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13 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Photocatalytic Hydrogen Evolution Using Mesoporous Honeycomb Iron Titanate

Mesoporous honeycomb iron titanate using a sol-gel, evaporation-induced self-assembly method is synthesized. A triblock copolymer, F127, serves as a structure-directing agents, with iron chloride and titanium (IV) isopropoxide as inorganic precursors. The strong intermolecular force of attraction among urea, metal precursors, and polymer led to the formation of the mesoporous honeycomb structure. The study of physicochemical properties using different techniques reveals the formation of microstructures with a remarkable degree of porosity. The amorphous iron titanate outperforms the photochemical generation of H 2 due to its disorderly structural arrangement and incomplete crystal formation. The randomness on the structure provides more area for catalytic reaction by providing more contact with the reactant and superior light absorption capability. The high amount of hydrogen gas, 40.66 mmolg -1 h -1 , is observed in the investigation over 3 h of activity for the iron titanate honeycomb sample. This yield is a more significant amount compared to the obtained for the commercially available TiO 2 (23.78 mmolg -1 h -1 ). The iron titanate materials synthesized with low-cost materials and methods are very effective and have the potential for hydrogen generation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

An Emerging Trend in the Synthesis of Iron Titanate Photocatalyst Toward Water Splitting

Hydrogen gas is a prominent focus in pursuing renewable and clean alternative energy sources. The quest for maximizing hydrogen production yield involves the exploration of an ideal photocatalyst and the development of a simple, cost-effective technique for its generation. Iron titanate has garnered attention in this context due to its photocatalytic properties, affordability, and non-toxic nature. Over the years, different synthesis routes, different morphologies, and some modifications of iron titanate have been carried out to improve its photocatalytic performance by enhancing light absorption in the visible region, boosting charge carrier transfer, and decreasing recombination of electrons and holes. The use of iron titanate photocatalyst for hydrogen evolution reaction has seen an upward trend in recent times, and based on available findings, more can be done to improve the performance. This review paper provides a comprehensive overview of the fundamental principles of photocatalysis for hydrogen generation, encompassing the synthesis, morphology, and application of iron titanate-based photocatalysts. The discussion delves into the limitations of current methodologies and present and future perspectives for advancing iron titanate photocatalysts. By addressing these limitations and contemplating future directions, the aim is to enhance the properties of materials fabricated for photocatalytic water splitting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multisublattice cluster expansion study of short-range ordering in iron-substituted strontium titanate

Owing to the challenges in obtaining realistic atomic configurations in large chemical phase spaces, it is not straightforward to describe structure–property relations in materials exhibiting configurational disorder. One example is iron-substituted strontium titanate (SrTi 1–x Fe x O 3–d , STF), a promising perovskite-derivative cathode material in solid oxide fuel cells that exhibits full solid solubility 0 ≤ x ≤ 1 and a tendency to exhibit short-range order. Here we demonstrate a multisublattice cluster expansion (CE) framework and apply it to STF across the full composition range. The CE approach is distinct from more traditional CE formulations in that clusters are defined explicitly by the chemical species distributed among multiple sublattices, rather than via cluster functions of occupation variables with decoration. The modified CE approach makes it easy to distinguish meaningful chemical interactions that are harder to extract from conventional CE, since for the latter chemical identity in a cluster is expressed as a product of site occupations. The least absolute shrinkage and selection operator (LASSO) is implemented as a regression analysis tool to select key clusters and avoid overfitting. We demonstrate this formulation on STF, and show that it can accurately predict configurational energies in comparison to conventional CE. From the key clusters, we identify that short-range ordering between substitutional Fe and oxygen vacancies (V O ) results in the formation of Fe–VO strings. In addition, we consider the stability of STF through CE-based Monte Carlo (MC) simulations and confirm the presence of superstructures that were previously observed in transmission electron microscopy. In this work, analysis of atomic configurations from MC samples reveals variations in the oxidation state of Fe atoms, which can be explained by the ordering tendency of Fe and V O . The cluster description and selection formalism described here may be applied to other disordered multisublattice systems for accurate and efficient material modeling.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lithium-Ion Batteries with Lithium Manganese Iron Phosphate Cathodes and Lithium Titanate Anodes: Linking Electrode Dynamics to Cell Performance

This study examines the electrochemical performance, impedance behavior, and aging mechanisms of lithium-ion cells pairing lithium manganese iron phosphate (LiMn 0.6 Fe 0.4 PO 4 , LMFP64) cathodes with lithium titanate (Li 4 Ti 5 O 12 , LTO) anodes. LMFP64 half-cells display distinct Fe and Mn redox plateaus at ∼3.5 and ∼4.1 V, respectively, and deliver excellent rate capability. Three-electrode measurements show that LMFP64 dominates cell impedance, which changes sharply across the Fe–Mn redox transition and decreases with increasing temperature (30 °C–50 °C). Voltage hysteresis arises mainly from the cathode, with higher C-rates shortening redox plateaus and broadening the transition region. Elevated temperature lowers impedance, especially near the Mn-redox and transition regions, but accelerates capacity fade. Post-cycling analyses of electrodes confirm structural stability of LMFP64 and indicate loss of lithium inventory (LLI) as the source of capacity fade. This LLI causes potential slippage between the LMFP64 and LTO electrodes, which decreases the Fe-redox plateau width. Long-term cycling highlights the critical role of electrode overhang: cathode overhang mitigates capacity fade by buffering lithium loss, whereas anode overhang cells experience faster capacity decline due to uncompensated lithium depletion. These results clarify LMFP64/LTO battery impedance evolution, thermal effects, and degradation pathways and provide insights for their applications in electric vehicles.

Area Specific Impedance↗
DOE OSTI2025

Infiltrated electrodes for metal supported solid oxide electrolysis cells

Metal-supported solid oxide cells (MSOCs) are an alternative to conventional solid oxide cells (SOCs) based on ceramic cermets, offering lower material costs and higher operational flexibility. In this study symmetric MSOCs with infiltrated electrodes are explored for steam electrolysis operation to understand the underlying operation and degradation principles and suggest a direction for future MSOCs development. Two different fuel electrode backbones are used: an electronically-conductive lanthanum strontium co-doped iron nickel titanate (LSFNT) infiltrated with cerium-gadolinium oxide (CGO), or an ionic conductive zirconia based backbone (10ScYSZ) infiltrated with Ni:CGO. At the oxygen side, the backbone is 10ScYSZ, which is infiltrated with lanthanum-strontium co-doped cobalt oxide (LSC), or praseodymium oxide as cobalt-free alternative for comparison. This study suggests that the backbone electronic conductivity is key for good electrochemical performance as well as for boosting cell durability. Highly electronically conductive nanoparticles, especially nickel, were observed to irreversibly agglomerate driven by thermal conditions, whereas CGO proved to be a very stable electrocatalyst. At the fuel side, CGO (LSFNT) electrode showed lower ASR and degradation rate than Ni:CGO(ScYSZ) configuration with measured values of 0.50 Ω cm2 and 11 %/1000 h (at 0.60 A/cm2), and 0.70 Ω cm2 and 26 %/1000 h (at 0.50 A/cm2) at 1.30 V, respectively (700 °C, 50 % steam in hydrogen at the fuel side and air at the oxygen electrode side, LSC(ScYSZ) oxygen electrode).

25 ENERGY STORAGE↗
DOE OSTI2022

Methyl Carbamate-Lithium Salt Deep Eutectic Electrolyte for Lithium-Ion Batteries

Deep eutectic electrolytes (DEEs) represent a burgeoning field in electrolytes for energy storage applications. Compared to the more conventionally studied Li-ion electrolyte systems, these electrolytes offer numerous advantages, such as high ion concentration, costs, lower temperature operation, and safety. In this work, the formation of a novel eutectic electrolyte based on lithium salts and methyl carbamate was reported. These DEEs were formed via mixing lithium salts and low-cost methyl carbamate at ratios varying from 1:2 to 1:5 (mol:mol). Here, the DEE formed from methyl carbamate and lithium hexafluorophosphate (LiPF 6 ) at a 1:5 molar ratio generated a 4V stability window and a 25°C conductivity of up to 3.16E –3 S cm –1 . The DEE formed from methyl carbamate and lithium bis(trifluoromethane)sulfonimide (LiTFSI) at a 1:5 molar ratio generated a 3.2 V stability window and a 25°C conductivity of up to 2.87E –3 S cm –1 . The LiPF 6 DEE also demonstrated a discharge capacity of 128 mAh g –1 after 50 cycles with 93% discharge capacity retention at moderate cycling rates of 0.5C in a lithium titanate (LTO)/lithium iron phosphate (LFP) full cell. These results demonstrate the potential for methyl carbamate to generate eutectics from lithium salts and offer alternative electrolytes for use in low-temperature Li-ion battery applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Role of Fe Doping on Local Structure and Electrical and Magnetic Properties of PbTiO 3

In this work, the local structure and multiferroic properties of iron-doped lead titanate (PbTi 1-x Fe x O 3-δ ) samples was investigated over the entire composition range (x = 0-1). Inherent polarization in PbTiO 3 decreases due to Fe 3+ incorporation up to the solubility limit (x similar to 0.3), although homogeneous doping persists only up to x = 0.1. Ti prefers highly distorted oxygen octahedra for any x value, while Fe prefers more symmetric O-deficient polyhedra (Fe-O n ). The charge compensating oxygen vacancies induce local tilting of the Fe-O n polyhedra beyond a critical x value (x ≥ 0.2), promoting magnetic interaction between two adjacent Fe atoms. The strain induced by local heterogeneity could act as a coupling force between magnetic and ferroelectric properties. Fe-rich clusters evolve into ferromagnetic PbFe 12 O 19 with increased Fe doping. PbTi 1-x Fe x O 3-δ (x ≥ 0.3) samples therefore have separate origins for the ferroelectric (PbTi 1-x Fe x O 3-δ ) and magnetic (PbFe 12 O 19 ) phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Revealing the role of redox reaction selectivity and mass transfer in current–voltage predictions for ensembles of photocatalysts

Photocatalysts are conceptually simple reaction units where nanoscale semiconductors integrated with catalysts drive a pair of redox reactions on illumination. However, the proximity of reaction sites performing cathodic and anodic reactions poses dire challenges to realize large light-to-fuel conversion efficiencies. In this study, a powerful, yet straightforward, equivalent-circuit detail-balance modeling framework is developed and applied to evaluate the performance of photocatalytic systems featuring multiple light absorbers. Specifically, low bandgap iridium-doped strontium titanate is modeled as a Z-scheme photocatalyst to achieve desirable hydrogen evolution and iron-based redox shuttle oxidation reactions. Our model has unique capabilities to simulate competing redox reactions and address mass-transfer limitations. In a significant departure from state-of-the-art circuit models, our study develops tools to perform load-line analyses by incorporating a net electrochemical load curve that includes both desired and competing redox reactions. Consequently, reaction selectivity is predicted from equivalent circuit models for photocatalytic and photoelectrochemical systems. Our investigation into ensembles comprised of multiple, semi-transparent light absorbers reveals their potential to outperform a single, optically thick light absorber, particularly when operated under mass-transfer-limited conditions. However, this outcome hinges on minimizing mass-transfer rates of select redox species to prevent undesired reactions of hydrogen oxidation and/or redox shuttle reduction. Our findings demonstrate that reaction selectivity can be achieved by tuning asymmetry in redox species mass-transfer even with perfectly symmetric electrocatalytic charge-transfer coefficients. The influences of various kinetic, mass-transfer, and thermodynamic parameters are explored to offer crucial insights for synthesis of the next-generation of photocatalysts and selective coatings, and reactor designs.

25 ENERGY STORAGE↗
DOE OSTI2020

GeoMelt{sup R} In-Container Vitrification (ICV){sup TM} for Fukushima Daiichi Water Treatment Secondary Wastes - 20212

The Japanese government is supporting development work implemented jointly by Veolia subsidiaries Kurion Japan, K.K., Veolia Nuclear Solutions (VNS), Inc., and Veolia Nuclear Solutions Federal Services, LLC for treating radioactive waste generated from Fukushima Daiichi Nuclear Power Station (NPS) water treatment using the GeoMelt{sup TM} In-Container Vitrification (ICV){sup TM} technology. The initial work consisted of glass formulation and engineering-scale testing which was completed in 2018, in the frame of an IRID (International Research Institute for Nuclear Decommissioning) program as part of a project subsidized by Japan's Ministry of Economy, Trade and Industry (METI). The Fukushima Daiichi NPS Mid- and Long-Term Road-map requires investigation of methods to stabilize solid wastes (and to immobilize radioisotopes in the wastes) generated as a result of emergency response and decommissioning activities. Cooling water treatment has resulted in a significant amount of solid and slurry secondary wastes (mostly adsorbents and ion-exchange materials) which will require processing at some point. GeoMelt{sup R} ICV{sup TM} is a joule-heated melter technology which uses a refractory-lined single-use container combining the melter and disposal container. There is no pouring required nor concerns with refractory corrosion which allows the process to accommodate a wide range of waste chemistries and high waste loadings. The testing described here consisted of three engineering-scale melts, each processing between 212 kg and 240 kg of waste simulants, glass formers, and non-radioactive cesium (Cs) and strontium (Sr) tracers. Continuous isokinetic stack sampling of off-gas emissions was performed for each test in order to calculate Cs and Sr retention in the glass wasteform. Single-pass retention of Cs in the final glass wasteform ranged from 91.46 to 99.30%, and single-pass retention of Sr ranged from 99.76 to 100%. Planned particulate recycle will increase these retention levels. Melt 1 processed a mixture of KUR-EH (a zeolite-based ion-exchange material), simulated Advanced Liquid Processing System (ALPS) Carbonate and Iron Slurries, and glass additives. Melt 2 processed a mixture of KUR-EH, KUR-TSG (a titanate-based adsorbent), and glass additives. Melt 3 processed a mixture of KUR-EH, simulated barium sulfate/iron ferrocyanide sludge (AREVA sludge), and glass additives. Waste loadings for these melts ranged from 70 weight percent (wt%) to 82 wt%. Vitrification produces a waste form much denser than the stored water treatment secondary waste wastes, resulting in significant volume reduction. Volume reductions for the three tests ranged from 74 to 79 vol%. Vitrification produces a chemically durable wasteform. Pacific Northwest National Laboratory (PNNL) tested three glass samples from each engineering-scale melt) by the Materials Characterization Center 1 (MCC-1) test, an international standard leach test of the chemical durability of nuclear waste glasses. PNNL also obtained one U.S. reference glass (EA Glass) and two Japan reference glasses P0798) and tested these under the same MCC-1 conditions (90 deg. C, 10 m-1, DIW, and 7, 14, 28-day) as the GeoMelt{sup R} ICV{sup TM} glasses. The GeoMelt{sup R} ICV{sup TM} glasses exhibited lower total normalized releases and 14- to 28-day normalized release rates than the three reference glasses. These results suggest that the GeoMelt{sup R} ICV{sup TM} glasses have durabilities on par with high-level waste glasses under standard test conditions. Post-melt process sampling and analysis indicated no Cs migration into the melter refractory materials and very little deposition of Cs or Sr onto the melter hood or off-gas piping internals. The results of the testing indicated good Cs retention in the glass, high volume reduction and waste loadings, and excellent chemical durability. These factors are important to minimize treatment costs and to protect workers and the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks

We use graph convolutional neural networks (GCNNs) to produce fast and accurate predictions of the total energy of solid solution binary alloys. GCNNs allow us to abstract the lattice structure of a solid material as a graph, whereby atoms are modeled as nodes and metallic bonds as edges. This representation naturally incorporates information about the structure of the material, thereby eliminating the need for computationally expensive data pre-processing which would be required with standard neural network (NN) approaches. We train GCNNs on ab-initio density functional theory (DFT) for copper-gold (CuAu) and iron-platinum (FePt) data that has been generated by running the LSMS-3 code, which implements a locally self-consistent multiple scattering method, on OLCF supercomputers Titan and Summit. GCNN outperforms the ab-initio DFT simulation by orders of magnitude in terms of computational time to produce the estimate of the total energy for a given atomic configuration of the lattice structure. We compare the predictive performance of GCNN models against a standard NN such as dense feedforward multi-layer perceptron (MLP) by using the root-mean-squared errors to quantify the predictive quality of the deep learning (DL) models. We find that the attainable accuracy of GCNNs is at least an order of magnitude better than that of the MLP.

Lupo Pasini, Massimiliano↗
DOE OSTI2021

FePt binary alloy with 32 atoms - LSMS-3 data

This dataset contains the estimate of atomic charge density, atomic magnetic moment and total energy for 32,000 configurations of the iron-platinum (FePt) binary alloy with body-centered cubic (BCC) structure. The configurations span all the compositions from 0%Fe - 100% Pt through 100%Fe - 0% Pt. The results have been produced running ab-initio density functional theory (DFT) calculations with the LSMS-3 code on OLCF supercomputer Titan. LSMS-3 GitHub repository: https://github.com/mstsuite/lsms Deep Learning research papers published with results based on this dataset: Fast and stable deep-learning predictions of material properties for solid solution alloys Massimiliano Lupo Pasini, Ying Wai Li, Junqi Yin, Jiaxin Zhang, Kipton Barros and Markus Eisenbach Published 14 December 2020 • © 2020 IOP Publishing Ltd Journal of Physics: Condensed Matter, Volume 33, Number 8 Citation Massimiliano Lupo Pasini et al 2021 J. Phys.: Condens. Matter 33 084005 https://iopscience.iop.org/article/10.1088/1361-648X/abcb10

36 MATERIALS SCIENCE↗
DOE OSTI2021

CuAu binary alloy with 32 atoms - LSMS-3 data

This dataset contains the estimate of atomic charge density, atomic magnetic moment and total energy for 32,000 configurations of the iron-platinum (CuAu) binary alloy with face-centered cubic (FCC) structure. The configurations span all the compositions from 0%Cu - 100% Au through 100%Cu - 0% Au. The results have been produced running ab-initio density functional theory (DFT) calculations with the LSMS-3 code on OLCF supercomputer Titan. LSMS-3 GitHub repository: https://github.com/mstsuite/lsms Deep Learning research papers published with results based on this dataset: Fast and stable deep-learning predictions of material properties for solid solution alloys Massimiliano Lupo Pasini, Ying Wai Li, Junqi Yin, Jiaxin Zhang, Kipton Barros and Markus Eisenbach Published 14 December 2020. 2020 IOP Publishing Ltd Journal of Physics: Condensed Matter, Volume 33, Number 8 Citation Massimiliano Lupo Pasini et al 2021 J. Phys.: Condens. Matter 33 084005 https://iopscience.iop.org/article/10.1088/1361-648X/abcb10

36 MATERIALS SCIENCE↗
DOE OSTI2024

Composite Ionogel Electrodes for Polymeric Solid-State Li-Ion Batteries

Realizing rechargeable cells with practical energy and power density requires electrodes with high active material loading, a remaining challenge for solid-state batteries. Here, we present a new strategy based on ionogel-derived solid-state electrolytes (SSEs) to form composite electrodes that enable high active material loading (>10 mg/cm 2 , ~9 mA/cm 2 at 1C) in a scalable approach for fabricating Li-ion cells. By tuning the precursor and active materials composition incorporated into the composite lithium titanate electrodes, we achieve near-theoretical capacity utilization at C/5 rates and cells capable of stable cycling at 5.85 mA/cm 2 (11.70 A/g) with over 99% average Coulombic efficiency at room temperature. Finally, we demonstrate a complete polymeric solid-state cell with a composite anode and a composite lithium iron phosphate cathode with ionogel SSEs, which is capable of stable cycling at a 1C rate.

25 ENERGY STORAGE↗