arXiv subjects

Vladimir Bulovic

Publications and source records attributed to Vladimir Bulovic.

9 recordsLinked to original sources

arXiv2025

Morphological and Chemical Changes in Cd-free Colloidal QD-LEDs During Operation

Heavy metal-free quantum-dot light-emitting devices (QD-LEDs) have demonstrated remarkable brightness, saturated color, and high efficiencies across a broad spectral range. However, in contrast to organic LEDs (OLEDs), QD-LED operational lifetimes remain limited, with the underlying degradation mechanisms not fully understood. In the present study, we show that InP/ZnSe/ZnS (red-emitting) and ZnTeSe/ZnSe/ZnS (blue-emitting) cadmium-free colloidal QD-LEDs undergo nanoscale morphological changes during operation. Specifically,interparticle coarsening and layer thinning are observed in the electron transport layer (ETL) consisting of ZnMgO nanoparticles (NPs), in the QD emissive layer, and in the organic hole transport layer. This is accompanied by the generation and diffusion of compositional oxygen- and hydrogen-radicals throughout the device, with oxygen accumulating at the electrode/ETL interfance. Moreover, in situ transmission electron microscopy reveals the electron beam exposure, in the presence of hydrogen radicals, accelerates ZnMgO NPs coarsening. To mitigate these degradation pathway, we show that acrylate-based resin-encapsulation treatment stabilize the ETL/QD layers by suppressing the radical formation and halting morphology changes. This approach achieves dramatic stability enhancements, exhibits an 8-fold and 5000-fold lifetime improvement on InP/ZnSe/ZnS and ZnTeSe/ZnSe/ZnS QD-LEDs, respectively. Our findings establish the causal relationships between the morphological degradation, interlayer radical dynamics, and state-of-the-art QD-LEDs instability, providing new insights into a scalable encapsulation treatment that enables efficient and long-lived Cd-free QD-LEDs.

physics.app-ph↗

arXiv2025

Disentangling the Effects of Simultaneous Environmental Variables on Perovskite Synthesis and Device Performance via Interpretable Machine Learning

Despite the rapid rise in perovskite solar cell efficiency, poor reproducibility remains a major barrier to commercialization. Film crystallization and device performance are highly sensitive to environmental factors during fabrication, yet their complex interactions are not well understood. In this work, we present a systematic framework to investigate the influence of both individual and coupled environmental variables on device efficiency and crystallization kinetics. We developed an integrated fabrication platform with precise, independent control over ambient solvent partial pressure, absolute humidity, and temperature during spin-coating and thermal-annealing processes, respectively. Using the platform, we implemented a closed-loop Bayesian optimization framework to efficiently explore the multi-dimensional processing space. We mapped the impact of these environmental variables on device performance and identified coupled effects among them. In-situ grazing-incidence wide-angle X-ray scattering measurements further validated these findings by revealing a nonlinear interaction between absolute humidity and solvent partial pressure during spin-coating, which affects crystallization dynamics. To isolate and quantify these interactions, we developed an interpretable machine learning approach that combines knowledge distillation with Shapley interaction analysis. The model revealed the contribution of each interaction varies across different processing conditions. Our study highlights the importance of integrated ambient sensing and control to achieve repeatable perovskite solar cells, and demonstrates the utility of combining active learning with interpretable machine learning to navigate complex, high-dimensional processing landscapes.

cond-mat.mtrl-sci↗

arXiv2024

Predicting Organic-Inorganic Halide Perovskite Photovoltaic Performance from Optical Properties of Constituent Films through Machine Learning

We demonstrate a machine learning (ML) approach that accurately predicts the current-voltage behavior of 3D/2D-structured (FAMA)Pb(IBr)3/OABr hybrid organic-inorganic halide perovskite (HOIP) solar cells under AM1.5 illumination. Our neural network algorithm is trained on measured responses from several hundred HOIP solar cells, using three simple optical measurements of constituent HOIP films as input: optical transmission spectrum, spectrally-resolved photoluminescence, and time-resolved photoluminescence, from which we predict the open-circuit voltage (Voc), short-circuit current (Jsc), and fill factors (FF) values of solar cells that contain the HOIP active layers. Determined average prediction accuracies for 95 % of the predicted Voc, Jsc, and FF values are 91%, 94% and 89%, respectively, with R2 coefficients of determination of 0.47, 0.77, and 0.58, respectively. Quantifying the connection between ML predictions and physical parameters extracted from the measured HOIP films optical properties, allows us to identify the most significant parameters influencing the prediction results. With separate ML-classifying algorithms, we identify degraded solar cells using the same optical input data, achieving over 90% classification accuracy through support vector machine, cross entropy loss, and artificial neural network algorithms. To our knowledge, the demonstrated regression and classification work is the first to use ML to predict device photovoltaic properties solely from the optical properties of constituent materials.

cond-mat.mtrl-sci↗

arXiv2022

Reduced ITO for Transparent Superconducting Electronics

Absorption of light in superconducting electronics is a major limitation on the quality of circuit architectures that integrate optical components with superconducting components. A 10 nm thick film of a typical superconducting material like niobium can absorb over half of any incident optical radiation. We propose instead using superconductors which are transparent to the wavelengths used elsewhere in the system. In this paper we investigated reduced indium tin oxide (ITO) as a potential transparent superconductor for electronics. We fabricated and characterized superconducting wires of reduced indium tin oxide. We also showed that a $\SI{10}{nm}$ thick film of the material would only absorb about 1 - 20\% of light between 500 - 1700 nm.

physics.app-ph↗

arXiv2022

Processing Induced Distinct Charge Carrier Dynamics of Bulky Organic Halide Treated Perovskites

State-of-the-art metal halide perovskite-based photovoltaics often employ organic ammonium salts, AX, as a surface passivator, where A is a large organic cation and X is a halide. These surface treatments passivate the perovskite by forming layered perovskites (e.g., A2PbX4) or by AX itself serving as a surface passivation agent on the perovskite photoactive film. It remains unclear whether layered perovskites or AX is the ideal passivator due to an incomplete understanding of the interfacial impact and resulting photoexcited carrier dynamics of AX treatment. In the present study, we use TRPL measurements to selectively probe the different interfaces of glass/perovskite/AX to demonstrate the vastly distinct interfacial photoexcited state dynamics with the presence of A2PbX4 or AX. Coupling the TRPL results with X-ray diffraction and nanoscale microscopy measurements, we find that the presence of AX not only passivates the traps at the surface and the grain boundaries, but also induces an α/δ-FAPbI3 phase mixing that alters the carrier dynamics near the glass/perovskite interface and enhances the photoluminescence quantum yield. In contrast, the passivation with A2PbI4 is mostly localized to the surface and grain boundaries near the top surface where the availability of PbI2 directly determines the formation of A2PbI4. Such distinct mechanisms significantly impact the corresponding solar cell performance, and we find AX passivation that has not been converted to a layered perovskite allows for a much larger processing window (e.g., larger allowed variance of AX concentration which is critical for improving the eventual manufacturing yield) and more reproducible condition to realize device performance improvements, while A2PbI4 as a passivator yields a much narrower processing window. We expect these results to enable a more rational route for developing AX for perovskite.

cond-mat.mtrl-sci↗

arXiv2021

Accurate Determination of Semiconductor Diffusion Coefficient Using Optical Microscopy

Energy carrier transport and recombination in emerging semiconductors can be directly monitored with optical microscopy, leading to the measurement of the diffusion coefficient (D), a critical property for design of efficient optoelectronic devices. D is often determined by fitting a time-resolved expanding carrier profile after optical excitation using a Mean Squared Displacement (MSD) Model. Although this approach has gained widespread adoption, its utilization can significantly overestimate D due to the non-linear recombination processes that artificially broaden the carrier distribution profile. Here, we simulate diffusive processes in both excitonic and free carrier semiconductors and present revised MSD Models that take into account second-order (i.e. bimolecular) and third-order (i.e. Auger) processes to accurately recover D for various types of materials. For perovskite thin films, utilization of these models can reduce fitting error by orders of magnitude, especially for commonly deployed excitation conditions where carrier densities are > 5x10$^1$$^6$ cm$^-$$^3$. In addition, we show that commonly-deployed MSD Models are not well-suited for the study of films with microstructure, especially when boundary behavior is unknown and feature sizes are comparable to the diffusion length. Finally, we find that photon recycling only impacts energy carrier profiles on ultrashort time scales or for materials with fast radiative decay times. We present clear strategies to investigate energy transport in disordered materials for more effective design and optimization of electronic and optoelectronic devices.

physics.app-ph↗

arXiv2019

Triplet-sensitization by lead halide perovskite thin films for near-infrared-to-visible upconversion

Lead halide-based perovskite thin films have attracted great attention due to the explosive increase in perovskite solar cell efficiencies. The same optoelectronic properties that make perovskites ideal absorber materials in solar cells are also beneficial in other light-harvesting applications and make them prime candidates as triplet sensitizers in upconversion via triplet-triplet annihilation in rubrene. In this contribution, we take advantage of long carrier lifetimes and carrier diffusion lengths in perovskite thin films, their high absorption cross sections throughout the visible spectrum, as well as the strong spin-orbit coupling owing to the abundance of heavy atoms to sensitize the upconverter rubrene. Employing bulk perovskite thin films as the absorber layer and spin-mixer in inorganic/organic heterojunction upconversion devices allows us to forego the additional tunneling barrier owing from the passivating ligands required for colloidal sensitizers. Our bilayer device exhibits an upconversion efficiency in excess of 3% under 785 nm illumination.

physics.app-ph↗

arXiv2019

State-of-the-Art Perovskite Solar Cells Benefit from Photon Recycling at Maximum Power Point

Photon recycling is required for a solar cell to achieve an open-circuit voltage ($V_{OC}$) and power conversion efficiency (PCE) approaching the Shockley-Queisser theoretical limit. In metal halide perovskite solar cells, the achievable performance gains from photon recycling remain uncertain due to high variability in perovskite material quality and the non-radiative recombination rate ($k_{1}$). In this work, we study state-of-the-art $\textrm{Cs}_{0.05}(\textrm{MA}_{0.17}\textrm{FA}_{0.83})_{0.95}\textrm{Pb}(\textrm{I}_{0.83}\textrm{Br}_{0.17})_{3}$ films and analyze the impact of varying non-radiative recombination rates on photon recycling and device performance. Importantly, we predict the impact of photon recycling at the maximum power point (MPP), demonstrating an absolute PCE increase of up to 2.0% in the radiative limit, primarily due to a 77 mV increase in $V_{MPP}$. Even with finite non-radiative recombination, benefits from photon recycling can be achieved when non-radiative lifetimes and external LED electroluminescence efficiencies measured at open-circuit, $Q_{e}^{LED}(\textrm{V}_{OC})$, exceed 2 $μ$s and 10%, respectively. This analysis clarifies the opportunity to fully exploit photon recycling to push the real-world performance of perovskite solar cells toward theoretical limits.

physics.app-ph↗

arXiv2015

Plexcitons: Dirac points and topological modes

Plexcitons are polaritonic modes that result from the strong coupling between excitons and plasmons. We consider plexcitons emerging from the interaction of excitons in an organic molecular layer with surface plasmons in a metallic film. We predict the emergence of Dirac cones in the two-dimensional bandstructure of plexcitons due to the inherent alignment of the excitonic transitions in the organic layer. These Dirac cones may open up in energy by simultaneously interfacing the metal with a magneto-optical layer and subjecting the whole system to a perpendicular magnetic field. The resulting energy gap becomes populated with topologically protected one-way modes which travel at the interface of this plexcitonic system. Our theoretical proposal suggests that plexcitons are a convenient and simple platform for the exploration of exotic phases of matter as well as of novel ways to direct energy flow at the nanoscale.

cond-mat.mes-hall↗