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At least 721 records · Page 40

Gridded Sub-daily Climate Forcings for North America Based on Daymet and ERA5 (Daymet-ERA5)

To support high spatial and temporal resolution land surface modeling, this dataset provides hourly time step historic weather forcing at 1-km spatial resolution for the entire North America. The latest Daymet V4 data provides gridded historic daily weather observations at 1-km spatial resolution from 1980 to 2024. Using sub-daily temporal information from the ECMWF ERA5 reanalysis, Daymet was further temporally downscaled to hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each hourly time step from ERA5 while maintaining the total and average values from Daymet for each day. This results in a blended 1980-2024 Daymet-ERA5 dataset. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.

54 ENVIRONMENTAL SCIENCES

Heat load measurements for the PIP-II pHB650 cryomodule

Phase-3 testing of the pHB650 cryomodule at the PIP-II Injector Test Facility was conducted to evaluate the effectiveness of heat load mitigations performed after earlier phases of testing and to continue pinpointing any sources of unexpectedly high heat loads.. The programme measured HTTS, LTTS, and 2 K isothermal/non-isothermal loads under "standard", "linac", and "simulated dynamic" operating modes, recording data both inside the cryomodule and across the bayonet can circuits. Thermal-acoustic oscillations were eliminated by replacing the original G10 cooldown-valve stem with a stainless-steel stem fitted with wipers. A newly developed Python script automated acquisition of ACNET data, performed real-time heat-load calculations, and generated plots and tables that were posted to the electronic logbook within minutes, vastly reducing manual effort and accelerating feedback between SRF and cryogenics teams. Analysis showed that JT heat-exchanger effectiveness and temperature stratification in the two-phase and relief piping strongly influence the observed loads and helped isolate sources of excess heat. The campaign demonstrates that rigorous pre-test planning, real-time diagnostics, and automated reporting can improve both accuracy and efficiency, providing a template for future PIP-II cryomodule tests and for implementing targeted heat-load mitigations.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.] (ORCID:

Modeling Occupant Core Temperatures Across the Boston Building Stock to Advance Public Health

In recent history, extreme heat has been the cause of most deaths from a natural disaster. Exposure to extreme heat can aggravate preexisting conditions, increase hospitalization, and even cause death. Thus, modeling the thermal resilience of households across the United States will allow for a quantitative assessment of the health and safety risks posed by extreme heat. For the first time, we simulate occupant comfort in representative households across Boston by combining the granular results of the ResStock(TM) model with a two-node heat strain model. This model calculates occupants' core body temperature in each simulated household over a year. We compare the simulated core temperatures to two public health metrics: hyperthermia and heat stroke. Our results show for households in Boston that do not have or use aid conditioning, thousands potentially experience many dangerous heat events each summer and these events can last for more than a day at a time. These heat events peak during the late afternoon and evening, just as residents are coming home, cooking meals, and trying to go to sleep. We have found that multi-family buildings, renters, and low-income homes in more airtight and insulated homes are the most at risk for these events. These results demonstrate the scale and urgency of exposure to extreme heat.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Relationship Between Filler Type, Thermomechanical Properties, and Aging of RTV Silicone Foams

Room-temperature vulcanizing (RTV) silicone foams are used in many industrial applications that require the material to perform over long time periods. However, mechanical properties tend to deteriorate when these foams age under a compressive load. The chemical aging is attributed to the presence of unreacted functional groups of the prepolymers, residues from acid, and catalytically active tin (II) species. Here, an optimized thermal treatment of an RTV foam that achieves completion of curing reactions and deactivation of reactive species is proposed. Foams that were thermally aged for three months under compressive load showed no signs of compression set, indicative of the effectiveness of the implemented post-curing approach. In addition, the effects of fillers (diatomaceous earth, fumed silica, and carbon nanofibers) on thermomechanical properties were investigated. Tensile strength, tear strength, and thermal conductivity increased when these fillers were added to the unfilled RTV formulation, with carbon nanofibers (CNFs) being the most effective filler. Rheological studies of RTV formulations indicated that 2.5 wt.% of CNFs is the upper limit that can be added to the RTV formulation.

36 MATERIALS SCIENCE

Performance of the Satellite Test Assistant Robot in JPL's Space Simulation Facility

An innovative new telerobotic inspection system called STAR (the Satellite Test Assistant Robot) has been developed to assist engineers as they test new spacecraft designs in simulated space environments. STAR operates inside the ultra-cold, high-vacuum, test chambers and provides engineers seated at a remote Operator Control Station (OCS) with high resolution video and infrared (IR) images of the flight articles under test. STAR was successfully proof tested in JPL's 25-ft (7.6-m) Space Simulation Chamber where temperatures ranged from +85 C to -190 C and vacuum levels reached 5.1 x 10 -6 torr. STAR's IR Camera was used to thermally map the entire interior of the chamber for the first time. STAR also made several unexpected and important discoveries about the thermal processes occurring within the chamber. Using a calibrated test fixture arrayed with ten sample spacecraft materials, the IR camera was shown to produce highly accurate surface temperature data. This paper outlines STAR's design and reports on significant results from the thermal vacuum chamber test.

Douglas McAffee

Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology

Refrigerator technology has advanced significantly over the last couple of decades. Today’s refrigerators use only about 25% of the energy that was required to power models built in 1975. Even as they continually improve efficiency to meet standards, refrigerators have increased in size by almost 20%, added energy-consuming features such as through-the-door ice, and provide more benefits than ever before. However, a few challenges and technology gaps are preventing further improvement of the demand responsiveness and efficiency of the refrigerators. One of the major technology gaps in existing refrigerators is their outdated de-icing process. When the evaporator generates frost, an old-fashioned resistive heating element melts the ice. Most refrigerators have a timed defrost cycle, rather than an active system that could monitor the state of the frost. In these systems, not only is the precious electricity used at its least efficient form of conversion (direct conversion of electricity to heat), but also all the latent heat associated with the ice is wasted during the melting process. On top of that, the refrigerator needs to work harder to pull the temperature down after defrosting, and, last but not least, the food quality is severely impacted by the temperature swings during the defrost cycle. According to a study, the EU alone wastes 89 million tons of food in the supply chain every year. Any temperature swing during defrosting (about 6F according to Emerson for low-temperature cases) can negatively impact the shelf life of meat and other products for multiple days. All these issues can happen during the peak demand time of the electric grid. Unlike the conventional systems, the proposed novel advanced micro-vibrational deicing process uses no heat for defrosting. Instead, it uses the micro vibrations generated by a piezoelectric or vibration-generating module to mechanically break ice from the heat exchanger almost instantaneously. The project titled “Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology, performed by Ultrasonic Technology Solutions, LLC (UTS) of Knoxville, TN, in collaboration with Emerson (now Copeland), represents the final phase of a multi-year effort funded under the U.S. Department of Energy’s Building Technologies Office (BTO) BENEFIT FOA 2020. Initiated on October 1, 2021, and completed after a nine-month no-cost extension ending September 30, 2025, this project aimed to develop and validate a novel micro-vibrational mechanical defrosting system, achieving more than 25% improvement in defrosting energy efficiency over conventional baseline defrosting technologies. Over sixteen quarters, the project advanced from fundamental ice-mechanical characterization and prototype development to full-scale system integration and validation. Initial efforts established project management infrastructure and characterized ice adhesion properties, followed by the design and fabrication of early aluminum-based prototypes for resonance frequency testing. Subsequent quarters saw rapid technical progression, including the identification of optimal piezoelectric and motor-based vibration mechanisms, the demonstration of effective de-icing over 6x6-inch aluminum surfaces. The team achieved its Go/No-Go milestone by exceeding the 25% energy-efficiency improvement target—reaching up to 3,340% under optimized conditions—and later confirmed that motor-driven systems offered superior performance and energy efficiency compared to piezoelectric alternatives. Continued refinement led to the development of amplifier systems on printed circuit boards, improved control and instrumentation hardware, and integration into full-scale heat exchanger (HX) prototypes at both UTS and Copeland facilities. Multiple vibration-mounting studies and frost-growth experiments guided mechanical optimization and noise-mitigation strategies, achieving a 17.5 dB reduction in sound pressure level and verifying robust mechanical performance. Advanced analyses, including modal and harmonic simulations, established a quantitative understanding of vibrational behavior and de-icing efficiency across >1000 cm² systems. The final project phase successfully demonstrated scalable integration within reach-in and chest freezer prototypes, confirmed >25% efficiency improvements in large-area systems, and completed a comprehensive business model and scale-up strategy identifying electric defrost systems as the primary beachhead market. The culmination of this DOE-supported effort establishes micro-vibrational defrosting as a viable, high-efficiency, low-noise, and demand-flexible de-icing technology, paving the way for commercial deployment and broader application in next-generation refrigeration systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Methyl formate oxidation kinetics up to 100 atm

Methyl formate (MF, CH3OCHO), the simplest ester, is a representative oxygenated fuel with high oxygen content, and low sooting tendency. However, its oxidation behavior under high-pressure and intermediate-temperature conditions remains insufficiently understood, especially where low-temperature peroxy radical chemistry, methanol chemistry, and pressure-dependent reaction pathways play a critical role. In this study, MF oxidation experiments were conducted in the Princeton supercritical-pressure jet-stirred reactor (SP-JSR) at 20 and 100 atm over the temperature range of 400–950 K under both fuel-lean and fuel-rich conditions. Based on the experimental results, an updated HP-Mech was developed by incorporating previous MF sub-mechanisms, expanded low-temperature peroxy pathways, and evaluated pressure-dependent decomposition kinetics. The newly updated HP-Mech shows greatly improved performance in predicting the onset temperature, the key intermediate species fractions, methanol formation, and the progression of MF oxidation across all the experimental conditions. Path flux analysis indicates that MF consumption at the onset stage is dominated by H-abstraction at the methyl site, forming CH2OCHO radicals that lead to the formation and isomerization of O2CH2OCHO, driving low-temperature chain propagation. Moreover, H-abstraction at the formate site forms CH3OCO radicals that preferentially decompose to CH3, initiating the methanol formation pathway linked to CH3O2 and HO2 chemistry. At the same time, HO2 formation is strongly coupled to MF oxidation through multiple MF-derived radical pathways. HCO originates from MF oxidation and acts as a key coupling species linking fuel consumption to HO2 buildup, especially under high-pressure and intermediate-temperature conditions. In addition to this dominant channel, supplementary HO2 formation pathways involving CH3, CH3O, CH2OH, and CH3O2 reacting with O2 further connect methanol chemistry and oxygenated radical chemistry to the HO2 pool, indicating the central role of HO2 in governing MF oxidation. Sensitivity analysis identifies MF with OH/HO2/CH3O2 reactions and the HO2/H2O2/OH sequence as the key factors controlling reactivity in the high-pressure and intermediate-temperature regime. MF directly reacts with OH/HO2/CH3O2 to consume the fuel and produce reactive radicals like CH2OCHO and CH3OCO that undergo subsequent oxidation pathways. Moreover, HO2 recombination suppresses oxidation at lower temperatures, while thermal decomposition of H2O2 accelerates OH production and promotes fuel consumption as temperature increases. The direct formation of active OH from HO2 radicals further completes the mechanism, improving its prediction especially during the oxidation onset stage.

Low-temperature Chemistry

Real-Time Lifetime Prediction of Semiconductor Devices Using Hardware-in-the-Loop

This paper presents a unique approach to enable real-time lifespan prediction of semiconductor power modules using a Hardware-in-the-Loop (HIL) system. By integrating the module's overall loss characteristics-specifically switching and conduction losses-with a thermoelectric model of the thermal management system, this research demonstrates that the model can dynamically estimates the junction temperature profile of the semiconductor devices in response to a changing torque demand profile for the motor drive system. This capability enables continuous monitoring of the module's operational time and cumulative stress induced on the devices to compute accumulated remaining lifetime or time-to-failure (TTF). This study provides an architectural framework for the HIL system with high-fidelity component models of multiple physical domains, allowing simulation of dynamic behaviors of a closely-coupled motor drive system. The advanced real-time computation and measurement functionalities of the HIL system allow for both dynamic lifetime calculations based on simulated data and aggregate lifetime predictions utilizing historical data. Moreover, this paper details an algorithm that not only computes cumulative damage but also synthesizes these data into a comprehensive aggregated lifetime metric. This methodology can enhance the maintenance scheduling strategies and operational reliability of semiconductor devices in critical applications, ultimately extending their service life while optimizing performance.

hardware-in-the-loop (HIL)

A radar view of ice microphysics and turbulence in Arctic cloud systems

Ice microphysical processes are inherently complex because of their sensitivity to temperature and humidity, the diversity of ice crystal habits, and their interaction with supercooled liquid water (SCL) and turbulence. Long-term surface-based radar observations have been systematically used to unravel the different processes that affect ice particle growth. In this study, we present a statistical analysis of 6.5 years of Ka-band radar observations in Arctic cloud systems, combined with thermodynamic profiles derived from radiosonde measurements. For the first time, ice particle growth and sublimation – diagnosed from vertical gradients of radar reflectivity and mean Doppler velocity – are systematically mapped across a broad range of temperature and moisture conditions. These vertical gradients correspond closely to saturation levels relative to ice and exhibit a strong temperature dependence in supersaturated regions. Notably, distinct signatures near −15 °C are indicative of dendritic growth. Turbulence, quantified via the eddy dissipation rate (EDR), is most frequently observed in regions containing SCL. The co-occurrence of SCL and elevated turbulence results in significantly enhanced ice particle growth compared to conditions in which either is present alone. This work provides new observational constraints that are critical for improving the representation of ice microphysics in atmospheric models.

54 ENVIRONMENTAL SCIENCES

Photosynthetic responses to temperature across the tropics: a meta-analytic approach

Background and Aims Tropical forests exchange more carbon dioxide (CO 2 ) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. Methods Here, we used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (A sat ) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (J max ) and Rubisco carboxylation (V cmax ). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. Key Results Optimum temperatures for A sat (T optA ) and J max (T optJ ) increased with MAT but not for V cmax (T optV ). Although photosynthetic rates were higher for ‘light’ than ‘shaded’ leaves, light conditions did not generate differences in temperature response parameters. T optA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher T optA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single ‘broadleaf evergreen’ functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. Conclusions This novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.

Carter, Kelsey R. [Oak Ridge National Laboratory (

Machine learning approach for vibronically renormalized electronic band structures

Here, we present a machine learning (ML) method for efficient computation of vibrational thermal expectation values of physical properties from first principles. Our approach is based on the nonperturbative frozen phonon formulation in which stochastic Monte Carlo algorithm is employed to sample configurations of nuclei in a supercell at finite temperatures based on a first-principles phonon model. A deep-learning neural network is trained to accurately predict physical properties associated with sampled phonon configurations, thus bypassing the time-consuming ab initio calculations. To incorporate the point-group symmetry of the electronic system into the ML model, group-theoretical methods are used to develop a symmetry-invariant descriptor for phonon configurations in the supercell. We apply our ML approach to compute the temperature dependent electronic energy gap of silicon based on density functional theory (DFT). We show that, with less than a hundred DFT calculations for training the neural network model, an order of magnitude larger number of sampling can be achieved for the computation of the vibrational thermal expectation values. Our work highlights the promising potential of ML techniques for finite temperature first-principles electronic structure methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Assessing plasma face component thermal response to rotating 3D magnetic fields for SPARC tokamak

Thermal response simulations of plasma-facing components (PFCs) in the SPARC tokamak, performed with the HEAT code, show that three-dimensional (3D) heat loads resulting from stationary n=1 perturbations require highly radiative scenarios, with up to 95% of the power crossing the separatrix (P SOL ) being radiated, to maintain PFC temperatures within acceptable operational limits, whereas the application of slowly rotating 3D fields substantially reduces the thermal loads. The HEAT module, developed to predict heat loads from non-axisymmetric plasmas, is extended to model time-dependent heat flux patterns generated by rotating 3D fields, and a comprehensive thermal analysis is performed on PFCs subjected to both the maximum and minimum power loads, as well as to rotating heat flux distributions, to evaluate the temperature evolution for varying perturbation amplitudes and rotation frequencies. The extension of this analysis to 3D fields with toroidal mode number n=2 shows that this configuration leads to weaker localized heat flux peaks relative to the n=1 case, enabling safe operation with less than 80% of the power radiated when static 3D fields of low amplitude are applied, while using slowly rotating fields at higher amplitudes. These results indicate that n=2 perturbations are generally less detrimental to divertor power exhaust, emphasizing the strong dependence of divertor power exhaust on the characteristics of the applied 3D fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Proton diffusion and hydrogen/deuterium exchange in amorphous solid water at temperatures from 114 to 134 K

The reaction coefficient for hydrogen/deuterium (H/D) exchange and the diffusion of hydrated excess protons within amorphous solid water (ASW) are characterized as a function of temperature. For these experiments, water films are deposited on a Pt(111) substrate at 108 K, and reactions with pre-adsorbed hydrogen atoms produce hydrated protons. Upon heating, protons diffuse within the water, and H/D exchange occurs when they encounter D2O probe molecules deposited in the films. The time-dependent concentration of D2O is monitored with infrared spectroscopy, and it indicates the protons diffusion from the substrate and establish an equilibrium distribution prior to significant H/D exchange for temperatures 114 K ≤T≤ 134 K. By controlling the distance between the D2O molecules and the substrate, we probe the distribution of protons within the film. It decays as x−2 for the examined range of x (12–52 nm) due to the electric field that develops between the diffusing protons and their image charges in the metal substrate. This agrees with the theoretical distance scaling for the equilibrated proton concentration in a dielectric near a metal boundary. From the proton concentration and the measured D2O decay rate, a lower bound for the proton diffusion coefficient ranging from 10−20 m2/s at 114 K to 10−18 m2/s at 134 K is estimated. The diffusion coefficient has an activation energy of 0.40 eV, which is comparable to energies reported for molecular translations and rotations of H2O, suggesting they may play a critical role in the proton diffusion mechanism within ASW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Uncertainty quantification and sensitivity analysis of a nuclear thermal propulsion reactor startup sequence

The research presented in this article describes progress in applying stochastic methods, uncertainty quantification, parametric studies, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated via the radiation transport code Griffin to simulate neutronics. Our goal is to develop a reduced-order (surrogate) model that can be rapidly sampled with perturbations to multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums (CDs), which is itself controlled by a hybrid proportional-integral-derivative (PID) controller actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time [Λ] and effective delayed neutron fraction [ β eff ] from a transient Griffin simulation executed via Griffin’s improved quasi-static solver to provide the kinetic parameters) as inputs to functions that control the CD rotation angle. By investigating numerous stochastic approaches, we developed a dual-purpose surrogate model of the NTP system, using polynomial regression in the Multiphysics Object-Oriented Simulation Environment (MOOSE) Stochastic Tools Module (STM). The trained model can be rapidly sampled while simultaneously perturbing various input parameters, such as coefficients on the PID control or temperature (directly affecting the neutron cross section). The surrogate model delivers accurate (within 5%) results at speeds orders of magnitude faster (minutes, not days of computational time) than the base model. Once the surrogate model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs as well as the effects of these inputs on the model output. For example, coefficients used in the PID control system may vary due to some type of physical interference, or uncertainty may exist in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters, and operational boundaries can be determined. The goal of this work is to support development of an advanced control system for operating CDs in a functioning NTP system. This work is a scoping study of the MOOSE STM.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN

Enhancing mobility and interface state engineering via UV-ozone treatment in BEOL-compatible ultrathin TiO 2 transistors

It has emerged as a potential candidate to improve the performance of monolithic-three-dimensional (M3D) integration of fused logic and memories through low-temperature in situ synthesis of high-performance metal–oxide–semiconductor (MOS) transistors. Here, we report the demonstration of the BEOL-compatible low thermal budget (350 °C) fabrication process of ultrathin-TiO2 transistors by the combination of RTA and UV-ozone treatment (RTA-UVOz). UV–ozone (UVOz) treatment of TiO2 anatase films significantly enhances stability, boosting ION current and field effect mobility (μ FE ) by two times of magnitude in TiO2 TFTs. UV ozone treatment helps to eliminate pre-existing oxygen vacancies and carbon contamination on TiO2 channels even at low temperature (100 °C), resulting in high-quality channel/dielectric interfaces with low interface states (D it ). During UVOz treatment, oxygen species (O x ) passivate the oxygen vacancies ($V$$^{2+}_{o}$), and hence low concentration of $V$$^{2+}_{o}$ would be left for ionization/de-ionization under PBS/NBS, leading to improved bias stress stability. Furthermore, the TiO 2 TFTs with thin ZrO 2 gate dielectric exhibited excellent performance including a lower subthreshold swing (SS) of 98 mV/dec with high drive I ON current ∼ 4.5 μA/μm, a high I ON /I OFF > 10 9 , and mobility μFE of 7 cm 2 /V-s under a battery powered voltage of 1 V. UV–ozone treatment enables high-performance, CMOS-compatible TiO 2 transistors with a low thermal budget, ideal for next-generation flexible, energy-efficient electronics.

BEOL

Coalescence formation of muonic atoms at RHIC

The discovery of exotic muonic atoms, including antimatter hydrogen muonic atoms and kaon muonic atoms, constitutes a milestone in our ability to make and study new forms of matter. Relativistic heavy-ion collisions provide the only likely condition for production and detection of these exotic atoms. Taking Coulomb correlations into account from the time of the fireball freeze-out, which refers to the cessation of hadronic interactions in the high-temperature, high-density region formed after the collision, until the formation of a stable atom has dramatic consequences on the expected yields of these atoms. When the coalescence model with the assumption of quantum wave function localization is applied to the formation of muonic atoms, we find that the atom yields are about two orders of magnitude higher than previously predicted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Mechanically Accelerated Depolymerization of Entangled Linear Polymer Melts

Mechanical forces can enhance the chemical depolymerization of synthetic polymers when shear flow accelerates chain scission. To quantify the extent of mechanically-accelerated scission, the effect of simple shear flow (duration and strength) with low Weissenberg and Deborah numbers was investigated by considering the impact of applied work in both simple shear and shear dominated mixed flows. Hydrogenated polyisoprene was chosen as a model linear, entangled system. The conditions (strain amplitude, frequency, and shearing time) necessary to increase chain scission were assessed in the rubbery melt. Shear flow accelerated chain scission at higher temperatures, suggesting an activated process. Isothermal scission versus work curves were superposed by applying shift factors a T,S , whose Arrhenius-like temperature dependence gave an apparent activation energy for chain scission of ~ 110 kJ/mol, which is likely a combination of the activation energy of viscosity and bond energy. This work provides a base for quantifying the impact of shear on depolymerization of polymer melts and highlight the connection between viscous dissipation and scission chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

A tweezer array with 6,100 highly coherent atomic qubits

Optical tweezer arrays have transformed atomic and molecular physics, now forming the backbone for a range of leading experiments in quantum computing, simulation and metrology. Typical experiments trap tens to hundreds of atomic qubits and, recently, systems with around 1,000 atoms were realized without defining qubits or demonstrating coherent control. However, scaling to thousands of atomic qubits with long coherence times and low-loss and high-fidelity imaging is an outstanding challenge and critical for progress in quantum science, particularly towards quantum error correction (QEC). Here we experimentally realize an array of optical tweezers trapping more than 6,100 neutral atoms in around 12,000 sites, simultaneously surpassing state-of-the-art performance for several metrics that underpin the success of the platform. Specifically, while scaling to such a large number of atoms, we demonstrate a coherence time of 12.6(1) s, a record for hyperfine qubits in an optical tweezer array. We show room-temperature trapping lifetimes of about 23 min, enabling record-high imaging survival of 99.98952(1)% with an imaging fidelity of more than 99.99%. We present a plan for zone-based quantum computing and demonstrate necessary coherence-preserving qubit transport and pick-up/drop-off operations on large spatial scales, characterized through interleaved randomized benchmarking. Our results, along with recent developments, indicate that universal quantum computing and QEC with thousands to tens of thousands of physical qubits could be a near-term prospect.

atomic and molecular physics