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At least 1,063 records · Page 59

Using "AI Poincare" to analyze non-linear integrable optics

This study dives into the applicability of using automated discovery of conserved quantities in dynamical systems relevant to accelerator physics. Specifically, we explore the performance of AI Poincaré in analyzing numerical trajectory data obtained using the McMillan system of non-linear integrable optics. A comprehensive evaluation of the algorithm's performance is conducted through diverse methodologies. These include the analysis of the estimated number of conserved quantities embedded in a dataset and the deviation of interpolated points on the inferred manifold with respect to points in actually in the dataset. the investigation identifies an optimal range of perturbation distances where the underlying manifold extraction algorithm inside AI Poincaré exhibits optimal performance. Additionally, an improved neural network architecture is proposed based on the observed results. Finally, we apply the algorithm to preliminary experimental data from the Integrable Optics Test Accelerator at Fermilab to successfully infer the number of conserved quantities even in the presence of fast decoherence of the measured signal.

Osmanov, Lazare [Free U. Tbilisi]↗

A Roadmap for a Lightning Modeling Grand Challenge

This document is a roadmap for building an interconnected model of the physical processes that produce a lightning discharge, and its observable optical and radio signals. We call this a Lightning Modeling Grand Challenge, recognizing that significant effort and coordination of human and financial resources is required to realize the capability. The roadmap serves to outline the coordination of resources necessary to enable stitching together existing knowledge and model components to make a lightning prediction, and to test these predictions with observations. Such a capability does not currently exist. The roadmap is motivated not only by a spirit of scientific inquiry, but by practical challenges faced by US Federal and societal stakeholders. Advancements in lightning observations have outpaced our tests of integrated understanding, leaving many stakeholders unsure how to design their missions to properly detect and discriminate lightning, and unsure how to apply the sometimes-disagreeing lightning signals from diverse instruments. The time is right to connect existing theories and models to support stakeholders in understanding the signals they observe, for needs as diverse as climate monitoring, national security, weather forecasting, public safety, and protection of natural and built environments. The roadmap’s two main technical sections describe the components of a linked physical model, followed by a description of models of lightning signals and sensors that are driven by outputs from the physical model. The goal is to predict the time-varying physical properties of lightning that are self-consistent with the thunderstorm’s structure and dynamics. These lightning signals then propagate through the storm, with realistic dispersion and attenuation, to receivers on the ground or in space. At a high level, the model begins with weather (cloud) model output, including explicit prediction of the electrification of cloud particles. The cloud’s electrical structure drives a model of lightning physics, from initiation, through channel development, and discharges along those channels. Key lightning parameters, such as the temperature and currents in the channel, and their space and time distribution, are then used to produce optical and electromagnetic signal sources that propagate to modeled receivers. This architecture therefore generates a dataset suitable for comparison to existing and envisioned observing systems. The need for additional measurements and field campaigns to support model development is described. In each model sub-component, inputs, outputs, uncertainties, evaluation methods, and next steps are summarized, interleaved with references to the scientific literature. Identifying boundaries between the model sub-components aids in segmenting an integrated, complex model into practical work packages and system sub-components, allowing a diverse team to contribute and maintain the system. We estimate that at least five years of effort and a $\$$10M initial investment is necessary to make a significant step forward. Mechanisms to facilitate community coordination, including annual workshops and open-source code repositories, are described.

54 ENVIRONMENTAL SCIENCES↗

Beam results for the new super-conducting booster at Jefferson Lab

The performance results of a new super-conducting booster for the CEBAF injector at Jefferson Lab, could be of interest for other similar electron injectors. A recent addition of this new booster has provided us the ability to achieve a more adiabatic acceleration and therefore an improvement to the beam dynamics and beam brightness. It has also simplified the design and operation of the section of the injector responsible for accelerating the electron beam from a few hundred keV to several MeV (typically 6.7 MeV). The addition of the new booster was part of an upgrade to the CEBAF injector to improve the beam quality for future physics experiments with high sensitivity to beam quality. The booster consists of two cavities: a 2-cell cavity followed by a 7-cell cavity. This combination allows for a wide range of input electron beam energies, from 130 keV to more than 300 keV. In fact, during the last year, the booster was successfully operated with 140,180, and 200 keV input beam energies as the electron gun was being upgraded. This paper describes the new booster, presents beam optics data results from different beam studies, commissioning, and the physics quality beam operation.

Accelerator Physics↗

Signal processing to reduce dark noise impact in precision timing

We introduce a technique to mitigate the effects of low frequency noise on precision timing. The example of Dark Count Noise Rate (DCR) in Silicon Photomultipliers (SiPMs) is emphasized. This technique exploits the correlation between time shifts on the leading edge of a signal and the residual slope of the baseline (due to noise) which remains after baseline subtraction. In fast timing applications (such as for Time-of-flight particle ID) the signal arrival time is typically captured on the signal leading edge. The signal risetime is often fixed by the physics of the sensor and input circuit. Then accurate pulse timing can be achieved by correcting a leading edge threshold time (depending on a slope proportional to both the Amplitude and the risetime) to a “constant fraction” time. This compensation for time walk due to amplitude fluctuations breaks down once we introduce interference from low frequency noise on the leading edge. In this paper we demonstrate that an additional measurement of the slope at threshold can be used to correct for this noise jitter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Topological Materials for Functional Optoelectronic Devices

The recent realization of topology as a mathematical concept in condensed matter systems has shattered Landau's widely accepted classification of phases by spontaneous symmetry breaking as he famously said, “a particular symmetry property exists or does not exist.” Topological materials (TMs) such as topological insulators and topological semimetals, are characterized by properties that depend on the topology of the band structure. Such dependence has drastic implications on the optical, electrical, and thermal properties of the material. Fundamental physics of TMs is currently under active research in condensed matter, materials science, and high energy physics. Here, recent advances in exploiting the unique properties of TMs to realize functional optoelectronic devices are surveyed. Current and future applications that are, or may be, enabled by their unique properties are discussed. Although many theoretical ideas have been proposed over the past decade or so on using TMs in optoelectronic applications, the focus will be on experimentally realized devices.

36 MATERIALS SCIENCE↗

Achieving clean production with nanostructured coated milling tools dry machining low carbon steel

The advancement of clean production using nanostructured materials in subtractive manufacturing processes has focused on replacing the use of liquid lubrication with solid lubricants coated to conventional cutting tools machining low carbon steel (~ 0.2 wt. % carbon). However, little is known about the wear mechanisms that dominate such tools when coated with functional graded nanostructured coatings. The present study follows an international standard for characterizing such wear (ISO 8688) but uses advanced measurement techniques such as x-ray fluorescence technology to measure the diffusion of chemical species from tool to workpiece and vice versa, that contributes to tool wear with the view to enhance the principles of cleaner production. The results show that when commercially-available tools coated with the appropriate functionally graded industrial coating, diffusion does not take place and creates an effective chemical barrier during machining. The experimental methods used in the study include machining workpieces using a CNC milling machine, tachometer for measuring spindle speed, dynamometer for measuring cutting forces, infra-red camera for measuring cutting temperatures, chemical species diffusion wear using x-ray florescence detector, and an optical microscope for measuring tool wear. Coupled with the physical measurement of wear, it is concluded that mechanical wear dominates the milling of a low carbon steel and that thermal properties of the coatings do not correlate with such wear. It is also concluded that flank wear as a function of volume of workpiece removed and machining duration (machining index) is a sound method for assessing the transition of the stages of wear during clean machining operations. The present study not only has implication for the design of better cutting tools, but also advances dry machining processes that eliminate the use of liquid lubricants making subtractive production processes cleaner. The main conclusions drawn from this study show that coated tools have a longer life under dry conditions compared to uncoated tools and that there is no correlation between coating properties and tool wear. In conclusion, diffusion of chemical species into the cut chips did not occur because of the lack of thermally induced chemical wear of the cutting tool and that wear is caused by the gradual erosion of the flank face due to the chip abrading the cutting tool.

36 MATERIALS SCIENCE↗

Determining processing behaviour of pure Cu in laser powder bed fusion using direct micro-calorimetry

We report copper is challenging to process by laser powder bed fusion (LPBF) given its high reflectivity at common infrared laser diode wavelengths and high thermal conductivity. Successful deposition of copper in a predictable and repeatable fashion relies on understanding the development of the keyhole melting regime, as well as heating, melting, boiling and vapour formation behaviour when interacting with a laser beam within an LPBF environment. In this study, in situ optical absorptivity measurements are used to clarify the complex physics of the laser material interaction. Absorptivity of laser energy is measured using direct micro-calorimetry and compared to melt pool depth in correlation to processing parameters. The measured absorptivity for a 100 μm layer thickness of powder was found to be approximately four times higher than that of the bare polished discs. It was also shown that high laser power above 500 W and scan speed up to 150 mm/s are appropriate for effective melting of the powder layer, with these parameters overcoming the threshold required to achieve keyhole melting. This is explained by multiple reflections withing the powder particles and the lower thermal conductivity of packed powder in comparison to bare discs. Melt pool formation was found to be highly unstable and an explosive behavior was observed when in the keyhole regime, caused by high fluctuations in absorptivity values. This work demonstrates calorimetry can be used to monitor melting behaviour in a real-time fashion during processing for this challenging to process material, thereby avoiding unnecessary parametric optimisation. In addition, the parametric window for optimum processing revealed here can inform future work.

36 MATERIALS SCIENCE↗

Size Dependence of Lattice Parameter and Electronic Structure in CeO2 Nanoparticles

Intrinsic properties of a compound (e.g. electronic structure, crystallographic structure, optical and magnetic properties) define notably its chemical and physical behavior. In the case of nanomaterials, these fundamental properties depend on the occurrence of quantum mechanical size effects and on the considerable increase of the surface to bulk ratio. However, the literature on this size-dependence and on the involved mechanisms is quite elusive and scarce. Here, we explore the size-dependence of both crystal and electronic properties of CeO2 nanoparticles (NPs) with different sizes by state-of-the art spectroscopic techniques. XRD, XPS and HERFD-XANES demonstrate that the as-synthesized NPs crystallize in the fluorite structure and they are predominantly composed of CeIV ions. The strong dependence of the lattice parameter with the NPs size was attributed to the presence of adsorbed species at the NPs surface thanks to FTIR and TGA measurements. In addition, the size-dependence of the eg level in the Ce LIII XANES spectra was experimentally observed by HERFD-XANES and confirmed by theoretical calculations.

Lanthanide, CeO2, HEFRD-XANES, Electronic structur↗

Pore-Scale Microenvironments Control Anthropogenic Carbon Mineralization Outcomes in Basalt

Thin sections and hand samples from 50 sidewall cores from the Wallula Basalt Pilot Demonstration, a basaltic carbon sequestration demonstration, provided the opportunity for the in-depth analysis of carbon mineralization induced by the injection of supercritical CO 2 . In this study, we used optical petrography and scanning electron microscopy to characterize the physical and chemical characteristics of the basalt components influenced by carbon mineralization reactions from all available hand samples and thin sections within the three CO 2 injection zones and caprock flow interiors. We found extensive carbonate mineralization, mostly in the form of nodules that were shown to be chemically zoned: Ca-dominant in the core regions and Ca-bearing Fe-dominant in the outer regions. Carbonate mineralization also took the form of fracture-filling carbonate cement, and acicular aragonite was also observed. Overall, we clarified the structural and paragenetic relationships between newly formed minerals, identifying a new fibro-palagonite-like, poorly crystalline silicate phase that grew on the carbonate nodules and pore-lining zeolites. Here we observed Fe-dominant carbonate precipitates surrounding acicular aragonite and rhombohedral Ca-carbonate cores, whereas previous studies of these zoned nodules did not observe these structures. A comprehensive accounting of the carbon mineralization products is vital to understand and predict the behavior of supercritical CO 2 in the subsurface given both the diversity of the host rock between and within injection zones, especially considering that the morphology and chemistry of the diverse precipitates are influenced by the pore-scale microenvironments of the basalt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulating charged defects at database scale

Point defects have a strong influence on the physical properties of materials, often dominating the electronic and optical behavior in semiconductors and insulators. The simulation and analysis of point defects is, therefore, crucial for understanding the growth and operation of materials, especially for optoelectronics applications. In this work, we present a general-purpose Python framework for the analysis of point defects in crystalline materials as well as a generalized workflow for their treatment with high-throughput simulations. The distinguishing feature of our approach is an emphasis on a unique, unit cell, structure-only, definition of point defects which decouples the defect definition, and the specific supercell representation used to simulate the defect. This allows the results of first-principles calculations to be aggregated into a database without extensive provenance information and is a crucial step in building a persistent database of point defects that can grow over time, a key component toward realizing the idea of a “defect genome” that can yield more complex relationships governing the behavior of defects in materials. We demonstrate several examples of the approach for three technologically relevant materials and highlight current pitfalls that must be considered when employing these methodologies as well as their potential solutions.

36 MATERIALS SCIENCE↗

Spatial resolution in secondary-electron microscopy

Here, we first review the significance of resolution and contrast in electron microscopy, and the effect of the electron optics on these two quantities. We then outline the physics of the generation of secondary electrons (SE) and their transport and emission from the surface of a specimen. Contrast and resolution are discussed for different kinds of SE imaging in scanning (SEM) and scanning-transmission (STEM) instruments, with some emphasis on the observation of individual atoms and atomic columns in a thin specimen. The possibility of achieving atomic resolution from a bulk specimen at SEM energies is also considered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Topological solitons in square-root graphene nanoribbons controlled by electric fields

Conjugational defects, also known as solitons, play an important role in the electronic, magnetic, and optical properties of materials. Understanding solitons can uncover intriguing physics and provide insights for designing quantum materials with tailored band structures and electronic properties. Here we propose a framework to create and control solitons via topological phase transitions in a class of graphene nanoribbons (GNRs) called square-root GNRs, using a transverse electric field. To demonstrate the experimental feasibility, we design and synthesize a representative GNR with a bottom-up approach, with first-principles calculations revealing topological soliton states at the domain wall induced by the electric field. In conclusion, the framework introduced in this work can potentially enable direct manipulation of solitons and provide a platform to study them systematically.

36 MATERIALS SCIENCE↗

Development and Validation of Predictive Models for In-Cylinder Radiation and Wall Heat Transfer

The lack of accurate submodels for in-cylinder radiation and heat transfer has been identified as a key shortcoming in developing truly predictive, physics-based computational fluid dynamics (CFD) models that can be used to develop and design combustion systems for advanced high-efficiency, low-emissions engines. Measurements of wall boundary layers in engines show discrepancies of up to 100% with respect to standard CFD boundary layer models. And analysis of in-cylinder radiation based on the most recent spectral property databases and high-fidelity radiative transfer equation solvers has shown that at operating pressures and exhaust-gas recirculation levels typical of modern compression-ignition truck engines, molecular gas radiation (mainly carbon dioxide and water vapor) can be more important than soot particle radiation, and that a significant fraction of the emitted radiation (50% or more) can be reabsorbed before reaching the walls, thereby acting to redistribute energy in the combustion chamber. In this project, an integrated experimental and simulation approach has been used to generate new physical insight into in-cylinder heat-transfer processes in engines, and to develop computationally practicable CFD-based models that accurately represent the physics. New experimental data have been taken in an optically accessible single-cylinder research engine, and in a multi-cylinder production engine. Those data have provided new insight into the radiative environment in engines. New CFD models have been developed and validated for in-cylinder heat transfer, focusing mainly on radiative heat transfer and coupling between turbulent boundary layer wall heat transfer and radiative heat transfer. The CFD models have been developed and implemented in an open-source software framework that can be shared with other researchers. The models are compatible both with unsteady Reynolds-averaged Navier Stokes (URANS) formulations and with large-eddy simulations (LES) of in-cylinder processes in engines.

02 PETROLEUM↗

Distributed sensing of electromagnetic components using optical fiber based methods

An OFDR based fiber-optics sensor for distributed real-time temperature rise monitoring of a transformer in operation has been disclosed. The fiber-optic sensor provides an effective solution to monitoring the physical structures of the transformer core, as well as accurately detecting the non-uniform temperature distribution inside the transformer, and thus provides innovative feedback to the transformer design by minimizing the core losses. Additionally, the method may be responsive to the presence of magnetic and electric fields, as well as responsive to various chemical species. The method allows novel approaches to real-time asset monitoring of power transformers while operational.

Ohodnicki, Paul R.↗

Physically realistic, parametric model for excitonic critical point parabolic band oscillators

Critical point parabolic band (CPPB) oscillators are often useful to model the optical response of semiconductor materials, such as hybrid organic–inorganic lead halide-based perovskites, to incident photons in the form of the complex dielectric function (ε=ε1+iε2) spectra. Some models of ε using CPPB oscillators are not guaranteed Kramers–Kronig (KK) consistent (and therefore not physically realistic), may have excess or arbitrary parameter values, or may require prohibitively long computational time when used to fit ellipsometric spectra. For excitonic CPPBs, commonly used to describe the optical response of hybrid organic–inorganic lead halide-based perovskite materials, a physically realistic, parametric model of ε is developed from the KK relationship between ε1 and ε2 for a number of CPPB oscillators with an Urbach tail below the lowest direct transition. This parametric model is shown to produce the same line shape reported from previous works accurately and more quickly than other available KK-consistent CPPB models.

Physics↗

Gain roll-off in cadmium selenide colloidal quantum wells under intense optical excitation

Colloidal quantum wells, or nanoplatelets, show among the lowest thresholds for amplified spontaneous emission and lasing among solution-cast materials and among the highest modal gains of any known materials. Using solution measurements of colloidal quantum wells, this work shows that under photoexcitation, optical gain increases with pump fluence before rolling off due to broad photoinduced absorption at energies lower than the band gap. Despite the common occurrence of gain induced by an electron–hole plasma found in bulk materials and epitaxial quantum wells, under no measurement conditions was the excitonic absorption of the colloidal quantum wells extinguished and gain arising from a plasma observed. Instead, like gain, excitonic absorption reaches a minimum intensity near a photoinduced carrier sheet density of 2 × 10 13 cm –2 above which the absorption peak begins to recover. To understand the origins of these saturation and reversal effects, measurements were performed with different excitation energies, which deposit differing amounts of excess energy above the band gap. Across many samples, it was consistently observed that less energetic excitation results in stronger excitonic bleaching and gain for a given carrier density. Transient and static optical measurements at elevated temperatures, as well as transient X-ray diffraction of the samples, suggest that the origin of gain saturation and reversal is a heating and disordering of the colloidal quantum wells which produces sub-gap photoinduced absorption.

36 MATERIALS SCIENCE↗

Layered metals as polarized transparent conductors

The quest to improve transparent conductors balances two key goals: increasing electrical conductivity and increasing optical transparency. To improve both simultaneously is hindered by the physical limitation that good metals with high electrical conductivity have large carrier densities that push the plasma edge into the ultra-violet range. Technological solutions reflect this trade-off, achieving the desired transparencies only by reducing the conductor thickness or carrier density at the expense of a lower conductance. Here we demonstrate that highly anisotropic crystalline conductors offer an alternative solution, avoiding this compromise by separating the directions of conduction and transmission. We demonstrate that slabs of the layered oxides Sr 2 RuO 4 and Tl 2 Ba 2 CuO 6+δ are optically transparent even at macroscopic thicknesses >2 μm for c-axis polarized light. Underlying this observation is the fabrication of out-of-plane slabs by focused ion beam milling. This work provides a glimpse into future technologies, such as highly polarized and addressable optical screens.

36 MATERIALS SCIENCE↗