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DOE OSTI2022

Extracting energy from ocean thermal and salinity gradients to power unmanned underwater vehicles: State of the art, current limitations, and future outlook

Thermal gradient energy-generation technologies for powering unmanned underwater vehicles (UUVs) or autonomous sensing systems in the ocean are mainly in the research development phase or commercially available at a limited scale, and salinity-gradient energy-generation technologies have not been adequately researched yet. The demand for self-powered UUVs suitable for long-term deployments has been growing, and further research related to small-scale ocean gradient energy systems is needed. In this study, we conducted a comprehensive review about harvesting energy from ocean thermal or salinity gradients for powering UUVs, focusing on gliders and profiling floats. Thermal gradient energy systems for UUVs based on phase change materials (PCM) cannot provide the energy required for powering autonomous sensing systems because of the systems' low energy conversion efficiency. Besides reducing energy consumption by developing more efficient electrical-mechanical systems, enhancing the thermal conductivity of the PCMs may help address this challenge by increasing the power generation rate of the UUVs. Several other emerging technologies, such as thermoelectric generators, shape memory alloys, and small-scale thermodynamic cycle systems, have shown potential for powering UUVs, but they are still only at the laboratory testing or conceptual design phase. The most advanced power generation technologies based on salinity gradients, reverse electrodialysis and pressure-retarded osmosis, are still not economically viable for large-scale deployment, mainly because of the high cost of the components required to operate in harsh saline environments. Our feasibility evaluation showed that existing salinity gradient power generation technologies are not directly feasible for powering UUVs in the open ocean.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Cryogenic optical beam steering for superconducting device calibration

We have developed a calibration system based on a micro-electromechanical systems (MEMS) mirror that is capable of delivering an optical beam over a wavelength range of 180 -- 2000 nm (0.62 -- 6.89 eV) in a sub-Kelvin environment. This portable, integrated system can steer the beam over a $\sim$3 cm $\times$ 3 cm area on the surface of any sensor with a precision of $\sim$100 $μ$m, enabling characterization of device response as a function of position. This fills a critical need in the landscape of calibration tools for sub-Kelvin devices, including those used for dark matter detection and quantum computing. These communities have a shared goal of understanding the impact of ionizing radiation on device performance, which can be pursued with our system. This paper describes the design of the first-generation calibration system and the results from successfully testing its performance at room temperature and 20 mK.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

NGFC-Lib/NGFC-Lib

Automated NGFC system design tool set to develop optimized, next-generation solid oxide fuel cell (SOFC) based natural gas fuel cell (NGFC) system designs with >70% fuel efficiency and <30 g/kWh CO2 emissions

Bao, Jie↗

DOE OSTI2024

Processing MCNP Elemental Edit Outputs

The Monte Carlo N-Particle (MCNP) transport code version 6 (also known as MCNP6) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into constructive solid geometry (CSG) cells. A UM geometry is a collection of elements representing a solid geometry. The first step of MCNP UM modeling is using other software packages to create a finite element mesh representation of a solid 3D geometry. Computer-aided design (CAD) or computer-aided manufacturing (CAM) software is typically used to create a solid geometry model, which is later imported into mesh generation software to create a UM model. The MCNP UM feature was originally designed for models generated by the Abaqus/CAE software. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. MCNP can process a UM model consisting of several different element types including linear tetrahedral or hexahedral elements and calculate quantities of interest such as flux and energy deposition at elements. An MCNP UM simulation provides high-fidelity elemental edit (i.e., tally) outputs, which can be further used in multiphysics calculations. The MCNP UM feature was used for multiphysics simulations where quantities of interest calculated by MCNP are used as inputs for heat transfer calculations in Abaqus. MCNP6.3 can produce two types of elemental edit output (EEOUT) file formats: ASCII and HDF5. An EEOUT file type must be requested on an EMBED card while output type (flux or energy deposition) must be requested on an EMBEE card. We wrote Python3 scripts to extract energy deposition values in an ASCII or HDF5 EEOUT file and compute a heat flux profile for an Abaqus heat transfer calculation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

IDAES GTEP 0.1 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Generation and Transmission Expansion Planning (GTEP) package provides a Pyomo-based implementation of a modular, flexible, Generalized Disjunctive Programming (GDP) formulation for power infrastructure planning problems. This package is designed with the following goals in mind: - Abstract GTEP modeling away from any particular case study or fixed modeling assumptions (e.g., technologies, temporal resolution, spatial resolution, policy implications, etc.) - Admit flexible decision sets and heterogeneous parameterization - Allow high-level modeling options to be understood easily, chosen modularly, and changed rapidly

AS↗

DOE OSTI2026

MADA: Multi-Agent Design Assistant

MADA (Multi-Agent Design Assistant) is a Large Language Model (LLM) powered multi-agent framework that coordinates specialized agents for complex design workflows. The system was designed for HPC workflows with the following agents in mind: 1) A Job Management Agent (JMA) launches and manages ensemble simulations on HPC systems, 2) a Geometry Agent (GA) generates meshes, and 3) an Inverse Design Agent (IDA) proposes new designs informed by simulation outcomes. Our framework reduces cumbersome manual workflow setup, and enables automated design exploration at scale. However, the software also enables users to rapidly create new multi-agent systems. Simply define new agents in a configuration file, giving each their own set of tools (via MCP), and then chat and prompt your new multi-agent system. Is

Gunnarson, BrianS [Lawrence Livermore National Lab↗

DOE OSTI2026

Colloidal Synthesis of Palladium Nanocluster‐Decorated Cs 3 Sb 2 Cl 9 Perovskite Heterostructural Nanorods for Enhanced CO 2 Photoreduction

Developing efficient and sustainable photocatalysts for CO 2 reduction remains a significant challenge, particularly with environmentally benign materials. Here, in this study, we report the first one-step synthesis of metal–lead-free perovskite heterostructural nanocrystals by decorating Cs 3 Sb 2 Cl 9 perovskite nanorods with size-controlled Pd nanoclusters via a one-step hot-injection method. The resulting Pd-Cs 3 Sb 2 Cl 9 heteronanorods (HNRs) exhibit strong interfacial electronic coupling, enhanced charge separation, and excellent colloidal stability. Transient absorption spectroscopy and DFT calculations reveal a built-in electric field that drives directional electron transfer from the perovskite host to the Pd domains. Under UV irradiation, the Pd-Cs 3 Sb 2 Cl 9 HNRs demonstrate excellent CO 2 photoreduction activity with high CH 4 selectivity, achieving a record apparent quantum yield (AQY) of 2.62% among halide perovskite nanocrystal-based systems with a large electronic yield of 689.3 ± 12.2 µmol·g cat −1 . In situ spectroscopic monitoring and Gibbs free energy analysis further unveil a Pd-facilitated reaction pathway involving stabilization of key intermediates. This work introduces a new class of lead-free perovskite-based heterostructures through a facile one-step synthesis strategy and offers a new design principle for next-generation photocatalysts for solar fuel production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Low Thermal Conductivity and Diffusivity at High Temperatures Using Stable High–Entropy Spinel Oxide Nanoparticles

The realization of low thermal conductivity at high temperatures (0.11 W m –1 K –1 800 °C) in ambient air in a porous solid thermal insulation material, using stable packed nanoparticles of high-entropy spinel oxide with 8 cations (HESO-8 NPs) with a relatively high packing density of ≈50%, is reported. The high-density HESO-8 NP pellets possess around 1000-fold lower thermal diffusivity than that of air, resulting in much slower heat propagation when subjected to a transient heat flux. The low thermal conductivity and diffusivity are realized by suppressing all three modes of heat transfer, namely solid conduction, gas conduction, and thermal radiation, via stable nanoconstriction and infrared-absorbing nature of the HESO-8 NPs, which are enabled by remarkable microstructural stability against coarsening at high temperatures due to the high entropy. Furthermore, this work can elucidate the design of the next-generation high-temperature thermal insulation materials using high-entropy ceramic nanostructures.

thermal insulation↗

DOE OSTI2025

Revisiting the Role of Entropy for Charge Separation in 1D Pi-Conjugated Semiconductors

Free carrier generation in organic donor/acceptor heterojunctions and redox-doped organic semiconductors is poorly understood, since assumed tight electron-hole binding conflicts with observed high free carrier yields. Cornerstone analyses that have guided the field for over 15 years predict that entropy can stabilize free charges in 2D and 3D pi-conjugated semiconductors but not in 1D systems. Here, the impact of entropy on charge generation in 1D pi-conjugated semiconductors is revisited by exploiting a greatly simplified system where enthalpy considerations alone should not allow for free charge generation. Noncontact solution-phase microwave conductivity is used to investigate the carrier density-dependent conductivity and dielectric constant in isolated chemically doped semiconducting single-walled carbon nanotubes in a low-dielectric solvent. Dopant chemical structure dramatically influences the carrier density-dependent complex conductivity, with bulky dopants facilitating carrier escape even at carrier densities below one carrier per nanotube. Three distinct numerical calculations show that entropic stabilization dramatically lowers the Gibbs energy barrier for free charge generation, explaining the high yield of free carriers, even in 1D. This renewed understanding of entropy's role in carrier generation has important implications for designing organic electronic devices-such as solar cells and thermoelectric energy harvesters-for enhanced carrier yield, conductivity, and performance.

36 MATERIALS SCIENCE↗

DOE OSTI2024

High‐Energy LiNiO 2 Li Metal Batteries Enabled by Hybrid Electrolyte Consisting of Ionic Liquid and Weakly Solvating Fluorinated Ether

Abstract In pursuit of the highest possible energy density, researchers shift their focus to the ultimate anode material, lithium metal (Li 0 ), and high‐capacity cathode materials with high nickel content (Ni > 80%). The combination of these aggressive electrodes presents unprecedented challenges to the electrolyte. Here, we report a hybrid electrolyte consisting of a highly fluorinated ionic liquid and a weakly solvating fluorinated ether, whose hybridization structure enables the reversible operation of a battery chemistry based on Li 0 and LiNiO 2 (Ni = 100%), delivering nearly theoretical capacity of the latter (up to 249 mAh g −1 ) for >300 cycles with retention of 78.6% and in absence of unwanted morphological changes in both electrodes. Extensive characterization assisted by molecular dynamic simulation and density functional theory calculations reveals the function of the fluorinated ether to be far more profound than simple dilution and viscosity reduction. Instead, it induces drastic changes in Li + ‐solvation environment, the consequence of which engenders simultaneous stabilization of electrode/electrolyte and interfacing via formation of respective interfacial chemistries. This study further unlocks fundamental knowledge underneath the prevailing “diluent strategy” that is extensively applied by the electrolyte researchers and opens more design space for the next‐generation electrolytes and interphases for these coveted battery chemistries.

25 ENERGY STORAGE↗

DOE OSTI2026

On the Ordering Mechanism of Cu + in 2D van der Waals Multiferroic CuCrP 2 S 6

CuCrP 2 S 6 is a van der Waals multiferroic where the tunable Cu + sublattice underpins its exceptional ferroelectric and electronic switching properties. Yet, the microscopic mechanism governing Cu + ordering has remained elusive. Here, we combine single-crystal X-ray and neutron diffraction with pair distribution function analysis to uncover a temperature-driven evolution of Cu + ordering, giving rise to an incommensurate quasi-antipolar phase between the paraelectric and antiferroelectric states. The modulation originates from correlated Cu + occupancy redistribution coupled to breathing distortion of surrounding S 3 triangles, establishing a symmetry-adapted lattice distortion mode. Diffuse scattering persisting over 35 K above the transition confirms that the structural instability follows an order-disorder mechanism. The spontaneous off-centering of Cu + positions CuCrP 2 S 6 as a model platform for correlated order-disorder phenomena in 2D layered ferroics, and provides design principles for next-generation memory and logic devices.

ferroelectrics↗

DOE OSTI2020

Direct Characterization of Atomically Dispersed Catalysts: Nitrogen-Coordinated Ni Sites in Carbon-Based Materials for CO 2 Electroreduction

Metal, nitrogen-doped carbon materials have attracted interest as heterogenous catalysts that contain MN x active sites that are analogous to molecular catalysts. Of particular interest is Ni,N-doped carbon, a catalyst that is active for the electrochemical reduction of CO 2 to CO. Critical to the understanding of these materials is proof of single atomic sites and characterization of the environment surrounding the metal atom; however, directly probing this coordination remains challenging. This challenge is addressed in this study by combining scanning transmission electron microscopy (STEM), single atom electron energy loss spectroscopy (EELS), and time-of-flight secondary ion mass spectrometry (ToF-SIMS). Through STEM imaging, atomic dispersion of Ni in the carbon framework is confirmed and image analyses are utilized to give semiquantitative estimates of neighbor distance distributions and site densities of Ni atoms. Atomic resolution EELS demonstrates that N and Ni are colocated at the single Ni atom sites suggesting Ni–N coordination. ToF-SIMS reveals a distribution of NiN x C y - fragments that reflect the Ni–N bonding environments within Ni,N-doped carbon. The fragmentation from Ni,N-doped carbon is similar to Ni phthalocyanine, suggesting the existence of heterogenized, molecular-like NiN 4 active sites which motivates future studies that leverage insight from molecular catalysis design to develop next-generation heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Prediction of Reactive Nitrous Acid Formation in Rare‐Earth MOFs via ab initio Molecular Dynamics

Abstract Reactive gas formation in pores of metal–organic frameworks (MOFs) is a known mechanism of framework destruction; understanding those mechanisms for future durability design is key to next generation adsorbents. Herein, an extensive set of ab initio molecular dynamics (AIMD) simulations are used for the first time to predict competitive adsorption of mixed acid gases (NO 2 and H 2 O) and the in‐pore reaction mechanisms for a series of rare earth (RE)‐DOBDC MOFs. Spontaneous formation of nitrous acid (HONO) is identified as a result of deprotonation of the MOF organic linker, DOBDC. The unique DOBDC coordination to the metal clusters allows for proton transfer from the linker to the NO 2 without the presence of H 2 O and may be a factor in DOBDC MOF durability. This is a previously unreported mechanisms of HONO formation in MOFs. With the presented methodology, prediction of future gas interactions in new nanoporous materials can be achieved.

Vogel, Dayton J.↗

DOE OSTI2021

Prediction of Reactive Nitrous Acid Formation in Rare‐Earth MOFs via ab initio Molecular Dynamics

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Developing AlMn Films for Argonne TES Fabrication

The reference design for the next-generation cosmic microwave background (CMB) experiment, CMB-S4, relies on large arrays of transition-edge sensor (TES) bolometers coupled to Superconducting Quantum Interference Device (SQUID)-based readout systems. Mapping the CMB to near cosmic variance limits will enable the search for signatures of inflation and constrain dark energy and neutrino physics. AlMn TESes provide simple film manufacturing and highly uniform arrays over large areas to meet the requirements of the CMB-S 4 experiment. TES parameters such as critical temperature and normal resistance must be tuned to experiment specifications and can be varied based on geometry and steps in the fabrication process such as deposition layering, geometry, and baking time and temperature. Using four-terminal sensing, we measured T C and R N of AlMn 2000 ppm films and devices of varying thicknesses fabricated at Argonne National Laboratory to motivate device geometries and fabrication processes to tune T C to 150–200 mK and R N to ~10 mΩ. Furthermore, measurements of IV curves and time constants for the resulting devices of varying leg length were made using time-division SQUID multiplexing and determined TC, G, k, f 3db , and RN. We present the results of these tests along with the geometries and fabrication steps used to tune the device parameters to the desired limits.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Creep Behavior and Phase Equilibria in Model Precipitate Strengthened Alumina-Forming Austenitic Alloys

Abstract Creep-rupture behavior and microstructural response in alumina-forming austenitic (AFA) alloys with two different precipitation strengthening mechanisms, “Laves-phase + M 23 C 6 carbide” and “coherent L1 2 γ′-Ni 3 (Al,Ti),” were explored as “model” cases of multi-phase, multi-scale heat-resistant AFA alloys for 650–750°C use. These alloys will be used to guide and verify computational alloy design and life-prediction modeling under an on-going eXtremeMAT project through the Office of Fossil Energy and Carbon Management, US Department of Energy. Computational thermodynamics were used to design and predict the amounts of strengthening and deteriorating secondary phases at 750°C. Creep-rupture lives of the alloys tested at 750°C and 100 MPa were in a range of 4000–9000 h, and the microstructure at the gage/grip after creep-rupture testing was compared with isothermally aged alloys for 1500 h, as well as the calculated phases. Detailed microstructure characterization includes phase identification, volume fraction measurement, and compositional analysis, which were correlated with the creep-rupture properties. High-temperature oxidation resistance was also screened and compared with commercial, chromia-forming heat-resistant steels. These model alloys also provide the basis for further design and optimization of next generation AFA alloys with improved creep resistance.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Continuous-variable quantum Boltzmann machine

Here, we propose a continuous-variable quantum Boltzmann machine (CVQBM) using a powerful energy-based neural network. It can be realized experimentally on a continuous-variable (CV) photonic quantum computer. We used a CV quantum imaginary time evolution (QITE) algorithm to prepare the essential thermal state and then designed the CVQBM to proficiently generate continuous probability distributions. We applied our method to both classical and quantum data. Using real-world classical data, such as synthetic-aperture radar (SAR) images, we generated probability distributions. For quantum data, we used the output of CV quantum circuits. We obtained high fidelity and low Kullback–Leibler (KL) divergence showing that our CVQBM learns distributions from given data well and generates data sampling from that distribution efficiently. We also discussed the experimental feasibility of our proposed CVQBM. Our method can be applied to a wide range of real-world problems by choosing an appropriate target distribution (corresponding to, e.g., SAR images, medical images, and risk management in finance). Moreover, our CVQBM is versatile and could be programmed to perform tasks beyond generation, such as anomaly detection.

SAR images↗

DOE OSTI2023

High-throughput exploration of the WMoVTaNbAl refractory multi-principal-element alloys under multiple-property constraints

Development of next-generation gas turbines requires the design and fabrication of novel high-temperature structural materials capable of operating beyond 1300°C. Here, we propose a high-throughput alloy design framework under multiple-property constraints to discover new refractory multi-principal element alloys (MPEAs) for high-temperature applications. The framework treats the development of MPEAs as a composition-agnostic constraint satisfaction problem, i.e., no prescriptions are made concerning the design space before performing investigatory calculations. We target alloys in the WMoVTaNbAl chemistry space that are predicted to meet constraints on the following properties simultaneously: single-phase stability, density, solidus temperature, yield strength at 1300°C, and ductile-to-brittle-transition temperature. These properties are relevant to both applications in gas turbines and manufacturability. A set of 214 MoNbV-rich alloys meet these relevant constraints. These feasible alloys are investigated with density functional theory (DFT) to provide a fundamental electronic basis for their superior properties. Three compositionally representative alloys from the feasible design space (Mo 45 Nb 35 Ta 5 V 15 , Mo 25 Nb 50 V 20 W 5 , and Mo 30 Nb 35 Ta 5 V 25 W 5 ) are selected with a k-medoids-based design scheme for detailed DFT analysis and experimental characterization. The DFT analysis predicted a single-phase BCC at high temperatures with a high yield strength for all three MPEAs, in agreement with CALPHAD (CALculation of PHAse Diagrams) and experiments, respectively. These three alloys are benchmarked against a public database of 1546 MPEAs. Concerning the aforementioned constraints, the Mo 30 Nb 35 Ta 5 V 25 W 5 alloy outperforms these 1546 MPEAs. The present work demonstrates the ability of the proposed design methodology to identify candidate alloys for a given application under multiple property constraints in a combinatorically vast design space.

36 MATERIALS SCIENCE↗