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At least 109 records · Page 6

Photoinitiator Selection and Concentration in Photopolymer Formulations towards Large-Format Additive Manufacturing

Photopolymers are an attractive option for large-format additive manufacturing (LFAM), because they can be formulated from structural thermosets and cure rapidly in ambient conditions under low-energy ultraviolet light-emitting diode (UV LED) lamps. Photopolymer cure is strongly influenced by the depth penetration of UV light, which can be limited in the 2–4 mm layer thicknesses typical of LFAM. Photoinitiator (PI) systems that exhibit photobleaching have proven useful in thick-section cure applications, because they generate a photoinitiation wavefront, but this effect is time-dependent. This study investigates the light transmission and through-thickness cure behavior in (meth)acrylate photopolymer formulations with the photobleaching initiator bis(2,4,6-trimethylbenzoyl)-phenylphosphine oxide (BAPO). Utilizing an optical model developed by Kenning et al., lower concentrations (0.1 wt% to 0.5 wt%) of BAPO were predicted to yield rapid onset of photoinitiation. In situ cure measurements under continuous UV LED irradiation of 380 mW/cm2 showed that a 0.1 wt% concentration of BAPO achieved peak polymerization rate within 2.5 s at a 3-mm depth. With only 1 s of irradiation at 1.7 W/cm2 intensity, the 0.1 wt% BAPO formulation also achieved the highest level of cure of the formulas tested. For an irradiation dose of 5.5 J/cm2 at a duration of 3.7 s, cured polymer specimens achieved a flexural strength of 108 MPa and a flexural modulus of 3.1 GPa. This study demonstrates the utility of optical modeling as a potential screening tool for new photopolymer formulations, primarily in identifying an upper limit to PI concentration for the desired cure depth. The results also show that photobleaching provides only a limited benefit for LFAM applications with short (1.0 s to 3.7 s) UV irradiation times and indicate that excess PI concentration can inhibit light transmission even under extended irradiation times up to 60 s.

36 MATERIALS SCIENCE↗

Stress- and Time-Dependent Formation of Self-Lubricating In Situ Carbon (SLIC) Films on Catalytically-Active Noble Alloys

Abstract Low shear strength (30 MPa) organic films were grown in situ on Pt 0.9 Au 0.1 surfaces via cyclic sliding contact in dry N 2 with trace concentrations of ambient hydrocarbons. We present a systematic investigation of the stress- and time-dependent film formation. Steady-state friction coefficients were found to be as low as µ ~ 0.015 and inversely proportional to contact pressure, revealing non-Amontonian behavior. Above a Hertzian contact pressure of ~500 MPa, shear strength dropped, indicating an activated process. Raman spectroscopy identified non-uniformity in areal coverage and relative order with contact pressure. Regions of steady-state low-friction behavior exhibited spectra similar to DLC coatings. Atomic force microscopy was used to study the formation and growth of films at the nanoscale. Stress- and time-dependent measurements suggested a sublinear increase of film volume with time, and a transition from growth to wear at a Hertzian contact pressure of ~1.2 GPa.

Jones, Morgan R.↗

Coupled electronic and magnetic relaxation in Fe 1+y Te: direct evidence for the interaction between itinerant carriers and local moments

Iron chalcogenides are of particular interests among iron-based superconductors due to their distinct properties such as high-T c on FeSe monolayer and competing magnetic correlations in Fe 1+y Te. Here, in this work, we report unusual transport properties observed near the critical composition of Fe 1+y Te (y ~ 0.09) where competing magnetic correlations exist. The resistivity exhibits surprising temperature-dependent relaxation behavior below T N , resulting in the increase of resistivity with time for 35 K < T < T N , but the decrease of resistivity with time for 10 K < T < 35 K. Such resistivity relaxation is intimately coupled to the magnetization relaxation and can be attributed to the glassy magnetic states induced by the competing magnetic orders. These findings demonstrate strong coupling between itinerant carriers and local ordered moments in Fe 1+y Te.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗

Nonadiabatic dynamics of photoexcited thiopyridone isomers: An interplay between El-Sayed’s conditions and energy gap law

We investigated the non-adiabatic dynamics of photoexcited thiopyridone systems across their ortho-, meta-, and para-isomeric forms. The relaxation pathways of the three isomers in both gas phase and solvent environments are mapped using surface hopping dynamics based on time-dependent density functional theory. Our analysis highlights the influence of isomeric structures on photophysical behavior, offering insights into design principles to control photochemical phenomena. The simulations suggest a systematic reduction in the rate of intersystem crossing (ISC) from ortho- to meta- to para-isomer. Comparisons with multiconfigurational wave function methods in the gas phase further demonstrate how electronic structure influences the predicted dynamical pathways. The simulated dynamics demonstrates that the spin–orbit coupling strength alone does not determine the rate of ISC, as both state energetics and underlying electronic and structural features play decisive roles. These aspects explain the much slower ISC in the para-isomer, as well as the non-negligible role of the El-Sayed forbidden pathway in the computed ISC dynamics.

Complete-active space self-consistent field↗

Floquet engineering with spatially nonuniform driving fields

In Floquet engineering, we apply a time-periodic modulation to change the effective behavior of a wave system. In this work, we generalize Floquet engineering to more fully exploit spatial degrees of freedom, expanding the scope of effective behaviors we can access. We develop a perturbative procedure to engineer space-time dependent driving forces that effectively transform broad classes of tight-binding systems into one another. We demonstrate several applications, including removing disorder, undoing Anderson localization, and enhancing localization to an extreme in spatially modulated waveguides. This procedure straightforwardly extends to other types of physical systems and different Floquet driving field implementations.

42 ENGINEERING↗

Rapid Screening of Single-Atom Catalyst Synthesis Conditions Using ToF-SIMS and Facet-Dependent Single-Crystal Substrates

Single-atom catalysts (SACs) offer superior catalytic performance compared to traditional nanoparticle catalysts but are challenging to develop because of the need for extensive optimization and specialized characterization techniques. Here, this study presents a rapid and versatile method for detecting synthesis conditions and elucidating deposition mechanisms of SACs on various substrates. By depositing active elements (Au, Cu, Ni and Rh) on facet-specific single-crystalline substrates (CeO 2 , TiO 2 , MgO and Al 2 O 3 ) and employing time-of-flight secondary ion mass spectroscopy (ToF-SIMS), we assessed facet-dependent deposition behaviors and identified optimal conditions for solution-based SAC synthesis. On CeO 2 and TiO 2 , we confirmed facet-dependent deposition, primarily influenced by oxygen vacancy density and photocatalytic activity, respectively. MgO exhibited the formation of metal oxide/hydroxide clusters for all active elements, and the degree of clustering for Cu and Ni was correlated with the facet hydrolysis susceptibility. Notably, Au and Rh deposition on MgO was facet-independent, attributed to the formation of hydroxide species in solution. Al 2 O 3 , due to its chemical stability and lack of surface defects, did not show active element deposition. This study not only provides a time and cost-efficient method for prescreening SAC synthesis conditions, but it also provides valuable insights into the various deposition mechanisms governing SAC formation on different substrates, paving the way for the rational design of tailored SACs for various catalytic applications.

ToF-SIMS↗

GDB-9-Ex_TD-DFT-PBE0: Dataset containing Time Dependent Density Functional Theory (TDDFT) calculations for organic molecules of the GDB-9-Ex dataset.

This dataset contains data-intensive quantum chemical electronic structure calculations for 96,766 organic molecules of the GDB-9-Ex dataset. Calculations were performed using the Time Dependent Density Functional Theory (TDDFT) first principles method using the ORCA software. It provides UV-vis spectra calculations of molecules with a high level of accuracy. The optical spectra behavior was collected based on the optimized molecular geometries in the DFTB method with 3ob parameters. All calculations utilized the def2-TZVP basis sets with the auxiliary def2/J and def2-TZVP/C basis sets. The time-dependent density-functional theory (TDDFT) approach with the PBE0 exchange-correlation functional and ORCAs default integration grid was employed. For the excitation energy calculations, the lowest 50 excitation states were calculated.

AI dataset↗

COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior

This paper presents a deep learning framework for epidemiology system identification from noisy and sparse observations with quantified uncertainty. The proposed approach employs an ensemble of deep neural networks to infer the time-dependent reproduction number of an infectious disease by formulating a tensor-based multi-step loss function that allows us to efficiently calibrate the model on multiple observed trajectories. The method is applied to a mobility and social behavior-based SEIR model of COVID-19 spread. The model is trained on Google and Unacast mobility data spanning a period of 66 days, and is able to yield accurate future forecasts of COVID-19 spread in 203 US counties within a time-window of 15 days. Interestingly, a sensitivity analysis that assesses the importance of different mobility and social behavior parameters reveals that attendance of close places, including workplaces, residential, and retail and recreational locations, has the largest impact on the effective reproduction number. Furthermore, the model enables us to rapidly probe and quantify the effects of government interventions, such as lock-down and re-opening strategies. Taken together, the proposed framework provides a robust workflow for data-driven epidemiology model discovery under uncertainty and produces probabilistic forecasts for the evolution of a pandemic that can judiciously provide information for policy and decision making. All codes and data accompanying this manuscript are available at https://github.com/PredictiveIntelligenceLab/DeepCOVID19.

60 APPLIED LIFE SCIENCES↗

Modeling Ti–6Al–4V using crystal plasticity, calibrated with multi-scale experiments, to understand the effect of the orientation and morphology of the α and β phases on time dependent cyclic loading

Classically, crystal plasticity modeling has used a range of constitutive equations, in which the incorporation of additional physics-based relationships typically results in additional model parameters. These additional parameters need to be reliably calibrated, which often necessitates the use of a range of experimental data acquired at multiple length scales. In this work, a crystal plasticity based finite element (CPFE) model for a dual-phase Titanium alloy, Ti–6Al–4V, is developed. The α and β phases of the microstructure are explicitly modeled. The model is calibrated using a systematic optimization routine and experimental data that consist of macroscopic stress-strain curves coupled with lattice strains on different crystallographic planes for the two phases. These experimental data were obtained from in situ high energy X-ray diffraction experiments for multiple material pedigrees, with varying crystallographic orientation distribution and β volume fractions. Depending on the thermomechanical-processing route and the heat treatment used to manufacture the alloy, Ti–6Al–4V can exist in a wide number of microstructural forms, which often results in the α and β phases either having well aligned slip systems (following the Burgers orientation relationship (BOR)) or possessing no alignment of the slip systems across the interphase boundary (not following the BOR). In this study, the fully-calibrated CPFE model is used to gain a comprehensive understanding of the deformation behavior of Ti–6Al–4V, specifically, the effect of microstructures that follow the BOR (or not) on time-dependent cyclic loading (including the effects of dwell hold times).

36 MATERIALS SCIENCE↗

A random unitary circuit model for black hole evaporation

Inspired by the Hayden-Preskill protocol for black hole evaporation, we consider the dynamics of a quantum many-body qudit system coupled to an external environment, where the time evolution is driven by the continuous limit of certain 2-local random unitary circuits. We study both cases where the unitaries are chosen with and without a conserved U(1) charge and focus on two aspects of the dynamics. First, we study analytically and numerically the growth of the entanglement entropy of the system, showing that two different time scales appear: one is intrinsic to the internal dynamics (the scrambling time), while the other depends on the system-environment coupling. In the presence of a U(1) conserved charge, we show that the entanglement follows a Page-like behavior in time: it begins to decrease in the middle stage of the “evaporation”, and decreases monotonically afterwards. Second, we study the time needed to retrieve information initially injected in the system from measurements on the environment qudits. Based on explicit numerical computations, we characterize such time both when the retriever has control over the initial configuration or not, showing that different scales appear in the two cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermoplasticity of metallic glasses: Processing and applications

Owing to their extremely low shear viscosity and fragility, bulk metallic glasses (BMGs) are envisioned as new net-shaping material replacing conventionally used crystalline metals for various applications. The first part of this review describes the general technique and kinetics of thermoplastic forming. The second part elaborates on the thermal processing capability of metallic glasses from atomic- to meter-scale. The micro-/nano-structure obtained after various quenching rates followed by temperature, time and heating rate dependent thermoplastic forming is described in the third section. The deformation behavior and flow kinetics of BMGs in terms of composition, mold features, and applied conditions are elaborated in the fourth section. The variation of volume and enthalpy at the supercooled liquid region, strength retention of metallic glasses compared to other conventional metals and alloys, and kinetics of liquid fragility are given in the fifth section. Finite element modeling and molecular dynamics simulations of high-temperature deformation in BMGs are presented in the sixth part. Finally, thermally-formed BMGs used for different applications, including energy, biomedical and micro-optics, are presented in the final part. Altogether, this review provides an overview of shaping capabilities and modifications in the macro-scale properties and short-to-medium range order of BMGs upon thermoplastic forming.

36 MATERIALS SCIENCE↗

Comparison of Irradiated TRISO Fuel Radioactivity from Multiple Advanced Reactor Designs

The SCALE code system was used to model, deplete, and compare several different TRISO-fueled reactor designs: a helium-cooled prismatic reactor, a helium-cooled pebble-bed reactor (PBR), and a Fluoride-Lithium-Beryllium (FLIBE) molten-salt-cooled PBR. The purpose of this comparison was to understand how differences in the reactor designs affect the radioactivity of the fuel after discharge and whether those differences are significant. First, the various reactor designs were build and depleted in the TRITON module for each design and fuel enrichment. Then, the TRITON outputs were used to create burn-up dependent reactor libraries. These libraries were then used by ORIGEN to determine the activities of discharged fuel for each reactor, which were compared to generic Westinghouse 17x17 fuel. Overall, the results showed that short term decays are dominated by reactors with higher operating powers, and the reactor type, initial fuel enrichment, and maximum burn-up are of only secondary importance. Although this analysis only focuses on activities in becquerels, these dependencies are consistent with the expected behavior of decay heat. However, analysis of long- term time periods post-irradiation shows that the reactor type and maximum burn-up have strong impacts on the activities; initial fuel enrichment has a secondary impact while operating power is inconsequential. These results would be useful for analyses, such as dose assessment and modeling in post- release scenarios; normal fuel handling operations; and spent fuel transport, storage and disposal. Of particular interest, the results in this report show that analyses that focus on spent nuclear fuel of advanced reactors need to consider each parameter carefully. Unsurprisingly, if the correct operating power is not used in short term analyses, the results will not be correct. Perhaps unexpectedly, however, if the correct reactor type is not used, then the long term results will also be incorrect, especially for areas such as permanent disposal. Even though this report focuses on the total activity of nuclear fuel, it provides initial results on the effects of various input parameters and also provides a framework to extend the work into other analyses of spent fuel from advanced reactors, especially those employing TRISO fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Thermodynamics of continuous spin photons

Special relativity allows massless particles to have states of different integer (or half-integer) helicities that mix under boosts, much like the spin states of a massive particle. Such massless particles are known as “continuous spin” particles (CSPs), a term coined by Wigner, and they are notable for their infinite tower of spin polarizations. The mixing under boosts is controlled by a spin scale 𝜌 with units of momentum. Normally, we assume 𝜌 = 0. The interactions of CSPs are known to satisfy certain simple properties, one of which is that the 𝜌 → 0 limit generically recovers familiar interactions of massless scalars, photons, or gravitons, with all other polarizations decoupling in this limit. Thus, one can ask if the photon of the Standard Model is a CSP at small but nonzero 𝜌. One concern about this possibility—originally raised by Wigner—is that the infinite tower of polarizations could pose problems for thermodynamics. To address this question, we study the thermal evolution of a CSP photon gas coupled to isothermal matter, across CSP helicity modes and phase space. We find that the structure of the interactions dictated by Lorentz symmetry implies well-behaved thermodynamics. When the CSP photon’s interactions with charged matter are turned on, the primary ℎ =±1 helicity modes thermalize quickly, while the other modes require increasingly long time scales to thermalize, set by powers of 𝑇/𝜌. In familiar thermal systems, the CSP photon behaves like the QED photon with small 𝜌- and time-dependent corrections to its effective relativistic degrees of freedom. Sizable departures from familiar thermal behavior arise at energy scales comparable to 𝜌 and could have testable experimental consequences.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Water, Protons, and the Gating of Voltage-Gated Potassium Channels

Ion channels are ubiquitous throughout all forms of life. Potassium channels are even found in viruses. Every cell must communicate with its surroundings, so all cells have them, and excitable cells, in particular, especially nerve cells, depend on the behavior of these channels. Every channel must be open at the appropriate time, and only then, so that each channel opens in response to the stimulus that tells that channel to open. One set of channels, including those in nerve cells, responds to voltage. There is a standard model for the gating of these channels that has a section of the protein moving in response to the voltage. However, there is evidence that protons are moving, rather than protein. Water is critical as part of the gating process, although it is hard to see how this works in the standard model. Here, we review the extensive evidence of the importance of the role of water and protons in gating these channels. Our principal example, but by no means the only example, will be the Kv1.2 channel. Evidence comes from the effects of D2O, from mutations in the voltage sensing domain, as well as in the linker between that domain and the gate, and at the gate itself. There is additional evidence from computations, especially quantum calculations. Structural evidence comes from X-ray studies. The hydration of ions is critical in the transfer of ions in constricted spaces, such as the gate region and the pore of a channel; we will see how the structure of the hydrated ion fits with the structure of the channel. In addition, there is macroscopic evidence from osmotic experiments and streaming current measurements. The combined evidence is discussed in the context of a model that emphasizes the role of protons and water in gating these channels.

59 BASIC BIOLOGICAL SCIENCES↗

Nonlinear Shear Rheology of Entangled Polymer Rings

Steady-state shear viscosity η($\bar{γ}$) of unconcatenated ring polymer melts as a function of the shear rate $\bar{γ}$ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z ≈ 5 and Z ≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ~ $\bar{γ}$ –0.56 ± 0.02 , independent of chain length, for Weissenberg numbers up to about 10 2 . Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ~ $\bar{γ}$ -0.57 ± 0.08 for 4 ≤ Z ≤ 57. Viscosity decreases with chain length for high $\bar{γ}$. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi ~ 10 4 , the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ~ $\bar{γ}$ –0.57 , we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large $\bar{γ}$. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/$\bar{γ}$. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time‐Dependent Cation Selectivity of Titanium Carbide MXene in Aqueous Solution

Abstract Electrochemical ion separation is a promising technology to recover valuable ionic species from water. Pseudocapacitive materials, especially 2D materials, are up‐and‐coming electrodes for electrochemical ion separation. For implementation, it is essential to understand the interplay of the intrinsic preference of a specific ion (by charge/size), kinetic ion preference (by mobility), and crystal structure changes. Ti 3 C 2 T z MXene is chosen here to investigate its selective behavior toward alkali and alkaline earth cations. Utilizing an online inductively coupled plasma system, it is found that Ti 3 C 2 T z shows a time‐dependent selectivity feature. In the early stage of charging (up to about 50 min), K + is preferred, while ultimately Ca 2+ and Mg 2+ uptake dominate; this unique phenomenon is related to dehydration energy barriers and the ion exchange effect between divalent and monovalent cations. Given the wide variety of MXenes, this work opens the door to a new avenue where selective ion‐separation with MXene can be further engineered and optimized.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗