Phase segregation and miscibility of TiOx nanocomposites in Gd-doped ceria solid electrolyte material.

Electro-chemo-mechanical (ECM) coupling refers to mechanical deformation due to electrochemically driven compositional change in a solid. An ECM actuator producing micrometre-size displacements and long-term stability at room temperature was recently reported, comprising a 20 mol% Gd-doped ceria (20GDC), a solid electrolyte membrane, placed between two working bodies made of TiOx/20GDC (Ti-GDC) nanocomposites with Ti concentration of 38 mol%. The volumetric changes originating from oxidation or reduction in the local TiOx units are hypothesized to be the origin of mechanical deformation in the ECM actuator. Studying the Ti concentration-dependent structural changes in the Ti-GDC nanocomposites is therefore required for (i) understanding the mechanism of dimensional changes in the ECM actuator and (ii) maximizing the ECM response. Here, the systematic investigation of the local structure of the Ti and Ce ions in Ti-GDC over a broad range of Ti concentrations using synchrotron X-ray absorption spectroscopy and X-ray diffraction is reported. The main finding is that, depending on the Ti concentration, Ti atoms either form a cerium titanate or segregate into a TiO2 anatase-like phase. The transition region between these two regimes with Ti(IV) concentration between 19% and 57% contained strongly disordered TiOx units dispersed in 20GDC containing Ce(III) and Ce(IV) and hence rich with oxygen vacancies. As a result, this transition region is proposed to be the most advantageous for developing ECM-active materials.

Solving the structure of "single-atom" catalysts using machine learning - assisted XANES analysis.

"Single-atom" catalysts (SACs) have demonstrated excellent activity and selectivity in challenging chemical transformations such as photocatalytic CO2 reduction. For heterogeneous photocatalytic SAC systems, it is essential to obtain sufficient information of their structure at the atomic level in order to understand reaction mechanisms. In this work, a SAC was prepared by grafting a molecular cobalt catalyst on a light-absorbing carbon nitride surface. Due to the sensitivity of the X-ray absorption near edge structure (XANES) spectra to subtle variances in the Co SAC structure in reaction conditions, different machine learning (ML) methods, including principal component analysis, K-means clustering, and neural network (NN), were utilized for in situ Co XANES data analysis. As a result, we obtained quantitative structural information of the SAC nearest atomic environment, thereby extending the NN-XANES approach previously demonstrated for nanoparticles and size-selective clusters.

Comparative analysis of XANES and EXAFS for local structural characterization of disordered metal oxides.

In functional materials, the local environment around active species that may contain just a few nearest-neighboring atomic shells often changes in response to external conditions. Strong disorder in the local environment poses a challenge to commonly used extended X-ray absorption fine structure (EXAFS) analysis. Furthermore, the dilute concentrations of absorbing atoms, small sample size and the constraints of the experimental setup often limit the utility of EXAFS for structural analysis. X-ray absorption near-edge structure (XANES) has been established as a good alternative method to provide local electronic and geometric information of materials. The pre-edge region in the XANES spectra of metal compounds is a useful but relatively under-utilized resource of information of the chemical composition and structural disorder in nano-materials. This study explores two examples of materials in which the transition metal environment is either relatively symmetric or strongly asymmetric. In the former case, EXAFS results agree with those obtained from the pre-edge XANES analysis, whereas in the latter case they are in a seeming contradiction. The two observations are reconciled by revisiting the limitations of EXAFS in the case of a strong, asymmetric bond length disorder, expected for mixed-valence oxides, and emphasize the utility of the pre-edge XANES analysis for detecting local heterogeneities in structural and compositional motifs.

DNA-assisted photoinduced charge transfer between a cationic poly(phenylene vinylene) and a cationic fullerene.

Water-soluble cationic conjugated poly(phenylene vinylene) (PPV) and cationic fullerene were complexed with negatively charged single stranded DNA and double stranded DNA via electrostatic interactions to achieve photoinduced charge transfer with efficiencies as high as those observed from oppositely charged, cationic PPV and anionic fullerene but with distinctly different quenching mechanisms.

Biomimetic Control over Bimetallic Nanoparticle Structure and Activity via Peptide Capping Ligand Sequence.

The controlled design of bimetallic nanoparticles (BNPs) is a key goal in tailoring their catalytic properties. Recently, biomimetic pathways demonstrated potent control over the distribution of different metals within BNPs, but a direct understanding of the peptide effect on the compositional distribution at the interparticle and intraparticle levels remains lacking. We synthesized two sets of PtAu systems with two peptides and correlated their structure, composition, and distributions with the catalytic activity. Structural and compositional analyses were performed by a combined machine learning-assisted refinement of X-ray absorption spectra and Z-contrast measurements by scanning transmission electron microscopy. The difference in the catalytic activities between nanoparticles synthesized with different peptides was attributed to the details of interparticle distribution of Pt and Au across these markedly heterogeneous systems, comprising Pt-rich, Au-rich, and Au core/Pt shell nanoparticles. The total amount of Pt in the shells of the BNPs was proposed to be the key catalytic activity descriptor. This approach can be extended to other systems of metals and peptides to facilitate the targeted design of catalysts with the desired activity.

Restructuring dynamics of surface species in bimetallic nanoparticles probed by modulation excitation spectroscopy.

Restructuring of metal components on bimetallic nanoparticle surfaces in response to the changes in reactive environment is a ubiquitous phenomenon whose potential for the design of tunable catalysts is underexplored. The main challenge is the lack of knowledge of the structure, composition, and evolution of species on the nanoparticle surfaces during reaction. We apply a modulation excitation approach to the X-ray absorption spectroscopy of the 30 atomic % Pd in Au supported nanocatalysts via the gas (H2 and O2) concentration modulation. For interpreting restructuring kinetics, we correlate the phase-sensitive detection with the time-domain analysis aided by a denoising algorithm. Here we show that the surface and near-surface species such as Pd oxides and atomically dispersed Pd restructured periodically, featuring different time delays. We propose a model that Pd oxide formation is preceded by the build-up of Pd regions caused by oxygen-driven segregation of Pd atoms towards the surface. During the H2 pulse, rapid reduction and dissolution of Pd follows an induction period which we attribute to H2 dissociation. Periodic perturbations of nanocatalysts by gases can, therefore, enable variations in the stoichiometry of the surface and near-surface oxides and dynamically tune the degree of oxidation/reduction of metals at/near the catalyst surface.

Lead-free Zr-doped ceria ceramics with low permittivity displaying giant electrostriction.

Electrostrictors, materials developing mechanical strain proportional to the square of the applied electric field, present many advantages for mechanical actuation as they convert electrical energy into mechanical, but not vice versa. Both high relative permittivity and reliance on Pb as the key component in commercial electrostrictors pose serious practical and health problems. Here we describe a low relative permittivity (<250) ceramic, ZrxCe1-xO2 (x < 0.2), that displays electromechanical properties rivaling those of the best performing electrostrictors: longitudinal electrostriction strain coefficient ~10-16 m2/V2; relaxation frequency ≈ a few kHz; and strain ≥0.02%. Combining X-ray absorption spectroscopy, atomic-level modeling and electromechanical measurements, here we show that electrostriction in ZrxCe1-xO2 is enabled by elastic dipoles produced by anharmonic motion of the smaller isovalent dopant (Zr). Unlike the elastic dipoles in aliovalent doped ceria, which are present even in the absence of an applied elastic or electric field, the elastic dipoles in ZrxCe1-xO2 are formed only under applied anisotropic field. The local descriptors of electrostrictive strain, namely, the cation size mismatch and dynamic anharmonicity, are sufficiently versatile to guide future searches in other polycrystalline solids.

Latent Representation Learning for Structural Characterization of Catalysts.

Supervised machine learning-enabled mapping of the X-ray absorption near edge structure (XANES) spectra to local structural descriptors offers new methods for understanding the structure and function of working nanocatalysts. We briefly summarize a status of XANES analysis approaches by supervised machine learning methods. We present an example of an autoencoder-based, unsupervised machine learning approach for latent representation learning of XANES spectra. This new approach produces a lower-dimensional latent representation, which retains a spectrum-structure relationship that can be eventually mapped to physicochemical properties. The latent space of the autoencoder also provides a pathway to interpret the information content "hidden" in the X-ray absorption coefficient. Our approach (that we named latent space analysis of spectra, or LSAS) is demonstrated for the supported Pd nanoparticle catalyst studied during the formation of Pd hydride. By employing the low-dimensional representation of Pd K-edge XANES, the LSAS method was able to isolate the key factors responsible for the observed spectral changes.

Electron transfer dynamics from single near infrared emitting lead sulfide-cadmium sulfide nanocrystals to titanium dioxide.

In this study we report the first successful demonstration of electron transfer between single near infrared emitting PbS/CdS nanocrystals and an external acceptor, titanium dioxide (TiO2). We demonstrate distance-dependent electron transfer from single nanocrystals to TiO2 and explore the effect of this process on the photoluminescence dynamics of these nanocrystals. Isolated PbS/CdS QDs are found to exhibit blinking dynamics similar to other nanocrystals like CdSe/ZnS; however, their photoluminescence follows a quasi two-state pattern with heterogeneous photoluminescence lifetimes which may be the result of their emission originating from different energy states. Electron transfer of these nanocrystals with an external acceptor inhibits their photoluminescence lifetime heterogeneity and biases their blinking dynamics in a manner similar to that observed for visible emitting CdSe/ZnS nanocrystals undergoing electron transfer with external acceptors. While the present study reconfirms the universality of quantum dot blinking among various types of nanocrystals, it also demonstrates that universality remains valid for the communication of various types of nanocrystals with the exterior world, here pictured as electron transfer with external acceptors.

Nonradiative Energy Transfer from Individual CdSe/ZnS Quantum Dots to Single-Layer and Few-Layer Tin Disulfide.

The combination of zero-dimensional (0D) colloidal CdSe/ZnS quantum dots with tin disulfide (SnS2), a two-dimensional (2D)-layered metal dichalcogenide, results in 0D-2D hybrids with enhanced light absorption properties. These 0D-2D hybrids, when exposed to light, exhibit intrahybrid nonradiative energy transfer from photoexcited CdSe/ZnS quantum dots to SnS2. Using single nanocrystal spectroscopy, we find that the rate for energy transfer in 0D-2D hybrids increases with added number of SnS2 layers, a positive manifestation toward the potential functionality of such 2D-based hybrids in applications such as photovoltaics and photon sensing.

Core size dependent hole transfer from a photoexcited CdSe/ZnS quantum dot to a conductive polymer.

Photoinduced hole transfer from a CdSe/ZnS quantum dot to a conjugated polymer is tuned by varying the quantum dot core size. Hole transfer affects the photoluminescence blinking of the quantum dot, increasing the duration of the on-states and decreasing that of the off-states.