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At least 91 records · Page 5

Simulation of an inductively coupled plasma with a two-dimensional Darwin particle-in-cell code

A two-dimensional particle-in-cell code for the simulation of low-frequency electromagnetic processes in laboratory plasmas has been developed. The code uses the Darwin method omitting the electromagnetic wave propagation. The Darwin method separates the electric field into solenoidal and irrotational parts. The solenoidal electric field is calculated with a new algorithm based on the equation for the electric field vorticity. The system of linear equations in the new algorithm is readily solved using a standard iterative method. The irrotational electric field is the electrostatic field calculated with the direct implicit algorithm. The code is verified by reproducing the two-stream instability, electron electromagnetic waves, and shear Alfvén waves. The code is applied to simulate an inductively coupled plasma with the driving current flowing around the plasma region. In this simulation, a ring of dense plasma forms at the initial stage but then the density becomes maximal in the center and decays monotonically toward the walls. The skin effect is in the transitional mode between local and non-local, and the electron velocity distribution function is non-Maxwellian.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Tools for genetic engineering and gene expression control in Novosphingobium aromaticivorans and Rhodobacter sphaeroides

ABSTRACT Alphaproteobacteria have a variety of cellular and metabolic features that provide important insights into biological systems and enable biotechnologies. For example, some species are capable of converting plant biomass into valuable biofuels and bioproducts that have the potential to contribute to the sustainable bioeconomy. Among the Alphaproteobacteria, Novosphingobium aromaticivorans , Rhodobacter sphaeroides , and Zymomonas mobilis show promise as organisms that can be engineered to convert extracted plant lignin or sugars into bioproducts and biofuels. Genetic manipulation of these bacteria is needed to introduce engineered pathways and modulate expression of native genes with the goal of enhancing bioproduct output. Although recent work has expanded the genetic toolkit for Z. mobilis , N. aromaticivorans and R. sphaeroides still need facile, reliable approaches to deliver genetic payloads to the genome and to control gene expression. Here, we expand the platform of genetic tools for N. aromaticivorans and R. sphaeroides to address these issues. We demonstrate that Tn 7 transposition is an effective approach for introducing engineered DNA into the chromosome of N. aromaticivorans and R. sphaeroides . We screen a synthetic promoter library to identify isopropyl β-D-1-thiogalactopyranoside-inducible promoters with regulated activity in both organisms (up to ~15-fold induction in N. aromaticivorans and ~5-fold induction in R. sphaeroides ). Combining Tn 7 integration with promoters from our library, we establish CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) interference systems for N. aromaticivorans and R. sphaeroides (up to ~10-fold knockdown in N. aromaticivorans and R. sphaeroides ) that can target essential genes and modulate engineered pathways. We anticipate that these systems will greatly facilitate both genetic engineering and gene function discovery efforts in these species and other Alphaproteobacteria. IMPORTANCE It is important to increase our understanding of the microbial world to improve health, agriculture, the environment, and biotechnology. For example, building a sustainable bioeconomy depends on the efficient conversion of plant material to valuable biofuels and bioproducts by microbes. One limitation in this conversion process is that microbes with otherwise promising properties for conversion are challenging to genetically engineer. Here we report genetic tools for Novosphingobium aromaticivorans and Rhodobacter sphaeroides that add to the burgeoning set of tools available for genome engineering and gene expression in Alphaproteobacteria. Our approaches allow straightforward insertion of engineered pathways into the N. aromaticivorans or R. sphaeroides genome and control of gene expression by inducing genes with synthetic promoters or repressing genes using CRISPR interference. These tools can be used in future work to gain additional insight into these and other Alphaproteobacteria and to aid in optimizing yield of biofuels and bioproducts.

Hall, Ashley N.

Development of magnetic field monitoring system for the MAGIS-100 experiment

The MAGIS-100 collaboration is building a long-baseline atom interferometer designed to investigate dark matter, novel forces, gravitational waves, and quantum science. A major design challenge is external, time-varying magnetic fields, the effect of which can mimic gravitational waves or expected dark matter signals. Several mitigations will be enacted, including mu-metal shielding and a suite of magnetometers. This presentation will discuss the development of a magnetic field monitoring system based on commercial magneto-inductive sensors to be installed at several points along the interferometer.

Arce, Edwin [Unlisted; Fermilab]

Non-DNA radiosensitive targets that initiate persistent behavioral deficits in rats exposed to space radiation

Predicting future CNS risks for astronauts during deep-space missions will rely substantially on ground-based rodent data with space-relevant ions and behaviors. For rats, the accumulated evidence indicates that less densely ionizing radiation, such as 4 He and 12 C ions, induce behavior deficits at lower doses than densely ionizing ions, such as 48 Ti and 56 Fe. However, this observation conflicts with standard somatic radiobiology, in which densely ionizing ions are generally more effective than less densely ionizing ions, and where the DNA/nucleus is the accepted target for radiation-induced tumorigenesis, cytogenetic aberrations, genetic mutations, and reproductive cell death. To gain deeper insight into the subcellular nature of the radiation targets for behavior risks, we compared the effects of dose, fluence, and linear energy transfer (LET) of 4 He and 56 Fe particles using existing datasets for four distinct behavioral outcomes in rats: elevated plus maze (EPM-anxiety), novel object recognition (NOR-memory), operant responding (OR-response to environmental stimuli), and attentional set-shifting (ATSET-cognitive flexibility). We confirmed that less densely ionizing particles (except protons) showed ~100-fold lower threshold doses than densely ionizing particles for behavioral deficits (0.1–1 cGy for 4 He vs. 15–100 cGy for 56 Fe). However, when analyzed by fluence the behavioral responses converged, indicating that 4 He and 56 Fe were equally effective on a per-track basis. When analyzed by LET, there were ~100-fold differences in the LET for maximum effectiveness for behavioral deficits and DNA endpoints (~1 vs ~100 keV/μm, respectively). These unique features of radiation-induced behavioral deficits (high sensitivity to particles in the 1-keV/μm range, insensitivity to protons in the 0.2 keV/μm range, and isofluence dependence for particles with LET>1 keV/μm) provide evidence in support of a new hypothesis of sub-micron sized radiosensitive targets for behavioral effects consistent with the thickness of plasma membranes and/or small subcellular structures, smaller than a whole synapse. Like our behavior findings, mouse immature oocyte killing which is known to have a plasma membrane target was also better explained by fluence, rather than dose. In contrast, fluence analyses for DNA/nuclear endpoints in somatic cells (e.g., tumor induction, chromosome aberrations) showed opposite results, suggesting that behavior targets are not DNA. Our findings raise questions regarding the identity of subcellular targets and the multi-cellular functional unit for behavior risks, low-dose susceptibility, and generalizability from rat to other species and astronauts.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN

Why Seeding Works When Nucleation Barriers Vanish

This paper explains why seeds can speed up crystallization even when the formation of new crystal nuclei is not the slow step. In zeolite synthesis, local crystalline order can form relatively early, but the material may still appear poorly crystalline by X-ray diffraction because many small crystallites are misoriented and lack long-range coherence. Using coarse-grained molecular simulations, the study showed that seeds help solve this coherence problem. Rather than primarily lowering a nucleation barrier, seeds impose a common orientation on nearby growing crystallites, allowing them to merge into larger, better aligned domains. This accelerates the development of X-ray-detectable crystallinity even if the total amount of locally ordered material has not changed much. The work changes how induction times in zeolite synthesis should be interpreted: the delay before X-ray crystallinity appears can reflect the time needed to build long-range structural coherence, not simply the time needed to form crystalline material. This provides a new explanation for why seeding is effective in growth-limited crystallization and offers design principles for controlling crystallization rate and crystal quality.

36 MATERIALS SCIENCE

Chiral induction at the nanoscale and spin selectivity in electron transmission in chiral methylated BEDT-TTF derivatives

Great efforts have been made in the last few decades to realize electronic devices based on organic molecules. A possible approach in this field is to exploit the chirality of organic molecules for the development of spintronic devices, an applicative way to implement the chiral-induced spin selectivity (CISS) effect. In this work we exploit enantiopure tetrathiafulvalene (TTF) derivatives as chiral inducers at the nanoscale. The aim is to make use of TTF's well-known and unique semiconducting properties, to be expressed in the fields of enantio-selectivity and the chiral-induced spin selectivity (CISS) effect. Further, the experimental results shown in this paper further demonstrate how chirality and spin are deeply interrelated, as foreseen within the CISS effect theory, paving the way for the application of TTF derivatives in the field of spintronics. In this work, we demonstrate that tetramethyl-bis(ethylenedithio)-tetrathiafulvalene (TM-BEDT-TTF) (1) behaves as an efficient spin filter, as evidenced by magneto-atomic force microscopy (mc-AFM) measurements. Additionally, it is shown to be effective in transferring chirality to CdS/CdSe core–shell nanoparticles, as inferred from the analysis of circularly resolved photoluminescence spectra. This makes 1 a promising candidate for a variety of applications, ranging from plasmonics to quantum computing.

77 NANOSCIENCE AND NANOTECHNOLOGY

Nonequilibrium dynamics of two-level systems directly after cryogenic alternating bias

Two-level systems (TLSs) are a dominant decoherence mechanism in superconducting qubits, microwave kinetic inductance detectors, and quantum dots. TLSs are tunneling states commonly found in amorphous materials and interfaces, which interact electromechanically, leading to energy loss. Fluctuations in the frequency of the TLSs are a significant problem for qubit operation and force recalibration every few hours. In this study, we probe the effect of alternating bias at cryogenic temperatures on TLSs in a purpose-built LC oscillator. When an in situ alternating bias is applied, the steady-state spectra of the TLSs disappear. Spectroscopy reveals transient behavior, in which the TLS frequency fluctuates on the order of minutes. Thermal cycling above 10 K reverses these effects, restoring the TLS spectrum to its original state. Importantly, the intrinsic loss tangent of the LC oscillator remains unchanged before and after the application of the alternating bias. We propose that the disappearance of the steady-state spectrum is caused by nonequilibrium energy buildup from strain in the oxide film introduced by the pulsed voltage-bias sequence. Understanding this nonequilibrium energy could shed light on TLS fluctuations and reduce the calibration requirements for qubits.

general physics

Machine Learning–Guided Boolean Matrix Inference for Real-Time O-RAN Conflict Detection

Open Radio Access Networks (O-RAN) are emerging, software-driven cellular architectures that promote flexibility by enabling components from different vendors to interoperate. Multiple control applications called xApps can independently adjust network parameters in near real time, often without awareness of each other's actions. This creates a system highly prone to unintended conflicts and performance degradation due to the inherent complexity of such openness. To model such systems and ultimately prevent or mitigate xApp conflicts, it is essential to understand the dynamic relationships between xApps (A), the control parameters they adjust (P), and the resulting KPI responses (K). While the mappings from A to P and from K to A can often be derived from xApp specifications, the relationship from P to K is typically hidden within the system’s dynamics and must be inferred from observed data. We propose a novel data-driven Boolean inference framework that uncovers the hidden P?K dependencies using machine learning and interpretable rule induction. Continuous parameters and KPIs are first binarized using decision tree classifiers, and a binary influence matrix L is then inferred by solving Boolean matrix equations over time. This compact representation improves interpretability and enables real-time tracking of dynamically evolving parameter-KPI dependencies. We demonstrate the effectiveness of our method in a realistic mobile handover scenario, where it accurately recovers the underlying logic and enables proactive conflict detection.

42 - ENGINEERING

Splat Quenching as a High Throughput Rapid Solidification Testing Method for Developing Additive Manufacturing Alloys

Splat quenching as a high throughput rapid solidification screening tool is evaluated. Samples were made using known alloys (SS316, IN625, Ti-5553) to evaluate and establish the microstructures for a variety of alloy systems as well as the predicted cooling rates. The samples are inductively heated and levitated prior to being struck between two platens that produce a high contact pressure and a thin sample resulting in cooling rates on the order of 10 6 to 10 7 K/s. Process parameters were evaluated with analytical models in addition to numerical simulations to provide an effect of process variables such as substrate material, melt superheat, and platen velocity on the resulting solidification. The splat thickness was found to be controlled by platen velocity, melt superheat, as well as the feedstock volume. The sample thickness is the key controlling factor for varying the average cooling rate experienced by the splat quenched sample. The splat quenching techniques can reach regions of rapid solidification space that meet and exceed laser and electron beam techniques across the sample. In conclusion, the results of the study provide a useful foundation in understanding the splat quenching technique and its potential as a low effort tool to explore rapid solidification effects on alloys.

Alloy Design

Portable fiber optic sensor for rare earth elements and other critical metals using photoluminescence methods

Rare earth elements and other metals are vital to a range of technologies that are used in the energy and defense sectors. However, monopolistic market conditions have caused significant concern over the stability of the critical metal supply chain, and this has spurred extensive efforts in many nations to produce these metals domestically, both from conventional sources such as mining and well as from unconventional sources such as coal and its utilization byproducts. Slow and expensive characterization methods pose a significant barrier for both metals prospecting and process monitoring. A promising solution to this challenge is the development of highly sensitive luminescent sensors for metals, which can offer low costs, portability, and sensitivity. Anionic zinc adeninate metal-organic frameworks (BioMOFs) are known to distinguishing and detect part-per-billion levels of terbium, europium, samarium, and dysprosium in water by sensitizing the narrow, element-specific emission bands from these lanthanides. Here, a BioMOF material is immobilized onto a large diameter, solarization-resistant fiber optic tip integrated with a portable, low-cost spectrometer for rare earth element sensing. Immobilizing the sensing material on fiber instead of dispersing the sensing material in solution offers several advantages: it facilitates solvent removal, which enhances luminescent signal from the sensitized lanthanides, and it also allows the BioMOF to be recycled for multiple uses. The sensing system was deployed on a simulated process stream and exhibited qualitative agreement with inductively-coupled plasma mass spectrometry for terbium and europium detection, highlighting the potential for the sensing system to be deployed for real-world applications. By using different sensing materials, the same portable sensor may be deployed to detect other energy relevant metals such as cobalt, providing a cost-effective and sensitive platform for critical metal characterization.

Crawford, Scott

Improved signal stability in inductively coupled plasma–atomic emission spectrometry through use of tandem spray chambers and surfactant addition

A search for causes of intermittent mid-term (about two hours) instability in emission signals from an inductively coupled plasma led to adoption of a tandem spray-chamber arrangement and subsequently to use of a surfactant (Triton X-100) to mitigate the remaining and newly found instabilities. Through a series of investigations, abrupt signal excursions in the tandem setup were traced to droplet coagulation and drainage inside the glass tube that connected the two spray chambers. However, the signal shifts were not the result of sample-solution release directly but rather to the influence of the underlying factors on plasma behavior. Experiments tailored to the study included not only examination of temporal signal behavior but also collection of long-term videos and measurement of radiofrequency characteristics of the plasma. The addition of a surfactant, Triton X-100, for signal-stability improvement is applicable not only to systems that employ tandem spray chambers but also to conventional single Scott-type chamber arrangements. Further, use of the surfactant was unsuccessful in overcoming “acid effects”, either of the steady-state or transient nature, and did not alter plasma background or analyte signals significantly.

Inductively coupled plasma–atomic emission spectro

Transient Catalytic Reaction Analysis Through Signal Defragmentation

The Temporal Analysis of Products (TAP) pulse response technique provides valuable insights into catalytic function and reaction kinetics. However, complex fragmentation patterns in the TAP mass spectrometry signals can complicate precise quantification, particularly when analyzing transient gas flux data typical of TAP experiments. This work demonstrates a standard defragmentation method that deconvolves transient TAP signals while maintaining the temporal resolution of the experiment. First, the integrals of calibration gas fluxes are used to determine the fingerprint fragmentation pattern and construct a fragmentation matrix. This matrix is then used to defragment experimental flux data at each recorded time point via a non-negative least squares regression. The effectiveness of this method is demonstrated using virtual data and control experiments with a TAP reactor system. The defragmentation is then applied to the more complex propane dehydrogenation reaction on a chromia/alumina catalyst, which can contain up to ten significant gas species in the reactor outlet. Initial propane pulsing reveals an induction period during which propane is fully oxidized to CO2, followed by partial reduction to CO. Afterwards, there is a transition in chemistries towards coking and propylene production. Our example illustrates a practical method for the accurate determination of the time-dependent reactant/product concentrations and rates for a thorough analysis of the propane dehydrogenation kinetics. This approach can be broadly applied to any transient mass spectrometry experiment for a better understanding of catalyst-reaction dynamics.

36 - MATERIALS SCIENCE

Thermal Gradient Effects on Redox Evolution and Volatility-Driven Fractionation in Ternary U/Ce/Cs Condensates

Understanding how thermal history influences redox evolution and chemical fractionation is essential for characterizing high-temperature condensation in complex materials, including nuclear debris. Here, we tested the hypothesis that distinct thermal regimes in a plasma flow reactor influence redox pathways and elemental partitioning in ternary U/Ce/Cs systems. A configurable plasma flow reactor was modified with an external tube furnace to impose two distinct thermal gradients: continuous ambient cooling and a furnace-assisted thermal hold-up near 1400 K followed by rapid cooling. Transmission electron microscopy characterized phase identity, morphology, and nanoscale element distributions, while inductively coupled plasma-mass spectrometry quantified bulk elemental ratios. Across both thermal regimes, uranium and cerium condensed as UO 2 and CeO 2 as dominant refractory oxide products. Uranium partially oxidized to α-UO 3 during extended ambient cooling, while furnace-assisted hold-up preserved UO 2 and produced partial reduction of cerium to Ce 2 O 3 . Cesium remained volatile upstream and condensed later in the reactor, forming Cs 2 O and Cs-uranate phases with the highest incorporation after thermal hold-up. Bulk ICP-MS measurements supported these observations. U/Ce ratios remained comparatively stable and Cs displayed delayed and apparent transient enrichment that matched the nanoscale measurements. This integrated approach provides a quantitative method for linking thermal gradients to redox evolution and volatility-driven fractionation. These results show how the plasma flow reactor can identify where equilibrium descriptions remain adequate and where kinetic effects from residence time and temperature history must be considered when interpreting condensation behavior in multicomponent systems.

and nuclear chemistry

Durability of PGM catalyst MEAs of polymer electrolyte membrane fuel cells for heavy-duty vehicles

Polymer electrolyte membrane fuel cells (PEMFCs) are promising power sources for heavy-duty vehicles (HDVs) owing to cleanliness and efficiency. However, the degradation of membrane electrode assemblies (MEAs) under HDV conditions remains a huge challenge. Here, this work investigated MEA durability under HDV conditions using a US Department of Energy standard accelerated stress test for 180,000 cycles (equivalent to 1 million miles of HDV operation). Effects of catalyst Pt content on MEA durability were examined using homemade 30% Pt/C (H-Pt/C) and commercial 46% Pt/C (C-Pt/C) catalysts. Both MEAs experienced H 2 /air and H 2 /O 2 performance loss over cycles. Analysis with scanning transmission electron microscopy, X-ray diffraction, inductively coupled plasma mass spectrometry, and mercury intrusion porosimetry revealed severe degradation of Pt nanoparticles (NPs), support structures, and the catalyst layer. Two degradation stages for NPs were proposed: Ostwald ripening dominated the initial 60,000 cycles, followed by combined Ostwald ripening and particle migration. Measurements with ion chromatography, high-frequency resistance, and oxygen-diffusion resistance revealed degradation of membrane and ionomer, respectively.

25 ENERGY STORAGE

Quantifying Phospholipids in Organic Samples Using a Hydrophilic Interaction Liquid Chromatography–Inductively Coupled Plasma High-Resolution Mass Spectrometry (HILIC-ICP-HRMS) Method

Here, in this study, a novel method using hydrophilic interaction liquid chromatography (HILIC) coupled with inductively coupled plasma high-resolution mass spectrometry (ICP-HRMS) was introduced for the quantification of phospholipids in oil samples. The method employed a bridged ethyl hybrid (BEH) stationary phase HILIC column with a tetrahydrofuran (THF)/water mobile phase, enhancing the solubility and detection of phospholipids. During the study, a gradient/matrix effect on ICP-HRMS sensitivity was observed and successfully compensated for experimentally, ensuring reliable quantification results. This approach has proven effective for a wide range of different oil samples including vegetable oils, animal fats, and phospholipid supplements. Notably, this method allowed the direct quantification of phospholipids in oil samples, bypassing the need for prior sample preparation methods, such as solid phase extraction (SPE), thereby streamlining the analytical process. The precision, accuracy, and reduced need for extensive sample preparation offered by this method mark a significant advancement in lipids analysis. Its robustness and broad applicability have substantial implications for industries such as food and renewable energy production, where both efficient and accurate lipid identification and quantification are crucial.

09 BIOMASS FUELS

Initial testing of Alfvén eigenmode feedback control with machine-learning observers on DIII-D

A first of its kind fully data-driven system has been developed and implemented into the DIII-D plasma control system to detect and control Alfvén eigenmodes (AE) in real-time. Susceptibility to fast ion-induced AE is a challenge in fully non-inductive tokamak operation, which significantly reduces fast-particle confinement and results in degraded fusion gain. Controlling AEs in real-time to improve fast-ion confinement is, hence, important for future advanced tokamak fusion reactors. The models were implemented and tested in experiments which showed that neural networks (NN) are highly effective in detecting 5 types of AE (BAE, EAE, LFM, RSAE, TAE) using high resolution ECE. To estimate the neutron deficit, a NN has been trained that outputs the classical neutron rate using similar inputs to NUBEAM. Also a preliminary ML-based proportional control has been designed and gone through initial testing in experiment to use feedback-control on the neutral beam power to achieve desired amplitude of AE modes and neutron deficits. The effect of AEs on fast-ion confinement is measured by analysing the gap in classical neutron rate from the proposed NN-based NUBEAM and the measured neutron rate.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Control of core–shell nanoparticles properties through plasma synthesis: a computational study

The improved properties of core–shell nanoparticles (CSNPs) over homogeneous nanoparticles (NPs) have expanded and diversified the applications of these nanomaterials. However, controlling the properties of CSNPs can be a challenging task. Low temperature plasmas have proven to be an effective method of producing NPs with uniform size and morphology, and high yield. That said, NP transport and growth dynamics are sensitive to LTP properties. We report on a computational investigation of the evolution of Ge–Si CSNP properties as a function of operating conditions through the modeling of a flowing, two-zone inductively coupled plasma (ICP) reactor. Ar/GeH 4 and Ar/SiH 4 gas mixtures were supplied to separate plasma zones at a pressure of 1 Torr to promote growth of Ge cores and Si shells. The negatively charged CSNPs are trapped electrostatically in the vicinity of the antennas where the plasma is generated and where the majority of particle growth occurs. Particles that grow to a critical size are then de-trapped by fluid drag due to neutral gas flow. A two-dimensional hybrid plasma model coupled with a three-dimensional kinetic NP transport model were utilized to resolve plasma chemistry and NP growth processes that take place on distinct timescales. The trends in CSNP properties and trapping mechanisms associated with flow rate, applied ICP power and inlet precursor fraction are discussed. While the spatial distribution of plasma produced radical species can have significant impact on the NP growth process, the NP transport dynamics are what ultimately dictates the growth environment that is unique to each particle and so determines their final dimension and composition. The key to optimizing reactor conditions involves controlling the spatial density of growth species and plasma profile as a means to tailor particle trapping dynamics suitable to produce CSNPs for a specific application.

36 MATERIALS SCIENCE

Simulating the Phonon Collection Efficiency in KIPMDs

Kinetic inductance phonon-mediated (KIPM) detectors use microwave kinetic inductance detectors (MKIDs) to read out phonon signals in the substrate. They are a promising class of detectors to be used in light dark matter (DM) searches due to their potential eV-scale sensitivity and native frequency-domain multiplexability. In order to improve upon the design of these detectors, simulations are needed to understand the effects of detector design on measurable physical parameters including the phonon collection efficiency, $\eta_{ph}$, which is defined as the ratio of phonon energy detected by the sensitive target element to the incident energy deposited in the substrate. This work simulates the phonon collection efficiency for a KIPMD currently operated at the Northwestern EXperimental Underground Site (NEXUS).

Dang, Stella Q.