Manipulating Electronic Structure from the Bottom-Up: Colloidal Nanocrystal-Based Semiconductors

Highly-Directional, Highly-Efficient Solution-Processed Light-Emitting Diodes of All-Face-Down Oriented Colloidal Quantum Well Self-Assembly

Semiconductor colloidal quantum wells (CQWs) provide anisotropic emission behavior originating from their anisotropic optical transition dipole moments (TDMs). Here, solution-processed colloidal quantum well light-emitting diodes (CQW-LEDs) of a single all-face-down oriented self-assembled monolayer (SAM) film of CQWs that collectively enable a supreme level of IP TDMs at 92% in the ensemble emission are shown. This significantly enhances the outcoupling efficiency from 22% (of standard randomly-oriented emitters) to 34% (of face-down oriented emitters) in the LED. As a result, the external quantum efficiency reaches a record high level of 18.1% for the solution-processed type of CQW-LEDs, putting their efficiency performance on par with the hybrid organic-inorganic evaporation-based CQW-LEDs and all other best solution-processed LEDs. This SAM-CQW-LED architecture allows for a high maximum brightness of 19,800 cd m^-2 with a long operational lifetime of 247 h at 100 cd m^-2 as well as a stable saturated deep-red emission (651 nm) with a low turn-on voltage of 1.7 eV at a current density of 1 mA cm^-2 and a high J₉₀ of 99.58 mA cm^-2 . These findings indicate the effectiveness of oriented self-assembly of CQWs as an electrically-driven emissive layer in improving outcoupling and external quantum efficiencies in the CQW-LEDs.

Big Data in a Nano World: A Review on Computational, Data-Driven Design of Nanomaterials Structures, Properties, and Synthesis

The recent rise of computational, data-driven research has significant potential to accelerate materials discovery. Automated workflows and materials databases are being rapidly developed, contributing to high-throughput data of bulk materials that are growing in quantity and complexity, allowing for correlation between structural-chemical features and functional properties. In contrast, computational data-driven approaches are still relatively rare for nanomaterials discovery due to the rapid scaling of computational cost for finite systems. However, the distinct behaviors at the nanoscale as compared to the parent bulk materials and the vast tunability space with respect to dimensionality and morphology motivate the development of data sets for nanometric materials. In this review, we discuss the recent progress in data-driven research in two aspects: functional materials design and guided synthesis, including commonly used metrics and approaches for designing materials properties and predicting synthesis routes. More importantly, we discuss the distinct behaviors of materials as a result of nanosizing and the implications for data-driven research. Finally, we share our perspectives on future directions for extending the current data-driven research into the nano realm.

Ligand Dynamics in Nanocrystal Solids Studied with Quasi-Elastic Neutron Scattering

Nanocrystal surfaces are commonly populated by organic ligands, which play a determining role in the optical, electronic, thermal, and catalytic properties of the individual nanocrystals and their assemblies. Understanding the bonding of ligands to nanocrystal surfaces and their dynamics is therefore important for the optimization of nanocrystals for different applications. In this study, we use temperature-dependent, quasi-elastic neutron scattering (QENS) to investigate the dynamics of different surface bound alkanethiols in lead sulfide nanocrystal solids. We select alkanethiols with mono- and dithiol terminations, as well as different backbone types and lengths. QENS spectra are collected both on a time-of-flight spectrometer and on a backscattering spectrometer, allowing us to investigate ligand dynamics in a time range from a few picoseconds to nanoseconds. Through model-based analysis of the QENS data, we find that ligands can either (1) precess around a central axis, while simultaneously rotating around their own molecular axis, or (2) only undergo uniaxial rotation with no precession. We establish the percentage of ligands undergoing each type of motion, the average relaxation times, and activation energies for these motions. We determine, for example, that dithiols which link facets of neighboring nanocrystals only exhibit uniaxial rotation and that longer ligands have higher activation energies and show smaller opening angles of precession due to stronger ligand-ligand interactions. Generally, this work provides insight into the arrangement and dynamics of ligands in nanocrystal solids, which is key to understanding their mechanical and thermal properties, and, more generally, highlights the potential of QENS for studying ligand behavior.

General Route to Colloidal Nanocrystal Clusters with Precise Hierarchical Control via Star-like Nanoreactors

A colloidal nanocrystal cluster (CNC) is a hierarchical nanostructure formed by clustering several nanocrystals into one nano-ensemble, which may exhibit unique optical or catalytic properties different from individual nanocrystals owing to the mutual interactions among neighboring component nanocrystals. However, there is still no universal synthetic route that could be applicable to diverse material compositions with precisely controlled hierarchical structures (i.e., nanocrystal number density, component nanocrystal size, and overall diameter of the CNC) up to now. Herein, a general and novel synthetic strategy was reported for crafting a wide range of inorganic CNCs (i.e., noble metal, semiconductor, and metal oxide) via utilizing amphiphilic star-like poly(4-vinylpyridine)-block-polystyrene diblock copolymers as nanoreactors prepared by sequential atom transfer radical polymerization. The hierarchical structure of rationally designed CNCs could be readily tailored by varying the P4VP molecular weight of star-like nanoreactors and the parameter optimization during the CNC preparation process, which was inaccessible by conventional synthetic methods.

Diffusion-Limited Growth of a Spherical Nanocrystal in a Finite Space

Reason for the work: The potential applications of nanoscale materials in nanophotonics, nanoelectronics, bioimaging, and biosensing have stimulated the research in the synthesis of nanocrystals, nanowires, and so forth. There is a great need to understand the spatiotemporal evolution of nanocrystals in the solution-route synthesis in order to better design advanced synthesis techniques for the manufacturing of monodisperse nanocrystals of high quality. Most significant results: We analyze the size effect on the diffusion-limited growth of a spherical nanoparticle in a finite space (spherical cavity) on the basis of the Gibbs-Thomson relation and obtain an analytical formulation of the monomer concentration in the finite space in an implicit form and an integro-differential equation for the growth rate of the spherical nanoparticle. The monomer concentration in the finite space decreases slower than that with a stationary nanoparticle. The growth of the spherical nanoparticle consists of two stages-an initially linear growth stage and a later power-law stage. The result from the infinite space with a stationary nanoparticle is inapplicable to the analysis of the growth of spherical nanoparticles in a finite space. Conclusions: There exists a size effect on the growth of nanocrystals in a finite space. The dependence of the growth behavior of nanocrystals on the growth time and temperature needs to be investigated in order to experimentally determine the fundamental mechanisms controlling the growth of nanocrystals in the solution-route synthesis.

Molecular-Level Insight into Semiconductor Nanocrystal Surfaces

Semiconductor nanocrystals exhibit attractive photophysical properties for use in a variety of applications. Advancing the efficiency of nanocrystal-based devices requires a deep understanding of the physical defects and electronic states that trap charge carriers. Many of these states reside at the nanocrystal surface, which acts as an interface between the semiconductor lattice and the molecular capping ligands. While a detailed structural and electronic understanding of the surface is required to optimize nanocrystal properties, these materials are at a technical disadvantage: unlike molecular structures, semiconductor nanocrystals lack a specific chemical formula and generally must be characterized as heterogeneous ensembles. Therefore, in order for the field to improve current nanocrystal-based technologies, a creative approach to gaining a "molecular-level" picture of nanocrystal surfaces is required. To this end, an expansive toolbox of experimental and computational techniques has emerged in recent years. In this Perspective, we critically evaluate the insight into surface structure and reactivity that can be gained from each of these techniques and demonstrate how their strategic combination is already advancing our molecular-level understanding of nanocrystal surface chemistry.