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At least 973 records · Page 54

Towards modeling phage therapy

Patients infected with life-threatening multi-drug resistant (MDR) bacteria have been treated with cocktails of bacteriophages. This is a complicated form of personalized medicine as the phages given to a patient have to be selected beforehand on the basis of their lytic capacity of the infecting bacteria. Because bacteria rapidly become resistant, the evolution of resistance to a diverse cocktail of phages is a complicated dynamical process, during which competing bacterial strains replace one another by accumulating several resistance mechanisms, each of which may involve a fitness cost. As a consequence, it is typically not known why a particular phage therapy succeeded or failed, and how one can optimize the composition of the cocktails to maximize the rate of success. To improve upon this, we extend an existing in vivo -calibrated mouse model into a novel mathematical model for the human situation, and include multiple phages infecting multiple bacterial strains, differing in their resistance to each of the phages. We adjust several parameter estimates of the bacterial model to the human situation, and use the model to describe a successful case of phage therapy involving several cocktails, each containing several phages. In the model, treatment success crucially depended on pretreatment resistance levels, and on the diversity and the timing of the cocktails. Once an appropriate cocktail is found, it is less important to further optimize the infection rates of the phages. Resistant bacterial strains expand rapidly when sensitive strains decline, and the higher the infectivity of the phages, the faster resistant strains expand. Because resistance evolves rapidly, it is best to provide a diverse set of phages right from the start of therapy, i.e., to hit hard and early, and create a high genetic barrier to bacterial resistance.

59 BASIC BIOLOGICAL SCIENCES↗

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗

How to Obtain the Redshift Distribution from Probabilistic Redshift Estimates

Abstract A reliable estimate of the redshift distribution n ( z ) is crucial for using weak gravitational lensing and large-scale structures of galaxy catalogs to study cosmology. Spectroscopic redshifts for the dim and numerous galaxies of next-generation weak-lensing surveys are expected to be unavailable, making photometric redshift (photo- z ) probability density functions (PDFs) the next best alternative for comprehensively encapsulating the nontrivial systematics affecting photo- z point estimation. The established stacked estimator of n ( z ) avoids reducing photo- z PDFs to point estimates but yields a systematically biased estimate of n ( z ) that worsens with a decreasing signal-to-noise ratio, the very regime where photo- z PDFs are most necessary. We introduce Cosmological Hierarchical Inference with Probabilistic Photometric Redshifts ( CHIPPR ), a statistically rigorous probabilistic graphical model of redshift-dependent photometry that correctly propagates the redshift uncertainty information beyond the best-fit estimator of n ( z ) produced by traditional procedures and is provably the only self-consistent way to recover n ( z ) from photo- z PDFs. We present the chippr prototype code, noting that the mathematically justifiable approach incurs computational cost. The CHIPPR approach is applicable to any one-point statistic of any random variable, provided the prior probability density used to produce the posteriors is explicitly known; if the prior is implicit, as may be the case for popular photo- z techniques, then the resulting posterior PDFs cannot be used for scientific inference. We therefore recommend that the photo- z community focus on developing methodologies that enable the recovery of photo- z likelihoods with support over all redshifts, either directly or via a known prior probability density.

79 ASTRONOMY AND ASTROPHYSICS↗

Development of a Filtered CFD-DEM Drag Model with Multiscale Markers Using an Artificial Neural Network and Nonlinear Regression

Here, the accuracy of coarse-grained Euler-Lagrangian simulations of fluidized beds heavily depends on the mesoscale drag models to account for the influences of the unresolved sub-grid structures. Traditional filtered drag models are regressed with mesoscale markers such as voidage and slip velocities. In this research, a filtered drag was regressed with both mesoscale and macro-scale markers using fine grid Computational Fluid Dynamics - Discrete Element Method (CFD-DEM) simulations. The traditional non-linear regression method was compared with machine learning regression using an Artificial Neural Network (ANN) implemented in PyTorch and coupled with MFiX. The new drag showed higher accuracy than the Wen-Yu drag and another filtered drag derived from the two-fluid model. The nonlinear regression shows slightly better results than ANN regression in cases with similar R 2 values. The utilization of the gas inlet velocity as an additional macro-scale marker reduced the errors by up to 55.3% in the tested cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Insight into premixed diethoxymethane flames: Laminar burning velocities, temperatures, and emissions behaviour

Diethoxymethane ((CH 3 CH 2 O) 2 CH 2 , DEM) is a promising carbon-neutral fuel. DEM is a diether or acetal with a molecular structure similar to oxymethylene ethers (CH 3 O–(CH 2 O)n–CH 3 , OME n ). Thus, DEM can be expected to have a similar combustion behavior to OMEs, reducing harmful emissions such as NO x and particulate matter (PM) in internal combustion engines. From both experimental and kinetic modeling, fundamental studies on DEM are scarce in the literature. More studies are required to gain a detailed insight into the oxidation kinetics of DEM. Laminar burning velocity (LBV) is a critical property that allows a detailed assessment of the potential application of DEM in combustion devices. Unfortunately, the literature on the LBV of DEM is limited. Therefore, in this study we have investigated the LBV of DEM using two reactors for the first time, namely a heat flux burner and a combustion chamber. The experimental data is reported for equivalence ratio between 0.7 and 1.7, initial temperatures of 368–423 K, and initial pressure of 1–5 bar. In addition, we developed a detailed kinetic model extending our recent work of Shrestha et al. (Combust. Flame. 246 (2022) 112,426) to characterize the combustion behavior of DEM utilizing the new experimental data from this work and the literature data. Our model performs remarkably well in capturing the newly measured LBV experimental data over various experimental conditions. We found that DEM and dimethoxy methane (DMM) have similar values of LBVs (within ±1.5 cm/s) for a given condition, which indicates that intermediate chemistry governs the flame chemistry. Despite DEM being a larger molecule that is expected to have slightly lower LBVs than DMM, its effect on the measured values of LBVs is negligible. Finally, we experimentally measured NO x formation in DEM flame for the first time. The stochiometric flame has the highest NO x formation. The proposed model predicted the equivalence ratio dependence of NO x nicely. However, it overestimates the NO x formation for stoichiometric DEM/air mixtures by ~30 %. The model suggests that the thermal NO formation route is favored at lean and stochiometric conditions. In contrast, the prompt NO formation route is enhanced for rich mixtures.

10 SYNTHETIC FUELS↗

DECOVALEX-2023: Task D Final Report

Task D of DECOVALEX-2023 is focused on the simulation of the coupled thermal hydraulic-mechanical (THM) behaviour in the full-scale engineered barrier system (EBS). The Horonobe EBS experiment is the demonstration of the full-scale EBS in the underground research laboratory (URL) (performed by JAEA in the Horonobe URL in Japan). Task D consisted of the three steps, a preliminary step (Step 0), simulation of the laboratory tests (Step 1) and simulation of the in-situ full-scale EBS experiment (Step 2). Since the Horonobe EBS experiment demonstrates the vertical emplacement option of the EBS, the experiment gallery is also backfilled with the backfill material. Therefore, interaction between the EBS and the backfill material can also be demonstrated, such as deformation (change of density) of the buffer material. The underground water in the Horonobe URL is saline. This fact adds chemical processes to THM behaviour. For example, mechanical properties (such as swelling pressure of the buffer material and backfill material) and hydraulic properties (such as permeability of the buffer material and backfill material) change depending on the water chemistry. Task D was therefore a challenging Task focused on not only the relatively simple THM behaviour but also complex THM behaviour including chemical processes. Six research teams (BGR, CAS, JAEA, KAERI, SNL and Taipower) participated the Task D. BGR, CAS, JAEA, KAERI and Taipower research teams selected a THM approach, while the SNL research team selected a TH approach. Step 1 involved the simulation of laboratory test results and was important to check the numerical codes developed by the research teams. Step 1 was divided into four sub steps. The simulation results through the Step 1 identified the parameters for simulation of the Step 2. Basic parameters of the materials (buffer material, backfill material, rock mass, concrete, sand) were provided by JAEA. Special parameters which research team needed were identified by back analysis of Step 1. Most notably the mechanical behaviour of swelling and displacement depended on the applied model (elastic model or elastoplastic model). Parameters such as Young’s modulus were found to need smaller values than characterised in the fundamental laboratory test results (Step 1-1, 1-2) for the elastic model. Although laboratory experiments are usually simple, test results contained some error. For example, if the saturation level is 100 % or higher, it should be considered an error. This situation was presented in the Step 1-3. A possible reason is that the buffer material is a mixture of bentonite and silica sand. When a specimen is cut to measure volume or weight, sand grains will affect the measurement data. In Step 2, boundary conditions such as temperature on the surface of the simulated overpack, heater power of the electrical heaters installed in the simulated overpack, injection pressure and inflow rate of the test water, were applied. The outer boundary conditions can be selected using measured data (injection pressure and inflow rate of the test water that is controlled by the injection systems installed in the sand layer around the buffer material and in the boundary between backfill material and concrete support). Since such measured data has some noise, research teams developed their own simplified boundary conditions. Inner boundary conditions can be selected using measured data as heater power and temperature on the surface of the simulated overpack. These data also contain some noise, so research teams developed their own simplified developed boundary conditions. Task D validated various approaches thorough the simulation of the in-situ full scale EBS system including backfill of the gallery: variations in the coupling processes (THM or THC), analysis codes, and boundary conditions. Temperature distribution in the buffer material was simulated well by all research teams. This means thermal behaviour is not sensitive to the simulation approaches. Although the water content distribution on the outside of the buffer material was well simulated by all research teams, the simulation results differ from the measured values inside the buffer material (at the centre and inside, near the simulated overpack). The buffer material is made from tap water, but in the in-situ experiment, saline groundwater infiltrates the buffer material. Therefore, the selection of the hydraulic parameters of the buffer material greatly affects the simulation results of the re saturation behaviour of the buffer material. In the Horonobe EBS experiment, measured values suitable for validating the simulation results were not obtained near the simulated overpack. When simulating the pressure and deformation of the buffer material, the measurement data is easily affected by the installation conditions of the measurement sensors, so verifying the measurement data itself remains an issue. Mechanical simulation results differ depending on whether they are considered as elastic or elastoplastic phenomena. The accuracy of measured in-situ data can be assessed by detailed analysis comparing sampling specimen analysis and measured data. The Horonobe EBS experiment is scheduled to be dismantled in the future (FY2026 and 2027). This detailed dismantling investigation will finally confirm the measured data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Non-Contact Mass Density and Thermal Conductivity Measurements of Organic Thin Films Using Frequency–Domain Thermoreflectance

Thin-film organic materials are broadly used to study amorphous stabilization of active pharmaceuticals, control explosive detonation phenomena, and introduce insulation in novel thermal barriers. Their synthesis, however, introduces defects and thickness variations that warrant careful characterization of local thermophysical properties such as thermal conductivity and mass density. In this study, wide bandwidth (200 Hz to 20 MHz) frequency–domain thermoreflectance (FDTR) is demonstrated to simultaneously extract the thermal conductivity and mass density of 1 μm physical vapor-deposited indomethacin films on Si and SiO 2 substrates, as well as 10 and 100 μm films on Si. By assuming a bulk specific heat capacity, mass densities are determined with FDTR measurements of volumetric heat capacity and are in good agreement with the literature, as well as models based upon a dependence on porosity and the kinetic theory for phonons. Lastly, it is found that for broad-band FDTR measurements, insulating substrates provide improved fidelity for the extraction of thermal conductivity and volumetric heat capacity in organic thin films. Overall, this work demonstrates the potential for FDTR as a non-contact method to determine microscale mass density variations across the surface and thickness of organic thin films.

36 MATERIALS SCIENCE↗

Realizing Wide-Gamut Human-Centric Display Lighting with K 3 AlP 3 O 9 N:Eu 2+

Abstract Computers, televisions, and smartphones are revolutionized by the invention of InGaN blue light-emitting diode (LED) backlighting. Yet, continual exposure to the intense blue LED emission from these modern displays can cause insomnia and mood disorders. Developing “human-centric” backlighting that uses a violet-emitting LED chip and a trichromatic phosphor mixture to generate color images is one approach that addresses this problem. The challenge is finding a blue-emitting phosphor that possesses a sufficiently small Stokes’ shift to efficiently down-convert violet LED light and produce a narrow blue emission. This work reports a new oxynitride phosphor that meets this demand. K 3 AlP 3 O 9 N:Eu 2+ exhibits an unexpectedly narrow (45 nm, 2206 cm -1 ), thermally robust, and efficient blue photoluminescence upon violet excitation. Computational modeling and temperature-dependent optical property measurements reveal that the narrow emission arises from a rare combination of preferential excitation and site-selective quenching. The resulting chromaticity coordinates of K 3 AlP 3 O 9 N:Eu 2+ lie closer to the vertex of the Rec. 2020 than a blue LED chip and provides access to ≈10% more colors than a commercial tablet when combined with commercial red- and green-emitting phosphors. Alongside the wide gamut, tuning the emission from the violet LED and phosphor blend can reduce blue light emissions to produce next-generation, human-centric displays.

36 MATERIALS SCIENCE↗

Shape restricted additive hazards models: Monotone, unimodal, and U‐shape hazard functions

We consider estimation of the semiparametric additive hazards model with an unspecified baseline hazard function where the effect of a continuous covariate has a specific shape but otherwise unspecified. Such estimation is particularly useful for a unimodal hazard function, where the hazard is monotone increasing and monotone decreasing with an unknown mode. A popular approach of the proportional hazards model is limited in such setting due to the complicated structure of the partial likelihood. Our model defines a quadratic loss function, and its simple structure allows a global Hessian matrix that does not involve parameters. Thus, once the global Hessian matrix is computed, a standard quadratic programming method can be applicable by profiling all possible locations of the mode. However, the quadratic programming method may be inefficient to handle a large global Hessian matrix in the profiling algorithm due to a large dimensionality, where the dimension of the global Hessian matrix and number of hypothetical modes are the same order as the sample size. We propose the quadratic pool adjacent violators algorithm to reduce computational costs. The proposed algorithm is extended to the model with a time‐dependent covariate with monotone or U‐shape hazard function. In simulation studies, our proposed method improves computational speed compared to the quadratic programming method, with bias and mean square error reductions. We analyze data from a recent cardiovascular study.

Mathematical & Computational Biology↗

Measurement of the branching fractions of $$ \overline{B} $$ → D(*)K−$$ {K}_{(S)}^{\left(\ast \right)0} $$ and $$ \overline{B} $$ → D(*)$$ {D}_s^{-} $$ decays at Belle II

Abstract We present measurements of the branching fractions of eight$$ {\overline{B}}^0 $$ B ¯ 0 →D (*)+ K − $$ {K}_{(S)}^{\left(\ast \right)0} $$ K S ∗ 0 ,B − →D (*)0 K − $$ {K}_{(S)}^{\left(\ast \right)0} $$ K S ∗ 0 decay channels. The results are based on data from SuperKEKB electron-positron collisions at the Υ(4S) resonance collected with the Belle II detector, corresponding to an integrated luminosity of 362 fb −1 . The event yields are extracted from fits to the distributions of the difference between expected and observedBmeson energy, and are efficiency-corrected as a function ofm(K − $$ {K}_{(S)}^{\left(\ast \right)0} $$ K S ∗ 0 ) andm(D (*) $$ {K}_{(S)}^{\left(\ast \right)0} $$ K S ∗ 0 ) in order to avoid dependence on the decay model. These results include the first observation of$$ {\overline{B}}^0 $$ B ¯ 0 →D + K − $$ {K}_S^0 $$ K S 0 ,B − →D* 0 K − $$ {K}_S^0 $$ K S 0 , and$$ {\overline{B}}^0 $$ B ¯ 0 →D* + K − $$ {K}_S^0 $$ K S 0 decays and a significant improvement in the precision of the other channels compared to previous measurements. The helicity-angle distributions and the invariant mass distributions of theK − $$ {K}_{(S)}^{\left(\ast \right)0} $$ K S ∗ 0 systems are compatible with quasi-two-body decays via a resonant transition with spin-parityJ P = 1 − for theK − $$ {K}_S^0 $$ K S 0 systems andJ P = 1 + for theK − K* 0 systems. We also present measurements of the branching fractions of four$$ {\overline{B}}^0 $$ B ¯ 0 →D (*)+ $$ {D}_s^{-} $$ D s − ,B − →D (*)0 $$ {D}_s^{-} $$ D s − decay channels with a precision compatible to the current world averages.

Physics↗

Explainable discrepancy checker and diagnosis for digital Twin-based supervisory control system

By virtually representing a physical object and process, a digital twin (DT) enables optimal autonomous operations by combining classical and novel frameworks in sensors, state predictions, and multi-input/multi-output systems. A DT’s values depend on how well models estimate quantities of interest and on how uncertainty is handled. Moreover, DTs often combine physics-based and data-driven models with mixed fidelities, where classical uncertainty quantification (UQ) struggles with many sources of uncertainty and real-time constraints. Here, this work presents a UQ-based discrepancy checking and diagnosis tool for a DT-based supervisory control system. The tool is developed using metadata from an automated DT development process to learn correlations between sources of uncertainties and outcomes. During operation, it compares predictions with measurements, attributes discrepancies to dominant sources, and recommends parameter and configuration updates. We verify the workflow on a synthetic temperature-control problem and deploy it on a virtual Thermal Energy Delivery System, reducing mismatch and improving control robustness.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Inelastic equation of state for solids

In this study, a complete inelastic equation of state (IEOS) for solids is developed based on a superposition of thermodynamic energy potentials. The IEOS allows for a tensorial stress state by including an isochoric hyperelastic Helmholtz potential in addition to the zero-kelvin isotherm and lattice vibration energy contributions. Inelasticity is introduced through the nonlinear equations of finite strain plasticity which utilize the temperature dependent Johnson–Cook yield model. Material failure is incorporated into the model by a coupling of the damage history variable to the energy potentials. The numerical evaluation of the IEOS requires a nonlinear solution of stress, temperature and history variables associated with elastic trial states for stress and temperature. The model is implemented into the ALEGRA shock and multi-physics code and the applications presented include single element deformation paths, the Taylor anvil problem and an energetically driven thermo-mechanical problem.

42 ENGINEERING↗

A careful examination of closure models in Euler–Lagrange Simulations of compressible multiphase flow in a planar shock particle curtain problem

In this work we present a comprehensive investigation of state-of-the-art closure models employed to represent interphase momentum, thermal, and work exchange between the gas and particulate phases for Euler–Lagrange (EL) simulations in shock-driven flows. A complete list of closures for the force, torque, heat transfer, and work exchange models is provided. In particular, the present work includes a stochastic closure for the particle-to-particle variation in the quasi-steady force and a deterministic closure for particle-to-particle variation in the added mass force in an EL framework. These variations arise due to the presence of neighboring particles and particle–particle interactions. To investigate the importance of each closure term, we carry out fully three-dimensional simulations for a planar shock propagating over a random bed of inert particles. The primary goal is to evaluate the role of each closure term on the gas dynamic features (such as transmitted and reflected shock locations) and particle curtain features (such as upstream and downstream curtain locations). To this end, thirteen cases are considered, with each case progressively including a closure model with the goal to identify and quantify its contribution to the simulated dynamics. We show that the volume fraction dependence of the mean force models plays an important role in generating wave-like instabilities that lead to concentration bands. In addition, fluctuations in quasi-steady and added mass forces primarily decrease the internal instabilities that tend to enhance local volume fraction variations. Particle rotation is primarily due to inter-particle collisions, is generally weak, and does not play an important role in the translational dynamics for the present configuration. Inter-phase heat transfer has a strong effect on gas phase temperature, slows down the transmitted and reflected shocks, and decreases the width of the curtain. Furthermore, the absence of a work-coupling model fails to conserve the total energy, greatly under-predicts the gas temperature which in turn affects the particle dynamics.

Compressible flow↗

Activation of CO 2 by Actinide Cations (Th + , U + , Pu + , and Am + ) as Studied by Guided Ion Beam and Triple Quadrupole Mass Spectrometry

Reactions of CO 2 with Th+ have been studied using guided ion beam tandem mass spectrometry (GIBMS) and with An + (An + = Th + , U + , Pu + , and Am + ) using triple quadrupole inductively coupled plasma mass spectrometry (QQQ-ICP-MS). Additionally, the reactions ThO + + CO and ThO + + CO 2 were examined using GIBMS. Modeling the kinetic energy dependent GIBMS data allowed determination of bond dissociation energies (BDEs) for D o (Th + -O) and D o (OTh + -O) that are in reasonable agreement with previous GIBMS measurements. The QQQ-ICP-MS reactions were studied at higher pressures where multiple collisions between An + and the neutral CO 2 occur. As a consequence, both AnO + and AnO 2 + products were observed for all An + except Am + , where only AmO + was observed. Here, the relative abundances of the observed monoxides compared to the dioxides are consistent with previous reports of the AnO n + (n = 1, 2) BDEs. Comparison of the periodic trends of the group 4 transition metal, lanthanide (Ln), and actinide atomic cations in reactions with CO 2 (a formally spin-forbidden reaction for most M + ground states), and O 2 (a spin unrestricted reaction) indicate that spin conservation plays a minor role, if any, for the heavier An + metals. Further correlation of Ln + and An + + CO 2 reaction efficiencies with the promotion energy (E p ) to the first electronic state with two valence d-electrons (E p (5d 2 ) for Ln + and E p (6d 2 ) for An + ) indicates that the primary limitation in the activation of CO 2 is the energetic cost to promote from the electronic ground state of the atomic metal ion to a reactive state.

bond activation↗

Guided Ion Beam and Quantum Chemical Investigation of the Thermochemistry of Thorium Dioxide Cations: Thermodynamic Evidence for Participation of f Orbitals in Bonding

Kinetic energy dependent reactions of ThO + with O 2 are studied using a guided ion beam tandem mass spectrometer. The formation of ThO 2 + in the reaction of ThO + with O 2 is observed to be slightly endothermic and also exhibits two obvious features in the cross section. These kinetic energy dependent cross sections were modeled to determine a 0 K bond dissociation energy of D 0 (OTh + - O) = 4.94 ± 0.06 eV. This value is slightly larger but within experimental uncertainty of less precise previously reported experimental values. The higher energy feature in the ThO 2 + cross section was also analyzed and suggests formation of an excited state of the product ion lying 3.1 ± 0.2 eV above the ground state. Additionally, the thermochemistry of ThO 2 + was explored by quantum chemical calculations, including a full Feller-Peterson-Dixon (FPD) composite approach with correlation contributions up to CCSDT(Q) and four-component spin-orbit corrections, as well as more approximate CCSD(T) calculations including semiempirical estimates of spin-orbit energy contributions. The FPD approach predicts D 0 (OTh + -O) = 4.87 ± 0.04 eV, in good agreement with the experimental value. Analogous FPD results for ThO+, ThO, and ThO 2 are also presented, including ionization energies for both ThO and ThO 2 . The ThO 2 + bond energy is larger than those of its transition metal congeners, TiO 2 + and ZrO 2 + , which can be attributed partially to an actinide contraction, but also to contributions from the participation of f orbitals on thorium that are unavailable to the transition metal systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

High Pressure Infiltration/Expulsion of Aqueous NaCl in Planar Hydrophobic Nanopores

Pressure-driven permeation of water in a poorly wettable material results in a conversion of mechanical work into surface free energy representing a new form of energy storage, or absorption. When water is replaced by a concentrated electrolyte solution, the storage capacity of a nanoporous medium becomes comparable to high-end supercapacitors. The addition of salt can also reduce the hysteresis of the infiltration/expulsion cycle. Our molecular simulations provide a theoretical perspective into the mechanisms involved in the process, and underlying structures and interactions in compressed nanoconfined solutions. Specifically, we consider aqueous NaCl in planar confinements of widths of 1.0 nm and 1.64 nm and pressures of up to 3 kbar. Open ensemble Monte Carlo simulations utilizing fractional exchanges of molecules for efficient additions/removal of ions have been utilized in conjunction with pressure-dependent chemical potentials to model bulk phases under pressure. Confinements open to these pressurized bulk, aqueous electrolyte phases show reversibility at narrow pore sizes and irreversibility in wider ones, consistent with experiment, as well as strong hysteresis at both pore size. The addition of salt results in significant increases in the solid/liquid interfacial tension in narrower pores and associated infiltration and expulsion pressures. Furthermore, these changes are consistent with strong desalination effects at the lower pore size observed irrespective of external pressure and initial concentration.

25 ENERGY STORAGE↗

Frequency Conversion in a Time-Variant Dielectric Metasurface

The color of light is a fundamental property of electromagnetic radiation; as such, control of the frequency is a cornerstone of modern optics. Nonlinear materials are typically used to generate new frequencies, however the use of time-variant systems provides an alternative approach. Utilizing a metasurface that supports a high-quality factor resonance, we demonstrate that a rapidly shifting refractive index will induce frequency conversion of light that is confined in the nanoresonator meta-atoms. We experimentally observe this frequency conversion and develop a time-dependent coupled mode theory model that well describes the system. Finally, the intersection of high quality-factor resonances, active materials, and ultrafast transient spectroscopy leads to the demonstration of metasurfaces operating in a time-variant regime that enables enhanced control over light–matter interaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Electron–Phonon and Spin–Lattice Coupling in Atomically Thin Layers of MnBi 2 Te 4

MnBi 2 Te 4 represents a new class of magnetic topological insulators in which novel quantum phases emerge at temperatures higher than those found in magnetically doped thin films. Here in this paper, we investigate how couplings between electron, spin, and lattice are manifested in the phonon spectra of few-septuple-layer thick MnBi 2 Te 4 . After categorizing phonon modes by their symmetries, we study the systematic changes in frequency, line width, and line shape of a spectrally isolated A1g mode. The electron–phonon coupling increases in thinner flakes as manifested in a broader phonon line width, which is likely due to changes of the electron density of states. In 4- and 5-septuple thick samples, the onset of magnetic order below the Néel temperature is concurrent with a transition to an insulating state. We observe signatures of a reduced electron–phonon scattering across this transition as reflected in the reduced Fano parameter. Finally, spin–lattice coupling is measured and modeled from temperature-dependent phonon frequency.

36 MATERIALS SCIENCE↗