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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multi-cycle reload analysis of a long cycle gas-cooled fast modular reactor

There is currently significant interest in deploying HALEU-fueled fast reactors, including the General Atomics (GA) Fast Modular Reactor (FMR). Such reactors can achieve very long fuel cycles, but with multi-batch loading will take decades to reach equilibrium. This motivates design and analysis of both the initial core and multi-cycle reload, which is typically performed using fast-running, deterministic fast reactor codes such as the Argonne Reactor Computation (ARC) codes. In this paper, multicycle reload of the GA FMR is analyzed using the ARC codes. The GA FMR utilizes 19.75 % enriched fuel in a 16 year cycle with a three-batch strategy, with twice-burned fuel placed on the core periphery. The GA FMR has a softened neutron spectrum due to reflecting elements in the core, so the neutronic solution is first benchmarked against the OpenMC Monte Carlo code. Discrepancy on k eff is 400–600 pcm, likely due to the softened neutron spectrum, heterogeneous fuel assembly design and central reflector. However, the rms discrepancy on the assembly power distribution is only 0.6 %, despite the presence of the central reflector. A reload strategy is devised for the first three cycles of such a reactor, ultimately spanning the first 45–48 years of its operation. The fresh core uses 19.75 %, 19.25 % and 16.75 % enriched fuel in place of fresh, once-burned and twice-burned and is then subsequently refueled with only 19.75 % enriched fuel. The cycle length is varied over 3 cycles of operation to balance fuel utilization and reactor availability, specifically with use of an extended 18-year Cycle 1, followed by a shortened 11-year Cycle 2. Cycle 3 is close to the target 16-year length. Finally, placing twice burned assemblies next to the GA FMR central reflector can reduce power peaking by 3 %, at the expense of slightly reducing the cycle length.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Effect of electrode rinse solutions on the electrodialysis of concentrated salts

The data presented indicate that modest attention to the chemistry of the electrode rinse solution can yield as much as 56% improvement in process efficiency. When operating electrodialysis (ED) with salt concentrations greater than 10,000 mg/l (as NaCl) the amperage can be relatively high even at low voltages. To maximize the overall rate of ion transport from diluate to concentrate, there is a need to minimize resistances in the electrode cells since these can represent as much as 30% of the total resistances in the entire process and in this particular ED unit, represented resistance roughly equivalent to that within the membrane stack. This work describes the performance of a 10-cell pair, 200 cm 2 (0.02 m 2 ) per membrane, pilot ED unit operated in batch mode at 5 V potential. The feedstock to the stack was varied from 0.5% to 6% NaCl. Results from Volt-amp profiles (2.0–15 V) were used as the rationale for choosing the preferred electrode rinse solution, 90 g/l (kg/m 3 ) disodium sulfate at pH 12.5. The recommended solution of 30 g/l (kg/m 3 ) disodium sulfate at neutral pH was tested against stronger solutions (60, 90, and 120 g/l (kg/m 3 ) disodium sulfate) at neutral pH and with 1 g/l (kg/m 3 ) sodium hydroxide added to yield solutions at pH 12.5. There were stark differences in the performance of the ED unit between the solutions at pH 7 and those at pH 12.5. The slopes of the Volt-amp profiles improved indicating less resistance to ion flow at pH 12.5. Most of the difference can be attributed to the greater conductivity of sodium hydroxide compared to disodium sulfate, where even a modest addition of 1 g/l (kg/m 3 ) sodium hydroxide increased the conductivity of the solution between 8 and 20% depending on the concentration of disodium sulfate. Most notably, the initiation voltage was 2.39 ± 0.08 V with solutions at pH 7 and 1.99 V ± 0.04 V when the rinse solutions were around pH 12.5, a difference of around 0.42 V. Since the full batch runs were performed at 5.0 V, this 0.42 V differential represented a loss of 8% in process efficiency. A series of tests showed a shift in initiation voltage occurred between pH 11.5 and 12.5. Nernst equations for water electrolysis are coupled with a simple flux model that estimates the concentration of hydroxide and hydronium ions at the electrode surfaces. This model indicates that the potential demanded by the electrodes is directly linked to the current. Furthermore, there is a steep drop in the potential demanded by the anode when there is sufficient hydroxide available to generate oxygen from hydroxide as opposed to generation from water. The voltage demand is minimal at pH 12.5 and reflective of the reference standard voltage (just over 1.23 V predicted at 0.1 amps). However, the flux model predicts that the voltage demanded by the electrodes at pH 7 is 1.61 V at 0.1 amps (the lowest amperage measurable with the power pack). In conclusion, comparing this result to the reference standard (E 0 = -1.23 V) yields a satisfactory explanation for the observed difference below reference standard of 0.42 V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Sequential polymer infusion into solid substrates (SPISS): Impact of processing on sorbent CO 2 adsorption properties

Solid sorbents made of small amine molecules and polyamines infused into mesoporous substrates are promising materials for CO 2 capture technologies. To date, their preparation is mainly based on wet infusion with focus on increasing amine content by varying the structure of the amine sorbent and designing solid substrates of various pore parameters. Less explored in the field are changes in processing to afford efficient CO 2 sorbents. In this study, branched poly(ethylenimine) (bPEI, M w = 800 Da) alone and blends with linear poly(propylenimine) (LPPI, M n = 6,700 Da) are infused into solid SBA-15 substrates by a method that varies the solution processing called sequential polymer infusion into solid substrates (SPISS). The reference 40 % bPEI-SBA-15 samples are split by two methods: split batch in dry suspension (SBD) and split batch in liquid suspension (SBL). Sequentially, alcoholic 10% of bPEI (non-blends) and 10% of LPPI (blends) solutions are introduced to afford the desired products. Under dry conditions, the resulting 50% bPEI-SBA-15 SBD & SBL sorbents display high CO 2 capacities up to 3.47 mmol CO 2 /g SiO 2 for simulated flue gas (10% CO 2 ) and 2.62 mmol CO 2 /g SiO 2 for direct air capture (DAC, 400 ppm CO 2 ). Under humid DAC conditions the CO 2 performance is further enhanced with an uptake of 4.62 mmol CO 2 /gSiO 2 and amine efficiency of 0.22 mmol CO 2 /mmol N. Subjected to extended temperature swing adsorption kinetic cycling (20 cycles), the SPISS samples display stable working capacities and retain over 70% (blends) and over 90% (non-blends) of their initial 12 h adsorption performance. LPPI is demonstrated to be an effective water sorption limiting agent using dynamic vapor sorption measurements. Solid state NMR techniques reveal important insights into the dynamics of the amine polymers confined into SBA-15 pores, as impacted by processing conditions. The results suggest that the conformation of the polymers is different depending on the processing method, displaying relatively tight (SBD) and loose (SBL) packing. Finally, the simple solution processing approaches presented here show that processing variations may guide the design of solid amine sorbents with desirable properties relevant for integration into CO 2 capture technologies.

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

Fractal analysis on Ag 2 O thin film using a data-driven approach

The synthesis of fractal Ag oxide (Ag 2 O) on the surface of Ag thin film has been achieved at room temperature by using Synchrotron X-ray irradiation. We have performed an automated quantitative analysis of a batch of 1879 fractal Ag 2 O patterns in a scanning electron microscopy (SEM) image within a radius of 2000 mm outward from the center of the X-ray beam. The morphology is similar to that of the diffusion-limited cluster aggregation (DLCA) model. The fractal dimension (D) of Ag 2 O is between 1.7 and 1.5 from the center to the edge. The area distribution density of fractal Ag 2 O follows a quadratic function with radius R. It is found that the branches’ number of fractal Ag 2 O is a key factor affecting the fractal dimension. The more branches the fractal has, the greater the D is. This is the first time that Ag fractal has been investigated by combining automated data analysis methods with batch experimental data. This data-driven approach provides a new research perspective for rationally regulating materials’ fractal morphology and performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electro-assisted regeneration of pH-sensitive ion exchangers for sustainable phosphate removal and recovery

Removal and recovery of phosphate from wastewater can minimize deleterious environmental impacts and supplement fertilizer supply. Hybrid anion exchangers (HAIX, with doped ferric oxide nanoparticles (FeOnp)) can remove phosphate from complex wastewaters and recover concentrated phosphate solutions. Here, we integrate HAIX with a weak acid cation exchanger (WAC) to enrich phosphate and calcium in mild regenerants and precipitate both elements for recovery. We demonstrated an electro-assisted regeneration approach to avoid strong acid and base input. Based on demonstrated pH sensitivities of both materials, electrochemically produced mild electrolytes (pH 3 and pH 11), which are 100–1000 times less concentrated than typical regenerants, preserved 80% WAC and 50% HAIX capacities over five batch adsorption-regeneration cycles. FeOnp in HAIX facilitated regeneration due to pH sensitivity and their likely distribution on the resin particle surface, which reduced intraparticle diffusion path length. In column tests, repeatable phosphate removal (> 95%) from synthetic wastewater (3 mg P/L) was achieved with 20 kWh/kg P specific energy consumption. After removal, a similar 50% HAIX regeneration efficiency as batch experiments was achieved. In spent regenerant, more than 95% phosphorus was recovered as hydroxyapatite. This novel approach enhances ion exchange by minimizing chemical inputs.

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

Autonomous online optimization of a closed-circuit reverse osmosis system

As freshwater becomes increasingly scarce, many industrial and municipal water utilities look at premise-scale water treatment and reuse to meet water demand. Closed-circuit reverse osmosis (CCRO) has been proposed as a promising process design to do so. This sequencing batch process enables operation at higher brine salinity levels by means of a recycle flow. Optimal operation requires that the maximum salinity level at the membrane surface represents an optimal trade-off between brine disposal costs and energy efficiency. This maximum salinity level may change over time as the feed water composition changes and electricity markets fluctuate. In this article, we present the results of the experimental evaluation of an automatic technique for continuous online optimization, known as extremum seeking control. This technique has a long history in the process control community but has received little traction so far in the water industry. We modify this technique to enable its use for online optimization of CCRO, specifically to account for its sequential batch operation. We challenge the optimization schemes through several experimental tests and illustrate the advantages and drawbacks of extremum-seeking control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Scale-Up Studies for the Dehydration of C 4+ Alcohols into Drop-In Diesel Fuel

Herein, we demonstrate the production of liter quantities of drop-in diesel-range ethers from biomass-derived alcohols. We report scale-up resultsfor the dehydration of a mixture of C 4+ alcohols using powder and pellet zeolite Ycatalyst in continuous flow and batch reactors. The activity of zeolite Y decreaseswith the introduction of an alumina binder. Large alcohols, as well as branchedand secondary alcohols, increase the coke content over the pellet Y catalyst. Thepellet formulation had lower carbon balances and selectivity to C 10+ ethers,suggesting that the pellet formulation increases alcohol absorption and cokeproduction. Crushing the pellet Y catalyst to smaller particle sizes does notrecover the activity of zeolite Y in its powder form. Cold flow experiments showthat particle agglomeration contributes to pressure buildup in the continuous flowreactor. C 10+ ether blends can be produced in batch reactors at high alcohol conversion regimes. One liter of a diesel #2 blend wasproduced by scaling up this reaction. The final blend consists of a substantial portion of C 10+ ethers (63.7 wt %), followed by heavyunknown products (27.4 wt %). Furthermore, the final alcohol and butyl ether concentration values were 7.3 and 1.5 wt %, respectively. Theblendstock reported in this paper can satisfy diesel #2 ASTM standards for density, cloud point, flashpoint, and cetane number.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Microwave Heating-Induced Temperature Gradients in Liquid–Liquid Biphasic Systems

Microwaves (MWs) can enable the electrification and intensification of chemical manufacturing. They have been applied to various unit separations, such as drying, distillation, and extraction, entailing gas–liquid and solid–liquid systems. However, a limited quantitative understanding of MW-heated liquid–liquid biphasic systems related to extraction exists. This work measures the temporal and spatial temperature difference between an aqueous and an organic phase in batch and continuous microfluidic modes. We demonstrate permanent temperature differences between phases over 35 °C and spatiotemporal periodic and quasiperiodic oscillations modulated by the flow patterns. The temperature differences are primarily driven by the faster absorption rate of MW irradiation by the aqueous phase versus the slower heat transfer from the aqueous phase to the organic phase. These are amplified by low specific interfacial area and modifications of the electromagnetic field. We employ a multiphysics model to predict the temperature difference in a batch system. The model is in good agreement with the experiments. We demonstrate a strong effect of input power, dielectric properties of organic solvents, the volume of solvents, and the volume ratio between phases on the temperature difference. A simple analytical model describes the temperature difference and provides design principles. Furthermore, the combined approach offers new insights into the design and optimization of the MW-heated biphasic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Iodine Removal from Carbonate-Containing Alkaline Liquids Using Strong Base Resins, Hybrid Resins, and Silver Precipitation

The ability of several material types to remove aqueous iodine from a mildly alkaline, carbonate-rich nuclear waste stream was evaluated: strong base anion exchange resins (SBAR), hybrid resins, Ag-containing materials and Bi-containing hybrid resins. A combination of batch testing and flow through column testing were used in the evaluation. In batch testing, hybrid resins CHM-20, SIR-110-CE and RTBI were shown to have high efficiency for the removal of both iodide and iodate simultaneously, while Ag-containing materials and SBAR demonstrated high capacity for iodide removal. One example of each material type (CHM-20, A532E and Ionex 400) were further evaluated for their sorption isotherms and column performance. The Langmuir isotherm, or a Langmuir-Freundlich hybrid isotherm, best described the sorption of iodide to the CHM-20 hybrid resin and Purolite A532E. The Freundlich isotherm best described the uptake of iodate to CHM-20 and A532E and for both iodide and iodate to the Ag-containing Ionex-400. In column testing the Purolite A532E had exceptional performance for overall iodide removal. With the capacity demonstrated the A532E resin would exceed Class C waste classification before breakthrough initiated, and column change outs in processing would be dictated by eventual waste classification, not breakthrough. The Ionex 400, a Ag-zeolite, was observed to degrade over time in the column in the mild alkaline conditions whereas the hybrid CHM-20 was limited in the single pass through design and would be best suited for applications where iodide and iodate are present and recirculation of the column effluent is feasible. Here this work highlights the feasibility of commercially available materials to separate radioiodine from liquid environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Microwave-Assisted Plastic Upcycling: Dynamic Data Reconciliation, Parameter Estimation, and Kinetic Modeling

Microwave (MW)-assisted catalytic pyrolysis offers a promising pathway for efficient plastic upcycling. This work develops an integrated modeling framework combining dynamic data reconciliation, a temperature-dependent rate model, and a yield model to represent the time-varying production rate of components in MW-assisted LDPE pyrolysis conducted in a batch reactor. An Arrhenius-type rate model with a temperature-dependent reaction order is developed. A biexponential correlation is proposed for the yield of gaseous products that enables to capture the evolving product formation behavior during conversion. In the yield correlation, one term is used to represent the initial increase in yield, reflecting the rapid formation of intermediate or primary products at the early stages of the reaction when a larger fraction of the reactant remains available. As conversion progresses, the influence of this term gradually diminishes. The other term accounts for the subsequent decrease in the predicted yield, representing secondary reactions such as further cracking or coke formation that reduce the concentration of certain products at higher conversion. The model is found to accurately represent reconciled experimental flow rate profiles from an in-house MW-assisted catalytic batch reactor for major products, including ethylene, ethane, 1-butene, and benzene, across 250−350 °C. Ethylene remains the dominant product but decreases from about 41.95% at 250 °C to 30.14% at 350 °C, while heavier products increase significantly, with 1-butene rising to nearly 8.37% and benzene reaching 2.17% at intermediate temperatures. The model shows that the ethylene production rate can be maximized at around 270 °C. The models developed in this work can be utilized for process optimization, reactor design and scale-up of microwave-assisted plastic conversion technologies, and economic analysis.

Damahe, Harish [West Virginia Univ., Morgantown, W↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

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

Efficient Parameterization of Density Functional Tight-Binding for 5 f -Elements: A Th–O Case Study

Density functional tight binding (DFTB) models for f-element species are challenging to parametrize owing to the large number of adjustable parameters. The explicit optimization of the terms entering the semiempirical DFTB Hamiltonian related to f orbitals is crucial to generating a reliable parametrization for f-block elements, because they play import roles in bonding interactions. However, since the number of parameters grows quadratically with the number of orbitals, the computational cost for parameter optimization is much more expensive for the f-elements than for the main group elements. In this work we present a set of efficient approaches for mitigating the hurdle imposed by the large size of the parameter space. A novel group-by-orbital correction functions for two-center bond integrals was developed. With this approach the number of parameters is reduced, and it grows linearly with the number of elements, maintaining the accuracy and the number of parameters, in the case of f elements, by more than 40%. The parameter optimization step was accelerated by means of the mini-batch BFGS method. This method allows parameter optimizations with much larger training sets than other single batch methods. A stochastic optimizer was employed that helped overcome shallow local minima in the objective function. The proposed algorithm was used to parametrize the DFTB Hamiltonian for the Th–O system, which was subsequently applied to the study of ThO 2 nanoparticles. The training set consisted of 6322 unique structures, which is barely feasible with conventional optimization methods. The optimized parameter set, LANL-ThO, displays good agreement with DFT-calculated properties such as energies, forces, and structures for both clusters and bulk ThO 2 . Benefiting from the fewer number of parameters and lower computational costs for objective function evaluations, this new approach shows its potential applications in DFTB parametrization for elements with high angular momentum, which present a challenge to conventional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

High-Performance Semiempirical Excited-State Molecular Dynamics Powered by Graphics Processing Units

Here, this Letter introduces excited-state molecular dynamics in PYSEQM, a GPU-accelerated semiempirical quantum chemistry engine implemented in PyTorch. The new module enables Born–Oppenheimer molecular dynamics (BOMD) using configuration-interaction singles and random phase approximation for excited states, allowing long trajectories and large statistical ensembles to be simulated efficiently on a single GPU. We also implement an extended Lagrangian excited-state BOMD (XL-ESMD) scheme that propagates auxiliary electronic variables, enabling relaxed ground and excited-state convergence thresholds without compromising energy conservation. The excited-state BOMD implementation scales smoothly from small chromophores to a nearly 900-atom dendrimer (taking 6.5 s per MD step). PYSEQM also supports batched execution, allowing many geometries or trajectories to be evaluated in a single GPU launch, substantially increasing throughput and making ensemble-based protocols routine. As a demonstration, we compute absorption, emission, and infrared spectra from trajectories propagated on the ground and first excited states. The XL-ESMD scheme yields identical spectra at significantly lower computational cost, establishing the role of extended Lagrangian based dynamics for efficient excited-state BOMD simulations. Beyond raw performance, PYSEQM’s PyTorch foundation provides automatic differentiation for forces, efficient GPU batching, and seamless interfacing with machine learning models. These capabilities position PYSEQM as a practical platform for machine learning-augmented excited-state dynamics and lay the foundation for future data-driven nonadiabatic excited-state dynamics modeling of ultrafast spectroscopic probes.

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

Quantitative Encapsulation and Homogeneity Assessment of Sol–Gel Based Nuclear Explosive Debris Simulants

Nuclear explosive debris simulants are an important material in training and validating aspects of post-detonation nuclear forensic processes. Realistic simulants should replicate several aspects of nuclear explosive debris such as the size, shape, color, density, and chemical and radiological properties. Silica particles produced via sol-gel synthesis have recently been found to successfully reproduce many of these parameters including the controllable incorporation of radionuclide content. However, to be useful as a benchmarking material for validation and verification of laboratory methodologies, radionuclide content from batch-to-batch must be reproducible. Here, in this work, we explore the variance in radionuclide distribution incorporated into sol-gel benchmarking materials with respect to sample subdivision. Results will help inform the sample sizes required to minimize variance between samples.

36 - MATERIALS SCIENCE↗
DOE OSTI2020

Hybrid Sorbents for 129 I Capture from Contaminated Groundwater

Radioiodine ( 129 I) poses a risk to the environment due to its long half-life, toxicity, and mobility. It is found at the U.S. Department of Energy Hanford Site due to legacy releases of nuclear wastes to the subsurface where 129 I is predominantly present as iodate (IO 3 – ). To date, a cost-effective and scalable cleanup technology for 129 I has not been identified, with hydraulic containment implemented as the remedial approach. Here, novel high-performing sorbents for 129 I remediation with the capacity to reduce 129 I concentrations to or below the US Environmental Protection Agency (EPA) drinking water standard and procedures to deploy them in an ex-situ pump and treat (P&T) system are introduced. Furthermore, this includes implementation of hybridized polyacrylonitrile (PAN) beads for ex-situ remediation of IO 3 – -contaminated groundwater for the first time. Iron (Fe) oxyhydroxide and bismuth (Bi) oxyhydroxide sorbents were deployed on silica substrates or encapsulated in porous PAN beads. In addition, Fe–, cerium (Ce)–, and Bi–oxyhydroxides were encapsulated with anion-exchange resins. The PAN–bismuth oxyhydroxide and PAN–ferrihydrite composites along with Fe- and Ce-based hybrid anion-exchange resins performed well in batch sorption experiments with distribution coefficients for IO 3 – of >1000 mL/g and rapid removal kinetics. Of the tested materials, the Ce-based hybrid anion-exchange resin was the most efficient for removal of IO 3 – from Hanford groundwater in a column system, with 50% breakthrough occurring at 324 pore volumes. The functional amine groups on the parent resin and amount of active sorbent in the resin can be customized to improve the iodine loading capacity. These results highlight the potential for IO 3 – remediation by hybrid sorbents and represent a benchmark for the implementation of commercially available materials to meet EPA standards for cleanup of 129 I in a large-scale P&T system.

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

Exploiting Saturation Regimes and Surface Effects to Tune Composite Design: Single Platelet Nanocomposites of Peptoid Nanosheets and CaCO 3

Mineral-polymer composites found in nature exhibit exceptional structural properties essential to their function, and transferring these attributes to the synthetic design of functional materials holds promise across various sectors. Biomimetic fabrication of nanocomposites introduces new pathways for advanced material design and explores biomineralization strategies. This study presents a novel approach for producing single platelet nanocomposites composed of CaCO 3 and biomimetic peptoid (N-substituted glycines) polymers, akin to the bricks found in the brick-and-mortar structure of nacre, the inner layer of certain mollusc shells. The significant aspect of the proposed strategy is the use of organic peptoid nanosheets as the scaffolds for brick formation, along with their controlled mineralization in solution. Here, we employ the B28 peptoid nanosheet as a scaffold, which readily forms free-floating zwitterionic bilayers in aqueous solution. The peptoid nanosheets were mineralized under consistent initial conditions (σ calcite = 1.2, pH 9.00), with variations in mixing conditions and supersaturation profiles over time aimed at controlling the final product. Nanosheets were mineralized in both feedback control experiments, where supersaturation was continuously replenished by titrant addition and in batch experiments without a feedback loop. Complete coverage of the nanosheet surface by amorphous calcium carbonate was achieved under specific conditions with feedback control mineralization, whereas vaterite was the primary CaCO 3 phase observed after batch experiments. Thermodynamic calculations suggest that time-dependent supersaturation profiles as well as the spatial distribution of supersaturation are effective controls for tuning the mineralization extent and product. We anticipate that the control strategies outlined in this work can serve as a foundation for the advanced and scalable fabrication of nanocomposites as building blocks for nacre-mimetic and functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Polystyrene-block-Polydimethylsiloxane as a Potential Silica Substitute for Polysiloxane Reinforcement

We report here on microphase-separated poly(styrene-block-dimethylsiloxane) (PS-b-PDMS) as a reinforcing filler in PDMS thermosets that overcomes the long-standing problem of aging in the processing of silica-reinforced silicone. Surprisingly, PS-b-PDMS reinforced composites display comparable mechanical performance to silica-modified analogs, even though the modulus of PS is much smaller than that of silica and there is no evidence of percolation with respect to the rigid PS domains. We have found that a few unique characteristics contribute to the reinforcing performance of PS-b-PDMS. The strong self-assembly behavior promotes batch-to-batch repeatability by having well-dispersed fillers. The structure and size of the fillers depend on the loading and characteristics of both filler and matrix, along with the shear effect. The reinforcing effect of PS-b-PDMS is mostly brought by the entanglements between the corona layer of the filler and the matrix, rather than the hydrodynamic reinforcement of the PS phase.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Lignin Extraction and Condensation as a Function of Temperature, Residence Time, and Solvent System in Flow-through Reactors

Solvolytic extraction of lignin from biomass is a critical step in lignin-first biorefining, including the reductive catalytic fractionation (RCF) process. Key to optimal RCF processing is the ability to rapidly extract lignin from biomass at high delignification extents and transfer the lignin molecules to a catalyst surface in a time frame that minimizes lignin condensation reactions. Here, we use a flow-through reactor to study the effects of temperature (175-250 °C), residence time (9 to 36 min), and solvent composition (methanol and methanol-water) on lignin extraction and condensation. We evaluated three metrics at each condition: total delignification, delignification rate, and extent of condensation, the latter measured by a decrease in monomer yield for batch hydrogenolysis reactions of solvolysis liquor compared to batch RCF reactions. We observe that delignification is predominantly determined by temperature, while residence time dictates the lignin condensation extent. Moreover, the extent of both extraction and condensation increased in the methanol-water solvent system compared to that in the methanol system. Lignin extracted in methanol is stable up to 18-min residence times at or below 225 °C, while a majority of the lignin extracted in methanol-water is condensed with a 9-min residence time at 200 °C. These results can inform reactor designs and solvent selection for lignin-first biorefining processes that aim to physically separate the biomass and catalyst.

09 BIOMASS FUELS↗