Showing papers by "Moungi G. Bawendi published in 2020"

How machine learning can help select capping layers to suppress perovskite degradation

Abstract: Environmental stability of perovskite solar cells (PSCs) has been improved by trial-and-error exploration of thin low-dimensional (LD) perovskite deposited on top of the perovskite absorber, called the capping layer. In this study, a machine-learning framework is presented to optimize this layer. We featurize 21 organic halide salts, apply them as capping layers onto methylammonium lead iodide (MAPbI3) films, age them under accelerated conditions, and determine features governing stability using supervised machine learning and Shapley values. We find that organic molecules’ low number of hydrogen-bonding donors and small topological polar surface area correlate with increased MAPbI3 film stability. The top performing organic halide, phenyltriethylammonium iodide (PTEAI), successfully extends the MAPbI3 stability lifetime by 4 ± 2 times over bare MAPbI3 and 1.3 ± 0.3 times over state-of-the-art octylammonium bromide (OABr). Through characterization, we find that this capping layer stabilizes the photoactive layer by changing the surface chemistry and suppressing methylammonium loss. The stability of perovskite solar cells can be improved by using hybrid-organic perovskites capping-layers atop the active material. Here the authors use machine learning to optimize capping layers by monitoring time to degradation of differently capped lead-halide perovskite solar cells.

Effect of Spectral Diffusion on the Coherence Properties of a Single Quantum Emitter in Hexagonal Boron Nitride.

Abstract: Quantum emitters capable of producing single photons on-demand with high color purity are the building blocks of emerging schemes in secure quantum communications, quantum computing, and quantum me...

Luminescent Surfaces with Tailored Angular Emission for Compact Dark-Field Imaging Devices.

Abstract: Dark-field microscopy is a standard imaging technique widely employed in biology that provides high image contrast for a broad range of unstained specimens1. Unlike bright-field microscopy, it accentuates high spatial frequencies and can therefore be used to emphasize and resolve small features. However, the use of dark-field microscopy for reliable analysis of blood cells, bacteria, algae and other marine organisms often requires specialized, bulky microscope systems, as well as expensive additional components, such as dark-field-compatible objectives or condensers2,3. Here, we propose to simplify and downsize dark-field microscopy equipment by generating the high-angle illumination cone required for dark-field microscopy directly within the sample substrate. We introduce a luminescent photonic substrate with a controlled angular emission profile and demonstrate its ability to generate high-contrast dark-field images of micrometre-sized living organisms using standard optical microscopy equipment. This new type of substrate forms the basis for miniaturized lab-on-chip dark-field imaging devices that are compatible with simple and compact light microscopes. A luminescent photonic substrate with a controlled angular emission profile is introduced and its ability to generate high-contrast dark-field images of micrometre-sized living organisms is demonstrated using standard optical microscopy equipment.

Scalable Synthesis of InAs Quantum Dots Mediated through Indium Redox Chemistry.

Abstract: Next-generation optoelectronic applications centered in the near-infrared (NIR) and short-wave infrared (SWIR) wavelength regimes require high-quality materials. Among these materials, colloidal InAs quantum dots (QDs) stand out as an infrared-active candidate material for biological imaging, lighting, and sensing applications. Despite significant development of their optical properties, the synthesis of InAs QDs still routinely relies on hazardous, commercially unavailable precursors. Herein, we describe a straightforward single hot injection procedure revolving around In(I)Cl as the key precursor. Acting as a simultaneous reducing agent and In source, In(I)Cl smoothly reacts with a tris(amino)arsenic precursor to yield colloidal InAs quantitatively and at gram scale. Tuning the reaction temperature produces InAs cores with a first excitonic absorption feature in the range of 700-1400 nm. A dynamic disproportionation equilibrium between In(I), In metal, and In(III) opens up additional flexibility in precursor selection. CdSe shell growth on the produced cores enhances their optical properties, furnishing particles with center emission wavelengths between 1000 and 1500 nm and narrow photoluminescence full-width at half-maximum (FWHM) of about 120 meV throughout. The simplicity, scalability, and tunability of the disclosed precursor platform are anticipated to inspire further research on In-based colloidal QDs.

Non-invasive monitoring of chronic liver disease via near-infrared and shortwave-infrared imaging of endogenous lipofuscin.

Abstract: Monitoring the progression of non-alcoholic fatty liver disease is hindered by a lack of suitable non-invasive imaging methods. Here, we show that the endogenous pigment lipofuscin displays strong near-infrared and shortwave-infrared fluorescence when excited at 808 nm, enabling label-free imaging of liver injury in mice and the discrimination of pathological processes from normal liver processes with high specificity and sensitivity. We also show that the near-infrared and shortwave-infrared fluorescence of lipofuscin can be used to monitor the progression and regression of liver necroinflammation and fibrosis in mouse models of non-alcoholic fatty liver disease and advanced fibrosis, as well as to detect non-alcoholic steatohepatitis and cirrhosis in biopsied samples of human liver tissue. Label-free imaging of the endogenous pigment lipofuscin at near-infrared and shortwave-infrared wavelengths enables the longitudinal monitoring of liver injury in mice and in biopsied human livers.

Seedless Continuous Injection Synthesis of IndiumPhosphide Quantum Dots as a Route to Large Size and Low Size Dispersity

Abstract: Because of their lower toxicity, indium phosphide (InP) quantum dots (QDs) are replacing cadmium selenide QDs in applications that require narrowband luminescence across the visible spectrum. Howev...

Superradiant emission from self-assembled light emitters: From molecules to quantum dots

Abstract: Colloidal synthesis methods and ultrahigh-vacuum molecular beam epitaxy can tailor semiconductor-based nanoscale single emitters—quantum dots—as the building blocks for classical optoelectronic devices, such as lasers, light-emitting devices, and display technologies. These novel light sources have a basic resemblance of luminescent organic molecules, individually and in the aggregated forms. Highly ordered superstructures of quantum dots, obtained via scalable bottom-up self-assembly, exhibit diverse collective phenomena, such as band-like charge transport or superradiant emission. Superradiance emerges from coherent coupling of several emitters via a common radiation field resulting in a single giant dipole leading to short (sub-nanosecond) and intense (proportional to the squared number of coupled emitters) bursts of light. In this article, we review the basic principles and progress in the development of superradiant emitters with organic molecules and inorganic quantum dots, in view of their integration into classical and novel quantum light sources.

Blue Light Emitting Defective Nanocrystals Composed of Earth‐Abundant Elements

Abstract: Copper-based ternary (I-III-VI) chalcogenide nanocrystals (NCs) are compositionally-flexible semiconductors that do not contain lead (Pb) or cadmium (Cd). Cu-In-S NCs are the dominantly studied member of this important materials class and have been reported to contain optically-active defect states. However, there are minimal reports of In-free compositions that exhibit efficient photoluminescence (PL). Here, we report a novel solution-phase synthesis of ≈4 nm defective nanocrystals (DNCs) composed of copper, aluminum, zinc, and sulfur with ≈20 % quantum yield and an attractive PL maximum of 450 nm. Extensive spectroscopic characterization suggests the presence of highly localized electronic states resulting in reasonably fast PL decays (≈1 ns), large vibrational energy spacing, small Stokes shift, and temperature-independent PL linewidth and PL lifetime (between room temperature and ≈5 K). Furthermore, density functional theory (DFT) calculations suggest PL transitions arise from defects within a CuAl5 S8 crystal lattice, which supports the experimental observation of highly-localized states. The results reported here provide a new material with unique optoelectronic characteristics that is an important analog to well-explored Cu-In-S NCs.

Monodisperse and Water-Soluble Quantum Dots for SWIR Imaging via Carboxylic Acid Copolymer Ligands.

Abstract: Compared to the visible and near-infrared, the short-wave infrared region (SWIR; 1000–2000 nm) has excellent properties for in vivo imaging: low autofluorescence, reduced scattering, and a low-abso...

Author Correction: How machine learning can help select capping layers to suppress perovskite degradation.

Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Room-Temperature Phosphorescence and Low-Energy Induced Direct Triplet Excitation of Alq3 Engineered Crystals.

Abstract: Crystal engineering is a practical approach for tailoring material properties. This approach has been widely studied for modulating optical and electrical properties of semiconductors. However, the properties of organic molecular crystals are difficult to control following a similar engineering route. In this Letter, we demonstrate that engineered crystals of Alq3 and Ir(ppy)3 complexes, which are commonly used in organic light-emitting technologies, possess intriguing functional properties. Specifically, these structures not only process efficient low-energy induced triplet excitation directly from the ground state of Alq3 but also can show strong emission at the Alq3 triplet energy level at room temperatures. We associate these phenomena with local deformations of the host matrix around the guest molecules, which in turn lead to a stronger host-guest triplet-triplet coupling and spin-orbital mixing.

A Physical Data Fusion Approach to Optimize Compositional Stability of Halide Perovskites

Abstract: Compositional search within multinary perovskites employing brute force synthesis are prohibitively expensive in large chemical spaces. To identify the most stable multi-cation lead iodide perovskites containing Cs, formamidinium (FA) and methylammonium (MA), we fuse results from density functional theory (DFT) calculations and in situ thin-film degradation test within an end-to-end machine learning (ML) algorithm to inform the compositional optimization of CsxMAyFA1-x-yPbI3. We integrate phase thermodynamics modelling as a probabilistic constraint in a Bayesian optimization (BO) loop, which effectively guides the experimental search while considering both structural and environmental stability. After three optimization rounds and only sampling 1.8% of the compositional space, we identify thin-film compositions centred at Cs0.17MA0.03FA0.80PbI3 that achieve a 3x delay in macroscopic degradation onset under elevated temperature, humidity, and light compared with the more complex state-of-the-art Cs0.05(MA0.17FA0.83)0.95Pb(I0.83Br0.17)3. We find up to 8% of MA can be incorporated into the perovskite structure before stability is significantly compromised. Cs is beneficial at low concentrations, however, beyond 17% is found to contribute to reduced stability. Synchrotron-based grazing-incidence wide-angle X-ray scattering (GIWAXS) further validates that the interplay of chemical decomposition and phase separation governs the non-linear instability landscape of this compositional space. We reveal the detrimental role of the ẟ-CsPbI3 minority phase in accelerating degradation and it can be kinetically suppressed by co-optimising Cs and MA content, providing insights into simplifying perovskite compositions for further environmental stability enhancement. Our approach realizes the effectiveness of ML-enabled data fusion in achieving a holistic, efficient, and physics-informed experimentation for multinary systems, potentially generalisable to materials search in the vast structural and alloyed spaces beyond halide perovskites.

Capping Layers Design Guidelines for Stable Perovskite Solar Cells via Machine Learning

Abstract: After reaching a device efficiency level comparable to silicon, perovskite solar cell's next big challenge is to tackle its environmental instability issue. To solve this problem, researchers have started incorporating a buffer layer called ‘capping layer’, consisting of low dimensional (LD) perovskite, sandwiched between perovskite absorber and hole transport layer. However, there is no conclusive agreement on how to select capping layer material that best extends the stability. By using feature importance rank on the regression models, we can start to see which molecular properties on capping layer have significant impact in suppressing degradation.

Nanocrystal synthesis, μfluidic sample dilution and direct extraction of single emission linewidths in continuous flow.

Abstract: The rational design of semiconductor nanocrystal populations requires control of their emission linewidths, which are dictated by interparticle inhomogeneities and single-nanocrystal spectral linewidths. To date, research efforts have concentrated on minimizing the ensemble emission linewidths, however there is little knowledge about the synthetic parameters dictating single-nanocrystal linewidths. In this direction, we present a flow-based system coupled with an optical interferometry setup for the extraction of single nanocrystal properties. The platform has the ability to synthesize nanocrystals at high temperature <300 °C, adjust the particle concentration after synthesis and extract ensemble-averaged single nanocrystal emission linewidths using flow photon-correlation Fourier spectroscopy.

Sensitization of silicon by singlet exciton fission in tetracene

Abstract: Singlet fission can split a high energy singlet exciton and generate two lower energy triplet excitons. This process has shown near 200 percent triplet exciton yield. Sensitizing solar cells with singlet fission material, it can potentially increase the power conversion efficiency limit from 29 percent to 35 percent. Singlet fission in the tetracene is known to be efficient, and the energy of the triplet excitons are energetically matched to the silicon bandgap. In this work, we designed an optical measurement with an external magnetic field to determine the efficiencies of triplet exciton transfer from tetracene to silicon. Using this method, we have found that a passivation layer of 8 angstroms of hafnium oxynitride on silicon allows efficient triplet exciton transfer around 133 percent.