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Phase unwrapping is the reconstruction of a phase given its values mod 2$\pi$. Phase unwrapping is an important image processing technique used in synthetic aperture radar interferometry, in the context of height estimation and ground deformation. By formulating the phase unwrapping problem as a global minimization problem, $L^{p}$ norm techniques form the backbone of many established phase unwrapping algorithms. The $L^{0}$ norm is commonly agreed to produce the best unwrapping solutions, but the necessary brute-force calculations are infeasible for the phase unwrapping of SAR interferograms. Developments in variational quantum algorithms suggest computational advantages, when compared to classical approaches, for a multitude of applications. We therefore investigate the application of quantum algorithms to the phase unwrapping problem and introduce and derive an approximate $L^{0}$ norm optimization solver utilizing the quantum approximate optimisation algorithm. This hybrid algorithm uses classical nonconvex parameter optimization to produce optimal parameters for a quantum circuit encoding the $L^{0}$ phase unwrapping. Subsequent execution of this quantum circuit allows for an estimate of the solution of the phase unwrapping problem with advantages compared to brute force approaches. We validate our approach for small topographies, by demonstrating improved results when compared to established $L^{1}$ optimization.

We report the use of streaming data interfaces to perform fully online data processing for serial crystallography experiments, without storing intermediate data on disk. The system produces Bragg reflection intensity measurements suitable for scaling and merging, with a latency of less than 1 s per frame. Our system uses the CrystFEL software in combination with the ASAP::O data framework. In a series of user experiments at PETRA III, frames from a 16 megapixel Dectris EIGER2 X detector were searched for peaks, indexed and integrated at the maximum full-frame readout speed of 133 frames per second. The computational resources required depend on various factors, most significantly the fraction of non-blank frames (`hits'). The average single-thread processing time per frame was 242 ms for blank frames and 455 ms for hits, meaning that a single 96-core computing node was sufficient to keep up with the data, with ample headroom for unexpected throughput reductions. Further significant improvements are expected, for example by binning pixel intensities together to reduce the pixel count. We discuss the implications of real-time data processing on the `data deluge' problem from recent and future photon-science experiments, in particular on calibration requirements, computing access patterns and the need for the preservation of raw data.

Abstract The emergence and spread of antibiotic resistance represent a growing threat to public health. Of particular concern is the appearance of β-lactamases, which are capable to hydrolyze and inactivate the most important class of antibiotics, the β-lactams. Effective β-lactamase inhibitors and mechanistic insights into their action are central in overcoming this type of resistance, and in this context boronate-based β-lactamase inhibitors were just recently approved to treat multidrug-resistant bacteria. Using boric acid as a simplified inhibitor model, time-resolved serial crystallography was employed to obtain mechanistic insights into binding to the active site serine of β-lactamase CTX-M-14, identifying a reaction time frame of 80–100 ms. In a next step, the subsequent 1,2-diol boric ester formation with glycerol in the active site was monitored proceeding in a time frame of 100–150 ms. Furthermore, the displacement of the crucial anion in the active site of the β-lactamase was verified as an essential part of the binding mechanism of substrates and inhibitors. In total, 22 datasets of β-lactamase intermediate complexes with high spatial resolution of 1.40–2.04 Å and high temporal resolution range of 50–10,000 ms were obtained, allowing a detailed analysis of the studied processes. Mechanistic details captured here contribute to the understanding of molecular processes and their time frames in enzymatic reactions. Moreover, we could demonstrate that time-resolved crystallography can serve as an additional tool for identifying and investigating enzymatic reactions.

The growth of renewables in public energy networks requires suitable strategies to assess the stable operation of the respective power electronic devices, e.g., inverters. Different assessment methods can be performed with regard to the available knowledge and the assessment objective, e.g., a specific frequency range or the input signal characteristics that are typically classified into small-signal and large-signal disturbances. This paper addresses the limits of the measurement-based small-signal stability analysis in the harmonic frequency range of commercially available single-phase inverters for photovoltaic applications. The harmonic stability is analyzed, and the results for a sinusoidal background voltage and distorted background voltages are assessed based on measurements. The measurements prove that even in the harmonic frequency range, the harmonic stability analysis can only provide a sufficient but not a necessary condition in terms of the statement towards an instable operation.

Voltage notches are steady-state sub-cycle waveform distortions caused by the normal operation of line-commutated power converters, significantly impacting power quality in industrial low-voltage (LV) networks. Despite their common occurrence, research on this phenomenon is still incipient, and realistic simulation platforms are lacking. This paper introduces a detailed MATLAB (R2024a)/Simulink-based simulation platform that models a benchmark low-voltage industrial installation, including a six-pulse controlled rectifier, linear loads, and a capacitor bank for power factor correction. Systematic simulations are performed with the platform to examine the sensitivity of notch characteristics to key parameters within plausible ranges, such as short-circuit power at the point of common coupling, commutation reactance, firing angle, snubber circuits, and rated power of the rectifier. In addition, parameters such as the rated power of linear loads and the compensation power of the capacitor bank are examined. Other influencing parameters including background voltage unbalance and distortion are also modeled and considered. A comparative analysis with field measurements from German industrial LV networks validates the plausibility and suitability of the simulations. Building upon this platform, a Monte Carlo simulation approach is adopted to generate extensive datasets of realistic voltage notch waveforms by randomly varying these key parameters. A case study conducted under conditions typical of German LV networks demonstrates the applicability of the simulations. To support further research, the simulation platform and exemplary synthetic waveforms are provided alongside the paper, serving as a valuable tool for testing and designing strategies for analysis, detection, and monitoring of voltage notches.

Abstract This paper presents a study on the temperature dependent photo-elastic coefficient in single-crystal silicon with (100) and (110) orientations at a wavelength of 1550 nm. The measurement of the photo-elastic coefficient was performed using a polarimetric scheme across a wide temperature range from 5 to 300 K. The experimental setup employed high-sensitivity techniques and incorporated automatic beam path correction, ensuring precise and accurate determination of the coefficient’s values. The results show excellent agreement with previous measurements at room temperature, specifically yielding a value of $$dn/d\sigma = -2.463 \times 10^{-11}$$ d n / d σ = - 2.463 × 10 - 11 1/Pa for the (100) orientation. Interestingly, there is a significant difference in photo-elasticity between the different crystal orientations of approximately $$50\%$$ 50 % . The photo-elastic coefficient’s absolute value increases by approximately 40% with decreasing temperature down to 5 K. These findings provide valuable insights into the photo-elastic properties of silicon and its behavior under varying mechanical stress, particularly relevant for optomechanical precision experiments like cryogenic gravitational wave detectors and microscale optomechanical quantum sensors.

With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image analysis heavily relies on manufacturer-supplied software, which often demands extensive training and lacks automation capabilities for handling diverse datasets. A critical challenge arises if the fluorophores employed exhibit low brightness and a low signal-to-noise ratio (SNR). Consequently, manual intervention may become a necessity, introducing variability in the analysis outcomes even for identical samples when analyzed by different users. This leads to the incorporation of blinded analysis, which ensures that the outcome is free from user bias to a certain extent but is extremely time-consuming. To overcome these issues, we developed a tool called DL-SCAN that automatically segments and analyzes fluorophore-stained regions of interest such as cell bodies in fluorescence microscopy images using deep learning. We demonstrate the program’s ability to automate cell identification and study cellular ion dynamics using synthetic image stacks with varying SNR. This is followed by its application to experimental Na+ and Ca2+ imaging data from neurons and astrocytes in mouse brain tissue slices exposed to transient chemical ischemia. The results from DL-SCAN are consistent, reproducible, and free from user bias, allowing efficient and rapid analysis of experimental data in an objective manner. The open-source nature of the tool also provides room for modification and extension to analyze other forms of microscopy images specific to the dynamics of different ions in other cell types.

The growth of renewables in the energy sector, e.g., in public low-voltage networks, leads to an increasing share of installed power electronic devices, e.g., inverters for photovoltaic applications. To rely on these devices, suitable analyses have to be performed. This includes studies of the device stability in the harmonic frequency range, i.e., above 50 Hz up to 2 kHz. State-of-the-art time-domain studies for harmonic stability analyses require detailed knowledge about the inverter design. Black-box studies must identify the inverter characteristics in the laboratory, which can differ depending on specific operating points, i.e., specific operating powers. This study analyzes the operating-point dependency of inverters on the critical inductance values of the network impedance, e.g., the inductances at which the inverter is expected to become unstable. Measurements are performed for three operating powers of an unknown, commercially available single-phase inverter to validate the critical inductances. Two further commercially available inverters and four simulative implementations are analyzed as well with regard to the critical inductance and the critical frequency. The results demonstrate the importance of considering a representative range of operating powers of the inverter for the small-signal stability analysis.

This paper explores the potential of some remarkable power theories derived from Fryze’s approach to assessing waveform distortion contributions. The analysis is limited to a simplified system composed of one load and one voltage source connected by a point of common coupling. Finally, some keys to assess are proposed for two types of systems: strong networks (traditional distribution systems) and weak networks (islanded microgrids).

Meta-mirrors may help realize ultra-stable lasers for high-precision metrology, for applications like gravitational wave detection and quantum optics. The authors experimentally realize a new type of microstructured meta-mirror and use it to form a Fabry-Perot cavity with low thermal noise and a high finesse of 12,000.

Abstract This paper offers a systematic literature review of real-time detection and classification of Power Quality Disturbances (PQDs). A particular focus is given to voltage sags and notches, as voltage sags cause huge economic losses while research on voltage notches is still very incipient. A systematic method based on scientometrics, text similarity and the analytic hierarchy process is proposed to structure the review and select the most relevant literature. A bibliometric analysis is then performed on the bibliographic data of the literature to identify relevant statistics such as the evolution of publications over time, top publishing countries, and the distribution by relevant topics. A set of articles is subsequently selected to be critically analyzed. The critical review is structured in steps for real-time detection and classification of PQDs, namely, input data preparation, preprocessing, transformation, feature extraction, feature selection, detection, classification, and characterization. Aspects associated with the type of disturbance(s) addressed in the literature are also explored throughout the review, including the perspectives of those studies aimed at multiple PQDs, or specifically focused on voltage sags or voltage notches. The real-time performance of the reviewed tools is also examined. Finally, unsolved issues are discussed, and prospects are highlighted.

This article presents the results of the immunity evaluation of mass-market electrical appliances subjected to harmonic and interharmonic distortion of the supply voltage. Therefore, the immunity of twenty selected single-phase electrical appliances is evaluated within a comprehensive framework that considers perceptible malfunctions and long-term adverse impacts. Furthermore, a specially designed test procedure is employed to optimize the characterization of appliances with variable operating states and to ensure the reproducibility of results. In light of that, the feasibility of increasing compatibility levels for harmonics and interharmonics is discussed. The results shall serve as input for the ongoing discussion about appropriate compatibility levels in low voltage networks acceptable to all stakeholders.

Serial crystallography at conventional synchrotron light sources (SSX) offers the possibility to routinely collect data at room temperature using micrometre-sized crystals of biological macromolecules. However, SSX data collection is not yet as routine and currently takes significantly longer than the standard rotation series cryo-crystallography. Thus, its use for high-throughput approaches, such as fragment-based drug screening, where the possibility to measure at physiological temperatures would be a great benefit, is impaired. On the way to high-throughput SSX using a conveyor belt based sample delivery system – the CFEL TapeDrive – with three different proteins of biological relevance (Klebsiella pneumoniae CTX-M-14 β-lactamase, Nectria haematococca xylanase GH11 and Aspergillus flavus urate oxidase), it is shown here that complete datasets can be collected in less than a minute and only minimal amounts of sample are required.

Coordination polymer (CP) glasses have recently emerged as a new glass state. Given the young state of the field, the discovery of concepts that guide the synthesis of CP glasses with targeted thermal and macroscopic properties is at the center of ongoing research. In our work, we draw inspiration from research on inorganic glasses, investigating the impact of Li(C2N3) as a modifier on the thermal properties of the new molecular perovskite [(C3H7)3N(C4H9)]Mn(C2N3)3 (with [C2N3]− = dicyanamide, DCA). We derive the phase diagram and show that Li(C2N3) and [(C3H7)3N(C4H9)]Mn(C2N3)3 form a eutectic mixture, in which the melting temperature is decreased by 30 K. Additionally, for the eutectic mixture at xLiDCA ≈ 0.4, a CP glass forms under slow cooling, opening interesting pathways for scalable synthesis routes of CP glasses. Given the virtually unlimited parameter space of hybrid modifiers, they will play a major role in the future to alter the glass’ properties where the availability of rigorously derived phase diagrams will be important to identify material class overarching trends.

Serial crystallography is a rapidly developing method for the determination of the structure of biomolecules at room temperature at near-atomic resolution from an ensemble of small crystals. Numerous advances in detectors, data analysis pipelines, sample delivery methods, and crystallization protocols expand the scope of structural biology to understand the fundamental processes that take place in living cells. Many experimental strategies for serial crystallography are in use, depending on the type and sizes of the crystals or other needs of the experiment. Such strategies should ideally minimize the wastage of samples or beamtime without compromising experimental goals. This paper proposes a way to optimize beamtime utilization in serial crystallography experiments that use fixed-target sample delivery methods, such as chips. The strategy involves two key steps. Firstly, a fast raster scan of the chip is performed to determine the positions of the crystals based on their diffraction. Subsequently, a rotational series is collected at each identified crystal position, covering a narrow range of chip orientations. This approach enables the exclusion of empty positions during data acquisition, resulting in significant savings in beam time utilization and a reduced volume of measured data.

In recent years, operation and control strategies in distribution systems have changed due to the increase in the connection of distributed generation sources (DGs). Small local networks with electricity users and DGs are known as microgrids. These microgrids can operate independently (islanded) or in collaboration (interconnected) with the main network or other microgrids. Some advantages of interconnected microgrids include the reduction of losses, an increase in reliability, and decentralized operation under fault conditions. Nevertheless, when a microgrid operates in islanded mode, its electrical characteristics change and, consequently, the severity of power quality disturbances can increase, as well as their negative impact on electronic devices (loads and DG devices). This paper presents a comprehensive literature review of existing studies on power quality disturbances in islanded microgrids and identifies the most relevant needs for future research on this topic. Detailed information is analyzed to compare the differences between disturbance levels in both interconnected and islanded microgrids. In the case of harmonic disturbances, the impact of the different microgrid configurations is also analyzed.

Advances in power electronics, increasing share of renewables in the energy system and e-mobility cause an increase of disturbances in the frequency range 2-150 kHz, also known as supraharmonics. A rigorous, credible and agreed measurement framework is essential to evaluate electromagnetic compatibility (EMC) in this frequency range. While a normative method exists for measuring equipment emission in the laboratory, no normative method exists yet for the measurement of supraharmonic disturbance levels in the grid. The aim of this research is a detailed comparison of potential measurement methods derived from existing standards IEC 61000-4-7, IEC 61000-4-30, CISPR 16-1-1 and a critical assessment of their suitability for disturbance measurements in grid applications. Based on a comprehensive set of synthetic signals and real measurements from laboratory and field, this article studies the ability of the methods to assess the typical characteristics of supraharmonic emission with relevance to EMC coordination. It presents the benefits and drawbacks of the existing measurement methods and discusses the suitability of possible modifications for grid compliance assessment. The results and recommendations intend to be an input for the present activities of IEC SC 77A WG 9 to define a normative method for the measurement of supraharmonic disturbance levels to be included in the next edition of IEC 61000-4-30.

Unravelling the interaction of biological macromolecules with ligands and substrates at high spatial and temporal resolution remains a major challenge in structural biology. The development of serial crystallography methods at X-ray free-electron lasers and subsequently at synchrotron light sources allows new approaches to tackle this challenge. Here, a new polyimide tape drive designed for mix-and-diffuse serial crystallography experiments is reported. The structure of lysozyme bound by the competitive inhibitor chitotriose was determined using this device in combination with microfluidic mixers. The electron densities obtained from mixing times of 2 and 50 s show clear binding of chitotriose to the enzyme at a high level of detail. The success of this approach shows the potential for high-throughput drug screening and even structural enzymology on short timescales at bright synchrotron light sources.

This paper introduces a new black-box approach for time domain modeling of commercially available single-phase photovoltaic (PV) inverters in low voltage networks. An artificial neural network is used as a nonlinear autoregressive exogenous model to represent the steady state behavior as well as dynamic changes of the PV inverter in the frequency range up to 2 kHz. The data for the training and the validation are generated by laboratory measurements of a commercially available inverter for low power applications, i.e., 4.6 kW. The state of the art modeling approaches are explained and the constraints are addressed. The appropriate set of data for training is proposed and the results show the suitability of the trained network as a black-box model in time domain. Such models are required, i.e., for dynamic simulations since they are able to represent the transition between two steady states, which is not possible with classical frequency-domain models (i.e., Norton models). The demonstrated results show that the trained model is able to represent the transition between two steady states and furthermore reflect the frequency coupling characteristic of the grid-side current.

Power quality (PQ) is an increasing concern in the distribution networks of modern industrialized countries. The PQ monitoring activities of distribution system operators (DSO), and consequently the amount of PQ measurement data, continuously increase, and consequently new and automated tools are required for efficient PQ analysis. Time characteristics of PQ parameters (e.g., harmonics) usually show characteristic daily and weekly cycles, mainly caused by the usage behaviour of electric devices. In this paper, methods are proposed for the classification of harmonic emission profiles for typical consumer configurations in public low voltage (LV) networks using a binary decision tree in combination with support vector machines. The performance of the classification was evaluated based on 40 different measurement sites in German public LV grids. This method can support network operators in the identification of consumer configurations and the early detection of fundamental changes in harmonic emission behaviour. This enables, for example, assistance in resolving customer complaints or supporting network planning by managing PQ levels using typical harmonic emission profiles.

In the last decade, mainly due to political incentives towards energy efficiency, the share of lamps with power electronic interfaces, like Compact Fluorescent Lamps (CFL) and Light Emitting Diode (LED) lamps, has significantly increased in the residential sector. Their massive use might have a substantial impact on harmonic currents and, consequently, on the current flowing in the neutral conductor. This paper analyzes the impact of modern energy-efficient lighting technologies on the neutral conductor current by using a synthetic Low Voltage residential grid. Different load scenarios reflecting the transition from incandescent lamps, via CFL, to LED lamps are compared concerning the neutral conductor current at different points in the network. The inherent randomness related to the use of lighting devices by each residential customer is considered employing a Monte Carlo simulation. Obtained results show that the use of CFL has a greater impact on the neutral conductor current of Low Voltage (LV) residential grids and that, with increasing use of LED lamps, a decreasing impact can be expected in the future.

Current and voltage harmonic levels in LV grids depend not only on the harmonic emission of non-linear loads, but also on the characteristics of the grid and the voltage distortion of the upstream grid. Based on several measurements, it was found that Colombia and Germany have considerable differences in the current harmonic emission of electronic devices and voltage distortion in the LV-grids. These differences are the result of different regulation methodologies and the characteristics of the grid. Detail measurement campaigns are needed in both countries in order to verify the voltage and current harmonic levels, and to analyze the network efficiency and hosting capacity in terms of harmonics.

Component-based harmonic studies in public Low Voltage grids require realistic models of individual loads as well as their typical penetration ratios. As fundamental basis for the development of comprehensive models for residential users, this paper identifies the most commonly used household loads in Colombia. The loads are classified according to their Power Factor Correction (PFC) circuit topology in no-PFC, passive-PFC and active-PFC devices, and a comprehensive set of loads is selected. Their behavior in terms of harmonic emission is characterized by intensive lab measurements with systematically varied supply voltage distortion. Based on several indices, the suitability of different frequency-domain modeling approaches (e.g. constant current source, decoupled and coupled Norton models) is assessed.

Smart Grid paradigm promotes advanced load monitoring applications to support demand side management and energy savings. Recently, considerable attention has been paid to Non-Intrusive Load Monitoring to estimate the individual operation and power consumption of the residential appliances, from single point electrical measurements. This approach takes advantage of signal processing in order to reduce the hardware effort associated to systems with multiple dedicated sensors. Discriminative characteristics of the appliances, namely load signatures, could be extracted from the transient or steady state electrical signals. In this paper the effect of impact factors that can affect the steady state load signatures under realistic conditions are investigated: the voltage supply distortion, the network impedance and the sampling frequency of the metering equipment. For this purpose, electrical measurements of several residential appliances were acquired and processed to obtain some indices in the time domain. Results include the comparison of distinct scenarios, and the evaluation of the suitability and discrimination capacity of the steady state information.

Los dispositivos electrónicos son cargas no lineales que inyect an armónicos a las redes de baja tensión. Existen varios estudi os que analizan el impacto de estos d ispositivos sobre la red basados en difere ntes tipos de modelos, siendo el más común la fuente de corrien te. Mediciones han demostrado que la emisión de armónicos de dispos itivos electrónicos depende de la topología del circuito y la d istorsión de la señal de tensión. Este artículo cuantifica el impacto de la distorsión de la señal de ten sión sobre la emisión de armóni cos de diferentes dispositivos y grupos de ellos. Primero se desarrollan modelos eléctricos de las topologías más comunes. Luego se analiza el efecto individual y combinado de las armónicos de tensión sobre la em isión de armónicos de los dispo sitivos seleccionados. Finalmente se analiza el impacto de la d istorsión de tensión sobre un grupo de dispositivos y se evalúa la precisión de la fuente de corriente.

Optical sensors, such as fiber Bragg gratings, offer advantages compared to other sensors in many technological fields due to their outstanding characteristics. This sensor technology is currently transferred to polymer waveguides that provide the potential for cost-effective, easy, and flexible manufacturing of planar structures. While sensor production itself, in the majority of cases, is performed by means of phase mask technique, which is limited in terms of its degrees of freedom, other inscription techniques enable the manufacture of more adaptable sensor elements for a wider range of applications. In this article, we demonstrate the point-by-point femtosecond laser direct inscription method for the processing of polymer Bragg gratings into waveguides of the epoxy-based negative photoresist material EpoCore for a wavelength range around 850 nm. By characterizing the obtained grating back-reflection of the produced sensing element, we determined the sensitivity for the state variables temperature, humidity, and strain to be 45 pm/K, 19 pm/%, and 0.26 pm/µε, respectively. Individual and more complex grating structures can be developed from this information, thus opening new fields of utilization.

A new approach for collecting data from many hundreds of thousands of microcrystals using X-ray pulses from a free-electron laser has recently been developed. Referred to as serial crystallography, diffraction patterns are recorded at a constant rate as a suspension of protein crystals flows across the path of an X-ray beam. Events that by chance contain single-crystal diffraction patterns are retained, then indexed and merged to form a three-dimensional set of reflection intensities for structure determination. This approach relies upon several innovations: an intense X-ray beam; a fast detector system; a means to rapidly flow a suspension of crystals across the X-ray beam; and the computational infrastructure to process the large volume of data. Originally conceived for radiation-damage-free measurements with ultrafast X-ray pulses, the same methods can be employed with synchrotron radiation. As in powder diffraction, the averaging of thousands of observations per Bragg peak may improve the ratio of signal to noise of low-dose exposures. Here, it is shown that this paradigm can be implemented for room-temperature data collection using synchrotron radiation and exposure times of less than 3 ms. Using lysozyme microcrystals as a model system, over 40 000 single-crystal diffraction patterns were obtained and merged to produce a structural model that could be refined to 2.1 Å resolution. The resulting electron density is in excellent agreement with that obtained using standard X-ray data collection techniques. With further improvements the method is well suited for even shorter exposures at future and upgraded synchrotron radiation facilities that may deliver beams with 1000 times higher brightness than they currently produce.

We present the manufacturing and utilization of an all-polymer arrayed waveguide grating (AWG) interacting with a fiber Bragg grating (FBG) for battery status monitoring on the example of a 40 Ah lithium-ion battery. The AWG is the main component of a novel low-cost approach for an optical interrogation unit to track the FBG peak wavelength by means of intensity changes monitored by a CMOS linear image sensor, read out by a Teensy 3.2 microcontroller. The AWG was manufactured using laser direct lithography as an all-polymer-system, whereas the FBG was produced by point-by-point femtosecond laser writing. Using this system, we continuously monitored the strain variation of a battery cell during low rate charge and discharge cycles over one month under constant climate conditions and compared the results to parallel readings of an optical spectrum analyzer with special attention to the influence of the relative air humidity. We found our low-cost interrogation unit is capable of precisely and reliably capturing the typical strain variation of a high energy pouch cell during cycling with a resolution of 1 pm and shows a humidity sensitivity of −12.8 pm per %RH.

In this scientific publication, a new sensor approach for status monitoring, such as state of charge and state of health, of lithium ion batteries by using special Bragg gratings inscribed into standard optical glass fibers is presented. In addition to well-known core gratings, embedded into the anode of 5 Ah lithium ion pouch cells as a strain monitoring unit, the manufacturing of a surface cladding waveguide Bragg grating sensor incorporated into the cell’s separator, that is sensitive to changes of the refractive index of the surrounding medium, is demonstrated. On the basis of the experiments carried out, characteristics of the cell behavior during standard cyclization and recognizable marks in subsequent post-mortem analyses of the cell components are shown. No negative influence on the cell performance due to the integrated sensors have been observed; however, the results show a clear correlation between fading cell capacity and changes of the interior optical signals. Additionally, with the novel photonic sensor, variations in the electrolyte characteristics are determinable as the refractive index of the solution changes at different molar compositions. Furthermore, with the manufactured battery cells, abuse tests by overcharging were conducted, and it was thereby demonstrated how internal battery sensors can derive additional information beyond conventional battery management systems to feasibly prevent catastrophic cell failures. The result of the research work is an early stage photonic sensor that combines chemical, mechanical and thermal information from inside the cell for an enhanced battery status analysis.