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At least 289 records · Page 16

The Low-Yield Nuclear Monitoring (LYNM) Experimental Science Plan

The Low-Yield Nuclear Monitoring (LYNM) Program is a long-term NNSA research and development effort designed to improve the United States’ explosion monitoring capabilities, particularly with respect to low-yield and potentially evasive underground nuclear testing. The LYNM Program focuses on researching, discovering, and exploiting unique and useful signatures, from all available technologies and sensors (e.g., seismic, acoustic, electromagnetic, gases, and particulates (both stable and radioactive)). Four Department of Energy laboratories participate in LYNM and together are referred to as the ‘quad-lab’. The R&D program execution is performed under NNSA defined structures known as “ventures”. Four science ventures were established: 1) Explosion Source Functions; 2) Containment of Low-Yield Underground Tests; 3) Local Signatures; 4) Dynamic Monitoring Networks. To organize and execute the large field scale experiment a fifth venture was established: 5) Physics Experiment One (PE-1). As part of the LYNM Program, a series of experiments are planned at various scales and levels of venture involvement. These vary from those that involve a subset of labs and/or LYNM ventures (e.g., small experiments), to full quad-lab LYNM Program field-scale integrated experiments. Such experiments may involve chemical explosions with tracer materials or other means of simulating the expected signals from a nuclear explosion. The LYNM Program does not conduct actual nuclear explosions. Since 1992, the U.S. has observed a moratorium on underground nuclear explosions. This document is intended to provide the underlying scientific basis for the LYNM planned experimental work. Each specific LYNM experiment will develop a goals, objectives, and requirements (GOR) plan following the guidance in this document. The LYNM technical staff will define the numbers and types of experiments required over the course of the Program based on technical needs and within funding constraints. As with any scientific experiment series, the number and types of experiments may change based upon the experimental results obtained. An experiment that agrees with models/codes/software signature predictions may need fewer repetitions/variations, depending upon the level of statistical rigor desired, as compared to one in which the predictions and experimental data do not match. The large LYNM field-scale integrated experiments require the longest lead-time for planning, and these are discussed in more detail near the end of this document.

58 GEOSCIENCES↗

Study of the Segmental Dynamics and Ion Transport of Solid Polymer Electrolytes in the Semi-crystalline State

Solid polymer electrolytes are promising in fulfilling the requirements for a stable lithium metal anode toward higher energy and power densities. In this work, we investigate the segmental dynamics, ionic conductivity, and crystallinity of a polymer electrolyte consisting of poly(ethylene oxide) (PEO) and lithium triflate salt, in the semi-crystalline state. Using quasi-elastic neutron scattering, the segmental dynamics of PEO chains confined between the crystalline lamellae is quantified, using Cole–Cole analysis. We show that the structural relaxation time, τ 0 , of PEO equilibrated near room temperature is six-fold longer than the same sample that had just cooled down to room temperature. This corresponds to a three-fold smaller ionic conductivity in the equilibrated condition. This work reveals that the segmental dynamics of semi-crystalline polymer electrolytes is very sensitive to thermal history. We demonstrate that quasi-elastic neutron scattering can be used to characterize the ion transport and segmental dynamics in the semi-crystalline state.

36 MATERIALS SCIENCE↗

WRF-simulated low-level jets over Iowa: characterization and sensitivity studies

Abstract. Output from 6 months of high-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize local low-level jets (LLJs) over Iowa for winter and spring in the contemporary climate. Low-level jets affect rotor plane aerodynamic loading, turbine structural loading and turbine performance, and thus accurate characterization and identification are pertinent. Analyses using a detection algorithm wherein the wind speed above and below the jet maximum must be below 80 % of the jet wind speed within a vertical window of approximately 20–530 m a.g.l. (above ground level) indicate the presence of an LLJ in at least one of the 14 700 4 km×4 km grid cells over Iowa on 98 % of nights. Nocturnal LLJs are most frequently associated with stable stratification and low turbulent kinetic energy (TKE) and hence are more frequent during the winter months. The spatiotemporal mean LLJ maximum (jet core) wind speed is 9.55 m s−1, and the mean height is 182 m. Locations of high LLJ frequency and duration across the state are seasonally varying, with a mean duration of 3.5 h. The highest frequency occurs in the topographically complex northwest of the state in winter and in the flatter northeast of the state in spring. Sensitivity of LLJ characteristics to the (i) LLJ definition and (ii) vertical resolution at which the WRF output is sampled is examined. LLJ definitions commonly used in the literature are considered in the first sensitivity analysis. These sensitivity analyses indicate that LLJ characteristics are highly variable with definition. Use of different definitions identifies both different frequencies of LLJs and different LLJ events. Further, when the model output is down-sampled to lower vertical resolution, the mean jet core wind speed height decreases, but spatial distributions of regions of high frequency and duration are conserved. Implementation of a polynomial interpolation to extrapolate down-sampled output to full-resolution results in reduced sensitivity of LLJ characteristics to down-sampling.

17 WIND ENERGY↗

Inferring UAV Position Relative to Smartphone Sensor Based on Acoustic Characteristics

As commercial and non-commercial unmanned aerial vehicles (UAVs) improve technologically and increase in accessibility, their potential for use in actions antithetical to nuclear non-proliferation efforts increases as well. The ability to identify and locate UAVs using ubiquitous, inexpensive hardware and software would be advantageous as both a deterrent and an initial warning system. Our team looks to utilize smartphones as acoustic sensors to record and characterize UAV movement based on the sound produced while in flight. Multi-rotor UAVs produce identifiable acoustic spectral characteristics with frequencies and harmonics corresponding to motor revolutions per minute and the propeller characteristics. As the source moves closer to the receiver these spectral patterns remain relatively stable (at slow speeds), while the energy observed from the waves increases. The goal of this work is to utilize a small network of smartphone sensors with known, fixed positions to infer the relative position of an in-flight UAV with respect to the position of the smartphones through the variation in acoustic energy.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Laser Powder Bed Fusion of ODS 14YWT from Gas Atomization Reaction Synthesis Precursor Powders

Abstract Laser powder bed fusion (LPBF) additive manufacturing (AM) is a promising route for the fabrication of oxide dispersion strengthened (ODS) steels. In this study, 14YWT ferritic steel powders were produced by gas atomization reaction synthesis (GARS). The rapid solidification resulted in the formation of stable, Y-containing intermetallic Y 2 Fe 17 on the interior of the powder and a stable Cr-rich oxide surface. The GARS powders were consolidated with LPBF. Process parameter maps identified a stable process window resulting in a relative density of 99.8%. Transmission electron microscopy and high-energy x-ray diffraction demonstrated that during LPBF, the stable phases in the powder dissociated in the liquid melt pool and reacted to form a high density (1.7 × 10 20 /m 3 ) of homogeneously distributed Ti 2 Y 2 O 7 pyrochlore dispersoids ranging from 17 to 57 nm. The use of GARS powder bypasses the mechanical alloying step typically required to produce ODS feedstock. Preliminary mechanical tests demonstrated an ultimate tensile and yield strength of 474 MPa and 312 MPa, respectively.

36 MATERIALS SCIENCE↗

Surface energetics of wurtzite and sphalerite polymorphs of zinc sulfide and implications for their formation in nature

Surface energetics of zinc sulfide nanoparticles determines their structure, properties, and occurrence. Using a combination of experimental techniques, we investigated the thermodynamics of the two polymorphs, sphalerite and wurtzite at bulk and nanoscale to understand their occurrence. Calorimetric measurements confirmed that wurtzite has a lower surface energy than sphalerite, which causes a reversal in phase stability at the nanoscale, with wurtzite energetically stable for particle size below 10 nm. Taking these surface energies into account, a simple model of the thermodynamics of the sphalerite - wurtzite transformation as a function of particle size and temperature can explain the occurrence of the zinc sulfide polymorphs in environments as diverse as ore bodies and planetary atmospheres.

58 GEOSCIENCES↗

Tolerance of Perovskite Solar Cells to Targeted Proton Irradiation and Electronic Ionization Induced Healing

Mixed organic–inorganic halide perovskite solar cells (PSCs) are of interest for space photovoltaic applications due to their apparent tolerance to high-energy proton radiation. Here, the use of a more stable wide-bandgap FA0.8Cs0.2PbI2.4Br0.6Cl0.02 perovskite with thin encapsulation enables, for the first time, the detailed dependence of fluence and energy of energetic protons on device performance. Energies were chosen to provide the highest concentration of displacements within the active region, and therefore the highest amount of degradation. Not only are these devices tolerant when compared to conventional technologies, but an unexpected increase in open circuit voltage and power density is observed for increased electronic ionization when the proton energy is increased. This study aims to expand the description of the proton radiation tolerance to include not only nonionizing nuclear energy losses that are most detrimental to current technologies, but electronic ionization, which is shown to yield benefits in PSCs.

device performance↗

Lab-scaled performance evaluation of novel water-lean solvents for post combustion CO 2 capture

Here, this work focuses on demonstrating the energetic performance and operational reliability in a continuous system of RTI's water-lean solvents for post-combustion CO 2 capture applications. RTI's Non-Aqueous Solvent, NAS-1A was subjected to 100 h of continuous, CO 2 capture and regeneration operation using a Lab-scale Gas Absorption System (LsGAS) while the CO 2 capture efficiency, mass balance, and total energy inputs were monitored. Throughout the test period, NAS-1A demonstrated stable operation with 90% CO 2 capture while requiring about 15% lower total energy input for solvent regeneration compared to 30 wt% monoethanolamine (MEA) solution. The use of a slipstream of CO 2 -rich solvent from the absorber sump reduced the regenerated CO 2 temperature before the gas was further cooled by the overhead condenser at the top of the desorber. The rich-split setup combined with a wash section may be an effective approach to remove water and solvent vapor from the regenerated CO 2 as well as to recover heat at the top of the desorber. NAS-1B was later developed and included a modifier component that lowers the heat of CO 2 absorption and reduces the vapor pressure of the amine component. The total energy inputs for 90% CO 2 capture with NAS-1B was found to be 25% less than that of the MEA. A gas chromatograph was used to monitor the amine concentration in the gas leaving the absorber wash section. It was found that under similar operating conditions, the presence of the modifier in NAS-1B reduces the amine in the absorber off-gas from 143 ppm in NAS-1A to 20 ppm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Clean Energy Deployment Baseline for the Energy Community and Low-Income Tax Credit Bonuses [Slides]

The Inflation Reduction Act of 2022 introduced, for the first time, place-based federal tax incentives for projects sited in “Energy Communities,” potentially changing the economic calculus of where projects are best sited. Storage projects can qualify for a 10-percentage-point bonus to the Investment Tax Credit (e.g., from 30% to 40%), while wind and solar projects may qualify for either the ITC bonus or a 10% bonus to the Production Tax Credit (e.g., from $\$27.5$ to $\$30.25$/MWh). Energy Communities are areas with historical ties to fossil fuel industries and above average unemployment levels (FFEU), with closed coal mines or power plants, or contaminated properties. They seek to identify locations across the US that could especially benefit from economic revitalization. This report explores how the new federal tax credit incentives are impacting clean energy deployment patterns and establishes historical baselines against which future changes can be compared. We include a few case studies of clean energy projects going specifically to areas that were recently impacted by coal power plant closures to provide concrete examples of investments in Energy Communities. However, this publication does not assess how much of the incentive benefits pass from clean energy developers to hosting communities, nor does it offer a comprehensive view of the economic effects of clean energy deployment on Energy Communities. Key highlights include: - As clean energy projects take multiple years to conceptualize and develop, it is likely too early to see shifts towards Energy Community locations either among newly built projects or those that entered interconnection queues in 2023. - Approximately 35% of onshore wind, 50% of solar, and 60% of storage capacity built in 2023 and the first half of 2024 are located in Energy Communities, making them likely eligible for bonus incentives. While these bonus incentives were not available to projects coming online before 2023, we used 2023 Energy Community definitions to classify whether past projects were built in what is now considered an Energy Community. The deployment levels for 2023-2024 are similar to recent years (2020-2022) for solar and storage but slightly lower for wind. - Clean energy capacity has surged in the interconnection queues over the last few years, with about 45-50% of both recently proposed and total queued capacity being located in Energy Communities. While the amount of capacity in Energy Communities has also grown, its relative share is either stable (solar and storage) or slightly lower (wind) among projects that entered the queue in 2023. - Clean energy projects can be built at lower costs in Energy Communities. The levelized cost of energy after incentives was on average $\$9$/MWh (24%) lower for solar projects and $\$2$/MWh (6%) lower for wind projects built in 2023, relative to projects not located in Energy Communities. Wholesale electricity values at Energy Community locations relative to the rest of the market vary by region. The average value was often higher for wind projects (-$\$3$ to $\$11$/MWh) but lower for solar projects (-$\$6$ to 0/MWh). - Distributed solar that is owned by commercial entities is eligible for the Energy Community bonus and also, potentially, a Low-Income Community bonus. Residential solar installations in qualifying Energy Communities that are third-party owned represent about 10% of the total residential market. Larger commercial and industrial solar installations in Energy Communities make up 17% of the total market in 2023. Nearly 2 GW of distributed solar was built in areas qualifying as Low-Income Communities in 2023, exceeding the available annual program cap of 700 MW. Continued tracking of these trends will be important for system planners, investors, and local communities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Cross sections of the 83 Rb⁢(p,γ)⁢ 84 Sr and 84 Kr⁢(p,γ)⁢ 85 Rb reactions at energies characteristic of the astrophysical γ process

We have measured the cross section of the Rb 83 ( p , γ ) Sr 84 radiative capture reaction in inverse kinematics using a radioactive beam of Rb 83 at incident energies of 2.4 and 2.7 A MeV. Prior to the radioactive beam measurement, the Kr 84 ( p , γ ) Rb 85 radiative capture reaction was measured in inverse kinematics using a stable beam of Kr 84 at an incident energy of 2.7 A MeV. The effective relative kinetic energies of these measurements lie within the relevant energy window for the γ process in supernovae. The central values of the measured partial cross sections of both reactions were found to be 0.17 – 0.42 times the predictions of statistical model calculations. Assuming the predicted cross section at other energies is reduced by the same factor leads to a slightly higher calculated abundance of the p nucleus Sr 84 , caused by the reduced rate of the Sr 84 ( γ , p ) Rb 83 reaction derived from the present measurement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Mixed Enthalpy–Entropy Descriptor for the Rational Design of Synthesizable High-Entropy Materials Over Vast Chemical Spaces

The practically unlimited high-dimensional composition space of high-entropy materials (HEMs) has emerged as an exciting platform for functional material design and discovery. However, the identification of stable and synthesizable HEMs and robust design rules remains a daunting challenge. Here, we propose a mixed enthalpy–entropy descriptor (MEED) that enables highly efficient, robust, high-throughput prediction of synthesizable HEMs across vast chemical spaces from first-principles. The MEED is based on two parameters: the relative formation enthalpy with respect to the most stable competing compound and the spread of the point-defect formation energy spectrum. The former measures the relative synthesizability of an HEM to its most stable competing phase, going beyond the conventional thermodynamic understanding. Further, the latter gauges the relative entropy forming ability of an HEM, entailing no sampling over numerous alloy configurations. By applying the MEED to two structurally distinct representative material systems (i.e., 3D rocksalt carbides and 2D layered sulfides), we not only successfully identify all experimentally reported HEMs within these systems but also reveal a cutoff criterion for assessing their relative synthesizability within each system. By the MEED, tens of new high-entropy carbides and 2D high-entropy sulfides are also predicted, which have the potential for a wide variety of applications such as coating in aerospace devices, energy conversion and storage, and flexible electronics.

36 MATERIALS SCIENCE↗

Toward Energy-Efficient HPC: Insights from Power Profiling a Cloud-Resolving Earth System Model

Power is a fundamental constraint as supercomputing advances to exascale. Efficient operation within strict power budgets requires application-aware power management based on a detailed understanding of application-level power behavior. This work analyzes the Energy Exascale Earth System Model (E3SM) atmosphere component, SCREAM, on Perlmutter (NERSC) and Frontier (OLCF). We characterize power variation across inputs, concurrency levels, and power caps, evaluate the energy impact of code optimizations, and attribute energy within the code using a newly developed GPU energy model. Results show that SCREAM’s peak power remains stable during its core execution phase and decreases gradually as concurrency increases. Power capping experiments reveal a performance–energy "sweet spot". On Perlmutter, limiting GPU power to 50% of thermal design power (TDP) achieves up to 15% energy savings with a 7% performance penalty. On Frontier, a 40% TDP cap yields up to 10% energy savings with less than 10% performance loss. Code optimizations reduce SCREAM energy by shortening run time without increasing power. Modeling reveals a critical insight: data movement accounts for approximately 70% of SCREAM’s GPU energy. This fundamentally shifts the optimization focus from FLOPS to data transfer reduction for this class of applications, offering the most impactful strategy for improving energy efficiency. This work establishes a foundation for practical, application-aware power management at exascale.

Zhao, Zhengji [Lawrence Berkeley National Laborato↗

Modeling Tool Development and Validation for Solar Industry Process Heat Using Particle Thermal Energy Storage

U.S. industry sectors used 26.2 quadrillion Btu and accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of industrial energy use with application temperatures ranging from 60 degrees -1100 degrees C. Industry processes, heavily relying on fossil fuels of cheap coal or natural gas, differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes great challenges in decarbonization. Industry processes require reliable energy supply and vary widely in temperature ranges. Storing energy from renewable sources is necessary to improve reliability and to mitigate renewable intermittency when replacing carbon fuel-based heat supplies to achieve energy savings and reduce emissions. To this end, we have developed a particle-based thermal energy storage (TES) technology using low-cost and highly stable silica sand as a storage medium. The economic and performance-based analysis is key for renewable energy sources to reliably supply industry process heat and ultimately displace fossil fuels for decarbonization. The diversified industrial processes need case-by-case analysis and design. Therefore, an adaptive modeling tool is key for renewable power with energy storage to meet industry demands. Thus, a modeling tool to simulate a solar industry process heat system using the particle TES has been developed using the object-oriented equation-based language Modelica and the commercial platform of Modelon Impact. The Modelica-based software tool provides a general simulation environment for the design of reliable solar energy sources integrated with TES for various industrial process applications at different temperatures for economic competence with fossil fuels such as coal and natural gases. It uses both customized and standard component modeling modules in Modelon libraries for the flexibility to be adapted to a specific energy demand application. The particle TES system establishes a uniform energy supply platform with an efficient heat exchanger and particle thermal energy reservoir integrated with renewable powers. The particle TES system can provide a wide temperature range and can have a large storage temperature difference that increases storage energy density; therefore, it can be an adaptable energy storage system integrated with renewable power to supply 24/7 heat for industry decarbonization.

concentrated solar thermal↗

Chemical compatibility of hollow ceramic cenospheres as thermal insulation for high-temperature thermal energy storage applications with molten nitrate salt

An effective insulation material that is both thermally and chemically stable in molten salts could transform the design of molten-salt-based thermal energy storage (TES) tanks. Most current molten salt TES tanks hold the metallic tank structure in direct contact with hot salt inventory, a design which leads to thermal expansion of the tank and triggers stresses that can lead to thermomechanical failures. With an internal insulation to lower the temperature at the tank structure, the extent of thermal expansion can be reduced, thereby reducing expansion-induced stresses and allowing for consideration of lower-cost tank structure materials. Conventional insulation materials are either 1) too porous and allow molten salts to permeate into the matrix, which significantly increases the thermal conductivity or 2) too dense and have a thermal conductivity that cannot provide sufficient thermal insulation. This paper presents an alternative thermal insulation concept using cenospheres which have an alumino-silicate structure. The cost analysis suggests that the low-density cenospheres can be one of the cheapest materials to provide cost-effective thermal insulation. The chemical compatibility of cenospheres is investigated in molten 60 wt% NaNO3/40 wt% KNO3 salt which is close to industrial-grade Solar Salt. This paper shows that diffusion of the sodium and potassium cations from the salt into the cenospheres occurs based on weight analysis, energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) spectroscopy. The cation diffusion breaks the bridging oxygen bonds and causes volume expansion of the microstructure which is responsible for the failure of the cenosphere particles. The chemical composition of the cenospheres is found to affect their compatibility with molten nitrate salt. A cenosphere product with low iron content showed the best compatibility with an average survival rate of 77.9% +/- 9.8% after 7 days of immersion in the molten nitrate salt. While even the low-iron cenospheres appear to require protection from direct molten salt contact, their slow degradation rate, closed-cell porosity, and low cost hold potential for effective use as internal tank insulation.

14 SOLAR ENERGY↗

Diffusion of alloying and fission atoms in α-U investigated by first-principles calculation

Stability and diffusion of small defect clusters containing alloying or fission atoms (“F” is used to represent both atoms) in an α-uranium (U) crystal are investigated using first-principles calculations. Here, results indicate that different stable defect structures are observed for an interstitial defect and a cluster (F n V m ) containing different alloying or fission atoms and vacancies. An interstitial defect is found to be most stable either at the center of a pyramid pentahedron or in a 〈010〉 mixed dumbbell configuration and the latter one is reported for the first time. Formation energy of a small F n V m cluster depends on the distribution of vacancies. Based on these stable defects, new migration energies and paths have been explored in this work. Anisotropic migration of an interstitial defect by jumping between nearest centers of two pyramid pentahedrons or jumping between two mixed U-Zr dumbbells has been suggested. Furthermore, a new migration-rotation mechanism has been explored for the first time for a FV 2 cluster, resulting in a 3D diffusion. Finally, the effect of substitutional Pu atoms on the migration of a FV 2 cluster suggests that optimizing the Pu concentration may prohibit the diffusion of some alloying or fission atoms, increasing the safe performance of metallic fuels.

3D diffusion↗

Bond Dissociation Energies in Heavy Element Chalcogen and Halogen Small Molecules

Thermodynamic properties including bond dissociation energies, heats of formation, and gas phase acidities for the hydrides and dimers of chalcogens and halogens: H 2 Y, HX, Y 2 and X 2 for Y = Se, Te, At and X = Br, I, and At have been predicted using the Feller-Peterson-Dixon composite correlated molecular orbital theory approach. A full 4-component CCSD(T) approach was used to calculate the spin-orbit effects on thermodynamic properties, except for Se 2 where the AoC-DHF value was used due to strong multireference effects in Se 2 for the SO calculations. The calculated results show that the At 2 bond dissociation energy is quite small, 19.5 kcal/mol, with much of the low bond energy due to spin orbit effects. H 2 Po is not predicted to be stable to dehydrogenation to Po + H 2 in terms of the free energy at 298 K. In the gas phase, HAt is predicted to be a stronger acid than H 2 SO 4 . Here, the current results provide insights into potential difficulties in the actual experimental observation of such species for heavy elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Liquid crystal defect structures with Möbius strip topology

Topological solitons commonly appear as energy-minimizing field configurations, but examples of stable, spatially localized objects with coexisting solitonic structures and singular defects are rare. Here we use a nonpolar chiral liquid crystal system to show how twist domain walls can co-self-assemble with vortices to form spatially localized topological objects with spontaneous folding. These soliton–vortex assemblies, which we call ‘möbiusons’, have a topology of the molecular alignment field resembling that of the Möbius strip’s surface and package localized field excitations into folded structures within a confinement-frustrated uniform far-field background. Upon supplying energy in the form of electric pulses, möbiusons with different overall symmetries of structure exhibit folding-dependent rotational and translational motions, as well as topological cargo-carrying abilities that can be controlled by tuning the amplitude and frequency of the applied fields. We demonstrate on-demand transformations between various möbiusons and show examples of encoding information by manipulating folds in such structures. A model based on the energetics of solitons and vortices provides insights into the origins of the folding instability, whereas minimization of the Landau–de Gennes free energy closely reproduces details of their internal structure. Our findings may provide a route towards topology-enabled light-steering designs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗