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At least 19 records

Integrating computation and experiment to investigate photoelectrodes for solar water splitting at the microscopic scale.

CONSPECTUS: Photoelectrochemical water-splitting is a promising and sustainable way to store the energy of the sun in chemical bonds and use it to produce hydrogen gas, a clean fuel. The key components in photoelectrochemical cells (PECs) are photoelectrodes, including a photocathode that reduces water to hydrogen gas and a photoanode that oxidizes water to oxygen gas. Materials used in photoelectrodes for PECs must effectively absorb sunlight, yield photogenerated carriers, and exhibit electronic properties that enable the efficient shuttling of carriers to the surface to participate in relevant water-splitting reactions. Discovering and understanding the key characteristics of optimal photoelectrode materials is paramount to the realization of PEC technologies. Oxide-based photoelectrodes can satisfy many of these materials requirements, including stability in aqueous environments, band edges with reasonable alignment with the redox potentials for water splitting, and ease of synthesis. However, oxide photoelectrodes generally suffer from poor charge transport properties and considerable bulk electron-hole separation, and they have relatively large band gaps. Numerous strategies have been proposed to improve these aspects and understand how these improvements are reflected in the photoelectrochemical performance. Unfortunately, the structural and compositional complexity of multinary oxides accompanied by the inherent complexity of photoelectrochemical processes makes it challenging to understand the individual effects of composition, structure, and defects in the bulk and on the surface on a material's photoelectrochemical properties. The integration of experiment and theory has great potential to increase our atomic-level understanding of structure-composition-property relationships in oxide photoelectrodes. In this Account, we describe how integrating experiment and theory is beneficial for achieving scientific insights at the microscopic scale. We highlight studies focused on understanding the role of (i) bulk composition via solid-state solutions, intercalation, and comparison with isoelectronic compounds, (ii) dopants for both the anion and cation and their interactions with oxygen vacancies, and (iii) surface/interface structure in the photocurrent generation and photoelectrochemical performance in oxide photoelectrodes. In each instance, we outline strategies and considerations for integrating experiment and theory and describe how this integration led to valuable insights and new directions in uncovering structure-composition-property relationships. Our aim is to demonstrate the unique value of combining experiment and theory in studying photoelectrodes and to encourage the continued effort to bring experiment and theory in closer step with each other.

Wang, Wennie↗

Spectro-Microscopic Analysis of Soot Particle Composition and Source Attribution

Ambient soot particles significantly impact Earth’s radiative balance, human health, and atmospheric visibility. Their microstructural properties depend on formation and aging mechanisms, which vary by emission source and atmospheric processes. Hence, accurately identifying sources of soot enhances our understanding of their physicochemical properties and atmospheric implications. This study used a multi-modal approach to characterize and attribute sources of submicron soot particles collected in Israel during new particle formation events, biomass burning episodes, and background atmospheric conditions. Synchrotron-based X-ray microscopy was used to map soot (elemental carbon), organic carbon, and inorganic species. Implemented atomic force microscopy showed highly diverse phase states, with soot consistently exhibiting a solid-like phase. Automated µ-Raman analysis was subsequently performed on ~690 particles, identifying three soot classes based on spectral features corresponding to the "Defect" (D) and "Graphite" (G) bands of soot. We applied two-peak and five-peak fitting approaches to deconvolute the “Defect” peaks (D1, D2, D3, and D4) and G band from average Raman, revealing varying degrees of graphitic order. The degree of graphitic order was determined from metrics such as the D3 peak area, often observed when soot was internally mixed with organic material. Raman spectral features, along with temporal variations in particle classes contributions, suggest that Particle Type 1 corresponds to traffic related soot and Particle Type 2 to less graphitic soot from biomass burning, while Particle Type 3 is associated with more heterogeneous particulate representative of soot-OC mixtures emitted during new particle formation and biomass burning episodes.

Rivera-Adorno, Felipe (ORCID:0000000273557999)↗

Developing an Automated Microscopic Traffic Simulation Scenario Generation Tool

Traffic simulation is an effective tool for urban planners, traffic engineers, and researchers to study traffic. In particular, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, has demonstrated its importance in analyzing and managing transportation systems. However, integrating data from various sources, generating traffic scenarios, and importing information into traffic simulators to conduct microscopic simulations have always been a challenge. This paper presents a solution to overcome this challenge: RealTwin, a comprehensive tool for automated scenario generation for microscopic traffic simulation. Following a streamlined scenario generation and calibration workflow, RealTwin effectively bridges gaps between traffic data from various sources and traffic simulators, making microscopic traffic simulation more accessible for researchers and engineers across various levels of expertise. Using RealTwin to generate a real-world traffic scenario in Simulation of Urban Mobility (SUMO), VISSIM, and AIMSUN, RealTwin’s ability is demonstrated in the construction of realistic and consistent traffic scenarios in different simulators. Furthermore, this paper introduces and illustrates RealTwin’s capability for technology (e.g., autonomous vehicle) scenario generation. This feature can contribute to more comprehensive microscopic simulations, facilitating the analysis of potential effects of various technological innovations on mobility, energy efficiency, and safety. Finally, RealTwin is used to calibrate a simulation in SUMO. In conclusion, the calibration module enhances RealTwin’s ability to generate consistent simulations across different platforms and more realistic simulations that reflect real-world traffic operations.

autonomous vehicle↗

Microscopic and Macroscopic Characterization of Grain Boundary Energy and Strength in Silicon Carbide via Machine-Learning Techniques

Predicting the properties of grain boundaries poses a challenge because of the complex relationships between structural and chemical attributes both at the atomic and continuum scales. Grain boundary systems are typically characterized by parameters used to classify local atomic arrangements in order to extract features such as grain boundary energy or grain boundary strength. The present work utilizes a combination of high-throughput atomistic simulations, macroscopic and microscopic descriptors, and machine-learning techniques to characterize the energy and strength of silicon carbide grain boundaries. Additionally, a diverse data set of symmetric tilt and twist grain boundaries are described using macroscopic metrics such as misorientation, the alignment of critical low-index planes, and the Schmid factor, but also in terms of microscopic metrics, by quantifying the local atomic structure and chemistry at the interface. These descriptors are used to create random-forest regression models, allowing for their relative importance to the grain boundary energy and decohesion stress to be better understood. Results show that while the energetics of the grain boundary were best described using the microscopic descriptors, the ability of the macroscopic descriptors to reasonably predict grain boundaries with low energy suggests a link between the crystallographic orientation and the resultant atomic structure that forms at the grain boundary within this regime. For grain boundary strength, neither microscopic nor macroscopic descriptors were able to fully capture the response individually. However, when both descriptor sets were utilized, the decohesion stress of the grain boundary could be accurately predicted. These results highlight the importance of considering both macroscopic and microscopic factors when constructing constitutive models for grain boundary systems, which has significant implications for both understanding the fundamental mechanisms at work and the ability to bridge length scales.

36 MATERIALS SCIENCE↗

Design of Neutron Microscopes Equipped with Wolter Mirror Condenser and Objective Optics for High-Fidelity Imaging and Beam Transport

We present and compare the designs of three types of neutron microscopes for high-resolution neutron imaging. Like optical microscopes, and unlike standard neutron imaging instruments, these microscopes have both condenser and image-forming objective optics. The optics are glancing-incidence axisymmetric mirrors and therefore suitable for polychromatic neutron beams. The mirrors are designed to provide a magnification of 10 to achieve a spatial resolution of better than 10 μm. The resolution of the microscopes is determined by the mirrors rather than by the L/Dratio as in conventional pinhole imaging, leading to possible dramatic improvements in the signal rate. We predict the increase in the signal rate by at least two orders of magnitude for very high-resolution imaging, which is always flux limited. Furthermore, in contrast to pinhole imaging, in the microscope, the samples are placed far from the detector to allow for a bulky sample environment without sacrificing spatial resolution.

47 OTHER INSTRUMENTATION↗

Agentic traffic intelligence: Augmented human-in-the-loop scenario generation for microscopic traffic simulation

Traditional microscopic traffic simulation generation often relies on static datasets and manual design, limiting its ability to simulate complex conditions easily. This paper presents a novel framework, Agentic Traffic Intelligence, which combines human approval large language models (LLMs), the Real-Twin tool, and multi-agent systems to perform realistic microscopic traffic simulation scenario generation. The proposed framework incorporates human-in-the-loop (HIL) control, retrieval-augmented generation (RAG), and multi-agent control mechanisms. HIL mechanisms are used to guide multiple LLMs focused on attributes for microscopic simulation generation and to improve the interpretability and transparency of LLM execution for users. RAG enhances context extraction by dynamically integrating external knowledge sources for traffic scenario generation foundations. A multi-agent architecture with supervisory control coordinates the interaction of simulation components, including traffic simulators, control logic, and calibration tools. This enables the synthesis of simulation-ready scenarios that reflect dynamic demand profiles and behavior controls. Furthermore, the framework fuses multisource traffic data with unstructured context and supports iterative refinement through interactive user feedback. Validated through microscopic simulation using Simulation of Urban Mobility, the generated scenarios demonstrate high-fidelity network generation with inflow and turn movement and behavioral calibration, offering a robust and efficient tool for stress-testing and optimizing urban mobility systems.

Hierarchical multi-agent control↗

Enhancing traffic safety analysis with digital twin technology: integrating vehicle dynamics and environmental factors into microscopic traffic simulation

Traffic safety is a critical concern in transportation engineering and urban planning. Traditional traffic safety analysis requires trained observers to collect data in the field, which is time-consuming, labor-intensive, and sometimes inaccurate. In recent years, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, have been utilized to study traffic safety. However, microscopic traffic simulation only focuses on traffic-related factors, such as traffic volume, traffic signals, and lane configurations, neglecting vehicle dynamics and environment-related factors like weather and lighting conditions, which can significantly impact traffic safety. In light of this, this paper explores the application of digital twin technology in traffic safety analysis, integrating vehicle simulators, which consider vehicle dynamics and environmental factors, and microscopic traffic simulators, which simulate the operations of traffic flow, for enhanced safety evaluations. Various scenarios, including different weather conditions and visibility levels, are simulated using a digital twin of a road segment in Tuscaloosa, Alabama. The simulations employ Surrogate Safety Measures (SSMs) like Time to Collision (TTC) and Deceleration Rate to Avoid a Crash (DRAC) to assess safety under varying conditions. The results demonstrate that traffic digital twin can identify potential safety issues that traditional microscopic simulation cannot, providing insights for improving traffic control strategies and transportation infrastructure to enhance traffic safety.

Civil engineering↗

How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution

The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population’s mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of a simulated evolving population subject to a standard serial dilution protocol. Through extensive numerical experimentation, we find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that increasing the level of clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but leaves the rate of growth invariant when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape. The simulation package for this work may be found at https://github.com/nmboffi/spin_glass_evodyn .

59 BASIC BIOLOGICAL SCIENCES↗

How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution

The adaptive dynamics of evolving microbial populations takes place on a complex fitness landscape generated by epistatic interactions. The population generically consists of multiple competing strains, a phenomenon known as clonal interference. Microscopic epistasis and clonal interference are central aspects of evolution in microbes, but their combined effects on the functional form of the population’s mean fitness are poorly understood. Here, we develop a computational method that resolves the full microscopic complexity of a simulated evolving population subject to a standard serial dilution protocol. Through extensive numerical experimentation, we find that stronger microscopic epistasis gives rise to fitness trajectories with slower growth independent of the number of competing strains, which we quantify with power-law fits and understand mechanistically via a random walk model that neglects dynamical correlations between genes. We show that increasing the level of clonal interference leads to fitness trajectories with faster growth (in functional form) without microscopic epistasis, but leaves the rate of growth invariant when epistasis is sufficiently strong, indicating that the role of clonal interference depends intimately on the underlying fitness landscape. The simulation package for this work may be found at https://github.com/nmboffi/spin_glass_evodyn .

59 BASIC BIOLOGICAL SCIENCES↗

Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networks

Microscopic images from multiple modalities can produce plentiful experimental information. In practice, biological or physical constraints under a given observation period may prevent researchers from acquiring enough microscopic scanning. Recent studies demonstrate that image synthesis is one of the popular approaches to release such constraints. Nonetheless, most existing synthesis approaches only translate images from the source domain to the target domain without solid geometric associations. To embrace this challenge, we propose an innovative model architecture, BANIS, to synthesize diversified microscopic images from multi-source domains with distinct geometric features. The experimental outcomes indicate that BANIS successfully synthesizes favorable image pairs on C. elegans microscopy embryonic images. To the best of our knowledge, BANIS is the first application to synthesize microscopic images that associate distinct spatial geometric features from multi-source domains.

Wang, Dali↗

Microscopic Theory of Nuclear Fission

Nuclear fission represents the ultimate test for microscopic theories of nuclear structure and reactions. Fission is a large-amplitude, time-dependent phenomenon taking place in a self-bound, strongly interacting many-body system. It should, at least in principle, emerge from the complex interactions of nucleons within the nucleus. The goal of microscopic theories is to build a consistent and predictive theory of nuclear fission by using as only ingredients protons and neutrons, nuclear forces, and quantum many-body methods. Thanks to a constant increase in computing power, such a goal has never seemed more within reach. This chapter gives an overview both of the set of techniques used in microscopic theories to describe the fission process and of some recent successes achieved by this class of methods.

Nuclear physics and radiation physics↗

Macroscopic instructions vs microscopic operations in quantum circuits

In many experiments on microscopic quantum systems, it is implicitly assumed that when a macroscopic procedure or “instruction” is repeated many times – perhaps in different contexts – each application results in the same microscopic quantum operation. But in practice, the microscopic effect of a single macroscopic instruction can easily depend on its context. If undetected, this can lead to unexpected behavior and unreliable results. Here, we design and analyze several tests to detect context-dependence. They are based on invariants of matrix products, and while they can be as data intensive as quantum process tomography, they do not require tomographic reconstruction, and are insensitive to imperfect knowledge about the experiments. We also construct a measure of how unitary (reversible) an operation is, and show how to estimate the volume of physical states accessible by a quantum operation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Microscopic Dynamics Controls Coupling and Cluster Formation in Brush Particle Solids

Thermodynamics-based models predict the structure of polymer-grafted nanoparticles (PGNs) as well as their assembly behavior based on geometric parameters such as particle size, degree of polymerization, and density of grafted chains. The role of microscopic polymer dynamics, such as the mobility of repeat units in the melt state, in the evolution of the structure and properties remains unknown. Brillouin light spectroscopy (BLS), due to its capability to concurrently discern the local and global elastic properties of PGN assemblies, enables the probing of microscopic processes, such as brush interdigitation, sensitive to the annealing of the assembly. For poly(methyl methacrylate) (PMMA)-grafted silica (SiO 2 ) PGNs in the dry powder state and annealed above the glass transition temperature, BLS revealed fully reversible local elasticity, indicative of limited interdigitation between adjacent PGNs. This contrasts with polystyrene (PS)−SiO 2 analogs that displayed ready (and irreversible) fusion of brush layers during annealing. The retardation of brush interdigitation in PMMA-grafted systems is surprising, given the similar thermomechanical properties of both polymers, and is rationalized as the consequence of higher friction between PMMA repeats compared to PS. Microscopic dynamics thus has a profound impact on the kinetic path of structure (and property) evolution and thus should be considered during the processing of PGNs into functional hybrid materials.

chemical structure↗

Microscopic Manipulation of Ferroelectric Domains in SnSe Monolayers at Room Temperature

Two-dimensional (2D) van der Waals ferroelectrics provide an unprecedented architectural freedom for the creation of artificial multiferroics and nonvolatile electronic devices based on vertical and coplanar heterojunctions of 2D ferroic materials. Nevertheless, controlled microscopic manipulation of ferroelectric domains is still rare in monolayer-thick 2D ferroelectrics with in-plane polarization. Here we report the discovery of robust ferroelectricity with a critical temperature close to 400 K in SnSe monolayer plates grown on graphene and the demonstration of controlled room-temperature ferroelectric domain manipulation by applying appropriate bias voltage pulses to the tip of a scanning tunneling microscope (STM). This study shows that STM is a powerful tool for detecting and manipulating the microscopic domain structures in 2D ferroelectric monolayers, which are difficult for conventional approaches such as piezoresponse force microscopy, thus facilitating the hunt for other 2D ferroelectric monolayers with in-plane polarization with important technological applications.

2D ferroelectric↗

Microscopic Origins of the Nonlinear Behavior of Particle-Filled Rubber Probed with Dynamic Strain XPCS

The underlying microscopic response of filler networks in reinforced rubber to dynamic strain is not well understood due to the experimental difficulty of directly measuring filler network behavior in samples undergoing dynamic strain. This difficulty can be overcome with in situ X-ray photon correlation spectroscopy (XPCS) measurements. The contrast between the silica filler and the rubber matrix for X-ray scattering allows us to isolate the filler network behavior from the overall response of the rubber. This in situ XPCS technique probes the microscopic breakdown and reforming of the filler network structure, which are responsible for the nonlinear dependence of modulus on strain, known in the rubber science community as the Payne effect. These microscopic changes in the filler network structure have consequences for the macroscopic material performance, especially for the fuel efficiency of tire tread compounds. In this work, we elucidate the behavior with in situ dynamic strain XPCS experiments on industrially relevant, vulcanized rubbers filled (13 vol %) with novel air-milled silica of ultrahigh-surface area (UHSA) (250 m 2 /g). The addition of a silane coupling agent to rubber containing this silica causes an unexpected and counterintuitive increase in the Payne effect and decrease in energy dissipation. For this rubber, we observe a nearly two-fold enhancement of the storage modulus and virtually equivalent loss tangent compared to a rubber containing a coupling agent and conventional silica. Interpretation of our in situ XPCS results simultaneously with interpretation of traditional dynamic mechanical analysis (DMA) strain sweep experiments reveals that the debonding or yielding of bridged bound rubber layers is key to understanding the behavior of rubber formulations containing the silane coupling agent and high-surface area silica. These results demonstrate that the combination of XPCS and DMA is a powerful method for unraveling the microscale filler response to strain which dictates the dynamic mechanical properties of reinforced soft matter composites. With this combination of techniques, we have elucidated the great promise of UHSA silica when used in concert with a silane coupling agent in filled rubber. Such composites simultaneously exhibit large moduli and low hysteresis under dynamic strain.

36 MATERIALS SCIENCE↗