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At least 721 records · Page 40

Computational Approaches for Clean Energy Materials

Currently, 80% of the global final energy consumption occurs in form of fuels and only 20% as electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, a successful energy transition will require enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies. As much as photovoltaic capacities have grown over the past 20 years, it is far from clear that current technologies and materials are up to the task to grow from here by yet another factor 100 until 2050. Therefore, sustained research efforts on emerging inorganic semiconductors for solar electricity and fuels are essential for facing the double challenge of climate change and energy security. Computational materials science can make important contributions, guiding and supporting research activities through both materials search and discovery and through detailed studies that help to develop a mechanistic understanding of materials performance and bottlenecks. This presentation will highlight three recent computational projects with relevance for photovoltaics and solar fuels (1) Defect graph neural networks (dGNN) for materials discovery in solar thermochemical hydrogen (STCH) [1]. The dGNN approach facilitates broad and fast materials screening for defect properties. (2) Modeling highly off-stoichiometric systems by evaluating the free energy of defect interaction [2]. This approach allows quantitative prediction of H2 production in complex STCH oxides. (3) First-principles atomic structure prediction for interfaces [3]. This work showed how an atomically thin CdCl2 interlayer phase enables in principle ideal electron transport across the incommensurate SnO2/CdTe interface. [1] M.D. Witman, A. Goyal, T. Ogitsu, A.H. McDaniel, S. Lany, Nat. Comput. Sci. (2023). https://doi.org/10.1038/s43588-023-00495-2. [2] A. Goyal, M.D. Sanders, R.P. O'Hayre, S. Lany, PRX Energy 3, 013008 (2024). https://doi.org/10.1103/PRXEnergy.3.013008. [3] A. Sharan, M. Nardone, D. Krasikov, N. Singh, S. Lany, Appl. Phys. Rev. 9, 041411 (2022). https://doi.org/10.1063/5.0104008.

density functional theory↗

Data Readiness for Scientific AI at Scale

This paper examines how Data Readiness for AI (DRAI) principles apply to leadership-scale scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, bio/health, and materials—to identify common preprocessing patterns and domain-specific constraints. We introduce a two-dimensional readiness framework that combines canonical preprocessing patterns with a five-level operational readiness scale, both tailored to high-performance computing (HPC) environments. This framework helps outline key challenges in transforming large-scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross-domain support for scalable and reproducible AI for science.

Brewer, Wes [ORNL] (ORCID:0000000236393956)↗

Principles of Fluid Dynamic Similarity Analysis for Slosh Experiments

Most tank slosh test programs are not conducted with flight hardware in a flight-like environment due to cost and schedule constraints. Instead, subscale tanks are typically tested on the ground. If the “real”, flight liquid in the tank is a cryogenic propellant, sometimes a cryogen is used during testing, but more often a simulant liquid is used. Fluid dynamic similarity analysis, or “scaling analysis” as it is sometimes called, for slosh examines nondimensional numbers to determine which fluid dynamic regime(s) a tank is operating in. If the relevant nondimensional numbers of a scale tank test are similar enough to the real tank’s nondimensional numbers, then it is likely that the scale test data will be similar to what would be obtained with the real tank. This type of analysis is useful for guiding experiment design, test liquid selection, and for understanding the physical relevance of prior test data to a specific application. The authors have performed scaling analyses for many slosh test programs conducted in ground, parabolic flight, suborbital, and in-orbit environments. Basics of how to perform the analysis, along with select examples from ground and microgravity environments, are presented. Suggestions for various assumptions and compromises to make are discussed. Limitations and challenges are also discussed.

slosh↗

Multiphysics modeling of printed surface acoustic wave thermometers

Surface acoustic wave (SAW) transducers are a class of sensors and actuators that operate on the fundamental principle of piezoelectricity. Aerosol jet printing and other additive manufacturing techniques have resulted in the low-cost fabrication of low-power and small-footprint SAW devices that are suitable for sensing in high-temperature and radioactive environments. In this work, we developed a series of temperature-dependent finite element models for a SAW transducer consisting of printed silver interdigitated transducers (IDTs) deposited onto piezoelectric lithium niobate. Modeling accuracy was evaluated experimentally from room temperature to 200 °C using an aerosol-jet-printed SAW thermometer. A time-domain study enabled visualization of the wave propagation and successfully guided the denoising of the scattering parameter measurement. Additionally, frequency-domain models using traditional modal analysis or the unique port boundary condition feature in COMSOL Multiphysics accurately predicted the temperature-driven natural frequency drift in the SAW thermometer. The finite element models developed in this study serve to facilitate the computer-aided design of future SAW transducers for applications in harsh environments.

47 OTHER INSTRUMENTATION↗

Polymer morphology and interfacial charge transfer dominate over energy-dependent scattering in organic-inorganic thermoelectrics

Hybrid (organic-inorganic) materials have emerged as a promising class of thermoelectric materials, achieving power factors (S 2 σ) exceeding those of either constituent. The mechanism of this enhancement is still under debate, and pinpointing the underlying physics has proven difficult. In this work, we combine transport measurements with theoretical simulations and first principles calculations on a prototypical PEDOT:PSS-Te(Cu x ) nanowire hybrid material system to understand the effect of templating and charge redistribution on the thermoelectric performance. Further, we apply the recently developed Kang-Snyder charge transport model to show that scattering of holes in the hybrid system, defined by the energy-dependent scattering parameter, remains the same as in the host polymer matrix; performance is instead dictated by polymer morphology manifested in an energy-independent transport coefficient. We build upon this language to explain thermoelectric behavior in a variety of PEDOT and P3HT based hybrids acting as a guide for future work in multiphase materials.

36 MATERIALS SCIENCE↗

Promoting Sustainable Transportation Modes: A Systematic Review of Behavior-Change Strategies

In previous studies, many travel-behavior-change strategies often relied on single behavior determinants or psychological theories, overlooking the incorporation of sociopsychological theories for guidance in their design. Integrating these theories could offer consistent guidance for program developers and enhance intervention effectiveness. This paper systematically reviews interventions targeting travel-behavior change, with a focus on self-determination theory and its principles of satisfying individuals’ competence, autonomy, and relatedness needs for enacting change. Additionally, experiment design methods, including randomized controlled trials and quasi-experimental designs, are reviewed and discussed. Key findings highlight the effectiveness of personalized interventions and integrating feedback with goal-setting strategies. Given the limited direct references to sociopsychological theories in existing studies, we explore relevant sociopsychological theories applicable to travel-behavior-change programs to provide examples of how strategies could be designed based on them. This review contributes valuable insights into the development of strategies for changing travel behavior, offering a theoretical framework for researchers and practitioners to guide intervention design, experimentation, and evaluation. In conclusion, leveraging these theories not only facilitates reproducibility but also provides a standardized approach for transportation demand management program developers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Embrace the darkness: An experimental perspective on organic exciton–polaritons

Organic polaritonics has emerged as a captivating interdisciplinary field that marries the complexities of organic photophysics with the fundamental principles of quantum optics. By harnessing strong light–matter coupling in organic materials, exciton–polaritons offer unique opportunities for advanced device performance, including enhanced energy transport and low-threshold lasing, as well as new functionalities like polariton chemistry. In this review, we delve into the foundational principles of exciton–polaritons from an experimental perspective, highlighting the key states, processes, and timescales that govern polariton phenomena. Our review centers on the spectroscopy of exciton–polaritons. We overview the primary spectroscopic approaches that reveal polariton phenomena, and we discuss the challenges in disentangling polaritonic signatures from spectral artifacts. We discuss how organic materials, due to their complex photophysics and disordered nature, not only present challenges to the conventional polariton models but also provide opportunities for new physics, like manipulating dark electronic states. As the research field continues to grow, with increasingly complex materials and devices, this review serves as a valuable introductory guide for researchers navigating the intricate landscape of organic polaritonics.

36 MATERIALS SCIENCE↗

Multi-scale Quantitative Risk Analysis of Seabed Minerals: Principles and Application to Seafloor Massive Sulfide Prospects

The potential for mining hydrothermal mineral deposits on the seafloor, such as seafloor massive sulfides, has become technically possible, and some companies (currently not many) are considering their exploration and development. Yet, no present methodology has been designed to quantify the ore potential and assess the risks relative to prospectivity at prospect and regional scales. Multi-scale exploration techniques, similar to those of the play analysis that are used in the oil and gas industry, can help to fulfill this task by identifying the characteristics of geologic environments indicative of ore-forming processes. Such characteristics can represent a combination of, e.g., heat source, pathway, trap and reservoir that all dictate how and where ore components are mobilized from source to deposition. In this study, the understanding of these key elements is developed as a mineral system, which serves as a guide for mapping the risk of the presence or absence of ore-forming processes within the region of interest (the permissive tract). The risk analysis is carried out using geoscience data, and it is paired with quantitative resource estimation analysis to estimate the in-place mineral potential. Resource estimates are simulated stochastically with the help of available data (bathymetric features in this study), conventional grade–tonnage models and Monte Carlo simulation techniques. In this paper, the workflow for a multi-scale quantitative risk analysis, from the definition to the evaluation of a permissive tract and related prospect(s), is described with the help of multi-beam data of a known hydrothermal vent site.

58 GEOSCIENCES↗

Catalytic hydrogenation of HMF to BHMF over copper catalysts

2,5-Bis(hydroxymethyl)furan (BHMF) is a bio-derived building block for polyester production, obtained via the hydrogenation of 5-hydroxymethylfurfural (HMF). First-principles thermodynamic equilibrium calculations indicate that this reaction is not thermodynamically limited under relevant conditions (e.g., 100 °C and high H 2 partial pressure). In this work, crude HMF was employed as the feedstock for BHMF synthesis. Initially, acidic impurities and humins were removed from unrefined HMF through filtration using a packed bed of γ-alumina. A comprehensive study of the filtration process is presented, including filtration kinetics, breakthrough curve analysis, and mathematical modeling. The purified HMF was subsequently hydrogenated over a 10 wt% CuZrO 2 catalyst, using ethanol as the reaction solvent. Batch reactions were first performed for collection of kinetic data to guide the transition to continuous flow operation. Kinetic data was collected in a fixed bed reactor at varying contact time, time on stream, temperature, and HMF concentration. This data was used to develop a kinetic model for HMF hydrogenation. Maximum BHMF production rates were achieved at 130 °C, accompanied by minor formation of byproducts from BHMF ring-opening reactions. The BHMF selectivity was 100 % at 100 °C although with lower reaction rates. Furthermore, catalyst stability tests revealed a loss of up to 50 % in catalytic activity within the first 24 h, likely due to the adsorption of HMF-derived oligomers that are not easily removed by filtration.

Crude HMF filtration↗

Variational Self-Consistent Theory for Beam-Loaded Cavities

A new variational theory is presented for beam loading in microwave cavities. The beam{field interaction is formulated as a dynamical interaction whose stationarity according to Hamilton’s principle will naturally lead to steady-state solutions that indicate how a cavity’s resonant frequency, Q and optimal coupling coefficient will detune as a result of the beam loading. A driven cavity Lagrangian is derived from first principles, including the effects of cavity wall losses, input power and beam interaction. The general formulation is applied to a typical klystron input cavity to predict the appropriate detuning parameters required to maximize the gain (or modulation depth) in the average Lorentz factor boost, (Δ γ). Numerical examples are presented, showing agreement with the general detuning trends previously observed in the literature. The developed formulation carries several advantages for beam-loaded cavity structures. It provides a self-consistent model for the dynamical (nonlinear) beam{field interaction, a procedure for maximizing gain under beam-loading conditions, and a useful set of parameters to guide cavity-shape optimization during the design of beam-loaded systems. Enhanced clarity of the physical picture underlying the problem seems to be gained using this approach, allowing straightforward inclusion or exclusion of different field configurations in the calculation and expressing the final results in terms of measurable quantities. Two field configurations are discussed for the klystron input cavity, using finite magnetic confinement or no confinement at all. Formulating the problem in a language that is directly accessible to the powerful techniques found in Hamiltonian dynamics and canonical transformations may potentially carry an additional advantage in terms of analytical computational gains, under suitable conditions

43 PARTICLE ACCELERATORS↗

Trends of Alkane Activation on Doped Cobalt (II, III) Oxide from First Principles

The surface doping of a metal oxide can tune its catalytic performance, but it remains unclear how the tuning depends on the dopant type and the surface facet. In this report we study doped Co 3 O 4 (1 1 1) and (3 1 1) surface facets using first-principles density functional theory (DFT) to obtain general descriptors for oxygen reactivity (which include vacancy formation energy and hydrogen adsorption energy) and correlate them to ethane C-H activation energy as a measure of the catalytic performance. The periodic trends of the dopants are investigated for a total of 20 dopants, namely, the elements from K to Ge. We find strong linear correlations between the oxygen reactivity descriptors and the computed energy barriers. We also discover a strong surface facet sensitivity among certain dopants such that different surface orientations and sites lead to different or even the opposite dopant performance. This work provides a useful guide for dopant performance in ethane activation on the two very different Co 3 O 4 surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Alloying Effects on the Transport Properties of Refractory High-entropy Alloys

Additive Manufacturing (AM) has opened new frontiers for the design of refractory high-entropy alloys (HEAs) for high-temperature applications. The thermal conductivity of the AM feedstock is among the most important thermo-physical properties that control the melting and solidification process. Despite its significance, there remains a notable gap in both computational and experimental research concerning the thermal conductivity of HEAs. Here, we use density functional theory (DFT) to systematically investigate the alloying effects on the transport properties of Ti-Cr-Mo-W-V-Nb-Ta RHEAs, including electrical and thermal conductivities and Seebeck coefficient. The relaxation time of charge carriers is a key underlying parameter determining thermal conductivity that is exceedingly challenging to predict from first principles alone, and we thus follow the approach by Mukherjee, Satsangi, and Singh [Chem Mater 32, 6507 (2022)] to optimize the relaxation time for RHEAs. Here we validated thermal conductivity predictions on elemental solids, binary and ternary alloys, and RHEAs and compared them against thermodynamic (CALPHAD) predictions and our experiments with good correlations. To understand observed trends in thermal conductivity, we assessed the phase stability, electronic structure, phonon, and intrinsic- and tensile strength of down-selected RHEAs. Our electronic structure and phonon results connect well with the observed compositional trends for thermal transport in RHEAs. Our DFT assessment and CALPHAD predictions provide a unique design guide for RHEAs with tailored thermal conductivity, a critical consideration for AM and thermal-management applications.

36 MATERIALS SCIENCE↗

Mass drivers. 3: Engineering

This paper is the last of a series of three by the Mass-Driver Group of the 1977 Ames Summer Study. It develops the engineering principles required to implement the basic mass-driver design defined in paper I and as presented previously in the literature. Optimum component mass trade-offs are derived from a set of four input parameters, and the program used to design a lunar launcher. The mass optimization procedure is then incorporated into a more comprehensive mission optimization program called OPT-4, which evaluates an optimized mass-driver reaction engine and its performance in a range of specified missions. Finally, this paper discusses, to the extent that time permitted, certain peripheral problems: heating effects in buckets due to magnetic field ripple; an approximate derivation of guide force profiles; the mechanics of inserting and releasing payloads; the reaction mass orbits; and a proposed research and development plan for implementing mass drivers. This paper also considers further optimization that depends on advances in component technology beyond the present state. It is concluded that significant advantage can be gained in the case of small reaction engines with high emission velocity by developing lightweight packaging technology for silicon-controlled rectifiers (SCR's).

William H. Arnold↗

Heteronuclear Correlation SSNMR Spectroscopy with Indirect Detection under Fast Magic-Angle Spinning [Book Chapter]

The main focus of this chapter is to address experimental strategies on the subject by providing a hands-on guide to fast MAS experiments, with a particular focus on indirect detection. Although our experience is limited to our respective laboratories in Ames and Yokohama, we hope that our descriptions of experimental setups and optimization procedures are sufficiently general to be applicable to all modern instruments. The chapter is organized as follows. Section 2 below introduces briefly the fast MAS technology and its main advantages. In Section 3, we describe the hardware associated with this remarkable technology and provide practical advices on its use, including procedures for loading and unloading the samples, maintaining the probe, reducing t 1 noise, etc. In Section 4, we describe the principles and hands-on aspects of experiments involving the indirect detection of spin-1/2 and 14 N nuclei

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Self-assembly directed one-step synthesis of [4]radialene on Cu(100) surfaces

The synthetic challenges of radialenes have precluded their practical applications. Here, we report a one-step synthetic protocol of [4]radialene on a copper surface. High-resolution scanning tunneling microscopy measurements reveal that such catalytic reaction proceeds readily with high selectivity at the temperature below 120 K. First-principles calculations show that the reaction pathway is characterized by firstly the cooperative inter-molecular hydrogen tautomerization and then the C–C bond formation. The feasibility of such cyclotetramerization reaction can be interpreted by the surface effect of Cu(100), which firstly plays an important role in directing the molecular assembly and then serves as an active catalyst in the hydrogen tautomerization and C–C coupling processes. This work presents not only a novel strategy to the scant number of synthetic methods to produce [4]radialenes via a novel [1 + 1 + 1 + 1] reaction pathway, but also a successful example of C–C bond coupling reactions guided by the surface-induced C–H/π assembly.

36 MATERIALS SCIENCE↗

Enhanced magnetic moments in Mn-doped FeCo clusters owing to ferromagnetic surface Mn atoms

Here, we provide an avenue to achieve optimized magnetic properties without relying on rare-earth elements. In particular, we focus on transition-metal nanoparticles with magnetic ordering that is rarely seen in bulk. By using first-principles real-space pseudopotential calculations, we show that Mn can exhibit ferromagnetic behavior similar to Fe when Mn is placed on the surface of a FeCo cluster. This ferromagnetic behavior of surface Mn is in sharp contrast with Mn bulk and Mn-based alloys, which are either antiferromagnetic or paramagnetic. The local magnetic moment carried by a surface Mn atom is larger than those of Fe and Co, leading to an increase of the total magnetic moment. We find that surface-Mn-induced magnetic enhancement is robust in ternary MnFeCo clusters with different sizes and various chemical compositions. Our theoretical findings provide a useful guide for designing new nanoparticles with a large magnetic moment.

36 MATERIALS SCIENCE↗

Nonperturbative Guiding Center Model for Magnetized Plasmas

Perturbative guiding center theory adequately describes the slow drift motion of charged particles in the strongly magnetized regime characteristic of thermal particle populations in various magnetic fusion devices. However, it breaks down for particles with large-enough energy. Here, we report on a data-driven method for learning a nonperturbative guiding center model from full-orbit particle simulation data. We show the data-driven model significantly outperforms traditional asymptotic theory in magnetization regimes appropriate for fusion-born α particles in stellarators, thus opening the door to nonperturbative guiding center calculations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

High-precision predictions of properties of chemically disordered crystals

Multiple scattering theory (MST) combined with density functional theory (DFT) allows to predict properties of chemically disordered materials from the first principles. However, such predictions often suffer from the systematic errors, which depend on crystal geometry. Each computed property of a particular crystal structure typically has a relatively small random error and a larger systematic error. Cancellation of systematic errors allows more accurate predictions. We propose a computational methodology based on the subtraction of the systematic errors in MST. To exemplify it, we apply it to the precipitated alloys. Considering precipitation strengthening in Ni superalloys, we compute the relative enthalpies of the competing Ni3(Al,Ti)1 crystal structures with a chemical disorder on the Al+Ti sublattice. Such predicted composition-structure-property dependencies are useful for the guided design of the next-generation alloys with improved strength. Our predictions are validated by comparison with the results of other DFT methods (having a higher computational cost) and with experiment. We acknowledge funding of the guided design of stronger superalloys for airspace by NASA Aeronautics Research Mission Directorate (ARMD) via Transformational Tools and Technologies (TTT) Project.

Computational↗