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At least 73 records · Page 4

Control of microphonics for a superconducting radio-frequency photo-injector cryomodule

A superconducting radio-frequency photo-injector cryomodule is being developed for the high-energy upgrade of the Linac Coherent Light Source (LCLS-II-HE). This effort is a collaboration between the Facility for Rare Isotope Beams at Michigan State University (MSU), Argonne National Laboratory, Helmholtz-Zentrum Dresden-Rossendorf, and SLAC National Accelerator Laboratory. The cryomodule features a 185.7 MHz superconducting quarter-wave resonator (QWR) designed to operate with an RF electric field of 30 MV/m at the photo-cathode. Mechanical vibrations must be controlled for operation with stable amplitude and phase. The first prototype cryomodule was cold-tested at MSU with a QWR, fundamental power coupler, tuner, and cathode stalk. In the cold test, we observed microphonics that made it difficult to control the RF phase at high gradient. The cryogenic circuit was identified as a likely culprit. This paper presents our studies of microphonics during the cryomodule cold test and follow-up investigations at room temperature. Our findings provided valuable feedback for modifications to the cryogenic circuit and a successful second cold test of the cryomodule.

Accelerator Physics

Thermal conductance of interfaces between titanium nitride and group IV semiconductors at high temperatures

Measuring the temperature dependence of material properties is a standard method for better understanding the microscopic origins for that property. Surprisingly, only a few experimental studies of thermal boundary conductance at high temperatures exist. This lack of high temperature data makes it difficult to evaluate competing theories for how inelastic processes contribute to thermal conductance. To address this, we report time domain thermoreflectance measurements of the thermal boundary conductance for TiN on diamond, silicon-carbide, silicon, and germanium between 120 and 1000 K. In all systems, the interface conductance increases monotonically without stagnating at higher temperatures. For TiN/SiC interfaces, G ranges from 330 to 1000 MW/m2-K, with a room temperature conductance of 750 MW/m2-K. The interface conductance for TiN/diamond ranges from 140 to 950 MW/m2-K. Notably, for all four interfacial systems, the conductance continues to increase with temperature even after all phonon modes in the vibrationally soft material are thermally excited. This observation suggests that inelastic processes are significant contributors to the thermal conductance in all four interfacial systems, regardless of whether the materials forming the interface are vibrationally similar or dissimilar. Our study fills a notable gap in the literature for how interfacial conductance evolves at high temperatures and tests burgeoning theories for the role of inelastic processes in interfacial thermal transport.

Physics

Scalable Enrichment of 48 Ca at the Solid/liquid Interface by Chemical and Electrochemical Methods

This award targets to develop methods to enrich 48 Ca, which is a critical isotope for synthesizing superheavy elements and testing the standard model through neutrinoless double beta decay. The team first tested chemical exchange-based separation between solids and liquids, which is based on the free energy change due to the different vibrational frequencies caused by Ca isotopes in a material. However, the separation factor (alpha), which is defined as the ratio of 40 Ca/ 48 Ca ratios in the two phases, only reach ~1.01. The team then developed liquid centrifugation-based isotope separation, where a Ca salt aqueous solution is centrifuged at a speed of ~60 kRPM, and 48 Ca is enriched at the bottom of a centrifuge tube due to its larger mass. A high α of ~1.2-1.4 is achieved for 40 Ca/ 48 Ca at 40 °C. This method is further approved to be generic for any isotope that can be dissolved in a liquid solution or form liquid chemicals near room temperature. The experimental results also align well with modeling prediction. The team further develop a model to evaluate isotope separation in countercurrent liquid centrifugation. The team found that the countercurrent configuration can also enhance isotope separation in liquids, similar with gas centrifugation, which boost separation for isotopes which are difficult to be gasified near room temperature.

07 ISOTOPE AND RADIATION SOURCES

Tuning Methanol Transformation Pathways for Sustainable Steam Reforming: Na-Promotion Effects on Ag/m-ZrO 2 Catalysts

This work investigates the influence of sodium promotion on Ag/m-ZrO 2 catalysts for methanol steam reforming (MSR), focusing on activity, selectivity, surface chemistry, and mechanistic pathways. Temperature programmed reduction (TPR), XANES/EXAFS, CO 2 TPD, DRIFTS, and temperature programmed surface reaction methods were combined with fixed bed MSR testing to develop an integrated structure–function understanding of Na-modified Ag-ZrO 2 interfaces. Na addition systematically increases surface basicity, stabilizes strongly basic O 2− sites, and weakens the ν(CH) vibrational mode of surface formate, thereby facilitating C–H bond scission and accelerating decarboxylation to CO 2 . At moderate promoter levels (0.5–1.0 wt.% Na), the catalysts show significantly enhanced CO 2 selectivity and increased conversion relative to unpromoted Ag/m-ZrO 2 , while CH 4 formation remains negligible. Excessive Na (≥1.8 wt.%) leads to slower formate decomposition, greater carbonate stabilization, and suppressed conversion, revealing a narrow optimum around 1 wt.% Na. Short-term stability testing demonstrates steady conversion and product selectivity for both unpromoted and Na-promoted catalysts, with the latter maintaining markedly higher CO 2 selectivity. Although Pt/YSZ retains far superior intrinsic activity at ~10× higher space velocity, Ag offers a cost-advantaged alternative where lower cost metals are desirable. Collectively, these findings show that Na promotion enables tunable MSR selectivity on Ag/m-ZrO 2 by directing formate decomposition toward the CO 2 -forming pathway.

CO2 selectivity

Energy Efficiency Improvement Approaches in Ice Related Processes

Application and development of energy efficient techniques to separate ice from different surfaces and substrates is of significant value in the context of building equipment performance. A hybrid approach to help dislocate the ice layer using advanced materials and ultrasonic vibration to lower ice adhesion strength was investigated. Application of advanced polymer materials in lowering the adhesion strength of ice was confirmed where the measured strength was lowered by 50-70% depending on the material and geometry. Additionally, utilization of induced ultrasonic vibration in further lowering the ice harvesting energy was confirmed on multiple materials and geometries. Durability of the coating enhancement was also confirmed in a thermal cycling test under realistic operating conditions. Integration of these technical approaches was implemented and validated in commercial ice makers showing energy consumption reduction by ~ 15% to 30% depending on the technical enhancement.

Cheekatamarla, Praveen

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Abstract Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a cost similar to that of conventional interatomic potential approaches. While MLIPs have been extensively tested across various classes of materials and molecules, a clear characterization of the anharmonic terms encoded in the MLIPs is lacking. Here, we benchmark popular MLIPs using the anharmonic vibrational Hamiltonian of ThO 2 in the fluorite crystal structure, which was constructed from density functional theory (DFT) using our highly accurate and efficient irreducible derivative methods. The anharmonic Hamiltonian was used to generate molecular dynamics (MD) trajectories, which were used to train three classes of MLIPs: Gaussian approximation potentials, artificial neural networks (ANN), and graph neural networks (GNN). The results were assessed by directly comparing phonons and their interactions, as well as phonon linewidths, phonon lineshifts, and thermal conductivity. The models were also trained on a DFT MD dataset, demonstrating good agreement up to fifth-order for the ANN and GNN. Our analysis demonstrates that MLIPs have great potential for accurately characterizing anharmonicity in materials systems at a fraction of the cost of conventional first principles-based approaches.

interatomic potentials

IDENTIFICATION OF POTENTIAL SUPERCONDUCTOR QUENCH PRECURSORS USING FREQUENCY DOMAIN FEATURE ANALYSIS

Superconducting magnets are important pieces of technology in the world of particle accelerators, allowing researchers to study atomic and subatomic phenomena, among other things. In some instances, superconductors can lose this non-resistive property in a phenomenon known as quenching, which can cause damage to the magnets. This potential danger prompts the introduction of systems to predict when a quench is imminent; one such implementation is through the use of acoustic sensors that detect vibrations within the magnet. Within these acoustic sensor signals, significantly above-noise disturbances (referred to as ”events”) can be identified. Our research applies the statistical framework of a permutation test to features calculated from the power spectral density (PSD) to distinguish between events far from the quench at the end of the signal to events at the start of the signal. We found that dividing the PSD into frequency bands produced a feature capable of distinguishing between events early in the signal and late in the signal leading up the quench, providing a promising starting place for future quench prediction systems.

Roehrig, Benjamin [Northern Illinois U.]

Improving the precision of forces in real-space pseudopotential density functional theory

The high-order finite difference real-space pseudopotential density functional theory (DFT) approach is a valuable method for large-scale, massively parallel DFT calculations. A significant challenge in the approach is the oscillating “egg-box” error introduced by aliasing associated with a coarse grid spacing. To address this issue while minimizing computational cost, we developed a finite difference interpolation (FDI) scheme [Roller et al., J. Chem. Theory Comput. 19, 3889 (2023)] as a means of exploiting the high resolution of the pseudopotential to reduce egg-box effects systematically. Here, we show an implementation of this method in the PARSEC code and examine the practical utility of the combination of FDI with additional methods for improving force precision and/or reducing its computational cost, including orbital-based forces, compensating charges (namely, adding and subtracting a judiciously chosen charge density such that the total density is unaltered), and a modified spatial domain in which the real-space grid is defined. Using selected small molecules, as well as metallic Li, as test cases, we show that a combination of all four aspects leads to a significant reduction in computational cost while retaining a high level of precision that supports accurate structures and vibrational spectra, as well as stable and accurate molecular dynamics runs.

Chemistry

Automated shaker placement and regularized input estimation for MIMO testing.

Multi-input, multi-output (MIMO) testing is used in component qualification to reproduce operational responses in the laboratory. It is often preferred to single-input and base-shake testing because of the potential for equivalent or better tests using smaller actuators and shorter test suites. Given a target response, two key steps in MIMO test design are selecting actuator locations and solving for input loads. Actuator locations are often manually selected using expert judgment. If an automatic method is used, locations are usually determined by simulating the vibration control problem and minimizing a combination of the input energy and control residuals. To select a configuration, the relative importance of input energy and residuals must be specified. Specifying relative weights is, in general, a manual and subjective process. This paper develops an objective function that compares actuator configurations based on control accuracy and required input energy without any manual parameter tuning. The objective function uses an optimally selected tradeoff parameter for each candidate configuration. To choose actuator locations using the new objective function, a pivoting algorithm for integer programming problems is developed. Starting with an initial configuration (such as the one generated by a greedy algorithm), the pivoting algorithm guarantees an objective function decrease in each iteration until convergence is reached. In a simulation featuring a structure excited by a diffuse acoustic field, electrodynamic shaker locations and regularized inputs are solved for without any analyst-specified parameters. Simulations are performed in MIMO configurations where the number of target responses is less than, equal to, and greater than the number of actuators.

Multi-input multi-output

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

We present GSCDB137, a rigorously curated benchmark library of 137 data sets (8377 entries) covering main-group and transition-metal reaction energies and barrier heights, (intra- and intermolecular) noncovalent interactions, dipole moments, polarizabilities, electric-field response energies, and vibrational frequencies. Legacy data from GMTKN55 and MGCDB84 have been updated to today's best reference values; redundant or low-quality points were removed, and many new, property-focused sets were added. Testing 29 popular density functional approximations (DFAs) confirms the expected Jacob's-ladder hierarchy overall but also reveals notable exceptions: functional performance for frequencies and electric-field properties correlates poorly with that for other ground-state energetics. ωB97M-V and ωB97X-V are the most balanced hybrid meta-GGA and hybrid GGA, respectively; B97M-V and revPBE-D4 lead the meta-GGA and GGA classes. Double hybrids lower mean errors by about 30% versus their hybrid analogues but demand careful frozen-core, basis set, and spin contamination treatment. GSCDB137 offers a comprehensive, openly documented platform for rigorous validation of DFA and universal machine learning potentials, and training of the next generation of exchange-correlation functionals.

Liang, Jiashu [University of California, Berkeley,

Coming Closer to High Frequency Gravitational Wave Detection With MAGO

In the last years, low frequency gravitational waves (GWs) have been consistently measured by the LIGOVirgo collaboration, but little to no attention has been paid to higher frequencies GWs in the range of 10 kHz to 100 MHz, at which confirmation for current theories or even new physics could be hidden. The MAGO 2.0 project aims at filling this gap in the parameter space using superconducting radio-frequency (SRF) cavities. Exploiting the excellent Q-factors of these resonators, we plan to detect tiny harmonic deformations induced by GWs which change the boundary conditions of the oscillating electromagnetic field. We present the results of the first cold tests ran at DESY and FNAL using the cavity prototype built 20 years ago at the end of the MAGO collaboration, characterizing the RF spectrum, Q-factor and surface resistance. Additionally we introduce the mechanical vibration spectrum characterization and the RF response of the cavity with the injection of a “fake GW” signal using piezoelectric actuators.

Marconato, Giovanni [Hamburg U.]

A meshing framework for digital twins for extrusion based additive manufacturing

Additive manufacturing (AM) allows for manufacturing of complex three-dimensional geometries not typically realizable with standard manufacturing practices. The internal microstructure of AM components has a significant impact on mechanical, vibrational, and shock properties and permits richer design space when this is controllable. Due to complex interactions of internal geometry of an extrusion-based AM component, it is common practice to assume homogeneous behavior or to perform characterization testing on specific toolpath configurations. To avoid testing or material waste, it is necessary to develop a consistently accurate numerical simulation framework with relevant boundary value problems that can handle the complicated geometry of internal material microstructure present in AM components. Herein, a framework is proposed to directly create computational meshes suitable for finite element analysis (FEA) of the fine-scale features generated from extrusion-based AM tool paths to maintain a strong process–structure–property-performance linkage. This mesh can be manually or automatically analyzed using standard FEA simulations such as quasi-static preloading or modal analysis. The framework allows an in-silico assessment of a target AM geometry where fine-scale features greatly impact quantities of design interest such as in soft elastomeric lattices where toolpath infill can greatly influence the self-contact of a structure in compression, which we use as a motivating exemplar. This approach greatly reduces both time and resource waste present in traditional build and test design cycles for non-intuitive design spaces, and acts as a tool for use in the production of a key component of a digital twin, a mesh suitable for finite element analysis. In conclusion, it also further allows for the exploration of toolpath infill to optimize component properties beyond simple linear properties such as density and stiffness.

Additive manufacturing

Target development using the method of High-Intensity Vibrational Powder Plating (HIVIPP) at the Center for Accelerator Target Science (CATS) at Argonne National Laboratory (ANL)

One of the primary goals of the Center for Accelerator Target Science (CATS) is to provide targets and foils in support of the ATLAS User Facility and the Low-Energy community at large. While a wide array of target production techniques are available at CATS, new methods that must be explored invariably arise. One such technique, the High-Intensity Vibrational Powder Plating (HIVIPP), was first reported in 1997 by Isao Sugai. It was developed to produce targets and stripper foils that were difficult to make by standard methods. At Argonne National Laboratory (ANL), we have successfully constructed and tested a simple system for this purpose. We have produced targets of carbon and titanium on various metal backings using the HIVIPP method. We are currently in the exciting phase of exploring the production of other elements, including isotopically enriched and radioactive material. This work is in progress and will be further detailed with specific examples.

47 OTHER INSTRUMENTATION

FAIR Data and Interpretable AI Framework for Architectured Metamaterials (Final Report)

This research program established a transformative framework for the discovery and design of mechanical metamaterials, which are architected structures engineered to control physical phenomena like sound and vibration in ways natural materials cannot. To overcome the traditional reliance on trial-and-error, the project developed an interpretable Artificial Intelligence (AI) framework that moves beyond "black box" models to reveal the specific geometric patterns—such as "unit-cell templates"—that govern a material’s performance. A major breakthrough was the development of a hierarchical design method, which allows a single material to block vibrations across multiple frequency ranges simultaneously by layering patterns at different scales without them interfering with one another. This was further expanded to include irregular, graph-based designs that use spanning tree algorithms to ensure structural connectivity while allowing for customized, direction-dependent properties like stiffness and acoustic impedance. Beyond design, the project addressed the practicalities of real-world production by developing uncertainty quantification techniques that account for manufacturing defects and material variability, reducing the need for expensive physical testing by orders of magnitude. To speed up the discovery process, the team implemented Gaussian Process Regression and other surrogate models that provide accurate performance predictions at a fraction of the traditional computational cost. The AI-generated designs were successfully validated through fabrication of physical samples and wave propagation experiments, confirming their ability to accurately guide or reflect waves as predicted. By contributing these tools and high-quality FAIR benchmark datasets to the wider scientific community, this work provides a scalable foundation for advancing technologies in aerospace vibration control, medical imaging, and noise reduction.

36 MATERIALS SCIENCE

Tests of the DFT Ladder for the Fulminic Acid Challenge

Properties of the historically pivotal fulminic acid (HCNO) molecule have been computed with a panoply of 473 density functionals of all varieties, providing a snapshot of the performance of contemporary density functional theory (DFT) for a challenging chemical system. Exhaustive tabulations and statistical analyses have been carried out for geometric parameters, vibrational frequencies, barriers to linearity, and the HCN–O dissociation energy. As the DFT ladder is climbed, confusion rather than consensus ensues regarding the details of the distinctive, extremely flat H–C–N bending potential of fulminic acid and whether the equilibrium structure is linear or bent. While high-ranking DFT functionals produce the smallest errors for the HCN + O( 3 P) → HCNO reaction energy, lower rungs emerge as the best performers for many of the bond distances and harmonic vibrational frequencies. This research shows that the current DFT zoo of approximations does not constitute a transparent ladder of increasingly accurate methods that consistently converges on definitive predictions for various properties of HCNO. Additional analyses are performed on the side effects of popular dispersion corrections on the covalently bonded properties and thermochemistry of HCNO.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Electric dipole polarizability of 58 Ni

The electric dipole strength distribution in 58 Ni between 6 and 20 MeV has been determined from proton inelastic scattering experiments at very forward angles at RCNP, Osaka. The experimental data are rather well reproduced by quasiparticle random-phase approximation calculations including vibration coupling, despite a mild dependence on the adopted Skyrme interaction. They allow an estimate of the experimentally inaccessible high-energy contribution above 20 MeV, leading to an electric dipole polarizability α D ⁡ ( 58 Ni) = 3.48 (31)⁢ fm 3 . This serves as a test case for recent extensions of coupled-cluster calculations with chiral effective field theory interactions to nuclei with two nucleons on top of a closed-shell system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

A high-throughput framework for lattice dynamics

We develop an automated high-throughput workflow for calculating lattice dynamical properties from first principles including those dictated by anharmonicity. The pipeline automatically computes interatomic force constants (IFCs) up to 4th order from perturbed training supercells, and uses the IFCs to calculate lattice thermal conductivity, coefficient of thermal expansion, and vibrational free energy and entropy. It performs phonon renormalization for dynamically unstable compounds to obtain real effective phonon spectra at finite temperatures and calculates the associated free energy corrections. The methods and parameters are chosen to balance computational efficiency and result accuracy, assessed through convergence testing and comparisons with experimental measurements. Deployment of this workflow at a large scale would facilitate materials discovery efforts toward functionalities including thermoelectrics, contact materials, ferroelectrics, aerospace components, as well as general phase diagram construction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

HamLib: A library of Hamiltonians for benchmarking quantum algorithms and hardware

In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem instances would allow for benchmarking studies that in turn help to improve both algorithms and hardware designs. To this end, here we present a large dataset of qubit-based quantum Hamiltonians. The dataset, called HamLib (for Hamiltonian Library), is freely available online and contains problem sizes ranging from 2 to 1000 qubits. HamLib includes problem instances of the Heisenberg model, Fermi-Hubbard model, Bose-Hubbard model, molecular electronic structure, molecular vibrational structure, MaxCut, Max- k -SAT, Max- k -Cut, QMaxCut, and the traveling salesperson problem. The goals of this effort are (a) to save researchers time by eliminating the need to prepare problem instances and map them to qubit representations, (b) to allow for more thorough tests of new algorithms and hardware, and (c) to allow for reproducibility and standardization across research studies.

97 MATHEMATICS AND COMPUTING