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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Heterogeneous Mixtures of Dictionary Functions to Approximate Subspace Invariance in Koopman Operators: Why Deep Koopman Operators Work

Abstract Koopman operators model nonlinear dynamics as a linear dynamic system acting on a nonlinear function as the state. This nonstandard state is often called a Koopman observable and is usually approximated numerically by a superposition of functions drawn from a dictionary . In a widely used algorithm, extended dynamic mode decomposition (EDMD), the dictionary functions are drawn from a fixed class of functions. Deep learning combined with EDMD has been used to learn novel dictionary functions in an algorithm called deep dynamic mode decomposition (deepDMD). The learned representation both (1) accurately models and (2) scales well with the dimension of the original nonlinear system. In this paper, we analyze the learned dictionaries from deepDMD and explore the theoretical basis for their strong performance. We explore State-Inclusive Logistic Lifting (SILL) dictionary functions to approximate Koopman observables. Error analysis of these dictionary functions show they satisfy a property of subspace approximation, which we define as uniform finite approximate closure. Typically, a Koopman dictionary’s nonlinear functions are homogeneous. In this paper, we discover that structured mixing of heterogeneous dictionary functions drawn from different classes of nonlinear functions achieve the same accuracy and dimensional scaling as the deep-learning-based deepDMD algorithm Yeung et al. ( In: 2019 American Control Conference (ACC), 2019). We specifically show this by building a heterogeneous dictionary comprised of SILL functions and conjunctive radial basis functions (RBFs). This mixed dictionary achieves similar accuracy and dimensional scaling to deepDMD with an order of magnitude reduction in parameters, while maintaining geometric interpretability. These results strengthen the viability of dictionary-based Koopman models to solving high-dimensional nonlinear learning problems.

Johnson, Charles A.↗
DOE OSTI2024

Moiré Patterns in Pt Overlayers on Gold: A Graph Neural Network Interatomic Potential Study

Overlayer structures in bimetallic catalysts are relevant to a variety of catalytic reactions, particularly in electrocatalysis for fuel cell applications. Previous computational studies largely consider these overlayer structures to be those of a pseudomorphic overlayer, where there is a 1:1 atomic ratio between the overlayer and the support metal. Our previous work based on density functional theory (DFT) has shown that there exist nonstoichiometric overlayer structures that are more stable than the stoichiometric ones. Here, in this work, we developed a graph neural network interatomic potential (GNN-IP) to analyze structures formed in Pt overlayers on Au(111). The GNN-IP was used to explore properties of nonstoichiometric overlayers at length scales that are prohibitively expensive to pursue with planewave DFT calculations. In particular, we examined large Pt islands on top of a 48 × 48 Au(111) unit cell to explore the influence of the rotational angle (α) between the Pt overlayer and support Au(111) on both the stability of and the preferred atomic density in the overlayer. Island structures with smaller rotational angles between the Pt overlayer and Au(111) tend to be more stable. Further, smaller rotational angles tend to result in lower atomic density in the Pt overlayer.

chemical structure↗
DOE OSTI2024

Adsorption Properties of Au−Ni Surface Alloys with a Nonstoichiometric Moiré Structure: A Density Functional Theory Study

Due to the large lattice mismatch between gold and nickel, gold–nickel surface alloys can form unique nonstoichiometric overlayer structures characterized by a moiré pattern and subsurface defects. For this work, we performed density functional theory (DFT) calculations to study the adsorption of molecular oxygen, atomic hydrogen, and atomic carbon on a gold–nickel(111) surface alloy with 0.46 monolayer gold randomly distributed in the surface layer. We observed six distinct adsorption structures for molecular oxygen characterized by intramolecular stretching frequencies of <700, 729, 795, 857, 929, and 1004 cm –1 , which describe well the experimentally observed high-resolution electron energy-loss spectra. Surface atomic hydrogen adsorption is associated with adsorbate–surface modes in the ∼1000 cm –1 range, while subsurface hydrogen can have features as low as ∼400 cm –1 . We observed a unique adsorption structure for atomic carbon inside the surface dislocation loop defect, which explains the experimentally observed low carbon-surface mode at ∼340 cm –1 . Our study sheds light on the unique adsorption properties of the gold–nickel surface alloys and helps with rationalizing vibrational frequency experimental studies for this system.

adsorption↗
DOE OSTI2024

High Selectivity Reactive Carbon Dioxide Capture over Zeolite Dual-Functional Materials

Reactive carbon dioxide capture (RCC) is a process where carbon dioxide (CO 2 ) is captured from a mixed gas stream (such as air) and converted to products without first performing a separation step to concentrate the CO 2 . Here, in this work, zeolite dual-functional materials (ZFMs) are introduced and evaluated for simulated RCC. The studied ZFMs feature high surface area, crystalline, microporous zeolite faujasite (FAU) as the support. Sodium oxide (“Na 2 O”) is impregnated as an effective capture agent capable of scavenging low concentration CO 2 (1,000 ppm). Exchanged and impregnated sodium on FAU chemisorbs CO 2 as carbonates and bicarbonates but does not promote the conversion of sorbed CO 2 to products when heated in hydrogen. The addition of Ru promotes the formation of formates, while the addition of Pt generates carbonyl surface species when heated in hydrogen. The active metal then promotes extremely high selectivity for CO 2 hydrogenation to either methane on Ru catalyst (~150 °C) or carbon monoxide on Pt catalyst (~200 °C) when heated in reducing atmospheres.

36 MATERIALS SCIENCE↗
DOE OSTI2025

First-Principles Dissociation Pathways of BCl 3 on the Si(100)-2 × 1 Surface

BCl 3 is a promising acceptor precursor for atomic-precision δ-doping of silicon, as it has been observed to rapidly dissociate into boron doped into the silicon surface and surface chlorine, which can be removed upon annealing. The chemical pathway and the resulting kinetics, through which BCl 3 adsorbs and dissociates on silicon, however, have only been partially explained. Here, in this work, we use density functional theory to expand the dissociation reactions of BCl 3 to include reactions that take place across multiple silicon dimer rows and reactions which end in a bare B atom either at the surface, substituted for a surface silicon, or in a subsurface position. We further simulate the resulting scanning tunneling microscopy images for each of these BCl x dissociation fragments, demonstrating that they often display distinct features that may allow for relatively confident experimental identification. Finally, we input the full dissociation pathway for BCl 3 into a kinetic Monte Carlo model, which simulates realistic reaction pathways as a function of environmental conditions, such as the pressure and temperature of dosing. We find that BCl 2 is broadly dominant at low temperatures, while high temperatures and ample space on the silicon surface for dissociation encourage the formation of bridging BCl fragments and B substitutions on the surface. This work provides the chemical mechanisms for understanding atomic-precision doping of Si with B, enabling a number of relevant quantum applications, such as bipolar nanoelectronics, acceptor-based qubits, and superconducting Si.

Campbell, Quinn T. [Sandia National Laboratories (↗
DOE OSTI2024

Addressing Issues with Working Memory in Video Object Segmentation

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models perform very well on clean video data, their reliance on a working memory of previous frames leaves room for error. Affinity-based algorithms include the inductive bias that there is temporal continuity between consecutive frames. To account for inconsistent camera views of the desired object, working memory models need an algorithmic modification that regulates the memory updates and avoid writing irrelevant frames into working memory. A simple algorithmic change is proposed that can be applied to any existing working memory-based VOS model to improve performance on inconsistent views, such as sudden camera cuts, frame interjections, and extreme context changes. The resulting model performances show significant improvement on video data with these frame interjections over the same model without the algorithmic addition. Our contribution is a simple decision function that determines whether working memory should be updated based on the detection of sudden, extreme changes and the assumption that the object is no longer in frame. By implementing algorithmic changes, such as this, we can increase the real-world applicability of current VOS models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Growth functions of periodic space tessellations

This work analyzes the rules governing the growth of the numbers of vertices, edges and faces in all possible periodic tessellations of the 2D Euclidean space, and encodes those rules in several types of polynomial growth functions. These encodings map the geometric, combinatorial and topological properties of the tessellations into sets of integer coefficients. Several general statements about these encodings are given with rigorous mathematical proof. The variation of the growth functions is represented graphically and analyzed in orphic diagrams, so named because of their similarity to orphic art. Several examples of 3D space groups are included, to emphasize the complexity of the growth functions in higher dimensions. A freely available Python library is presented to facilitate the discovery of the growth functions and the generation of orphic diagrams.

Chemistry↗
DOE OSTI2026

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2026

Transition Metal Taggants in UO 2 from First Principles

The incorporation of transition metals into nuclear fuel has gained attention both to improve fuel properties and as a possible nuclear forensics tool. Recent experimental studies by Ulrich et al. and Adorno Lopes et al. have investigated Ni and Fe as candidate transition metal dopants for potential nuclear forensics purposes and found that there is minimal alteration to key UO 2 fuel properties. In the present work, we performed density functional theory (DFT) investigations into possible defect structures for Ni and Fe incorporation. The dynamic stability of these defect structures was validated by calculating the phonon density of states. We found that transition metal incorporation likely occurs via substitution at U sites in the fluorite crystal structure with a nearby O vacancy for charge-balancing, which agrees with experimentally proposed structures. Additionally, this defect structure does not cause long-range alterations to the crystal parameters—an important consideration for use as a nuclear fuel taggant. Future needed work involves computational investigation of additional defect concentrations using larger supercells, additional transition metal charge states, and thermal effects. Such investigations can be carried forward into sintering models for a more complete understanding of the suitability of Ni and Fe as fuel taggants.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Anionic Lipids Regulate the Light-Harvesting Complex 1-Reaction Center Photocycle in Purple Bacteria

Photosynthetic purple bacteria can capture and convert sunlight with a remarkable, nearly 100% quantum efficiency. The light-harvesting complex 1-reaction center (LH1-RC) core complex is the membrane complex fundamentally responsible for solar energy conversion. LH1-RC has a highly conserved surrounding lipid composition known to favor anionic lipids for an unknown function. Here, in this work, we compared experimentally the rate of LH1-to-RC energy transfer in detergent, membrane nanodiscs with varying lipid compositions, purified membrane fragments, and live cells. The energy transfer rate indicated that RC turnover decreased in neutral lipids, yet was partially restored in anionic lipids, revealing an unexpected lipid dependence. In complementary molecular dynamics simulations, the anionic lipid cardiolipin showed electrostatic interactions with LH1-RC that may mediate quinone exchange, providing a mechanism for the observed lipid dependence. Overall, these results revealed that anionic lipids facilitate LH1-RC redox cycling, identifying a functional role for membrane composition in photosynthetic solar energy conversion.

bacteria↗
DOE OSTI2024

Water, Solute, and Ion Transport in De Novo-Designed Membrane Protein Channels

Biological organisms engineer peptide sequences to fold into membrane pore proteins capable of performing a wide variety of transport functions. Synthetic de novo-designed membrane pores can mimic this approach to achieve a potentially even larger set of functions. Here, in this work, we explore water, solute, and ion transport in three de novo designed β-barrel membrane channels in the 5–10 Å pore size range. We show that these proteins form passive membrane pores with high water transport efficiencies and size rejection characteristics consistent with the pore size encoded in the protein structure. Ion conductance and ion selectivity measurements also show trends consistent with the pore size, with the two larger pores showing weak cation selectivity. MD simulations of water and ion transport and solute size exclusion are consistent with the experimental trends and provide further insights into structure–function correlations in these membrane pores.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Ab initio thermodynamics of Ni and Co incorporation in Mg hydroxide, carbonate, and hydroxycarbonate minerals

Ni and Co are critical elements needed for modern technologies, and a better understanding of the ability of Mg-based minerals to incorporate these elements would benefit strategy development for Ni and Co recovery from mafic and ultramafic deposits. Here, in this work, we performed density functional theory (DFT) calculations of Ni and Co incorporation in six potential products of the carbonation of mafic and ultramafic silicates: brucite (Mg(OH) 2 ), magnesite (MgCO 3 ), nesquehonite (MgCO 3 ⸱3H 2 O), lansfordite (MgCO 3 ⸱5H 2 O), artinite (Mg 2 CO 3 (OH) 2 ⸱3H 2 O), and hydromagnesite (Mg 5 (CO 3 ) 4 (OH) 2 ⸱4H 2 O). The DFT results were used in an ab initio thermodynamics framework to explore the pH 2 O–pCO 2 conditions at which the Mg-based minerals were predicted to be thermodynamically stable and to quantify the Gibbs free energy of Ni and Co substitution at Mg sites. Among the six Mg-based minerals, brucite and magnesite were predicted to have the lowest Ni and Co substitution free energy. An analysis of the effect of temperature indicated that, at low temperature (<100 K), brucite more readily accommodated Ni and Co, while, at higher temperature (>335 K), magnesite more favorably incorporated Ni and Co. Between 100 K and 335 K, Ni was predicted to preferentially substitute for Mg in brucite and Co for Mg in magnesite, thus leading to a driving force for separating Ni and Co in conditions where brucite and magnesite both form. Insights gained in this work could therefore help select experimental conditions that either promote or inhibit incorporation of these critical elements into Mg-based mineral phases.

Critical elements↗
DOE OSTI2025

Near-field infrared imaging of polar domain walls in Ni 3 TeO 6

Domain walls are leading platforms for the development of ultra-low power switching and memory devices due to their potential to be moved, created, and erased in real time and to mitigate heat flux. Interface vs wavelength size effects unfortunately preclude the measurement of phonons by traditional spectroscopic techniques, so it has been challenging to unravel the primary excitations of the lattice and the symmetries that they represent across these functional interfaces. In this work, we employ synchrotron-based near-field infrared nanospectroscopy to image polar domain walls in multiferroic Ni 3 TeO 6 . This is a unique platform because, in addition to hosting polar and chiral domains that are interlocked with one another, Ni 3 TeO 6 displays both charged and neutral interfaces depending upon the direction allowing the development of structure–property relations. From a local structure and a strain point of view, we find charged walls that are twice as wide as neutral walls as well as strong frequency shifts of vibrational modes across the charged walls. The near-field amplitude drops across the walls as well. We discuss these trends in terms of polarization and chirality as well as phonon lifetimes at functional interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Self‐Assembled Membranes for High Ion Selectivity and Proton Blocking in Electrochemical Applications

Anion-exchange membranes (AEMs) with high anion/cation selectivity and exceptional proton-blocking ability are critical for applications such as bipolar membrane electrodialysis and electrochemical acid recovery. However, existing AEMs are constrained by a trade-off between ionic conductivity and selectivity, largely due to the intrinsic coupling between charge density and water content, and they suffer from excessive proton leakage facilitated by the Grotthuss hopping mechanism. In this work, poly(vinylimidazolium) membranes functionalized with long alkyl side chains that self-assemble into well-defined microphase-separated morphologies stabilized by hydrophobic and electrostatic interactions are reported. These unique structures localize the charge density along the polymer backbone to promote fast and selective ion transport. As a result, these membranes exhibit ionic conductivities and counter-ion diffusivities surpassing those of conventional homogeneous membranes, along with unprecedented counter-ion/co-ion selectivity and proton-blocking ability. These results establish a new design paradigm for high-performance, phase separated charged polymer membranes that overcome the limitations of homogeneous membranes, with broad implications for advanced electrochemical technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The effective number of parameters in kernel density estimation

We devise a new formula for measuring the effective degrees of freedom (EDoF) in kernel density estimation (KDE). Starting from the orthogonal polynomial sequence (OPS) expansion for the ratio of the empirical to the oracle density, we show how convolution with the kernel leads to a new OPS with respect to which one may express the resulting KDE. The expansion coefficients of the two OPS systems can then be related via a kernel sensitivity matrix, which leads to a natural oracle definition of EDoF through the trace operator. Asymptotic properties of the (empirical) plug-in EDoF are worked out through influence functions, and connections with other empirical EDoFs are established. Minimization of Kullback-Leibler divergence is investigated as an alternative to integrated squared error based bandwidth selection rules, yielding a new normal scale rule. The methodology, which arises from a proper oracle formulation and is not restricted to convolution kernels, suggests the possibility of a new bandwidth selection rule based on an information criterion such as AIC.

bandwidth selection↗
DOE OSTI2026

Metal oxide-promoted calcium cuprate catalysts for diol oxidative dehydrocyclization to lactones

Here, this work investigates structure-function relationships in electronically tunable, redox-active, basic Cu-Ca mixed metal oxide catalysts for oxidative dehydrocyclization of liquid diols to lactones. Compositional screening identified Ni 2+ and Zn 2+ as effective promoters that increase the surface Cu 2+ population by ∼1.7× and Cu-normalized activity for liquid 1,4-butanediol conversion to γ-butyrolactone by ∼3–4×. In situ Raman spectroscopy, in situ X-ray absorption spectroscopy (XAS), in situ diffuse-reflectance Fourier transform infrared spectroscopy (DRIFTS), ex situ X-ray diffraction (XRD), and H 2 -temperature-programmed reduction (H 2 -TPR) show that Ni 2+ or Zn 2+ incorporation promotes the formation of Ca 0.82 Cu 1.00 O 2 nanoparticles under mild calcination conditions. This cuprate phase features stronger and shorter Cu–O bonds (1.90 Å) than inactive bulk CuO (1.95 Å) and square-planar Cu 2+ O 4 sites with enhanced d z2 electrophilicity, strengthening alkoxy adsorption. Pyridine-DRIFTS confirms the purely basic nature of the catalyst surface, while methanol-DRIFTS indicates Cu 2+ surface enrichment with Ni or Zn promotion, where Cu–O(Ca)–Cu sites can exist as amorphous domains or a truncation layer on crystalline nanoparticles.

09 BIOMASS FUELS↗
DOE OSTI2025

Carbon dots from surface-capping/passivation of small carbon nanoparticles with nanoscale titanium dioxide

Carbon dots are classically defined as small carbon nanoparticles (CNPs) with effective surface passivation, which has been accomplished predominantly by surface organic functionalization. In the current work, the passivation is achieved by the surface coating of CNPs with nanoscale TiO 2 for CNP/TiO 2 core/shell nanostructures, which are analogous to conventional semiconductor core/shell quantum dots (QDs). The TiO 2 capping of CNPs results in substantial enhancements in the fluorescence quantum yields, also analogous to the similar enhancements famously known for the semiconductor QDs. In conclusion, mechanistic implications of the findings, including the associated further validation on the classical definition of carbon dots, are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Towards smarter green infrastructure: Fusing bark ecology and stemflow hydrodynamics on tree stems

A wide array of bark surfaces sheath wooded plants in rural and urban areas alike. Much work has examined the function and role of bark in different contexts and different environs, including urban areas, finding that it is rich in life and can play a role in the transfer of water and matter to the ground surface. Accordingly, this paper presents a first step to weld and fuse bark ecology and stemflow hydrodynamics. It is an effort to develop a physically-based understanding of the transport of water and matter (e.g., solutes, particulates, microorganisms) along tree stems using relevant equations to allow a more informed consideration of bark in green infrastructure initiatives. In particular, the hydrodynamical equations are based on the conservation of water mass, conservation of momentum, and conservation of scalar mass. These equations, coupled with contemplation of corticular life, underpin and substantiate bark’s unifying role as a modulator and cultivator. By elucidating the ‘black box’ of the tree stem and utilizing the formulations set forth in this paper, urban foresters and planners can develop green infrastructure to help advance ecosystem services and sustainability development goals (SDG), especially SDG 11 and SDG 15.

60 APPLIED LIFE SCIENCES↗