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DOE OSTI2026

Two-phase flow numerical analysis of electrode geometry for alkaline water electrolyzers

Hydrogen is a promising component of a future energy-secure and efficient economy, but its competitiveness depends on reducing production costs. One strategy is to operate alkaline water electrolyzers at higher current densities to increase output. However, this intensifies performance losses due to gas bubble accumulation, which blocks transport pathways and deactivates electrochemically active surfaces. Enhancing bubble evacuation through electrode design is therefore essential. Previous studies have explored various approaches — such as modifying surface morphology, applying sonication or pressure modulation, and introducing surfactants — but these efforts have addressed a limited range of conditions due to the complexity of two-phase flow and electrode geometries. Experiments have also largely been focused on either cell level improvements, which lack the information necessary to isolate each contributing factor, or on modified geometries that are not relevant to practical cell operation. From a modeling perspective, conventional Eulerian multiphase models do not track the complex gas–liquid interfacial dynamics and often neglect surface tension and contact angle effects, reducing their predictive accuracy. To provide insights on the effects of different electrode geometries on the performance of alklaine water electrolyzers this work employs an immersed boundary volume-of-fluid method to simulate bubble behavior in 3D porous electrodes. Multiple base electrode geometries, typically used in practice, with varying porosity are evaluated under a constant surface gas generation rate. Simulation data is analyzed to quantify electrode gas coverage, bubble size dynamics and other relevant metrics. Results show that porosity strongly influences bubble accumulation on electrode surfaces, with higher porosity reducing gas coverage, and its not strictly dependent on the electrode geometry. However, the electrode’s base geometry significantly affects gas accumulation at the separator gap, independent of porosity. A foam electrode geometry resulted in the lowest gas coverage of all electrodes with a median volumetric gas coverage of 11%, but at the cost of a 70% reduction in active area compared with the largest surface area electrode, while gyroid electrodes showed the best trade-off between gas coverage, particularly at the separator surface, and electrochemically active area. In conclusion, the results highlight the need for holistic electrode design strategies.

Alkaline↗

DOE OSTI2023

Weyl-ambient geometries

Weyl geometry is a natural extension of conformal geometry with Weyl covariance mediated by a Weyl connection. We generalize the Fefferman-Graham (FG) ambient construction for conformal manifolds to a corresponding construction for Weyl manifolds. We first introduce the Weyl-ambient metric motivated by the Weyl-Fefferman-Graham (WFG) gauge. From a top-down perspective, we show that the Weyl-ambient space as a pseudo-Riemannian geometry induces a codimension-2 Weyl geometry. Then, from a bottom-up perspective, we start from promoting a conformal manifold into a Weyl manifold by assigning a Weyl connection to the principal R+-bundle realizing a Weyl structure. We show that the Weyl structure admits a well-defined initial value problem, which determines the Weyl-ambient metric. Through the Weyl-ambient construction, we also investigate Weyl-covariant tensors on the Weyl manifold and define extended Weyl-obstruction tensors explicitly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Persistent Classification: Understanding Adversarial Attacks by Studying Decision Boundary Dynamics

ABSTRACT There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high‐dimensionality of the data, the high codimension in the ambient space of the data manifolds of interest, and that the structure of machine learning models may encourage classifiers to develop decision boundaries close to data points. This article proposes a new framework for studying adversarial examples that does not depend directly on the distance to the decision boundary. Similarly to the smoothed classifier literature, we define a (natural or adversarial) data point to be ( γ , σ)‐stable if the probability of the same classification is at least for points sampled in a Gaussian neighborhood of the point with a given standard deviation . We focus on studying the differences between persistence metrics along interpolants of natural and adversarial points. We show that adversarial examples have significantly lower persistence than natural examples for large neural networks in the context of the MNIST and ImageNet datasets. We connect this lack of persistence with decision boundary geometry by measuring angles of interpolants with respect to decision boundaries. Finally, we connect this approach with robustness by developing a manifold alignment gradient metric and demonstrating the increase in robustness that can be achieved when training with the addition of this metric.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Spacetime foam: a review

More than 65 years ago, John Wheeler suggested that quantum uncertainties of the metric would be of order one at the Planck scale, leading to large fluctuations in spacetime geometry and topology, which he termed ‘spacetime foam.’ In this review I discuss various attempts to implement this idea and to test it, both theoretically and, to a lesser extent, observationally.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Gravitizing the quantum

We discuss a new approach to the problem of quantum gravity in which the quantum mechanical structures that are traditionally fixed, such as the Fubini–Study metric in the Hilbert space of states, become dynamical and so implement the idea of gravitizing the quantum. In particular, in this formulation of quantum gravity the quantum geometry is still consistent with the principles of unitarity and also captures fundamental aspects of (quantum) gravity, such as topology change. As a result, we address specific ways of testing this new approach to quantum gravity by utilizing multipath interference and optical lattice atomic clocks.

Quantum gravity↗

DOE OSTI2025

Design and simulation of a SiPM-on-tile ZDC for the future EIC, and its performance with graph neural networks

We present a design for a high-granularity zero-degree calorimeter (ZDC) for the upcoming Electron-Ion Collider (EIC). The design uses SiPM-on-tile technology and features a novel staggered-layer arrangement that improves spatial resolution. To fully leverage the design’s high granularity and non-trivial geometry, we employ graph neural networks (GNNs) for energy and angle regression as well as signal classification. The GNN-boosted performance metrics meet, and in some cases, significantly surpass the requirements set in the report on science requirements and detector requirements for the EIC (Yellow Report), laying the groundwork for enhanced measurements that will facilitate a wide physics program. Our studies show that GNNs can significantly enhance the performance of high-granularity CALICE-style calorimeters by automating and optimizing the software compensation algorithms required for these systems. This improvement holds true even in the case of complicated geometries that pose challenges for image-based AI/ML methods.

Calorimeter↗

DOE OSTI2021

Performance Modeling of a Variable-Geometry Oscillating Surge Wave Energy Converter on a Raised Foundation

This paper analyzes the power capture potential, structural loadings, and costs associated with an oscillating surge wave energy converter (OSWEC) operating on a raised foundation. The raised OSWEC offers opportunities for reduced installation costs, improved energy production, and greater flexibility of deployment when compared with fixed-bottom models. In this investigation, we simulated several different foundation geometries using WEC-Sim to estimate power capture and structural loads. In an effort to maximize power capture, several cases in which flat plates of varying size were attached to the top of the foundation, under and parallel with the OSWEC, were also simulated. These plates were found to enhance power capture by preventing the wave-induced pressure from passing underneath the OSWEC, diverting this pressure toward the OSWEC instead. The OSWEC was simulated in the six Wave Energy Prize sea states, which were chosen as a representative sample of U.S. deployment sites. A first-order estimate of structural costs was calculated using the Wave Energy Prize ACE metric, with the foundation comprised predominantly of steel-reinforced concrete and the OSWEC comprised of A36 steel. Influence of foundation geometry on power capture, structural loadings, and ACE are topics of particular interest. This work has been inspired by advances in large-scale additive manufacturing techniques that have the potential to dramatically reduce the cost of subsea foundations. These advancements may enable cost-effective WEC systems to be deployed on raised foundations.

cost↗

DOE OSTI2021

Performance Modeling of a Variable-Geometry Oscillating Surge Wave Energy Converter on a Raised Foundation: Preprint

This paper analyzes the power capture potential, structural loadings, and costs associated with an oscillating surge wave energy converter (OSWEC) operating on a raised foundation. The raised OSWEC offers opportunities for reduced installation costs, improved energy production, and greater flexibility of deployment when compared with bottom-fixed models. In this investigation, several different foundation geometries were simulated using WEC-Sim to estimate power capture and structural loads. In an effort to maximize power capture, several cases in which flat plates of varying size were attached to the top of the foundation, under and parallel with the OSWEC, were also simulated. These plates were found to enhance power capture by preventing the wave induced pressure from passing underneath the OSWEC, diverting this pressure towards the OSWEC instead. The OSWEC was simulated in the six Wave Energy Prize sea states, which were chosen as a representative sample of U.S. deployment sites. A first-order estimate of structural costs was calculated using the Wave Energy Prize ACE metric, with the foundation comprised predominantly of steel-reinforced concrete and the OSWEC comprised of A36 steel. Influence of foundation geometry on power capture, structural loadings, and ACE are topics of particular interest. This work has been inspired by advances in large scale additive manufacturing techniques that have the potential to dramatically reduce the cost of subsea foundations. These advancements may enable cost effective WEC systems to be deployed on raised foundations.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2022

Compositionally Tuning Electron Transfer from Photoexcited Core/Shell Quantum Dots via Cation Exchange

It is critical to find methods to control the thermodynamic driving force for photoexcited charge transfer from quantum dots (QDs) and explore how this affects charge transfer rates, since the efficiency of QD-based photovoltaic and photocatalysis technologies depends on both this rate and the associated energetic losses. In this work, we introduce a single-pot shell growth and Cu-catalyzed cation exchange method to synthesize Cd x Zn 1-x Se/Cd y Zn 1-y S QDs with tunable driving forces for electron transfer. Functionalizing them with two molecular electron acceptors—naphthalenediimide (NDI) and anthraquinone (AQ)—allowed us to probe nearly 1 eV of driving forces. For AQ, at lower driving forces, we find that higher Zn content results in a 130-fold increase of electron transfer rate constants. However, at higher driving forces electron transfer dynamics are unaltered. Here, the data are understood using an Auger-assisted electron transfer model and analyzed with computational work to determine approximate binding geometries of these electron acceptors. Our work provides a method to tune QD reducing power and produces useful metrics for optimizing QD charge transfer systems that maximize rates of electron transfer while minimizing energetic losses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Turbulence statistical analysis of the L-H transition and RMPs in KSTAR

Here, we investigate the turbulence statistics associated with low-to-high confinement (L-H) transitions and externally applied resonant magnetic perturbations (RMPs) in KSTAR. Time-series fluctuations of electron density n e , electron temperature T e , and the time derivative of the poloidal magnetic field dB θ /dt (Mirnov coils) are analysed using information-geometric measures (information rate Γ and information length $\mathcal{L}$ = ∫ Γ dt), together with kurtosis κ and variance σ 2 . In low-density upper single-null plasmas (n e ~ 1.2 x 10 19 m -3 ), a ~80 kHz magnetic mode coupling n e , T e , dB θ /dt and emerges prior to the L-H transition and persists into the edge-localised modes H-mode. Edge-localised RMPs (ERMPs) suppress this coherent mode but enhance intermittency, producing frequent bursts that abruptly reshape the time-dependent probability density functions (PDFs) and generate large spikes in Γ (with smaller changes in κ), signalling ERMP-driven departures from quasi-stationarity. The impact of ERMPs on background fluctuation levels depends on density, radial location, and the fluctuating variable itself ($\tilde{n}$, $\tilde{T}$, $\dot{B}$ θ ), whereas $\mathcal{L}$ provides a robust, regime-agnostic measure of cumulative statistical reorganisation and spatial decorrelation. In particular, at low density we observe weaker coupling between $\tilde{n}$ and $\tilde{T}$, along with a tendency toward decreased radial correlation-most clearly for $\tilde{T}$-under ERMPs. Overall, information geometry cleanly captures intermittent events, quantifies non-equilibrium PDF evolution, and offers a compact, cross-diagnostic metric for assessing resonant magnetic perturbation effects on edge transport and correlation across densities, radial locations, and confinement states.

Kim, Eun-jin [Coventry Univ. (United Kingdom); Seo↗

DOE OSTI2023

Freeform thermoelectrics in single-step manufacturing: additive manufacturing of bismuth-telluride thermoelectrics

The project succeeded in producing crack-free Bismuth Telluride thermoelectric parts with density exceeding 98% through laser powder bed fusion (LPBF) additive manufacturing (AM). This greatly exceeded the highest previously reported density of 88% and is the highest among all semiconducting materials processed by LPBF. The additively manufactured material shows comparable Seebeck coefficient as conventional form and can be made into complex geometries with reduced material loss. On the other hand, measured properties are dramatically sensitive to the AM process parameters used, such that with identical composition, the Seebeck coefficient can be controllably tuned from +120 µV/K to -207 µV/K, which means the material switches between an n-type to a p-type semiconductor depending on processing. These changes are accompanied by significant differences in the as-processed microstructure due to rapid solidification. A machine learning protocol was developed and greatly reduced the experimental burden of the project, reducing the typical process optimization period of 2 years to 6 months. The project was fully successful in the objective of producing defect-free, complex geometry of bismuth-telluride parts through LPBF, but only partially successful in achieving performance goals. First, cost reduction of manufacturing, as measured by material waste, was successfully reduced by up to 70% compared to conventional manufacturing methods. This exceeded the proposed 30% reduction in materials waste needed to reach the 20% cost reduction goal of the project. On the other hand, the device performance, as measured by Seebeck coefficient, failed to reach the 40% improvement in efficiency. Rather, we observe comparable Seebeck coefficient between AM samples and conventionally processed counterparts. The device-level efficiency improvement does exceed 40% for complex geometry samples due to shape-induced increase in temperature gradients, but this was not the originally proposed metric. The machine learning approach developed in this project greatly accelerated the process optimization and can be adopted for fast development of AM processing parameters for other brittle and otherwise difficult-to-print materials. For the public, we deliver an efficient and widely adoptable process for incorporating waste-heat harvesting thermoelectric devices in both industrial and commercial heat exchangers. The geometric flexibility allows the capturing device to conform to the shape of the heat source to improve the system-level conversion efficiency. The technique can be deployed on any commercial LBPF systems with zero modifications, thus poses minimal adoption barrier for any manufacturer that already employed AM technology. Beyond bismuth-telluride, the machine-learning guided optimization protocol can be used in the future to reduce both the time and cost of process development for AM of other energy conversion and harvesting materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A geometric framework for momentum-based optimizers for low-rank training

Low-rank pre-training and fine-tuning have recently emerged as promising techniques for reducing the computational and storage costs of large neural networks. Training low-rank parameterizations typically relies on conventional optimizers such as heavy ball momentum methods or Adam. In this work, we identify and analyze potential difficulties that these training methods encounter when used to train low-rank parameterizations of weights. In particular, we show that classical momentum methods can struggle to converge to a local optimum due to the geometry of the underlying optimization landscape. To address this, we introduce novel training strategies derived from dynamical low-rank approximation, which explicitly account for the underlying geometric structure. Our approach leverages and combines tools from dynamical low-rank approximation and momentum-based optimization to design optimizers that respect the intrinsic geometry of the parameter space. We validate our methods through numerical experiments, demonstrating faster convergence, and stronger validation metrics at given parameter budgets.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗

DOE OSTI2024

Accessing bands with extended quantum metric in kagome Cs 2 Ni 3 S 4 through soft chemical processing

Flat bands that do not merely arise from weak interactions can produce exotic physical properties, such as superconductivity or correlated many-body effects. The quantum metric can differentiate whether flat bands will result in correlated physics or are merely dangling bonds. A potential avenue for achieving correlated flat bands involves leveraging geometrical constraints within specific lattice structures, such as the kagome lattice; however, materials are often more complex. In these cases, quantum geometry becomes a powerful indicator of the nature of bands with small dispersions. We present a simple, soft-chemical processing route to access a flat band with an extended quantum metric below the Fermi level. By oxidizing Ni-kagome material Cs 2 Ni 3 S 4 to CsNi 3 S 4 , we see a two orders of magnitude drop in the room temperature resistance. However, CsNi 3 S 4 is still insulating, with no evidence of a phase transition. Using experimental data, density functional theory calculations, and symmetry analysis, our results suggest the emergence of a correlated insulating state of unknown origin.

Science & Technology - Other Topics↗

DOE OSTI2025

Characterizing and Modeling the Influence of Geometry on the Performance of Superconducting Nanowire Cryotrons

The scaling of superconducting nanowire detectors to larger arrays is often limited by room-temperature-readout cabling. Cryogenic integrated circuits constructed from nanowire cryotrons, or nanocryotrons, can address this limitation by performing signal processing on chip. In this study, we characterize key performance metrics of the nanocryotron to elucidate its potential as a logical element in cryogenic integrated circuits and develop an electro-thermal model to connect material parameters with device performance. We find that the performance of the nanocryotron depends on the device geometry, and trade-offs are associated with optimizing the gain, jitter, and energy dissipation. Here, we demonstrate that nanocryotrons fabricated on niobium nitride can achieve a grey zone less than 210 nA wide for a 5 ns long input pulse corresponding to a maximum achievable gain of 48 dB, an energy dissipation of less than 20 aJ per operation, and a jitter of less than 60 ps.

Superconductor↗

DOE OSTI2020

A Custom Machine to Convey Radiologically Impacted Cohesive Soils to the Orion ScanSortSM System - 20382

An established method to reduce the volume of material required to be disposed of as radioactive waste is conveyor-based sorting of potentially radiologically impacted soils. With the Orion ScanSortSM system, potentially impacted soils are conveyed beneath radiation detectors and sorted into above and below criteria bins based on the detectors' response. Confident measurements can only be efficiently achieved when the soil column being conveyed has a reasonably consistent geometry. Highly cohesive soils present a very significant challenge as they tend to clump and adhere to the conveyor hopper, strike-off bar, and belt skirting. This causes voids and valleys in the soil column that affect the measurement geometry and reduce the confidence in the measurement. The reduction in confidence necessitates a longer residence time (i.e. reduction in conveyor belt speed and processing rates) or that the soils in highly unfavorable geometries be dispositioned as impacted or segregated for resurvey (should site logistics support that option). These outcomes may increase the volume of material required to be dispositioned as radiological waste and have a negative impact on project cost and schedule. To minimize impact to sorting operations, Wood designed and built a customized Extruder, to optimize the soil column prior to assay. The design was developed and refined to minimize the volume of highly cohesive soils presented in highly unfavorable geometries in the soil column in order to confidently assess and disposition such soils in a high-production environment. The Extruder is a customized 90 cm wide flat conveyor that has an oversized hopper with a pair of motor-driven rollers that force the soils in the hopper through an opening of adjustable height. The soils are extruded through the opening to produce a soil column that is ∼75 cm wide and ∼8-18 cm deep with a design rate of 225 metric tons/hr. The Extruder was recently deployed with the Orion ScanSort{sup SM} System to a site in northeast Ohio. The site has highly cohesive soils that result from the weathering of glacial sediments and consist of clay and clay loam, resulting in poor drainage and high moisture content. The project infrastructure only supported two bins of material (above and below criteria), which necessitated that soils with unfavorable geometries be discharged into the above criteria bin, along with material determined to have been contaminated. The Extruder was extremely successful in producing a stable soil column with favorable geometries for radiological assay. During production, less than 0.5% (by mass) of the soils processed were presented in unsatisfactory geometries requiring disposition as radioactive waste. The Extruder did not get clogged due to the cohesive soils (as is typical with conventional conveyors) and required very little maintenance, again minimizing impacts to sorting operations. The conveyor belt speed was operated at 14 cm/s with a typical belt loading of ∼109 kg/m resulting in a mean process rate of ∼49 metric tons/hr. The process rate was constrained by other project logistics, rather than by the capabilities of the Extruder, which was operated at less than 20% of the maximum design speed (75 cm/s). It is concluded that the Extruder is highly likely to produce a stable highly cohesive soil column suitable for efficient and confident radiological assay in production environments of 250 short tons/hr or more. The Extruder has the capability to drastically reduce the duration and costs of projects with radiologically impacted highly cohesive soils. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Effects of size, geometry, and testing temperature on additively manufactured Ti-6Al-4V titanium alloy

This article presents a comprehensive study concerning size and geometry effect on the ambient and high-temperature mechanical behavior of additively manufactured laser powder bed fusion Ti-6Al-4V alloy. Key mechanical property metrics are presented, including strain hardening rate, yield strength, and Young’s modulus as a function of thickness and testing temperature (ambient, 250 °C, and 450 °C). Here, the effect of specimen size on manufacturing-induced microstructural feature formation is demonstrated and discussed. A detailed analysis regarding Young’s modulus, yield strength, and strain hardening rate variation at elevated temperatures is also presented. Size effect and temperature-sensitive deformation mechanisms are linked to the underlying microstructural deformation mechanisms activated at respective temperatures. Counter-intuitively, this study determined that irrespective of the geometry, strain hardening rates increased as temperature increased. An in-depth microstructural examination is presented to explain the stated observation. The texture of Interrupted tensile test samples examined for ambient, 250 °C, and 450 °C post-yield was observed to be unchanged, indicating the strain hardening behavior was not texture dependent. Schmid factor analysis, coupled with experimental findings from previous work, was implemented to generate a hypothesis. This hypothesis suggests that the drop in critical resolved shear stress for basal and pyramidal slip systems, as temperature increases, paired with the high dislocation density of laser powder bed fusion Ti-6Al-4V, leads to dislocation entanglement and results in increased strain hardening at elevated temperatures.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Equivalence principle in Reissner–Nordström geometry

The Equivalence Principle is a key element in the development of General Relativity. In one of its formulations, the Equivalence Principle states that a reference frame at rest in a uniform gravitational field is equivalent to a reference frame in uniformly accelerated motion in the absence of any gravitation field. We analyze the spacetime surrounding a non-rotating spherically symmetric charged body, known as Reissner–Nordström geometry, and exhibit a coordinate transformation, which makes explicit its compatibility with the Equivalence Principle. We revisit the Schwarzschild case, previously analyzed in the literature. We also consider second order terms of the relevant expansion parameters in the approximate metric, which is needed for the computed curvature quantities to be correct at zeroth order.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Convex Programs for Minimal-Area Problems

The minimal-area problem that defines string diagrams in closed string field theory asks for the metric of least area on a Riemann surface with the condition that all non-contractible closed curves have length at least 2π. This is an extremal length problem in conformal geometry as well as a problem in systolic geometry. Here, we consider the analogous minimal-area problem for homology classes of curves and, with the aid of calibrations and the max flow-min cut theorem, formulate it as a local convex program. We derive an equivalent dual program involving maximization of a concave functional. These two programs give new insights into the form of the minimal-area metric and are amenable to numerical solution. We explain how the homology problem can be modified to provide the solution to the original homotopy problem.

97 MATHEMATICS AND COMPUTING↗