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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Molecular dynamics simulations of a dicationic ionic liquid for CO 2 capture

A dicationic ionic liquid ([DBU-PEG][Tf 2 N] 2 ) was studied using classical molecular dynamics simulations to examine its structural and gas separation properties. The dication was designed in an attempt to improve CO 2 solubility by means of tuning the cation-anion interactions of the ionic liquid (IL). The computational model was compared to experimentally obtained density, viscosity, and powder X-ray diffraction spectra. The structure of the IL was further investigated with radial distribution functions and free volume analysis through cavity distributions. It was found that the shape and charge distribution of the dication enhances CO 2 interaction: the CO 2 molecule is hugged by the dication along the PEG linker and close to one of the cationic ends. Here, the geminal design of the dication allows for strong interaction with CO 2 , showing promise as a means of carbon capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Systematic Way to Extend the Debye–Hückel Theory beyond Dilute Electrolyte Solutions

An extended Debye–Hückel theory with fourth order gradient term is developed for electrolyte solutions; namely, the electric potential φ(r) of the bulk electrolyte solution can be described by ∇ 2 φ(r) = κ 2 φ(r) + L Q 2 ∇ 4 φ(r), where the parameters κ and L Q are chosen to reproduce the first two roots of the dielectric response function of the bulk solution. Three boundary conditions for solving the electric potential problem are proposed based upon the continuity conditions of involving functions at the dielectric boundary, with which a boundary element method for the electric potential of a solute with a general geometrical shape and charge distribution is derived. Solutions for the electric potential of a spherical ion and a diatomic molecule are found and used to calculate their electrostatic solvation energies. In this work, the validity of the theory is successfully demonstrated when applied to binary as well as multicomponent primitive models of electrolyte solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Woolwich, Bruceton, Los Alamos: Munroe Jets and the Trinity Gadget

Prewar work on the hydrodynamics of explosives and U.S./UK scientific cooperation well beyond Los Alamos contributed to the design of the explosive lenses for the Trinity gadget. Researchers were deliberately brought together and encouraged to share ideas by the leaders of the wartime laboratory. James Tuck, one of the British mission scientists, made particularly interesting contributions in this area, but this paper is not a claim of British or any other individual parentage. Rather, it highlights the importance of collaboration at Los Alamos and more widely.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Smart pixel sensors Towards on-sensor filtering of pixel clusters with deep learning

High granularity silicon pixel sensors are at the heart of energy frontier particle physics collider experiments. At an collision rate of 40\,MHz, these detectors create massive amounts of data. Signal processing that handles data incoming at those rate and intelligently reduces the data within the pixelated region of the detector \textit{at rate} will enhance physics performance and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first work, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 54.4-75.4\%. The network is designed and simulated as a custom readout integrated circuit with 28\,nm CMOS technology and is expected to operate at less than 300\,$\mu W$ with an area of less than 0.2\,mm$^2$.

43 PARTICLE ACCELERATORS↗

Imaging the electron charge density in monolayer MoS 2 at the Ångstrom scale

Four-dimensional scanning transmission electron microscopy (4D-STEM) has recently gained widespread attention for its ability to image atomic electric fields with sub-Ångstrom spatial resolution. These electric field maps represent the integrated effect of the nucleus, core electrons and valence electrons, and separating their contributions is non-trivial. In this paper, we utilized simultaneously acquired 4D-STEM center of mass (CoM) images and annular dark field (ADF) images to determine the projected electron charge density in monolayer MoS 2 . We evaluate the contributions of both the core electrons and the valence electrons to the derived electron charge density; however, due to blurring by the probe shape, the valence electron contribution forms a nearly featureless background while most of the spatial modulation comes from the core electrons. Our findings highlight the importance of probe shape in interpreting charge densities derived from 4D-STEM and the need for smaller electron probes.

36 MATERIALS SCIENCE↗

Spectral line-shape in collinear laser spectroscopy after atomic charge exchange

Collinear laser spectroscopy experiments on fast, neutral beams have been extensively used for studies on short-lived radioactive nuclei, taking advantage of its high sensitivity. The resulting resonance line-shape is known to show significant distortion, due to the energy exchange during the charge-exchange neutralization process, which can cause large systematic uncertainty in the determined centroid. A model for the line shape was constructed and simulated to be compared to measured Al, Si, and Ni hyperfine spectra. It is shown that the distortion is caused mainly by the transfer of electron into many different energy levels in the projectile atom and subsequent decays, rather than secondary inelastic collisions, which were often assumed in the line shape analysis before. Furthermore, the model can also be applied to other projectile–alkali pairs, providing a reliable line-shape with less fitting parameters than conventional phenomenological models.

Atom↗

Structure–Capacitance Relationships of Graphene/Ionic Liquid Electrolyte Double Layers

The differential capacitance profile of electrochemical interfaces reflects the physical properties of the double layer. For carbon electrodes and ionic liquid based electrolytes, these capacitance profiles are not fully understood. In this work, we utilize constant voltage molecular dynamics simulations to compute differential capacitance profiles of ionic liquids [BMIm + ][BF 4 - ] and [BMIm + ][TFSI - ] mixed with acetonitrile and 1,2-dichloroethane, at model graphene electrodes. We find that both pure and 10% mole fraction ionic liquid electrolytes exhibit camel shaped capacitance profiles with two peaks on either side of a minimum centered at the potential of zero charge. This profile shape results from electric field induced rearrangement of ion structure within the inner layer closest to the electrode interface. At low potential, the ionic liquid inner layer is concentrated with non-polar tri-fluoromethyl and butyl functional groups of the anions and cations, corresponding to the minimum of the capacitance profiles. With increasing voltage, electrostatic interactions of polar/charged functional groups with the electrode surface compete with these non-polar interactions, leading to ion rearrangement that increases the inner layer charge density and results in higher capacitance. After the ion restructuring is complete, the response saturates and capacitance diminishes. The presence of organic solvent significantly changes the composition of the inner layer. For example, strong non-polar interactions between dichloroethane molecules and the graphene surface substantially block ion/electrode contact at moderate potentials. Overall, our simulations highlight the dynamic nature of the inner region of organic electrolyte double layers, and the sensitive dependence on electrolyte composition and applied voltage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Antiprotons and Elementary Particles over a Solar Cycle: Results from the Alpha Magnetic Spectrometer

We present results over an 11-year Solar cycle of cosmic antiprotons based on 1.1 × 10 6 events in the rigidity range from 1.00 to 41.9 GV. The $\bar{𝑝}$ fluxes exhibit distinct properties. The magnitude of the $\bar{𝑝}$ flux temporal variation is significantly smaller than those of 𝑝, 𝑒 − , and 𝑒 + . A hysteresis between the $\bar{𝑝}$ fluxes and the 𝑝 fluxes is observed, whereas the $\bar{𝑝}$ and 𝑒 − fluxes show a linear correlation. With a model-independent analysis, we found a universal relation between the shape of the rigidity spectrum and the magnitude of flux temporal variation over an 11-year Solar cycle for both positively and negatively charged particles. The simultaneous results on $\bar{𝑝}$ and 𝑝, 𝑒 − , and 𝑒 + provide unique information for understanding particle transport in the Solar System as a function of mass, charge, and spectral shape.

cosmic ray composition & spectra↗

Towards a reliable assessment of charging effects during surface analysis: Accurate spectral shapes of ZrO 2 and Pd/ZrO 2 via X-ray Photoelectron Spectroscopy

X-ray Photoelectron Spectroscopy of large bandgap or insulating material surfaces relies on an effective mechanism that compensates for the emission (loss) of electrons by maintaining the material surface at a steady-state uniform potential. While a steady-state may be attained by utilizing an active compensation, such as low power electron emitting filament, there is the possibility that the surface potential is not uniform over the area analyzed, leading to peak shifts and incorrect spectral interpretation. Here, in this work, a spectral data processing method based on mapping the ZrO 2 and Pd/ZrO 2 surfaces utilizing photoemission peak binding energy is proposed, which provides information about the response of specific material surfaces to charge compensation. Spectromicroscopy of ZrO 2 and Pd/ZrO 2 surfaces without spatial information is used to monitor the efficacy of charge compensation. Exploiting counts distributed over many bins require the use of procedures and algorithms essential to practical mapping peak positions. Iterative singular value decomposition is therefore introduced and utilized as a means of efficiently delivering spatially resolved spectra from which binding energy for peaks is computed. The concepts developed in this work result in robust and accurate peak models of ZrO 2 and Pd/ZrO 2 that can be applied in XPS analysis of not only ZrO 2 but other large bandgap or insulating material surfaces. Supporting arguments for a peak model representing signal from Zr 3p and Pd 3d are developed within this work are presented.

36 MATERIALS SCIENCE↗

Sensor Co-design for $\textit{smartpixels}$

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in the first level of the trigger for a hadron collider. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p$_T$) based on the geometrical shape of the charge deposition (``cluster''). To design a viable detector for deployment at an experiment, the dependence of the NN as a function of the sensor geometry, external magnetic field, and irradiation must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. A smaller sensor pitch in the bending direction improves the p$_T$ discrimination, but a larger pitch can be partially compensated with detector depth. An external magnetic field parallel to the sensor plane induces Lorentz drift of the electron-hole pairs produced by the charged particle, broadening the cluster and improving the network performance. The absence of the external field diminishes the background rejection compared to the baseline by $\mathcal{O}$(10%). Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by $\sim$ 30 - 60%, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data.

Shekar, Danush [Illinois U., Chicago]↗

Robustness of the smartpixels classifier for different simulated sensor geometries and non-ideal detector conditions

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in high-rate online event selection, such as the ATLAS or CMS first-level trigger systems. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p T ) based on the geometrical shape of the charge deposition (“cluster”). To design viable detectors for deployment, the dependence of the NN as a function of the sensor geometry, external magnetic field, irradiation, and noise must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. For the CMS HL-LHC sensor geometry, we obtain a signal efficiency of (91.9 ± 0.7)% and a data reduction of (29.7 ± 1.0)%. A smaller sensor pitch in the bending direction improves the p T discrimination, but a larger pitch can be partially compensated with detector thickness. Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by approximately 30–60% in absolute terms, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data. •ASIC-compatible track-momentum classifier is robust in realistic detector conditions.•About 90% signal efficiency and 30% data reduction per layer for CMS HL-LHC geometry.•Single-layer signal efficiency increases for smaller pixel pitch or thicker sensors.•Performance with noise or after radiation damage mostly recovered by retraining.

Shekar, Danush [Illinois U., Chicago] (ORCID:00000↗

The SparkPix-S ASIC for the sparsified readout of 1 MHz frame-rate X-ray cameras at LCLS-II: pixel design and simulation results

Exploiting the “sparse” nature of the information in XPCS (X-ray Photon Correlation Spectroscopy) and XSVS (Speckle Visibility Spectroscopy) experiments, we present the SparkPix-S, a 3-sides buttable Application Specific Integrated Circuit (ASIC) based on a sparsified readout strategy for large-format hybrid detectors. The SparkPix-S architecture, based on the successful ePix family, will be composed as follows: a front-end 2-D matrix of 384×352 square pixels with 50 µm pitch is arranged to match the dimensions of a PIN Si-sensor matrix; charge readout, signal shaping and amplitude discrimination is performed at pixel-level, by means of a low-power (<18 µW) analog processor, which, in case of an event, negotiates access to an analog bus placed every other column; on the chip periphery (balcony), the information on each bus is digitized by an array of successive approximation analog-to-digital converters (SAR-ADCs) running at 10 Msps; on the digital back-end the global logic will generate the output data stream using low-voltage differential signalling (LVDS). A first prototype of the SparkPix-S, with a reduced matrix size of 96×96 pixels, is currently under production on a 130 nm CMOS technology. Simulated performance results show an equivalent noise charge <60 el. r.m.s. at 1 MHz repetition rate, with a maximum input energy of 60 keV and capability to discriminate charge signals with equivalent energy as low as 900 eV.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Cryogenic Front-End ASICs for Low-Noise Readout of Charge Signals

This paper presents design details and measurement results of LArASIC, a front-end application specific integrated circuit (ASIC) designed for low-noise readout of charge signals generated in neutrino study experiments within liquid argon time projection chambers. LArASIC comprises of 16-channels of programmable charge amplification and pulse shaping stages that provide a voltage readout proportional to the input charge and was optimized for operation at liquid argon temperature, i.e., 89 K. The chip was fabricated in a 180 nm CMOS process. Measurements at liquid nitrogen temperature, i.e., 77 K, indicate that the channel outputs have high linearity (INL < 0.1%) within the operating range, an equivalent noise charge of 534 electrons for a peaking time of 1 µs and a detector capacitance of 150 pF, and a worst-case inter-channel cross-talk of 0.35%. The paper also presents design choices made in the process of migrating LArASIC to CHARMS, an ASIC to be fabricated in a 65 nm process that includes all features provided by LArASIC, along with additional digital programmability for improved robustness and flexibility. CHARMS is intended for use in future high-energy physics experiments that require high-resolution charge or light readout with shorter pulse peaking times.

47 OTHER INSTRUMENTATION↗

Effects of charge exchange on the evaporative wind of HD 209458b

ABSTRACT The role of charge exchange in shaping exoplanet photoevaporation remains a topic of contention. Exchange of electrons between stellar wind protons from the exoplanet’s host star and neutral hydrogen from the planet’s wind has been proposed as a mechanism to create ‘energetic neutral atoms’ (ENAs), which could explain the high absorption line velocities observed in systems where mass-loss is occurring. In this paper, we present results from three-dimensional hydrodynamic simulations of the mass-loss of a planet similar to HD 209458b. We self-consistently launch a planetary wind by calculating the ionization and heating resulting from incident high-energy radiation, inject a stellar wind into the simulation, and allow electron exchange between the stellar and planetary winds. We predict the potential production of ENAs by the wind–wind interaction analytically, and then present the results of our simulations, which confirm the analytic limits. Within the limits of our hydrodynamic simulation, we find that charge exchange with the stellar wind properties examined here is unable to explain the absorption observed at high Doppler velocities.

79 ASTRONOMY AND ASTROPHYSICS↗

Simulations of crack extensions in arc-shaped tension specimens of uncharged and hydrogen-charged 21-6-9 austenitic stainless steels using cohesive zone modeling with varying cohesive parameters

Crack extensions in uncharged and hydrogen-charged side-grooved A(T) specimens of conventionally forged 21-6-9 austenitic stainless steels are simulated using the cohesive zone modeling approach. Two-dimensional plane strain finite element analyses with fixed cohesive parameters are first conducted to fit the experimental load-displacement curves. Similar analyses using varying cohesive parameters as functions of the crack extension are then conducted to fit the experimental load-crack extension and crack extension-displacement curves. The computational results with varying cohesive parameters can fit very well the experimental data. The computational results also indicate that the average cohesive energy for the hydrogen-charged A(T) specimen is lower than that for the uncharged A(T) specimen.

42 ENGINEERING↗

Impact of the LiPF6 Concentration on the Interfacial Charge Transfer and Fast-charging Capabilities of Lithium-Ion Batteries

Fast-charging lithium-ion batteries (LIB) demand optimized electrolyte formulations to balance ionic conductivity, viscosity, and interfacial charge transfer kinetics. This study examines how LiPF 6 concentration shapes solvation structure, desolvation energy, charge transfer activation energy, and solid electrolyte interphase (SEI) properties, which are critical for fast-charging performance. Using Raman spectroscopy, electrochemical cycling, X-ray photoelectron spectroscopy, and atomistic modeling, we analyze how varying LiPF 6 concentrations impact interfacial and bulk transport properties. Our findings show that increasing LiPF 6 concentration alters lithium solvation structures, reduces desolvation energy, and accelerates charge transfer at the electrode interface. Higher concentrations lower the activation energy for charge transfer and suppress excessive SEI growth, improving interfacial kinetics. However, concentrations above a certain threshold increase viscosity and reduce ionic conductivity, limiting transport efficiency. These results offer insights into electrolyte solvation and interfacial charge transfer mechanisms, providing guidelines for designing next-generation fast-charging LIB electrolytes with enhanced efficiency, stability, and longevity.

Son, Seoung-Bum [Argonne National Laboratory (ANL)↗

Implementation of a High-Speed Multichannel Data Acquisition System for Magnetic Diagnostics and Plasma Centroid Position Control in ISTTOK

In tokamak and other fusion devices, magnetic control is the main tool that allows to regulate the plasma current, position and shape; it is in charge of actuating the desired plasma current waveform, steering the plasma position to a given set point and maintain the plasma shape close to a prescribed plasma equilibrium. This work describes the application of several physics concepts and computational tools in order to obtain a novel optimal controller for the plasma centroid position, which has been implemented and tested in the real-time plasma control system at the ISTTOK tokamak. A key point for the development of the new control system was the installation of a recently upgraded hardware, that numerically integrates in real-time the magnetic probes signals.

poloidal field coils↗

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗