Materials Science and Engineering

To combat the rise of antibiotic-resistance in bacteria and the resulting effects on healthcare worldwide, new technologies are needed that can perform rapid antibiotic susceptibility testing (AST). Conventional clinical methods for AST rely on growth-based assays, which typically require long incubation times to obtain quantitative results, representing a major bottleneck in the determination of the optimal antibiotic regimen to treat patients. Here, we demonstrate a rapid AST method based on the metabolic activity measured by fluorescence lifetime imaging microscopy (FLIM). Using lab strains and clinical isolates of Escherichia coli with tetracycline-susceptible and resistant phenotypes as models, we demonstrate that changes in metabolic state associated with antibiotic susceptibility can be quantitatively tracked by FLIM. Our results show that the magnitude of metabolic perturbation resulting from antibiotic activity correlates with susceptibility evaluated by conventional metrics. Moreover, susceptible and resistant phenotypes can be differentiated in as short as 10 min after antibiotic exposure. This FLIM-AST (FAST) method can be applied to other antibiotics and provides insights into the nature of metabolic perturbations inside bacterial cells resulting from antibiotic exposure with single cell resolution.

Oxide ceramic electrolytes (OCEs) have great potential for solid-state lithium metal (Li0) battery applications because, in theory, their high elastic modulus provides better resistance to Li0 dendrite growth. However, in practice, OCEs can hardly survive critical current densities higher than 1 mA/cm2. Key issues that contribute to the breakdown of OCEs include Li0 penetration promoted by grain boundaries (GBs), uncontrolled side reactions at electrode-OCE interfaces, and, equally importantly, defects evolution (e.g., void growth and crack propagation) that leads to local current concentration and mechanical failure inside and on OCEs. Here, taking advantage of a dynamically crosslinked aprotic polymer with non-covalent -CH3⋯CF3 bonds, we developed a plastic ceramic electrolyte (PCE) by hybridizing the polymer framework with ionically conductive ceramics. Using in-situ synchrotron X-ray technique and Cryogenic transmission electron microscopy (Cryo-TEM), we uncover that the PCE exhibits self-healing/repairing capability through a two-step dynamic defects removal mechanism. This significantly suppresses the generation of hotspots for Li0 penetration and chemomechanical degradations, resulting in durability beyond 2000 hours in Li0-Li0 cells at 1 mA/cm2. Furthermore, by introducing a polyacrylate buffer layer between PCE and Li0-anode, long cycle life >3600 cycles was achieved when paired with a 4.2 V zero-strain cathode, all under near-zero stack pressure.

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.

The Hippo pathway is commonly altered in cancer initiation and progression; however, exactly how this pathway becomes dysregulated to promote human cancer development remains unclear. Here we analyze the Hippo somatic mutations in the human cancer genome and functionally annotate their roles in targeting the Hippo pathway. We identify a total of 85 loss-of-function (LOF) missense mutations for Hippo pathway genes and elucidate their underlying mechanisms. Interestingly, we reveal zinc-finger domain as an integral structure for MOB1 function, whose LOF mutations in head and neck cancer promote tumor growth. Moreover, the schwannoma/meningioma-derived NF2 LOF mutations not only inhibit its tumor suppressive function in the Hippo pathway, but also gain an oncogenic role for NF2 by activating the VANGL-JNK pathway. Collectively, our study not only offers a rich somatic mutation resource for investigating the Hippo pathway in human cancers, but also provides a molecular basis for Hippo-based cancer therapy.

Fluoride-ion batteries have several potential advantages over lithium-ion batteries. Materials development is still needed, however, to realize electrolytes with sufficiently high anion conductivity and compatibility with anode and cathode layers. Fluoride compounds are difficult to synthesize directly as single crystals but can be realized from oxide film precursors via topotactic chemistry techniques. Here, we create crystalline alkaline earth bismuth fluoride films BaBiF5 and SrBiF5 through oxide molecular beam epitaxy and topotactic fluorination. We characterize their ionic conductivities and demonstrate their potential as electrolytes. Finally, we realize epitaxial synthesis of BaBiF5 on BaF2 substrates, providing a route to thin film fluoride-ion battery devices.

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.