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At least 631 records · Page 35

Unsupervised anomaly detection in MeV ultrafast electron diffraction

MeV ultrafast electron diffraction (MUED) is a pump-probe technique used to study the dynamic structural evolution of materials. An ultrashort laser pulse triggers structural changes, which are then probed by an ultrashort relativistic electron beam. To overcome low signal-to-noise ratios, diffraction patterns are averaged over thousands of shots. However, shot-to-shot instabilities in the electron beam can distort individual patterns, introducing uncertainty. Improving MUED accuracy requires detecting and removing these anomalous patterns from large datasets. In this work, we developed a fully unsupervised methodology for the detection of anomalous diffraction patterns. Using a convolutional autoencoder, we calculate the reconstruction mean squared error of the diffraction patterns. Based on the statistical analysis of this error, we provide the user an estimation of the probability that the pattern is normal, which also allows a posterior visual inspection of the images that are difficult to classify. This method has been trained with only 100 diffraction patterns and tested on 1521 patterns, resulting in a false positive rate between 0.2% and 0.4%, with a training time of 10 s per image and a test time of about 1 s per image. Here, the proposed methodology can also be applied to other diffraction techniques in which large datasets are collected that include faulty images due to instrumental instabilities.

43 PARTICLE ACCELERATORS↗

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗

Development and validation of the cavitation-induced erosion risk assessment tool

This work presents the development of a cavitation-induced erosion risk assessment (CIERA) tool that links multiphase flow simulation predictions with the progress towards material erosion. To develop a robust erosion modeling tool, the cavitation and erosion predictions for pressurized diesel fuel flow within a channel geometry were validated over a range of Reynolds and cavitation number conditions in two different aluminum channel geometries, one featuring a rounded inlet corner and the other with a sharp inlet corner. The multiphase flow development within the channel was modeled using a compressible mixture model, where phase change was represented with the homogeneous relaxation model and the turbulent flow evolution was modeled using a dynamic structure approach for Large Eddy Simulations. To improve representation of the incubation period before material rupture over existing approaches, a physics-based metric was derived based on the cumulative energy absorbed by the solid material from repeated hydrodynamic impacts. When the average peak pressure was related to the incubation period, the incubation period and its sensitivity to changes in flow conditions were found to be overpredicted. In contrast, predictions from CIERA provided a more accurate means to qualitatively and quantitatively predict the influence of flow conditions on the incubation period before material erosion. When the predicted stored energy was related to the solid material properties to estimate the incubation period, multiphase flow simulations demonstrated accurate representation of the sensitivity of erosion severity to changes in flow conditions. The use of CIERA led to quantitative agreement of the predicted incubation period within 5% of the experimentally measured incubation period.

42 ENGINEERING↗

Stroboscopic ultrafast imaging using RF strip-lines in a commercial transmission electron microscope

The development of ultrafast electron microscopy (UEM), specifically stroboscopic imaging, has brought the study of structural dynamics to a new level by overcoming the spatial limitations of ultrafast spectroscopy and the temporal restrictions of traditional TEM simultaneously. Combining the concepts governing both techniques has enabled direct visualization of dynamics with spatiotemporal resolutions in the picosecond-nanometer regime. Here, in this study, we push the limits of imaging using a pulsed electron beam via RF induced transverse deflection based on the newly developed 200 keV frequency-tunable strip-line pulser. We demonstrate 0.2 nm spatial resolution at high magnifications and elucidation of Lorentz imaging using the phase-microscopy method. We also present beam coherence measurements and expand our study using the breathing modes of a silicon interdigitated comb under RF excitation which achieves improved temporal synchronization between the electron pulse-train and electric field. A new RF holder has also been developed with impedance matching to the RF signal to minimize transmission power loss to samples and its performance is compared with a conventional sample holder.

47 OTHER INSTRUMENTATION↗

Characterization of transverse electron pulse trains using RF powered traveling wave metallic comb striplines

Advancements in ultrafast electron microscopy have allowed elucidation of spatially selective structural dynamics. However, as the spatial resolution and imaging capabilities have made progress, quantitative characterization of the electron pulse trains has not been reported at the same rate. In fact, inexperienced users have difficulty replicating the technique because only a few dedicated microscopes have been characterized thoroughly. Systems replacing laser driven photoexcitation with electrically driven deflectors especially suffer from a lack of quantified characterization because of the limited quantity. The primary advantages to electrically driven systems are broader frequency ranges, ease of use and simple synchronization to electrical pumping. Here, we characterize the technical parameters for electrically driven UEM including the shape, size and duration of the electron pulses using low and high frequency chopping methods. At high frequencies, pulses are generated by sweeping the electron beam across a chopping aperture. For low frequencies, the beam is continuously forced off the optic axis by a DC potential, then momentarily aligned by a countering pulse. Using both methods, we present examples that measure probe durations of 2 ns and 10 ps for the low and high frequency techniques, respectively. Here, we also discuss how the implementation of a pulsed probe affects STEM imaging conditions by adjusting the first condenser lens.

36 MATERIALS SCIENCE↗

Evaluation of automated stability testing in machining through closed-loop control and Bayesian machine learning

Here, this paper describes a system for automated identification of the optimal stable cutting parameters in milling through Bayesian machine learning and closed-loop control. The closed-loop control system consists of a process monitoring architecture, an analysis framework, and a feedback mechanism. The analysis framework consists of a Bayesian machine learning algorithm that learns a stability map given test results. The learned stability map is used to select parameters for stability testing using an expected improvement in the material removal rate criterion. The test parameters are communicated to the machine controller to complete the test cut through a feedback mechanism. The test cuts were monitored using an audio signal; the stability of the test cut was determined by analyzing the frequency content of the audio signal. The test result was fed back to the Bayesian learning algorithm to complete the loop. Experimental results demonstrate that the system can identify the optimal stable parameters without information about the cutting force model or the structural dynamics. The system provides a low-cost method for optimal stable parameter identification in an industrial environment.

Chatter↗

Structural Propensities in Cs2MBiX6 (M=Na, Ag; X=Cl, Br) Bismuth Halide Double Perovskites

A previously unreported low-temperature phase transition in the bismuth halide double perovskite Cs2AgBiCl6 is reported, thereby establishing trends in the structural ground state across Cs2NaBiCl6, Cs2AgBiCl6, and Cs2AgBiBr6. Using the combined toolkit of variable-temperature synchrotron X-ray and neutron powder diffraction, Raman spectroscopy, and density-functional theory–based electronic structure modeling, we demonstrate a cubic Fm¯3m → tetragonal I4/m transition upon cooling with distinct onset temperatures. Neutron powder diffraction refinements permit the unambiguously assignment of the low-temperature phase of Cs2NaBiCl6 to I4/m, correcting prior reports of an I4/mmm ground state. Cs2AgBiCl6 is also found to transforms to a structure crystallizing in the I4/m space group at low temperatures. Temperaturedependent Raman data and density-functional theory-based modeling capture the softening and freezing of out-of-phase octahedral-tilt modes and quantify relative instabilities. Solid-state nuclear magnetic resonance spectroscopy at room temperature completes the characterization and helps underpin the subtle differences in covalency across the compounds. Trends in the phase transition temperature Ts and tilt magnitudes emerge from coupled effects of halide identity, M(I)–site bonding character, and a mismatch between interatomic distances. These results establish the structure– dynamics–bonding framework for tuning tilt-driven instabilities in halide double perovskites.

Tian, Haowen↗

Ambient Synthesis for Fe(II) Polypyridyl Complexes with an Order of Magnitude Increase in Charge-Transfer Excited-State Lifetimes over [Fe(bpy) 3 ] 2+

Replacing precious metals with abundant metals is an important research focus in photochemical energy conversion and storage to meet global energy demands. However, transition metal complexes (TMCs) based on abundant 3d metals typically possess photochemical disadvantages─such as short charge-transfer excited-state lifetimes─and molecular modifications have focused on optimizing the interplay of structure, dynamics, and energetics to overcome their limitations. One strategy to do so is the use of bespoke ligands that can extend the lifetimes of chemically useful excited states. Here, in this study, we report the synthesis and characterization of novel Fe(II) complexes featuring lengthy polypyridyl ligands that can be readily synthesized. Steady-state and transient absorption spectroscopies indicate that these complexes have desirable properties and their excited metal-to-ligand charge-transfer states live an order of magnitude longer than in the benchmark [Fe(bpy) 3 ] 2+ . This lifetime is largely preserved in the heteroleptic complexes, thereby enabling the preparation of asymmetric complexes. Additionally, we apply nonradiative transition theory to explain the long-time decay kinetics. In light of their ease of preparation and reasonable excited-state lifetimes, we suggest the use of these complexes in Fe(II) dye-sensitized solar cells, where the rate of charge injection would be competitive with increased lifetime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Calculation of the Thermal Neutron Scattering Cross-Section of Solids Using OCLIMAX

The thermal neutron scattering cross-section of a solid depends on the energy (or wavelength) of the incident neutrons. Devising a method to calculate the energy dependence from first principles, without the approximations built in the scattering theory, has been a major undertaking in nuclear engineering. Here, we demonstrate such a calculation method using the program OCLIMAX. In this work, our approach eliminates various approximations and limitations involved in a regular calculation with the LEAPR module of NJOY code, and the results are compared with available experimental and theoretical data. It is also demonstrated how additional insight can be obtained from the calculated full dynamical structure factor. The results reported here show the great potential and excellent platform provided by OCLIMAX for future development in the study of neutron thermalization in solid materials for different applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating the Chemical Reactivity of DFT-Simulated Liquid Water with Hydrated Electrons via the Dual Descriptor

Modeling the various properties of liquid water, particularly its reactivity, has been a longstanding challenge for simulation methods. Recently, ab initio simulations based on density functional theory (DFT) have come to the fore as tenable methods for calculating the properties and reactivity of water, with varying degrees of success for different exchange-correlation functionals. In particular, hybrid-GGA and meta-GGA functionals have been shown to reproduce many of the structural, dynamical, and energetic properties of water to a high degree of accuracy relative to their computational cost. Here, we show that the dual descriptor (DD) measure of nucleophilicity and electrophilicity, which is sometimes used to elucidate organic chemistry reaction mechanisms, can also be used to characterize the reactivity of DFTsimulated liquid water. The DD is especially apt for understanding the reactivity of excess electrons with water as its calculation explicitly involves adding and removing an excess electron from a reference system. We use the DD to explore the reactivity of water simulated using three different DFT functionals: the LDA functional (LDA), a hybrid-GGA functional (PBE0), and a hybrid meta- GGA functional (SCAN0). Using the DD, we show that the SCAN0 functional with the standard 25% Hartree–Fock exchange produces simulated liquid water with many regions that are far more reactive than either PBE0 or LDA. To understand the implications of these highly reactive regions, we then add a strong nucleophile in the form of an excess electron and find that although PBE0 and LDA predict stable hydrated electrons, the excess electron reacts nearly instantaneously with SCAN0 water via proton abstraction to form a hydrogen atom and hydroxide ion. We show that the DD provides the ability to not only predict whether or not liquid water will react with a hydrated electron but also which particular waters will be involved solely from analyzing pure water configurations generated with each functional. We rationalize this result in terms of the known trap-seeking behavior of injected hydrated electrons, which are able to find the most electronegative region in bulk water. These results highlight the utility of the dual descriptor as a fast and interpretable method for investigating condensed-phase reactivity with excess electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pushing and Pulling: A Dual pH Trigger Controlled by Varying the Alkyl Tail Length in Heme Coordinating Peptide Amphiphiles

Some organisms in nature that undergo anaerobic respiration utilize 1D nanoscale arrays of densely packed cytochromes containing the molecule heme. The assemblies can be mimicked with 1D nanoscale fibrils composed of peptide amphiphiles designed to coordinate heme in dense arrays. To create such materials and assemblies it is critical to understand the assembly process and what controls the various aspects of hierarchical assembly. MD simulations suggest that shorter alkyl chains on the peptide lead to more dynamic structures than the peptides with longer chains that yield kinetically trapped states. The hydration parameters manifest themselves experimentally through the observation of a dual pH trigger which controls the peptide assembly rate, the heme binding affinity, and heme organization kinetics. Great strides in understanding the relative complexity of the self-assembly process in relation to incorporating a functional moiety like heme opens up many possibilities in developing abiotic assemblies for bioelectronic devices and assemblies

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-Isochronal Behavior of Charge Transport at Liquid–Liquid and Liquid–Glass Transition in Aprotic Ionic Liquids

A reversible, first-order transition separating two liquid phases of a single-component material is a fascinating yet poorly understood phenomenon. Here, we investigate the liquid–liquid transition (LLT) ability of two tetraalkylphosphonium ionic liquids (ILs), [P 666,14 ]Cl and [P 666,14 ][1,2,4-triazolide], using differential scanning calorimetry and dielectric spectroscopy. The latter technique also allowed us to study the LLT at elevated pressure. We found that cooling below 205 K transforms [P 666,14 ]Cl and [P 666,14 ][Trz] from one liquid state (liquid 1) to another (the self-assembled liquid 2), while the latter facilitates the charge transport decoupled from structural dynamics. In contrast to temperature, pressure was found to play an essential role in the self-organization of a liquid 2 phase, resulting in different time scales of charge transport for rapidly and slowly compressed samples. Furthermore, τ σ (P LL ) was found to be much shorter than τ σ (T LL , P=atm), which constitutes the first example of non-isochronal behavior of charge transport at LLT. In turn, dielectric studies through the liquid–glass transition revealed the non-monotonic behavior of τ σ at elevated pressure for [P 666,14 ]Cl, while for [P 666,14 ][Trz] τ σ (P g ) was almost constant. These results highlight the diversity of liquid–liquid transition features within the class of phosphonium ionic liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

STEPs-SOL, a Peptoid Force Field Parameterization to Include Solvent Effects

As peptoids (N-substituted glycines) continue to gain popularity as a class of biomimetic polymers, the importance and demand for accurate force fields in molecular simulations also grow. Building on the vacuum-optimized Systematic and Extensible Force Field for Peptoids (STEPs) force field, here we present STEPs-SOL, a novel peptoid force field parametrization that effectively incorporates solvent effects to enhance the accuracy of peptoid simulations. The development of STEPs-SOL is based on the need for precise electrostatic modeling achieved through solvent-specific partial charge optimization. Here, our systematic approach significantly improves agreement with experimental measurements, reducing the mean absolute error in cis/trans ratio predictions (ΔG c/t ) by an average of 38% across multiple peptoid residues and solvent environments. This improved parametrization addresses computational challenges associated with nonbonded energies while maintaining a workflow that relies on high-level quantum mechanical data rather than depending solely on limited experimental equilibrium properties. By evaluating the effects of conformational bias in restrained electrostatic potential (RESP) charge generation and examining their impact on peptoid conformations in various solvents, we enhance our understanding of peptoid structural dynamics while providing a more accurate modeling framework.

force field↗

Measuring Intermolecular Excited State Geometry for Favorable Singlet Fission in Tetracene

Singlet fission (SF) is the process of converting an excited singlet to a pair of excited triplets. Harvesting two charges from a single photon has the potential to increase photovoltaic device efficiencies. Acenes, such as tetracene and pentacene, are model molecules for studying SF. Despite SF being an endoergic process for tetracene and exoergic for pentacene, both acenes exhibit near unity SF quantum efficiencies, raising questions about how tetracene can overcome the energy barrier. Here, we use recently developed instrumentation to measure inelastic neutron scattering (INS) while optically exciting the model molecules using two different excitation energies. The spectroscopic results reveal intermolecular structural relaxation due to the presence of a triplet excited state. Here, the structural dynamics of the combined excited state molecule and surrounding tetracene molecules are further studied using time-dependent density functional theory (TD-DFT), which shows that the singlet and triplet levels shift due to the excited state geometry, reducing the uphill energy barrier for SF to within kT.

36 MATERIALS SCIENCE↗

Nanocrystal Geometry Governs Phase Transformation Pathways in Palladium Hydride

Pathways and structural dynamics of phase transformations impact performance of materials in energy and information storage technologies. Palladium hydride (PdH x ) nanocrystals are an ideal model system for studying solute-induced phase transformations, where elastic energy from lattice mismatch between α-PdH x and β-PdH x phases is often considered a key to determining the transformation pathways. α/β-PdH x interfacial elastic energy is affected by the confined geometry of a nanocrystal. However, how nanocrystal geometry influences phase transformation pathways is largely unknown. Using in situ liquid phase transmission electron microscopy, we directly visualize hydrogenation in Pd nanocrystals with two geometries, a nanocube and a hexagonal nanoplate. Both follow similar sequences of an initially curved nucleus, interface flattening, and reverse-stage nucleation; however, their evolving α/β-PdH x interfaces exhibit geometry-dependent crystallographic alignments. In nanocubes, {100}-aligned configurations conform to static elastic energy ordering, representing a pathway that maintains a local mechanical equilibrium, whereas nanoplates display both {110}- and {211}-aligned interfaces. Theoretical simulations show that geometry determines the accessibility of alternative phase transformation pathways as the system is driven far from equilibrium during hydrogenation. In conclusion, these findings identify geometry as a fundamental parameter for directing phase transformation pathways, offering design principles for accessing atypical configurations and improving properties of intercalation-based devices.

Lee, Daewon [Lawrence Berkeley National Laboratory↗

Tunable and Cooperative Thermomechanical Properties of Protein-Metal-Organic Frameworks

We recently introduced protein-metal-organic frameworks (protein-MOFs) as chemically designed protein crystals, composed of ferritin nodes that predictably assemble into 3D lattices upon coordination of various metal ions and ditopic, hydrox-amate-based linkers. Owing to their unique tripartite construction, protein-MOFs possess extremely sparse lattice connectivi-ty, suggesting that they might display unusual thermomechanical properties. Leveraging the synthetic modularity of ferritin-MOFs, we investigated the temperature-dependent structural dynamics of six distinct frameworks. Our results show that the thermostabilities of ferritin-MOFs can be tuned through the metal component or the presence of crowding agents. Our stud-ies also reveal a framework that undergoes a reversible and isotropic first-order phase transition near-room temperature, corre-sponding to a 4% volumetric change within ≤1 deg C and a hysteresis window of ~10 deg C. Here, this highly cooperative crystal-to-crystal transformation, which stems from the soft crystallinity of ferritin-MOFs, illustrates the advantage of modular con-struction strategies in discovering tunable–and unpredictable–material properties.

36 MATERIALS SCIENCE↗

Reversible Switch in Charge Storage Enabled by Selective Ion Transport in Solid Electrolyte Interphase

Solid-electrolyte interphases (SEIs) in advanced rechargeable batteries ensure reversible electrode reactions at extreme potentials beyond the thermodynamic stability limits of electrolytes by insulating electrons while allowing working ions to transport. Such selective ion transport occurs naturally in biological cell membranes as a ubiquitous prerequisite of many life processes and a foundation of biodiversity. In addition, cell membranes can selectively open and close the ion channels in response to external stimuli (e.g., electrical, chemical, mechanical, thermal), giving rise to “gating” mechanisms that help manage intracellular reactions. We wondered whether the chemistry and structure of SEIs can mimic cell membranes, such that ion gating can be replicated. That is, can SEIs realize a reversible switching between two electrochemical behaviors, i.e., the ion intercalation chemistry of batteries and the ion adsorption of capacitors? Herein, we report such SEIs that result in thermally activated selective ion transport. The function of open/close gate switches is governed by the chemical and structural dynamics of SEIs under different thermal conditions, with precise behaviors as conducting and insulating interphases that enable battery and capacitive processes within a finite temperature window. Such an ion gating function is synergistically contributed by Arrhenius-activated ion transport and SEI dissolution/regrowth. Following the understanding of this new mechanism, we then develop an electrochemical method to heal the SEI layer in situ. As a result, the knowledge acquired in this work reveals the possibility of hitherto unknown biomimetic properties of SEIs, which will guide us to leverage such complexities to design better SEIs for future battery chemistries.

25 ENERGY STORAGE↗