions. Our improved expression reveals that the photocurrent comprises of two components: the conventional photocurrent and a previously unrecognized backward photocurrent. Latter reduces the total photocurrent, yet it has not been discussed in prior literature. The essential role of the built-in potential is to suppress this backward current. Furthermore, our improved expression of photocurrent predicts that the photocurrent vanishes under certain forward bias conditions. This prediction is experimentally validated using a commercial silicon solar cell, confirming the direct impact of the built-in potential on photocurrent behavior.

We analyse the behaviour of the Rayleigh-Taylor instability (RTI) in the presence of a foam. Such a problem may be relevant, for example, to some inertial confinement fusion (ICF) scenarios such as foams within the capsule or lining the inner hohlraum wall. The foam displays 3 different phases: by order of increasing stress, it is first elastic, then plastic, and then fractures. Only the elastic and plastic phases can be subject to a linear analysis of the instability. The growth rate is analytically computed in these 2 phases, in terms of the micro-structure of the foam. In the first, elastic, phase, the RTI can be stabilized for some wavelengths. In this elastic phase, a homogenous foam model overestimates the growth because it ignores the elastic nature of the foam. Although this result is derived for a simplified foam model, it is likely valid for most of them. Besides the ICF context considered here, our results could be relevant for many fields of science.

Photonic integrated circuits are heavily researched devices for telecommunication, biosensing, and quantum technologies. Wafer-scale fabrication and testing are crucial for reducing costs and enabling large-scale deployment. Grating couplers allow non-invasive measurements before packaging, but classical designs rely on long tapers and narrow bandwidths. In this work, we present compact, inverse-designed grating couplers with broadband transmission. We optimized and fabricated arrays of devices and characterized them with a 4f-scanning setup. The nominal design reached simulated efficiencies of 52 %, while measurements confirmed robust performance with up to 32 % efficiency at the target 1540 nm wavelength and 46 % at shifted wavelengths. Without scaling and contour biasing, the measured efficiency at the target wavelength drops to only 4.4 %. Thus, a key finding is that systematic scaling and edge biasing recover up to an eightfold improvement in efficiency. These inverse-designed grating couplers can be efficiently corrected post-design, enabling reliable performance despite fabrication deviations. This approach allows simple layout adjustments to compensate for process-induced variations, supporting wafer-scale testing, cryogenic photonic applications, and rapid design wavelength tuning.

A huge interesting progress in the field of organic electronic materials and devices has been observed in the last decade. However, the understanding of these materials is still a challenge to overcome. Most studies in literature focus on active devices such as OTFTs, OLEDs and OPVs. Nevertheless, a complete technology has to have also passive devices in order to allow the design of interesting applications and complex circuits. This paper deals with the development of a complete set of passive devices allowing the fabrication of simple applications such as filters or sensors. The process flow is a fully screen printed technology that uses exclusively organic materials on gold laser ablated flexible substrate. Discrete passive (R, L, C) devices have been processed and characterized. This has permitted the fabrication of RLC low-band pass filters that are dedicated to RF applications, typically around 1GHz. Furthermore, based on these discrete passive components, we have developed a sensitive sensor on flexible substrate for RFID applications. We present the state of the art of our process development for RF applications using organic materials.

We report a high-performance thermochromic VO2-based coating prepared by using a three-step process, consisting of magnetron sputter depositions of SiO2 films and V-W films and their postannealing, on standard glass at a low substrate temperature of 350 {\deg}C without opening the vacuum chamber to atmosphere. It is formed by four layers of W-doped VO2 nanoparticles dispersed in SiO2 matrix. The coating exhibits a transition temperature of 33 {\deg}C with an integral luminous transmittance of 65.4% (low-temperature state) and 60.1% (high-temperature state), and a modulation of the solar energy transmittance of 15.3%. Such a combination of properties, together with the low temperature during preparation, fulfill the requirements for large-scale implementation on building glass and have not been reported yet.

Light pulses offer a faster, more energy-efficient, and direct route to magnetic bit writing, pointing toward a hybrid memory and computing paradigm based on photon transmission and spin retention. Yet progress remains hindered, as deterministic, single-pulse optical toggle switching has so far been achieved only with ferrimagnetic materials, which require too specific a rare-earth composition and temperature conditions for technological use. In mainstream ferromagnet--central to spintronic memory and storage--such bistable switching is considered fundamentally difficult, as laser-induced heating does not inherently break time-reversal symmetry. Here, we report coherent magnetization switching in ferromagnets, driven by thermal anisotropy torque with single laser pulses. The toggle switching behavior is robust over a broad range of pulse durations, from femtoseconds to picoseconds, a prerequisite for practical applications. Furthermore, the phenomenon exhibits reproducibility in CoFeB/MgO-based magnetic tunnel junctions with a high magnetoresistance exceeding 110%, as well as the scalability down to nanoscales with remarkable energy efficiency (17 fJ per 100-nm-sized bit). These results mark a notable step toward integrating opto-spintronics into next-generation memory and storage technologies.

Biofilms in porous media critically influence hydraulic properties in environmental and engineered systems. However, a mechanistic understanding of how microbial life controls permeability remains elusive. By combining microfluidics, controlled pressure gradient and time-lapse microscopy, we quantify how motile and non-motile bacteria colonize a porous landscape and alter its resistance to flow. We find that while both strains achieve nearly identical total biomass, they cause drastically different permeability reductions - 78% for motile cells versus 94% for non-motile cells. This divergence stems from motility, which limits biomass spatial accumulation, whereas non-motile cells clog the entire system. We develop a mechanistic model that accurately predicts permeability dynamics from the pore-scale biomass distribution. We conclude that the spatial organization of biomass, not its total amount, is the primary factor controlling permeability.

The duration of isolated attosecond pulses created via high-order harmonic generation is determined by the number of optical cycles in the driving laser. Achieving shorter attosecond soft X-ray pulses requires minimizing the number of cycles while maintaining a high pulse energy. Here, we demonstrate a carrier-envelope-phase-stable, 100-mJ-class sub-cycle mid-infrared laser that produces a supercontinuum coherent soft X-ray with unprecedented bandwidth. The system delivers 50-mJ, 6.7-fs (0.88-cycle) pulses at a center wavelength of 2.26 $\mu$m - over two orders of magnitude more energetic than any previous sub-cycle laser. We applied the system to high-order harmonic generation and compared the results to simulations based on the three-dimensional time-dependent Schr\"odinger equation to identify unique features of sub-cycle lasers. This work represents a decisive step toward high-energy half-cycle lasers and high-energy single-digit attosecond soft X-ray pulses that can be used to probe matter and light-matter interactions at previously inaccessible temporal resolutions.

Neuromorphic computing demands synaptic elements that can store and update weights with high precision while being read non-destructively. Conventional ferroelectric synapses store weights in remnant polarization states and might require destructive electrical readout, limiting endurance and reliability. We demonstrate a ferroelectric MEMS (FeMEMS) based synapse in which analog weights are stored in the piezoelectric coefficient $d_{31,eff}$ of a released Hf$_{0.5}$Zr$_{0.5}$O$_2$ (HZO) MEMS unimorph. Partial switching of ferroelectric domains modulates $d_{31,eff}$, and a low-amplitude mechanical drive reads out the weight without read-disturb in the device yielding more than 7-bit of programming levels. The mechanical switching distribution function follows a Lorentzian distribution as a logarithmic function of partial poling voltage ($V_p$) consistent with nucleation-limited switching (NLS), and the median threshold extracted from electromechanical data obeys a Merz-type field-time law with a dimensionless exponent $\alpha = 3.62$. These relationships establish a quantitative link between mechanical weights and electrical switching kinetics. This mechanically read synapse avoids depolarization and charge-injection effects, provides bipolar weights (well suited for excitatory and inhibitory synapses), directly reveals partial domain populations, and offers a robust, energy-efficient route toward high-bit neuromorphic hardware.

Radiation chemistry of model systems irradiated with ultra-high dose-rates (UHDR) is key to obtain a mechanistic understanding of the sparing of healthy tissue, which is called the FLASH effect. It is envisioned to be used for efficient treatment of cancer by FLASH radiotherapy. However, it seems that even the most simple model systems, water irradiated with varying dose-rates (DR), pose a challenge. This became evident, as differences within measured and predicted hydrogen peroxide (H2O2) yields (g-values) for exposure of liquid samples to conventional DR and UHDR were reported. Many of the recently reported values contradict older experiments and current Monte-Carlo simulations(MCS). In the present work, we aim to identify possible reasons of these discrepancies and propose ways to overcome this issue. Hereby a short review of recent and classical literature concerning experimental and simulational studies is performed. The studies cover different radiation sources, from gamma rays, high-energy electrons, heavy particles (protons and ions) with low and high linear energy transfer (LET), and samples of hypoxic & oxygenated water, with cosolutes such as bovine-serum albumine (BSA). Results are for additional experimental parameters, such as solvent, sample container and analysis methods used to determine the respective g-values of H2O2. Similarly the parameter of the MCS by the step-by-step approach, or the independent-reaction time (IRT) method are discussed. Here, UHDR induced modification of the radical-radical interaction and dynamics, not governed by diffusion processes, may cause problems. Approaches to test these different models are highlighted to allow progress: by making the step from a purely descriptive discourse of the effects observed, towards testable models, which should clarify the reasons of how and why such a disagreement came to light in the first place.

This paper presents an electromagnetic investigation of the crosstalk between two bent microstrip lines (MLs) separated by a perforated planar shield. As an extension of our previous study, the effects of various discontinuities in either the MLs or the shield along the coupling path are analyzed through numerical simulations and validated by measurements. The underlying electromagnetic mechanisms are also discussed. Furthermore, multimodal wave theory in a rectangular waveguide is applied to predict crosstalk behavior when the shield contains an aperture. This study aims to conceptually elucidate complex crosstalk phenomena that are difficult to model using circuit theory, and successful predictions of crosstalk behavior are presented for different problem cases.

A new protocol is presented to directly characterise the toughness of microstructural regions present within the weld heat-affected zone (HAZ), the most vulnerable location governing the structural integrity of hydrogen transport pipelines. Heat treatments are tailored to obtain bulk specimens that replicate predominantly ferritic-bainitic, bainitic, and martensitic microstructures present in the HAZ. These are applied to a range of pipeline steels to investigate the role of manufacturing era (vintage versus modern), chemical composition, and grade. The heat treatments successfully reproduce the hardness levels and microstructures observed in the HAZ of existing natural gas pipelines. Subsequently, fracture experiments are conducted in air and pure H2 at 100 bar, revealing a reduced fracture resistance and higher hydrogen embrittlement susceptibility of the HAZ microstructures, with initiation toughness values as low as 32 MPa$\sqrt{\text{m}}$. The findings emphasise the need to adequately consider the influence of microstructure and hard, brittle zones within the HAZ.

Quantum sensing utilizing nitrogen-vacancy (NV) centers in diamond has emerged as a transformative technology for probing magnetic phase transition1-4, evidencing Meissner effect of superconductors1,5-9, and visualizing stress distribution3,9 under extreme conditions. Recent development in NV configurations and hydrostatic environments have raised the operational pressures of NV centers to 140 GPa2,6,10,11, but substantial challenges remain in extending sensing capabilities into multi-megabar range, critical for research in hydrogen-rich superconductors like La-Sc-H ($T_{\text{c}}$ of 271-298 K at 195-266 GPa)12 and evolution of minerals near Earth's core13. Here we report the fabrication of shallow NV centers through ion implantation followed by high-pressure and high-temperature (HPHT) annealing, leading to increased density, improved coherence, and mitigated internal stresses, a pre-requisite for reducing their degradation under compression. This NV magnetometry enable breakthrough of pressure capabilities exceeding 240 GPa, constrained by structural integrity of the 50 um diamond anvils, suggesting that the untapped pressure limit may enable further advancements with smaller cutlets or more robust diamonds. We present compelling evidence of the Meissner effect and trapped flux at record-high pressure of 180 GPa for superconducting transition in elemental titanium (Ti) as benchmark, establishing a solid foundation for high-pressure magnetometry in exploring complex quantum phenomena at previously unreachable pressures.

Electronic and photonic chips revolutionized information technology through massive integration of functional elements, yet phonons as fundamental information carriers in solids remain underestimated. Here, we demonstrate large-scale programmable phononic integrated circuits (PnICs) for complex signal processing. We developed a comprehensive library of gigahertz-frequency phononic building blocks that control acoustic wave propagation, polarization, and dispersion. Combining these elements, we demonstrate an ultra-compact 1$\times$128 on-chip acoustic power splitter with unprecedented integration density of 3,000/cm$^2$, a 21-port acoustic frequency demultiplexer with 3.8~MHz resolution, and a four-channel reconfigurable frequency synthesizer. This work establishes scalable phononic integration as the third pillar of information processing alongside electronics and photonics, enabling hybrid chips that combine all three domains for advanced signal processing and quantum information applications.

Microplastics are increasingly recognized as a global environmental health threat, yet their detection and characterization remain constrained by the cost, form factor, and throughput of existing analytical tools. Portable micro/nanotechnology-based sensors are emerging to address this need, but most rely on the assumption of spherical particle geometry in their operating principle, limiting their relevance for environmental analysis. Here, we overcome this limitation by advancing microwave cytometry with machine learning-enabled shape recognition. Microwave cytometry is a flow-through electronic platform that integrates microwave resonator responses with low-frequency impedance signals to capture the dielectric signatures of individual particles. Using microscopy-derived shape measurements as ground truth, we trained a random forest model to decode these information-rich waveforms. Once trained, the system operates without optical input, enabling electronic-only determination of particle geometry. We demonstrate extraction of the major and minor axes of ellipsoidal microparticles with <8% relative error on average and use these predictions to derive the dielectric permittivity of ellipsoid particles. This approach removes long-standing shape assumptions in microplastic sensing and establishes a pathway toward portable, high-throughput, morphology-aware detection technologies.

Fluorescence-based single-molecule localization, transport, and sensing require spatial confinement to extend the molecule's residence time during imaging, sufficient temporal resolution to capture fast dynamics, and efficient fluorescence background suppression. Two-dimensional (2D) materials offer large-area, atomically flat surfaces suitable for massively parallel in-plane biomolecule imaging, yet achieving guided motion in one-dimensional confinements using top-down nanofabrication remains challenging. Here, we demonstrate that thermally induced wrinkles in exfoliated hexagonal boron nitride (hBN) act as self-assembled nanochannels that enable biomolecule confinement and imaging under wide-field fluorescence microscopy. By controlling annealing parameters and substrate properties, we obtain scalable and reproducible wrinkle networks whose densities and morphologies can be tuned. Structural characterization using atomic force and scanning electron microscopy is complemented by fluorescence imaging and Kelvin probe force microscopy, confirming that aqueous solutions fill and remain stably retained within the nanochannels for periods exceeding 10 hours. We further achieve selective ATTO647N-DNA localization and imaging in the one-dimensional channels through the formation of a graphene/hBN vertical heterostructure. The graphene overlayer serves as a quenching mask that suppresses background fluorescence both from high-strain hBN regions and from DNA adsorbed on top of the 2D layer. Overall, these results provide a scalable, lithography-free route for creating planar nanofluidic confinements fully compatible with single-molecule imaging. This platform enables fundamental nanobiology studies as well as on-chip biomolecule transport and sensing applications.

Illusion effects-where one object appears as another-arise from the non-uniqueness of physical systems, in which different material configurations yield identical external responses. Conventional approaches, such as coordinate transformation, map equivalent configurations but provide only specific solutions, while analytical or numerical optimization methods extend these designs by minimizing scattering yet remain constrained by model assumptions and computational cost. Here, we exploit this non-uniqueness through a data-driven framework that uses a variational autoencoder to compress high-dimensional thermal-field data into a compact latent space capturing geometrical relations between configurations and observations. In this latent space, thermal illusion corresponds to finding configurations that minimize geometric distance to a target configuration, with thermal cloaking as a special case where the target is free space. Specifically, we demonstrate the concept in a cylindrical shell with anisotropic thermal conductivities enclosing a core of arbitrary conductivity, achieving robust thermal illusion and cloaking using only positive conductivities. Such a latent-space distance approach provides a refreshed perspective for achieving illusion and can be applied to inverse-design problems in other classical wave systems.

This study proposes a quantitative framework to enhance curriculum coherence through the systematic alignment of Course Learning Outcomes (CLOs) and Program Learning Outcomes (PLOs), contributing to continuous improvement in outcome-based education. Grounded in accreditation standards such as ABET and NCAAA, the model introduces mathematical tools that map exercises, assessment questions, teaching units (TUs), and student assessment components (SACs) to CLOs and PLOs. This dual-layer approach-combining micro-level analysis of assessment elements with macro-level curriculum evaluation-enables detailed tracking of learning outcomes and helps identify misalignments between instructional delivery, assessment strategies, and program objectives. The framework incorporates alignment matrices, weighted relationships, and practical indicators to quantify coherence and evaluate course or program performance. Application of this model reveals gaps in outcome coverage and underscores the importance of realignment, especially when specific PLOs are underrepresented or CLOs are not adequately supported by assessments. The proposed model is practical, adaptable, and scalable, making it suitable for academic programs. Its systematic structure supports institutions in implementing evidence-based curriculum improvements and provides a reliable mechanism for aligning teaching practices with desired learning outcomes. Ultimately, this framework offers a valuable tool for closing the feedback loop between instructional design, assessment execution, and learning outcomes, thus promoting greater transparency, accountability, and educational effectiveness. Institutions that adopt this model can expect to strengthen their quality assurance processes and help ensure that students graduate with the competencies required by academic standards and professional expectations.