Materials Science and Engineering

Short-range ordering (SRO) in multi-principal element alloys influences material properties such as strength and corrosion. While some degree of SRO is expected at equilibrium, predicting the kinetics of its formation is challenging. We present a simplified isothermal concentration-wave (CW) model to estimate an effective relaxation time of SRO formation. Estimates from the CW model agree to within a factor of five with relaxation times obtained from kinetic Monte Carlo (kMC) simulations when above the highest ordering instability temperature. The advantage of the CW model is that it only requires mobility and thermodynamic parameters, which are readily obtained from alloy mobility databases and Metropolis Monte Carlo simulations, respectively. The simple parameterization of the CW model and its analytical nature makes it an attractive tool for the design of processing conditions to promote or suppress SRO in multicomponent alloys.

Highly scattering samples, such as polymer droplets or solid-state powders, are difficult to study via coherent two-dimensional infrared (2D IR) spectroscopy. Previously, researchers have employed (quasi-) phase cycling, local-oscillator chopping, and polarization control to reduce scattering, but the latter method poses a limit on polarization-dependent measurements. Here, we present a method for Scattering Elimination Immune from Detector Artifacts (SEIFDA) in pump-probe 2D IR experiments. Our method extends the negative probe delay method of removing scattering from pump-probe spectroscopy to 2D experiments. SEIFDA works well for all polarizations when combined with the optimized noise reduction scheme to remove additive and multiplicative noise. We demonstrate that our method can be employed with any polarization scheme and reliably lowers the scattering at parallel polarization to comparable levels to the conventional 8-frame phase cycling with probe chopping (8FPCPC) at perpendicular polarization. Our system can acquire artifact free spectra in parallel polarization when the signal intensity is as little as 5% of the intensity of the interference between the pump pulses scattered into the detector. It reduces the time required to characterize the scattering term by at least 50% over 8FPCPC. Through detailed analysis of detector nonlinearity, we show that the performance of 8FPCPC can be improved by incorporating nonlinear correction factors, but it is still worse than that of SEIFDA. Application of SEIFDA to study the encapsulation of Nile red in polymer droplets demonstrates that this method will be very useful for probing highly scattering systems.

DNA-stabilized silver nanoclusters (Ag_N-DNAs) have sequence-tuned compositions and fluorescence colors. High-throughput experiments together with supervised machine learning models have recently enabled design of DNA templates that select for Ag_N-DNA properties, including near-infrared (NIR) emission that holds promise for deep tissue bioimaging. However, these existing models do not enable simultaneous selection of multiple Ag_N-DNA properties, and require significant expert input for feature engineering and class definitions. This work presents a model for multiobjective, continuous-property design of Ag_N-DNAs with automatic feature extraction, based on variational autoencoders (VAEs). This model is generative, i.e., it learns both the forward mapping from DNA sequence to Ag_N-DNA properties and the inverse mapping from properties to sequence, and is trained on an experimental data set of DNA sequences paired with Ag_N-DNA fluorescence properties. Experimental testing shows that the model enables effective design of Ag_N-DNA emission, including bright NIR Ag_N-DNAs with 4-fold greater abundance compared to training data. In addition, Shapley analysis is employed to discern learned nucleobase patterns that correspond to fluorescence color and brightness. This generative model can be adapted for a range of biomolecular systems with sequence-dependent properties, enabling precise design of emerging biomolecular nanomaterials.

Hydrogen oxidation reaction in alkaline media is critical for alkaline fuel cells and electrochemical ammonia compressors. The slow hydrogen oxidation reaction in alkaline electrolytes requires large amounts of scarce and expensive platinum catalysts. While transition metal decoration can enhance Pt catalysts activity, it often reduces the electrochemical active surface area, limiting the improvement in Pt mass activity. Here, we enhance Pt catalysts activity without losing surface-active sites by using a Pd-Ru pair. Utilizing a mildly catalytic thermal pyrolysis approach, Pd-Ru pairs are decorated on Pt, confirmed by extended X-ray absorption fine structure and high-angle annular dark-field scanning transmission electron microscopy. Density functional theory and ab-initio molecular dynamics simulations indicate preferred Pd and Ru dopant adsorption. The Pd-Ru decorated Pt catalyst exhibits a mass-based exchange current density of 1557 ± 85 A g-1metal for hydrogen oxidation reaction, demonstrating superior performance in an ammonia compressor.

Understanding the dynamics of hot, highly energetic electrons resulting from nonradiative plasmon decay is crucial for optimizing applications in photocatalysis and energy conversion. This study presents an analysis of electron kinetics within plasmonic metals, focusing on the steady-state behavior during continuous-wave (CW) illumination. Using an inelastic spectroscopy technique, we quantify the temperature and lifetimes of distinct carrier populations during excitation. A significant finding is the monotonic increase in hot electron lifetime with decreases in electronic temperature. We also observe a 1.22× increase in hot electron temperature during intraband excitation compared to interband excitation and a corresponding 2.34× increase in carrier lifetime. The shorter lifetimes during interband excitation are hypothesized to result from direct recombination of nonthermal holes and hot electrons, highlighting steady-state kinetics. Our results help bridge the knowledge gap between ultrafast and steady-state spectroscopies, offering critical insights for optimizing plasmonic applications.

Electric double layers (EDLs) play fundamental roles in various electrochemical processes. Despite the extensive history of EDL modeling, there remain challenges in the accurate prediction of its structure without expensive computation. Herein, we propose a predictive multiscale continuum model of EDL that eliminates the need for parameter fitting. This model computes the distribution of the electrostatic potential, electron density, and species' concentrations by taking the extremum of the total grand potential of the system. The grand potential includes the microscopic interactions that are newly introduced in this work: polarization of solvation shells, electrostatic interaction in parallel plane toward the electrode, and ion-size-dependent entropy. The parameters that identify the electrode and electrolyte materials are obtained from independent experiments in the literature. The model reproduces the trends in the experimental differential capacitance with multiple electrode and nonadsorbing electrolyte materials (Ag(110) in NaF, Ag(110) in NaClO₄, and Hg in NaF), which verifies the accuracy and predictiveness of the model and rationalizes the observed values to be due to changes in electron stability. However, our calculation on Pt(111) in KClO₄ suggests the need for the incorporation of electrode/ion-specific interactions. Sensitivity analyses confirmed that effective ion radius, ion valence, the electrode's Wigner-Seitz radius, and the bulk modulus of the electrode are significant material properties that control the EDL structure. Overall, the model framework and findings provide insights into EDL structures and predictive capability at low computational cost.

ConspectusDNA-stabilized silver nanoclusters (Ag_N-DNAs) are sequence-encoded fluorophores. Like other noble metal nanoclusters, the optical properties of Ag_N-DNAs are dictated by their atomically precise sizes and shapes. What makes Ag_N-DNAs unique is that nanocluster size and shape are controlled by nucleobase sequence of the templating DNA oligomer. By choice of DNA sequence, it is possible to synthesize a wide range of Ag_N-DNAs with diverse emission colors and other intriguing photophysical properties. Ag_N-DNAs hold significant potential as "programmable" emitters for biological imaging due to their combination of small molecular-like sizes, bright and sequence-tuned fluorescence, low toxicities, and cost-effective synthesis. In particular, the potential to extend Ag_N-DNAs into the second near-infrared region (NIR-II) is promising for deep tissue imaging, which is a major area of interest for advancing biomedical imaging. Achieving this goal requires a deep understanding of the structure-property relationships that govern Ag_N-DNAs in order to design Ag_N-DNA emitters with sizes and geometries that support NIR-II emission.In recent years, major advances have been made in understanding the structure and composition of Ag_N-DNAs, enabling new insights into the correlation of nanocluster structure and photophysical properties. These advances have hinged on combined innovations in mass characterization and crystallography of compositionally pure Ag_N-DNAs, together with combinatorial experiments and machine learning-guided design. A combined approach is essential due to the major challenge of growing suitable Ag_N-DNA crystals for diffraction and to the labor-intensive nature of preparing and solving the molecular formulas of atomically precise Ag_N-DNAs by mass spectrometry. These approaches alone are not feasibly scaled to explore the large sequence space of DNA oligomer templates for Ag_N-DNAs.This account describes recent fundamental advances in Ag_N-DNA science that have been enabled by high throughput synthesis and fluorimetry together with detailed analytical studies of purified Ag_N-DNAs. First, short introductions to nanocluster chemistry and Ag_N-DNA basics are presented. Then, we review recent large-scale studies that have screened thousands of DNA templates for Ag_N-DNAs, leading to discovery of distinct classes of these emitters with unique cluster core compositions and ligand chemistries. In particular, the discovery of a new class of chloride-stabilized Ag_N-DNAs enabled the first ab initio calculations of Ag_N-DNA electronic structure and present new approaches to stabilize these emitters in biologically relevant conditions. Near-infrared (NIR) emissive Ag_N-DNAs are also found to exhibit diverse structures and properties. Finally, we conclude by highlighting recent proof-of-principle demonstrations of NIR Ag_N-DNAs for targeted fluorescence imaging. Continued efforts may future push Ag_N-DNAs into the tissue transparency window for fluorescence imaging in the NIR-II tissue transparency window.

The absolute band-edge potentials of semiconductors and their positions relative to solution redox potentials are often invoked as design principles for photoelectrochemical devices and particulate photocatalysts. Here we show that these criteria are not necessary and limit the exploration of materials that may advance the fields of photoelectrochemistry, photochemistry and photocatalysis. We discuss how band-edge energies are not singular parameters and instead shift with pH, electrolyte type and surface chemistry. The free energies of electrons and holes, rather than those of solution redox couples, dictate overall reaction spontaneity and thus reactivity. Favourable charge-transfer kinetics can occur even when the relevant electrolyte redox potential(s) appear outside the bandgap, enabled by the inversion or accumulation of electronic charge at the semiconductor surface. This discussion informs design principles for photocatalytic systems engineering for both one-electron and multi-electron redox reactions (for example, H2 evolution, H2O oxidation and CO2 reduction). (Figure presented.)

The tensile creep behavior of a vacuum arc-melted Nb45Ta25Ti15Hf15 refractory high entropy alloy was investigated over a constant true stress range of 50–300 MPa at a temperature of 1173 K. Creep tests were carried out in both high vacuum (5 × 10−6 torr) and ultrahigh purity Ar gas to examine the environmental effect. The samples tested in vacuum exhibited power law behavior with a stress exponent of 4.1 and exceptional tensile creep ductility, whereas those tested in Ar suffered significant embrittlement due to HfO2 formation at grain boundaries, which was exacerbated at low applied stresses where extended exposure to residual O2 gas resulted in more extensive brittle intergranular fracture. Phase decomposition occurred after long-term thermal exposure, where a second Hf-rich body-centered cubic phase formed predominantly at grain boundaries but did not cause embrittlement. Compared to the equiatomic TaNbHfZrTi (Senkov alloy) and face-centered cubic multiple-principal element alloys, Nb45Ta25Ti15Hf15 has superior creep resistance, especially at high applied stresses, while maintaining excellent creep ductility. Transmission electron microscopy revealed that creep deformation in Nb45Ta25Ti15Hf15 at 1173 K is controlled by cross-kink collisions from screw dislocations that results in dipole drag at lower strain rates and jog drag at higher strain rates.

Motor vehicles are among the major sources of pollutants and greenhouse gases in urban areas and a transition to "zero emission vehicles" is underway worldwide. However, emissions associated with brake and tire wear will remain. We show here that previously unrecognized volatile and semi-volatile organic compounds, which have a similarity to biomass burning emissions are emitted during braking. These include greenhouse gases or, these classified as Hazardous Air Pollutants, as well as nitrogen-containing organics, nitrogen oxides and ammonia. The distribution and reactivity of these gaseous emissions are such that they can react in air to form ozone and other secondary pollutants with adverse health and climate consequences. Some of the compounds may prove to be unique markers of brake emissions. At higher temperatures, nucleation and growth of nanoparticles is also observed. Regions with high traffic, which are often disadvantaged communities, as well as commuters can be impacted by these emissions even after combustion-powered vehicles are phased out.