arXiv subjects

Christoph J. Brabec

Publications and source records attributed to Christoph J. Brabec.

At least 19 recordsLinked to original sources

arXiv2026

Mobility-lifetime relation links photodegradation in spin-coated and gravure-printed organic solar cells

The degradation mechanisms of organic solar cells (OSCs) have been studied primarily in spin-coated, laboratory-scale devices, whereas scalable processing modifies the device architecture, active-layer morphology, and underlying charge-transport and recombination properties. Whether these changes also alter how solar cells degrade remains unclear. Here, we compare spin-coated and fully roll-to-roll-compatible gravure-printed PM6:Y12 solar cells during $\sim$1000 h of continuous illumination. Despite distinct initial properties and degradation signatures, the loss of power-conversion efficiency systematically follows the mobility-lifetime product $μτ$. Remarkably, ageing of the printed devices increases the recombination lifetime while strongly reducing charge-carrier mobility, showing that a longer lifetime alone does not imply improved device performance. The mobility reduction is accompanied by decreased PM6 lamellar order, whereas the additional open-circuit voltage loss originates predominantly from increased non-radiative recombination. Dark recovery further reveals a metastable contribution specific to the printed architecture. These results identify the mobility-lifetime product as a unifying physical descriptor for photodegradation, linking ageing-induced microscopic changes to macroscopic performance loss across spin-coated and scalable printed OSCs.

cond-mat.mtrl-sci↗

arXiv2026

3D Electron Diffraction -- The Missing Slice for a Complete Nanoscale Analysis of Organic Solar Cells in TEM

Optimizing the performance of organic solar cells (OSCs) hinges on a comprehensive understanding of their nanostructures, yet traditional characterization methods often fall short, delivering incomplete structural snapshots. We introduce elastically filtered 3D Electron Diffraction (3D ED) as a ground-breaking technique bridging full reciprocal- and real-space structural analysis within a single transmission electron microscope (TEM). Using solvent-vapor annealed DRCN5T:PC71BM, 3D ED reproduces key structural parameters from GIWAXS including lattice spacings, coherence lengths, and mosaicity, while uniquely delivering true in-plane access and direct registration with high-resolution imaging, diffraction imaging and nano-spectroscopy on the same sample. A low-dose, distributed tilt strategy plus energy filtering yields high signal-to-background below damage thresholds. Extension to a second archetypal blend (P3HT:PC71BM; annealing evolution) demonstrates generality. Our findings underscore the transformative potential of 3D ED, particularly in analysing beam-sensitive organic thin films. This paves the way for new avenues in advanced correlative structural characterization of OSCs and holds potential for application to a multitude of other nanostructured materials.

cond-mat.mtrl-sci↗

arXiv2025

Understanding the effect of drying time in process-structure-performance relationships for PM6-Y6 organic solar cells

Making solution-cast organic solar cells industrially available generally comes at the cost of significant performance losses compared to device prototypes manufactured under laboratory conditions. Adjusting solvent evaporation kinetics is postulated to recover efficiency. Yet, a comprehensive characterization of their effect, independently of other property-defining parameters, is lacking. Thus, the present objective is to isolate the influence of the solvent drying rate on solution-deposited organic active layer nanomorphologies and performances. To this end, a specially designed gas quenching technique is employed to fabricate PM6:Y6 donor-acceptor films under systematic variations of evaporation conditions. Using an extensive investigation protocol that combines insights from numerical simulations and experimental measurements, process-structure-performance relationships are unraveled. It is found that higher drying rates imply finer and more dispersed nanomorphologies with increased fractions of amorphous material. This enhances electric charge generation, thereby improving short-circuit current density and overall cell performance. The open-circuit voltage is also boosted under accelerated evaporation due to changes in the aggregation mode of the Y6 small molecule that induce higher effective bandgaps. The results demonstrate that the developed gas-quenching technique is a valuable tool for optimizing the performance of upscaled organic photovoltaics, as it is readily compatible with high-throughput equipment, such as roll-to-roll coating machines.

cond-mat.mtrl-sci↗

arXiv2025

A Simultaneous Synergistic Protection Mechanism in Hybrid Perovskite-Organic Multi-junctions Enables Long-Term Stable and Efficient Tandem Solar Cells

Perovskite-organic tandem solar cells (P-O TSCs) hold great promise for next-generation thin-film photovoltaics, with steadily improving power conversion efficiency (PCE). However, the development of optimal interconnecting layers (ICLs) remains one major challenge for further efficiency gains, and progress in understanding the improved long-term stability of P-O tandem configuration has been lagging. In this study, we experimentally investigate the enhanced stability of p-i-n P-O TSCs employing a simplified C60/atomic-layer-deposition (ALD) SnOx/PEDOT: PSS ICL without an additional charge recombination layer (CRL), which achieve an averaged efficiency of 25.12% and a hero efficiency of 25.5%. Our finding discovers that the recrystallization of C60, a widely used electron transport layer in perovskite photovoltaics, leads to the formation of grain boundaries during operation, which act as migration channels for the interdiffusion of halide and Ag ions. Critically, we demonstrate for the first time that the tandem device architecture, incorporating organic semiconductor layers, effectively suppresses the bi-directional ion diffusion and mitigates electrode corrosion. Thus, the P-O TSC establishes a mutual protection system: the organic layers stabilize the perovskite sub-cell by suppressing ion diffusion-induced degradation, and the perovskite layer shields the organic sub-cell from spectrally induced degradation. The simultaneous synergistic protection mechanism enables P-O TSCs to achieve exceptional long-term operational stability, retaining over 91% of their initial efficiency after 1000 hours of continuous metal-halide lamp illumination, and to exhibit minimal fatigue after 86 cycles (2067 hours) of long-term diurnal (12/12-hour) testing. These results demonstrate that tandem cells significantly outperform their single-junction counterparts in both efficiency and stability.

physics.app-ph↗

arXiv2025

Effect of particle and substrate wettability on evaporation-driven assembly of colloidal monolayers

Assembled monolayers of colloidal particles are crucial for various applications, including opto-electronics, surface engineering, as well as light harvesting, and catalysis. A common approach for self-assembly is the drying of a colloidal suspension film on a solid substrate using technologies such as printing and coating. However, this approach often presents challenges such as low surface coverage, stacking faults, and the formation of multiple layers. We numerically investigate the influence of substrate and particle wettability on the deposited pattern. Higher substrate wettability results in a monolayer with a hexagonal arrangement of deposited particles on the substrate. Conversely, lower substrate wettability leads to droplet formation after the film ruptures, leading to the formation of particle clusters. Furthermore, we reveal that higher particle wettability can mitigate the impact of the substrate wettability and facilitate the formation of highly ordered monolayers. We propose theoretical models predicting the surface coverage fraction dependent on particle volume fraction, initial film thickness, particle radius, as well as substrate and particle wettability, and validate these models with simulations. Our findings provide valuable insights for optimizing the deposition process in the creation of assembled monolayers of colloidal particles.

cond-mat.soft↗

arXiv2024

Discovering one molecule out of a million: inverse design of molecular hole transporting semiconductors tailored for perovskite solar cells

The inverse design of tailored organic molecules for specific optoelectronic devices of high complexity holds an enormous potential, but has not yet been realized1,2. The complexity and literally infinite diversity of conjugated molecular structures present both, an unprecedented opportunity for technological breakthroughs as well as an unseen optimization challenge. Current models rely on big data which do not exist for specialized research films. However, a hybrid computational and high throughput experimental screening workflow allowed us to train predictive models with as little as 149 molecules. We demonstrate a unique closed-loop workflow combining high throughput synthesis and Bayesian optimization that discovers new hole transporting materials with tailored properties for solar cell applications. A series of high-performance molecules were identified from minimal suggestions, achieving up to 26.23% (certified 25.88%) power conversion efficiency in perovskite solar cells. Our work paves the way for rapid, informed discovery in vast molecular libraries, revolutionizing material selection for complex devices. We believe that our approach can be generalized to other emerging fields and indeed accelerate the development of optoelectronic semiconductor devices in general.

cond-mat.mtrl-sci↗

arXiv2024

Fully printed flexible perovskite solar modules with improved energy alignment by tin oxide surface modification

Fully printed flexible perovskite solar cells (f-PSCs) show great potential for the commercialization of perovskite photovoltaics owing to their compatibility with high-throughput roll-to-roll (R2R) production. However, the challenge remains in the deficiency in controlling interfacial recombination losses of the functional layer, causing remarkable loss of power conversion efficiency (PCE) in industrial production. Here, a fullerene-substituted alkylphosphonic acid dipole layer is introduced between the R2R-printed tin oxide electron transport layer and the perovskite active layer to reduce the energetic barrier and to suppress surface recombination at the buried interface. The resulting f-PSCs exhibit a PCE of 17.0% with negligible hysteresis, retain 95% of their initial PCE over 3000 bending cycles and achieve a T95 lifetime of 1200 h under 1 sun and 65 degreeC in nitrogen atmosphere. Moreover, the fully printed flexible perovskite solar mini-modules (f-PSMs) with a 20.25 cm2 aperture area achieve a PCE of 11.6%. The encapsulated f-PSMs retain 90% of their initial PCE after 500 h damp-heat testing at 65 degreeC and 85% relative humidity (ISOS-D3). This work marks an important progress toward the realization of efficient and stable flexible perovskite photovoltaics for commercialization.

cond-mat.mtrl-sci↗

arXiv2024

Precise Control of Process Parameters for >23% Efficiency Perovskite Solar Cells in Ambient Air Using an Automated Device Acceleration Platform

Achieving high-performance perovskite photovoltaics, especially in ambient air relies heavily on optimizing process parameters. However, traditional manual methods often struggle to effectively control the key variables. This inherent challenge requires a paradigm shift toward automated platforms capable of precise and reproducible experiments. Herein, we use a fully automated device acceleration platform (DAP) to optimize the process parameters for preparing full perovskite devices using a two-step method in ambient air. Eight process parameters that have the potential to significantly influence device performance are systematically optimized. Specifically, we delve into the impact of the dispense speed of organic ammonium halide, a parameter that is difficult to control manually, on both perovskite film and device performance. Through the targeted design of experiments, we reveal that the dispense speed significantly affects device performance primarily by adjusting the residual PbI2 content in the films. We find that moderate dispense speeds, e.g., 50 μl/s, contribute to top-performance devices. Conversely, too fast or too slow speeds result in devices with relatively poorer performance and lower reproducibility. The optimized parameter set enables us to establish a Standard Operation Procedure (SOP) for additive-free perovskite processing under ambient conditions, which yield devices with efficiencies surpassing 23%, satisfactory reproducibility, and state-of-the-art photo-thermal stability. This research underscores the importance of understanding the causality of process parameters in enhancing perovskite photovoltaic performance. Furthermore, our study highlights the pivotal role of automated platforms in discovering innovative workflows and accelerating the development of high-performing perovskite photovoltaic technologies.

physics.app-ph↗

arXiv2024

All Inkjet-printed Organic Solar Cells on 3D Objects

Drop-on-demand inkjet printing is a promising and commercially relevant technology for producing organic electronic devices of arbitrary shape on a wide variety of different substrates. In this work we transfer the inkjet printing process of organic photovoltaic devices from 2D to 3D substrates, using a 5-axis robot system equipped with a multi nozzle inkjet printing unit. We present a ready-to-use 3D printing system for industrial application, using a 5-axis motion system controlled by commercial 3D motion software, combined with a commonly used multi-nozzle inkjet print head controlled by the corresponding printing software. The very first time inkjet-printed solar cells on glass/ITO with power conversion efficiencies (PCE) of up to 7% are realized on a 3D object with surfaces tilted by angles of up to 60° against the horizontal direction. Undesired ink flow during deposition of the inkjet-printed layers was avoided by proper ink formulation. In order to be able to print organic (opto-)electronic devices also on substrates without sputtered indium tin oxide bottom electrode, the bottom electrode was inkjet-printed from silver nanoparticle (AgNP) ink, resulting in the first all inkjet-printed (i.e., including bottom electrode) solar cell on a 3D object ever with a record PCE of 2.5%. This work paves the way for functionalizing even complex objects, such as cars, mobile phones, or Internet of Things (IoT) applications with inkjet-printed (opto-)electronic devices.

physics.app-ph↗

arXiv2024

On the theoretical framework for meniscus-guided manufacturing of large-area OPV modules

For the manufacturing of thin films of solution-processable organic semiconductors, e.g. for organic photovoltaics (OPV), meniscus guided-coating techniques are the method of choice for large-scale industrial applications. However, the process requires an in-depth understanding of the respective fluid dynamics to control the resulting film thickness. In this article, we derive an analytical expression to describe the layer thickness of coatings manufactured with a trapezoidal-shaped applicator as a function of various fluid and process parameters. The analytical calculations are compared with results from computational fluid dynamics (CFD) simulations and experimental data for an industrially relevant OPV active material system. The analytical calculations are compared with results from computational fluid dynamics (CFD) simulations and experimental data for an industrially relevant OPV active material system. The good agreement of all three approaches demonstrates the potential of the analytical and simulative methods to reduce time- and resource-consuming experiments to a minimum. Furthermore, our theoretical model can be used to enhance the homogeneity of large-area coatings by means of an acceleration profile of the applicator that can compensate the liquid loss during the coating process. The respective analytical expression is validated by simulated and experimentally obtained data for long-distance coatings. Finally, this approach is used to fabricate a large-area OPV module with new world record efficiency.

physics.comp-ph↗

arXiv2023

Beginner's guide to visual analysis of perovskite and organic solar cell current density-voltage characteristics

The current density-voltage characteristic (JV) is a critical tool for understanding the behaviour of solar cells. In this article, we present an overview of the key aspects of JV analysis and introduce a user-friendly flowchart that facilitates the swift identification of the most probable limiting process in a solar cell, based mainly on the outcomes of light-intensity-dependent JV measurements. The flowchart was developed through extensive drift-diffusion simulations and a rigorous review of the literature, with a specific focus on perovskite and organic solar cells. Moreover, the flowchart proposes supplementary experiments that can be conducted to obtain a more precise prediction of the primary performance losses. It therefore serves as an optimal starting point to analyse performance losses of solar cells.

cond-mat.mtrl-sci↗

arXiv2023

Guidelines for Material Design in Semitransparent Organic Solar Cells

Organic solar cells (OSCs) are uniquely suited for semitransparent applications due to their adjustable absorption spectrum. However, most high-performance semitransparent cells reported to date are based on materials that have shown high power conversion efficiency for opaque devices. We therefore present a model to assess the optimum efficiency and transparency for a specific donor and acceptor band gap. The absorption characteristics of both donor and acceptor are modeled with spectral data of typical absorber materials from the literature which are adjusted to achieve the desired band gap value. The results show three distinct regions of high light utilization efficiency if the photopic curve is employed as a weighting function (corresponding to window applications), and a broad maximum for the plant action spectrum as a weighting function (corresponding to greenhouse applications). When comparing these findings to reported experimental values, it is evident that the band gaps of the materials used for the experimental studies do not correspond to the maxima identified by our simulation model. The analysis of the energy levels of molecules recorded in the literature confirms that all band gaps and therefore all LUE maxima are chemically feasible so that the performance of semitransparent OSCs can be further improved by designing materials with optimized absorption spectra.

cond-mat.mtrl-sci↗

arXiv2023

Matching the photocurrent of perovskite/organic tandem solar modules by varying the cell width

Photocurrent matching in conventional monolithic tandem solar cells is achieved by choosing semiconductors with complementary absorption spectra and by carefully adjusting the optical properties of the complete top and bottom stacks. However, for thin film photovoltaic technologies at the module level, another design variable significantly alleviates the task of photocurrent matching, namely the cell width, whose modification can be readily realized by the adjustment of the module layout. Herein we demonstrate this concept at the experimental level for the first time for a 2T-mechanically stacked perovskite (FAPbBr3)/organic (PM6:Y6:PCBM) tandem mini-module, an unprecedented approach for these emergent photovoltaic technologies fabricated in an independent manner. An excellent Isc matching is achieved by tuning the cell widths of the perovskite and organic modules to 7.22 mm (PCEPVKT-mod= 6.69%) and 3.19 mm (PCEOPV-mod= 12.46%), respectively, leading to a champion efficiency of 14.94% for the tandem module interconnected in series with an aperture area of 20.25 cm2. Rather than demonstrating high efficiencies at the level of small lab cells, our successful experimental proof-of-concept at the module level proves to be particularly useful to couple devices with non-complementary semiconductors, either in series or in parallel electrical connection, hence overcoming the limitations imposed by the monolithic structure.

cond-mat.mtrl-sci↗

arXiv2023

Machine learning for ultra high throughput screening of organic solar cells: Solving the needle in the hay stack problem

Over the last two decades the organic solar cell community has synthesised tens of thousands of novel polymers and small molecules in the search for an optimum light harvesting material. These materials were often crudely evaluated simply by measuring the current voltage curves in the light to obtain power conversion efficiencies (PCEs). Materials with low PCEs were quickly disregarded in the search for higher efficiencies. More complex measurements such as frequency/time domain characterisation that could explain why the material performed as it did were often not performed as they were too time consuming/complex. This limited feedback forced the field to advance using a more or less random walk of material development and has significantly slowed progress. Herein, we present a simple technique based on machine learning that can quickly and accurately extract recombination time constants and charge carrier mobilities as a function of light intensity simply from light/dark JV curves alone. This technique reduces the time to fully analyse a working cell from weeks to seconds and opens up the possibility of not only fully characterising new devices as they are fabricated, but also data mining historical data sets for promising materials the community has over looked.

physics.app-ph↗

arXiv2023

Bypassing the single junction limit with advanced photovoltaic architectures

In single-junction photovoltaic (PV) devices, the maximum achievable power conversion efficiency (PCE) is mainly limited by thermalization and transmission losses, because polychromatic solar irradiation cannot be matched to a single bandgap. Several concepts are being investigated to reduce these losses, such as the classical vertical multijunction cells, 'lateral' tandem cells, and multi-exciton generation in the form of photon up- and down-conversion. While in theory, efficiencies exceeding 90% are possible (Landsberg or thermodynamic limit), there are severe practical limitations in terms of processability, cost, and spectral sensitivity. Here, we present a simulation environment based on Bayesian Optimization that is able to predict and optimize the electrical performance of multi-junction architectures, both vertical and lateral, in combination with multi-exciton materials. With respect to vertical stacks, we show that by optimizing bandgap energies of multi-exciton generation (MEG) layers, double junctions can reach efficiencies beyond those of five-junction tandem devices (57%). Moreover, such combinations of MEG and double junction devices would be highly resilient against spectral changes of the incoming sunlight. We point out three main challenges for PV material science to realize such devices. With respect to lateral architectures, we show that MEG layers might allow reducing nonradiative voltage losses following the Energy Gap Law. Finally, we show that the simulation environment is able to use machine learned quantitative structure-property relationships obtained from high-throughput experiments to virtually optimise the active layer (such as, the film thickness and the donor-acceptor ratio) for a given architecture. The simulation environment thus represents an important building block towards a digital twin of PV materials.

physics.app-ph↗

arXiv2023

Cutting 'lab-to fab' short: High Throughput Optimization and Process Assessment in Roll-to-Roll Slot Die Coating of Printed Photovoltaics

Commercialization of printed photovoltaics requires knowledge of the optimal composition and microstructure of the single layers, and the ability to control these properties over large areas under industrial conditions. While microstructure optimization can be readily achieved by lab scale methods, the transfer from laboratory scale to a pilot production line ('lab to fab') is a slow and cumbersome process. Here, we show how we can optimize the performance of organic solar cells and at the same time assess process performance in a 2D combinatorial approach directly on an industrially relevant slot die coating line. This is enabled by a multi-nozzle slot die coating head allowing parameter variations along and across the web. This modification allows us to generate and analyze 3750 devices in a single coating run, varying the active layer donor:acceptor ratio and the thickness of the electron transport layer (ETL). We use Gaussian Process Regression (GPR) to exploit the whole dataset for precise determination of the optimal parameter combination. Performance-relevant features of the active layer morphology are inferred from UV-Vis absorption spectra. By mapping morphology in this way, small undesired gradients of process conditions (extrusion rates, annealing temperatures) are detected and their effect on device performance is quantified. The correlation between process parameters, morphology and performance obtained by GPR provides hints to the underlying physics, which are finally quantified by automated high-throughput drift-diffusion simulations. This leads to the conclusion that voltage losses which are observed for very thin ETL coatings are due to incomplete coverage of the electrode by the ETL, which cause enhanced surface recombination.

physics.app-ph↗

arXiv2023

An integrated system built for small-molecule semiconductors via high-throughput approaches

High-throughput synthesis of solution-processable structurally variable small-molecule semiconductors is both an opportunity and a challenge. A large number of diverse molecules provide a possibility for quick material discovery and machine learning based on experimental data. However, the diversity of molecular structure leads to the complexity of molecular properties, such as solubility, polarity, and crystallinity, which poses great challenges to solution processing and purification. Here, we first report an integrated system for the high-throughput synthesis, purification, and characterization of molecules with a large variety. Based on the principle of Like dissolves like, we combine theoretical calculations and a robotic platform to accelerate the purification of those molecules. With this platform, a material library containing 125 molecules and their optical-electric properties was built within a timeframe of weeks. More importantly, the high repeatability of recrystallization we design is a reliable approach to further upgrading and industrial production.

physics.app-ph↗

arXiv2023

A Digital Twin to overcome long-time challenges in Photovoltaics

The recent successes of emerging photovoltaics (PV) such as organic and perovskite solar cells are largely driven by innovations in material science. However, closing the gap to commercialization still requires significant innovation to match contradicting requirements such as performance, longevity and recyclability. The rate of innovation, as of today, is limited by a lack of design principles linking chemical motifs to functional microscopic structures, and by an incapacity to experimentally access microscopic structures from investigating macroscopic device properties. In this work, we envision a layout of a Digital Twin for PV materials aimed at removing both limitations. The layout combines machine learning approaches, as performed in materials acceleration platforms (MAPs), with mathematical models derived from the underlying physics and digital twin concepts from the engineering world. This layout will allow using high-throughput (HT) experimentation in MAPs to improve the parametrization of quantum chemical and solid-state models. In turn, the improved and generalized models can be used to obtain the crucial structural parameters from HT data. HT experimentation will thus yield a detailed understanding of generally valid structure-property relationships, enabling inverse molecular design, that is, predicting the optimal chemical structure and process conditions to build PV devices satisfying a multitude of requirements at the same time. After motivating our proposed layout of the digital twin with causal relationships in material science, we discuss the current state of the enabling technologies, already being able to yield insight from HT data today. We identify open challenges with respect to the multiscale nature of PV materials and the needed volume and diversity of data, and mention promising approaches to address these challenges.

cond-mat.mtrl-sci↗