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At least 505 records · Page 28

Critical Contribution of Imbalanced Charge Loss to Performance Deterioration of Si-Based Lithium-Ion Cells during Calendar Aging

Increasing the energy density of lithium-ion batteries, and thereby reducing costs, is a major target for industry and academic research. One of the best opportunities is to replace the traditional graphite anode with a high-capacity anode material, such as silicon. However, Si-based lithium-ion batteries have been widely reported to suffer from a limited calendar life for automobile applications. Heretofore, there lacks a fundamental understanding of calendar aging for rationally developing mitigation strategies. Both open-circuit voltage and voltage-hold aging protocols were utilized to characterize the aging behavior of Si-based cells. Particularly, a high-precision leakage current measurement was applied to quantitatively measure the rate of parasitic reactions at the electrode/electrolyte interface. The rate of parasitic reactions at the Si anode was found 5 times and 15 times faster than those of LiNi 0.8 Mn 0.1 Co 0.1 O 2 and LiFePO 4 cathodes, respectively. Here, the imbalanced charge loss from parasitic reactions plays a critical role in exacerbating performance deterioration. In addition, a linear relationship between capacity loss and charge consumption from parasitic reactions provides fundamental support to assess calendar life through voltage-hold tests. These new findings imply that longer calendar life can be achieved by suppressing parasitic reactions at the Si anode to balance charge consumption during calendar aging.

25 ENERGY STORAGE↗

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs

Here, we develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) hardware. Our approach leverages Hessian-aware quantization of NNs, the Quantized Open Neural Network Exchange intermediate representation, and the hls4ml tool flow for transpiling NNs into FPGA firmware. This makes efficient NN implementations in hardware accessible to nonexperts in a single open sourced workflow that can be deployed for real-time machine-learning applications in a wide range of scientific and industrial settings. We demonstrate the workflow in a particle physics application involving trigger decisions that must operate at the 40-MHz collision rate of the CERN Large Hadron Collider (LHC). Given the high collision rate, all data processing must be implemented on FPGA hardware within the strict area and latency requirements. Based on these constraints, we implement an optimized mixed-precision NN classifier for high-momentum particle jets in simulated LHC proton-proton collisions.

47 OTHER INSTRUMENTATION↗

The GEM-T2 gravitational model

The GEM-T2 is the latest in a series of Goddard Earth Models of the terrestrial field. It was designed to bring modeling capabilities one step closer towards ultimately determining the TOPEX/Poseidon satellite's radial position to an accuracy of 10-cm RMS (root mean square). It also improves models of the long wavelength geoid to support many oceanographic and geophysical applications. The GEM-T2 extends the spherical harmonic field to include more than 600 coefficients above degree 36 (which was the limit for its predecessor, GEM-T1). Like GEM-T1, it was produced entirely from satellite tracking data, but it now uses nearly twice as many satellites (31 vs. 17), contains four times the number of observations (2.4 million), has twice the number of data arcs (1132), and utilizes precise laser tracking from 11 satellites. The estimation technique for the solution has been augmented to include an optimum data weighting procedure with automatic error calibration for the gravitational parameters. Results for the GEM-T2 error calibration indicate significant improvement over previous satellite-only models. The error of commission in determining the geoid has been reduced from 155 cm in GEM-T1 to 105 cm for GEM-T2 for the 36 x 36 portion of the field, and 141 cm for the entire model. The orbital accuracies achieved using GEM-T2 are likewise improved. Also, the projected radial error on the TOPEX satellite orbit indicates 9.4 cm RMS for GEM-T2, compared to 24.1 cm for GEM-T1.

Marsh, J. G.↗

The GEM-T2 gravitational model

The GEM-T2 is the latest in a series of Goddard Earth Models of the terrestrial field. It was designed to bring modeling capabilities one step closer towards ultimately determining the TOPEX/Poseidon satellite's radial position to an accuracy of 10-cm RMS (root mean square). It also improves models of the long wavelength geoid to support many oceanographic and geophysical applications. The GEM-T2 extends the spherical harmonic field to include more than 600 coefficients above degree 36 (which was the limit for its predecessor, GEM-T1). Like GEM-T1, it was produced entirely from satellite tracking data, but it now uses nearly twice as many satellites (31 vs. 17), contains four times the number of observations (2.4 million), has twice the number of data arcs (1132), and utilizes precise laser tracking from 11 satellites. The estimation technique for the solution has been augmented to include an optimum data weighting procedure with automatic error calibration for the gravitational parameters. Results for the GEM-T2 error calibration indicate significant improvement over previous satellite-only models. The error of commission in determining the geoid has been reduced from 155 cm in GEM-T1 to 105 cm for GEM-T2 for the 36 x 36 portion of the field, and 141 cm for the entire model. The orbital accuracies achieved using GEM-T2 are likewise improved. Also, the projected radial error on the TOPEX satellite orbit indicates 9.4 cm RMS for GEM-T2, compared to 24.1 cm for GEM-T1.

Marsh, J. G.↗

Electrically Reconfigurable Liquid Metal Nanophotonic Platform for Color Display and Imaging

Dynamically tunable optical materials and device architectures are essential for future photonic technologies, yet conventional solid metals lack the intrinsic tunability required for advanced functionalities. Gallium-based liquid metals (LMs) present an appealing alternative thanks to their distinctive mechanical and optical properties; however, their practical integration in tunable photonic elements remains largely unexplored. Here, in this study, an electrochemically controlled nanophotonic platform is demonstrated that integrates a dynamically reconfigurable LM ground plane with gold nanoantenna arrays within a microfluidic system, enabling precise and reversible modulation of optical resonances across the visible to mid-infrared spectral ranges. By employing moderate operational voltages (1.5–3.0 V), real-time tuning of high-resolution structural color patterns is achieved through nanoscale control of the interfacial gap between the LM and Au nanoantennas. This innovative platform facilitates electrically programmable, high-contrast color patterns suitable for dynamic optical displays, secure anti-counterfeiting labels, and imaging applications. Additionally, this platform enables tunable mid-infrared spectral responses, which may be utilized for chemical and biological sensing applications. This versatile integrated LM-based nanophotonic platform opens new paths toward multifunctional, actively tunable/reconfigurable photonic device and system technologies.

Imaging↗

Double echo symmetry-based REDOR and RESPDOR pulse sequences for proton detected measurements of heteronuclear dipolar coupling constants

1 H{X} symmetry-based rotational echo double resonance pulse sequences (S-REDOR) and symmetry-based rotational echo saturation pulse double resonance (S-RESPDOR) solid-state NMR experiments have found widespread application for 1 H detected measurements of difference NMR spectra, dipolar coupling constants, and internuclear distances under conditions of fast magic angle spinning (MAS). In these experiments the supercycled $\text{R4}^2_1 (\text{SR4}^2_1)$ symmetry-based recoupling pulse sequence is typically applied to the 1 H spins to reintroduce heteronuclear dipolar couplings. However, the timing of $\text{SR4}^2_1$ and other symmetry-based pulse sequences must be precisely synchronized with the rotation of the sample, otherwise, the evolution of 1 H CSA and other interactions will not be properly refocused. For this reason, significant distortions are often observed in experimental dipolar dephasing difference curves obtained with S-REDOR or S-RESPDOR pulse sequences. Here we introduce a family of double echo (DE) S-REDOR/S-RESPDOR pulse sequences that function in an analogous manner to the recently introduced $t_1$-noise eliminated (TONE) family of dipolar heteronuclear multiple quantum coherence (D-HMQC) pulse sequences. Through numerical simulations and experiments the DE S-REDOR/S-RESPDOR sequences are shown to provide dephasing difference curves similar to those obtained with S-REDOR/S-RESPDOR. However, the DE sequences are more robust to the deviations of the MAS frequency from the ideal value that occurs during typical solid-state NMR experiments. In this work, the DE sequences are shown to provide more reliable 1 H detected dipolar dephasing difference curves for nuclei such as 15 N (with isotopic labelling), 183 W and 35 Cl. The double echo sequences are therefore recommended to be used in place of conventional S-REDOR/S-RESPDOR sequences for measurement of weak dipolar coupling constants and long-range distances.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Proton reconstruction with the TOTEM Roman pot detectors for high- β * LHC data

The TOTEM Roman pot detectors are used to reconstruct the transverse momentum of scattered protons and to estimate the transverse location of the primary interaction. This paper presents new methods of track reconstruction, measurements of strip-level detection efficiencies, cross-checks of the LHC beam optics, and detector alignment techniques, along with their application in the selection of signal collision events. The track reconstruction is performed by exploiting hit cluster information through a novel method using a common polygonal area in the intercept-slope plane. The technique is applied in the relative alignment of detector layers with μm precision. A tag-and-probe method is used to extract strip-level detection efficiencies. The alignment of the Roman pot system is performed through time-dependent adjustments, resulting in a position accuracy of 3 μm in the horizontal and 60 μm in the vertical directions. The goal is to provide an optimal reconstruction tool for central exclusive physics analyses based on the high-β* data-taking period at $\sqrt({s})$ = 13 TeV in 2018.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Physics-Based Data-Driven Approach for Modeling of Environmental Degradation in Elastomers

Abstract Elastomers are now commonly used in a number of industries, including aerospace, structure, transportation, shipbuilding, and automotive, due to their excellent workability, formability, and flexibility. During their activity, elastomers are subjected to harsh environmental conditions, which decreases their resilience. False predictions made early in their lives can have major financial and environmental implications. Elastomers’ performance and properties, such as strength, durability, and density, are influenced by chemical changes in these materials, known as degradation, which occurs over time. This process can alter the morphology of a polymer matrix as well as cause chain scission and cross-linking, resulting in different behaviors than that of the unaged material. To demonstrate the effect of thermaloxidative aging on the mechanical behavior of elastomers, several experimental and theoretical models have been proposed. In view of the large volume of experimental data available on micro-structural evolution in the course of aging, we propose a physics-based data-driven approach to overcome the shortcomings of both phenomenological and micro-mechanical models. This work presents a novel thermodynamically consistent, multiagent machine-learned model for predicting the constitutive behavior of cross-linked elastomers during environmental aging, such as thermo-oxidative and hydrolytic aging for various states of deformation. Single mechanism degradation changes the polymer matrix over time where it is causing chain scission, reduction of cross-links, and morphology change. To capture the idealized Mullins effect and permanent set due to the effect of single aging mechanisms on nonlinear mechanical responses of elastomers, we propose a data-driven model for simulating inelastic elements in a polymer matrix. By using a sequential order reduction, we were able to reduce the 3D stress-strain tensor mapping problem to a small number of super-constrained 1D mapping problems. To systematically classify such mapping problems into a few categories, an assembly of multiple replicated conditional neural network learning agents (L-agents) is used based on our recent work. Each category is represented by a different type of agent. The effect of deformation history, aging time, and aging temperature is captured by this model. The model is validated using a broad collection of data, ranging from our experimental results to data from the literature. In addition, thermodynamic consistency and frame independence are investigated. The most significant achievements of this model are its precision, simplicity, and prediction of inelasticity under various states of deformation. The model’s accuracy and simplicity make it a good option for commercial and industrial applications. Conveniently, due to the model modular nature, it can be expanded in the future to include viscoelasticity and non-isotropic formation for better precision.

Ghaderi, Aref↗

Precision processing of earth image data

Precise corrections of Landsat data are useful for generating land-use maps, detecting various crops and determining their acreage, and detecting changes. The paper discusses computer processing and visualization techniques for Landsat data so that users can get more information from the imagery. The elementary unit of data in each band of each scene is the integrated value of intensity of reflected light detected in the field of view by each sensor. To develop the basic mathematical approach for precision correction of the data, differences between positions of ground control points on the reference map and the observed control points in the scene are used to evaluate the coefficients of cubic time functions of roll, pitch, and yaw, and a linear time function of altitude deviation from normal height above local earth's surface. The resultant equation, termed a mapping function, corrects the warped data image into one that approximates the reference map. Applications are discussed relative to shade prints, extraction of road features, and atlas of cities.

Bernstein, R.↗

Hardware Implementation of Serially Concatenated PPM Decoder

A prototype decoder for a serially concatenated pulse position modulation (SCPPM) code has been implemented in a field-programmable gate array (FPGA). At the time of this reporting, this is the first known hardware SCPPM decoder. The SCPPM coding scheme, conceived for free-space optical communications with both deep-space and terrestrial applications in mind, is an improvement of several dB over the conventional Reed-Solomon PPM scheme. The design of the FPGA SCPPM decoder is based on a turbo decoding algorithm that requires relatively low computational complexity while delivering error-rate performance within approximately 1 dB of channel capacity. The SCPPM encoder consists of an outer convolutional encoder, an interleaver, an accumulator, and an inner modulation encoder (more precisely, a mapping of bits to PPM symbols). Each code is describable by a trellis (a finite directed graph). The SCPPM decoder consists of an inner soft-in-soft-out (SISO) module, a de-interleaver, an outer SISO module, and an interleaver connected in a loop (see figure). Each SISO module applies the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm to compute a-posteriori bit log-likelihood ratios (LLRs) from apriori LLRs by traversing the code trellis in forward and backward directions. The SISO modules iteratively refine the LLRs by passing the estimates between one another much like the working of a turbine engine. Extrinsic information (the difference between the a-posteriori and a-priori LLRs) is exchanged rather than the a-posteriori LLRs to minimize undesired feedback. All computations are performed in the logarithmic domain, wherein multiplications are translated into additions, thereby reducing complexity and sensitivity to fixed-point implementation roundoff errors. To lower the required memory for storing channel likelihood data and the amounts of data transfer between the decoder and the receiver, one can discard the majority of channel likelihoods, using only the remainder in operation of the decoder. This is accomplished in the receiver by transmitting only a subset consisting of the likelihoods that correspond to time slots containing the largest numbers of observed photons during each PPM symbol period. The assumed number of observed photons in the remaining time slots is set to the mean of a noise slot. In low background noise, the selection of a small subset in this manner results in only negligible loss. Other features of the decoder design to reduce complexity and increase speed include (1) quantization of metrics in an efficient procedure chosen to incur no more than a small performance loss and (2) the use of the max-star function that allows sum of exponentials to be computed by simple operations that involve only an addition, a subtraction, and a table lookup. Another prominent feature of the design is a provision for access to interleaver and de-interleaver memory in a single clock cycle, eliminating the multiple clock-cycle latency characteristic of prior interleaver and de-interleaver designs.

Moision, Bruce↗

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

Langley, in the late nineteenth century, attempted to measure solar irradiance over an extended period of time in order to detect changes. The problem with this and other early attempts was that ground based measurements are not sufficiently accurate to measure solar irradiance fluctuations, which are on the order of 0.1%. It was not until the Active Cavity Radiometer Irradiance Monitor (ACRIM) experiment on the NASA Solar Maximum Mission (SMM) was launched in 1980 that continuous data with precision 0.1% was available.

Hoffert, M. I.↗

Power performance and loads characterization of laboratory-scale cross-flow rotors fabricated using additive manufacturing

Tidal energy conversion is a relatively new application for additive manufacturing (AM), where the focus has been on fabricating axial-flow turbine blades. AM techniques add material precisely where it is needed, creating more complex shapes with less waste. Cross-flow rotor geometry presents an opportunity for AM to improve rotor performance by fabricating features that cannot be created economically via conventional manufacturing. The challenges associated with using AM in cross-flow design include water resistance and degradation over time while retaining a level of quality equivalent to conventionally machined parts. In this work, AM materials were tested by environmentally conditioning samples in a seawater tank for 5 months, followed by performance and phase-resolved load testing of laboratory-scale rotors in a hydraulic flume. We found that while metals like titanium and Inconel have excellent performance in marine environments, achieving the desired geometry and performance is difficult. Thermoplastics degraded in seawater but were easier to form into desired geometries and could exceed the performance of an aluminum control rotor. Warping and surface finish were significant detractors from AM rotor performance. These results suggest that the primary benefits of using AM for cross-flow rotors is to quickly fabricate and test unconventional rotor geometries.

16 TIDAL AND WAVE POWER↗

CO 2 chirped-probe-pulse femtosecond CARS thermometry

The application of CO 2 chirped-probe-pulse (CPP) fs coherent anti-Stokes Raman scattering (CARS) for flame thermometry is discussed. A phenomenological model for CO 2 /O 2 CPP fs CARS was developed, and the simulations showed the potential for CO 2 temperature measurements free of interferences from O 2 and with no contribution from the nonresonant background by using a long-time delay for the chirped probe pulse. The accuracy and precision for CO 2 CPP fs CARS thermometry is compared with N 2 CPP fs CARS thermometry for temperatures between 295 K and 1420 K. The measurement accuracy for the CO 2 measurements is comparable with that for the N 2 measurements, while the precision for the CO 2 temperature measurements is significantly better at lower temperatures. In conclusion, we also demonstrate that accurate flame thermometry using a single set of laser parameters can be achieved using the delayed CPP approach.

42 ENGINEERING↗

Engineering advancements in microfluidic systems for enhanced mixing at low Reynolds numbers

Mixing within micro- and millichannels is a pivotal element across various applications, ranging from chemical synthesis to biomedical diagnostics and environmental monitoring. The inherent low Reynolds number flow in these channels often results in a parabolic velocity profile, leading to a broad residence time distribution. Achieving efficient mixing at such small scales presents unique challenges and opportunities. This review encompasses various techniques and strategies to evaluate and enhance mixing efficiency in these confined environments. It explores the significance of mixing in micro- and millichannels, highlighting its relevance for enhanced reaction kinetics, homogeneity in mixed fluids, and analytical accuracy. We discuss various mixing methodologies that have been employed to get a narrower residence time distribution. The role of channel geometry, flow conditions, and mixing mechanisms in influencing the mixing performance are also discussed. Various emerging technologies and advancements in microfluidic devices and tools specifically designed to enhance mixing efficiency are highlighted. We emphasize the potential applications of micro- and millichannels in fields of nanoparticle synthesis, which can be utilized for biological applications. Additionally, the prospects of machine learning and artificial intelligence are offered toward incorporating better mixing to achieve precise control over nanoparticle synthesis, ultimately enhancing the potential for applications in these miniature fluidic systems.

Biochemistry & Molecular Biology↗

Raman Sideband Cooling of Molecules in an Optical Tweezer Array to the 3D Motional Ground State

Ultracold polar molecules are promising for quantum information processing and searches for physics beyond the standard model. Laser cooling to ultracold temperatures is an established technique for trapped diatomic and triatomic molecules. Further cooling of the molecules to near the motional ground state is crucial for reducing various dephasings in quantum and precision applications. In this work, we demonstrate Raman sideband cooling (RSC) of CaF molecules in optical tweezers to near their motional ground state, with average motional occupation quantum numbers of n ¯ x = 0.16 ( 12 ) , n ¯ y = 0.17 ( 17 ) (radial directions), and n ¯ z = 0.22 ( 16 ) (axial direction), and a 3-D motional-ground-state probability of 54 ± 18 % of the molecules that survive the RSC. This process paves the way to increase molecular coherence times in optical tweezers for robust quantum computation and simulation applications. Published by the American Physical Society 2024

Physics↗

Coupled Lindblad Pseudomode Theory for Simulating Open Quantum Systems

Coupled Lindblad pseudomode theory is a promising approach for simulating non-Markovian quantum dynamics on both classical and quantum platforms, with dynamics that can be realized as a quantum channel. We provide theoretical evidence that the number of coupled pseudomodes only needs to scale as polylog⁡(𝑇/𝜖) in the simulation time 𝑇 and precision 𝜖. Inspired by the realization problem in control theory, we also develop a robust numerical algorithm for constructing the coupled modes that avoid the nonconvex optimization required by existing approaches. We demonstrate the effectiveness of our method by computing population dynamics and absorption spectra for the spin-boson model. Furthermore, this Letter provides a significant theoretical and computational improvement to the coupled Lindblad framework, which impacts a broad range of applications from classical simulations of quantum impurity problems to quantum simulations on near-term quantum platforms.

Anderson impurity model↗

Covariance Manipulation for Conjunction Assessment

Use of probability of collision (Pc) has brought sophistication to CA. Made possible by JSpOC precision catalogue because provides covariance. Has essentially replaced miss distance as basic CA parameter. Embrace of Pc has elevated methods to 'manipulate' covariance to enable/improve CA calculations. Two such methods to be examined here; compensation for absent or unreliable covariances through 'Maximum Pc' calculation constructs, projection (not propagation) of epoch covariances forward in time to try to enable better risk assessments. Two questions to be answered about each; situations to which such approaches are properly applicable, amount of utility that such methods offer.

Probability↗

Rapid custom prototyping of soft poroelastic biosensor for simultaneous epicardial recording and imaging

Abstract The growing need for the implementation of stretchable biosensors in the body has driven rapid prototyping schemes through the direct ink writing of multidimensional functional architectures. Recent approaches employ biocompatible inks that are dispensable through an automated nozzle injection system. However, their application in medical practices remains challenged in reliable recording due to their viscoelastic nature that yields mechanical and electrical hysteresis under periodic large strains. Herein, we report sponge-like poroelastic silicone composites adaptable for high-precision direct writing of custom-designed stretchable biosensors, which are soft and insensitive to strains. Their unique structural properties yield a robust coupling to living tissues, enabling high-fidelity recording of spatiotemporal electrophysiological activity and real-time ultrasound imaging for visual feedback. In vivo evaluations of custom-fit biosensors in a murine acute myocardial infarction model demonstrate a potential clinical utility in the simultaneous intraoperative recording and imaging on the epicardium, which may guide definitive surgical treatments.

36 MATERIALS SCIENCE↗