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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Removable coatings: Thermal stability and decontamination of steel surfaces from 241 Am

This study presents a comparative analysis of several strippable materials for decontamination of steel surfaces from 241 Am. The strippable coatings were chosen to have a history of application, to be commercially available, easily handled and have different composition and formulation. Carbon steel and stainless steel surfaces (coupons) were utilized as the most representative industrial materials, and the experimental series were expanded to include the rusting treatment of these surfaces as it is common for decommissioned old nuclear facilities. The experiments followed the path of pre-screening of the strippable materials (easiness of application, peeling etc.), their characterization with Fourier-transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA), decontamination factors (DF) or removal efficiencies for different types of steel surfaces, and enhancement of the removal efficiencies of the select strippable coatings via amendment with EDTA. As a result, DF and removal efficiencies for stainless steel (both pristine and with rusting treatment) are higher than for pristine carbon steel, and decontamination factors and removal efficiencies are higher for pristine than for rusted carbon steel across all the coatings. It is also shown that EDTA amendment can improve DF and removal efficiency for a strippable coating (i.e., CC Strip), however other factors should also be considered. Thus, the coating CC Strip exhibited easiness in handling and high DF (up to 97% when EDTA-amended), but its drying period was the longest among the rest of the materials and its thermal decomposition indicates on a risk of intense release of heat in case of a fire event.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗
DOE OSTI2023

Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems

We consider a high-dimensional nonlinear computational model of a dynamical system, parameterized by a vector-valued control parameter, in the presence of uncertainties represented by an uncontrolled parameter modeled by a vector-valued random variable, and possibly with stochastic excitation. The objective is to construct a statistical surrogate model where the input is any deterministic value of the control parameter, and the output is a vector-valued observation of the computational model, which is a random vector whose probability measure is updated using a target dataset. To construct this statistical surrogate model, the stochastic response of the computational model must be built, which is a vector-valued time-discretized stochastic process in high dimension, depending on the control parameter. It is assumed that the computational cost of a single evaluation of the deterministic model is high. For the probabilistic updating, we consider a subset of the components of the observation of the computational model, defined as the “identification observation” of the computational model, for which a small target dataset is available. Therefore, the target dataset is associated with partial observability, corresponding to an incomplete data case. Given a prior probability model of the random control and uncontrolled parameters, a training dataset is constructed, consisting of realizations of the random triplet composed of the stochastic response, the random identification observation, and the random control parameter. Since the computational cost of a single evaluation of the deterministic model is assumed to be large, the training dataset is also of small size. The main challenges in this problem are the high dimensionality, partial observability leading to incomplete data in the target dataset for the identification observation of the computational model (which is not sufficient to identify the computational stochastic responses), and the availability of a small training dataset. To address these challenges, we propose a methodology based on statistical methods for constructing necessary reduced representations, direct probabilistic learning under constraints using probabilistic learning on manifolds (PLoM) constrained by the target dataset, and the use of a weak formulation of the Fourier transform of probability measures. Statistical conditioning is also employed to explore the learned dataset. The constructed predictive statistical surrogate model can be implemented in the context of online computation. Here, we apply this approach to a problem of nonlinear stochastic dynamics in high dimensions within the framework of deformable solids mechanics.

Engineering↗
DOE OSTI2024

Effect of non-uniform void distributions on the yielding of metals

High-throughput (several thousand) calculations have been carried out to investigate the yield behavior of porous materials with randomly distributed pores, porosity levels over four orders of magnitude and up to a hundred pores per simulation box. To this end, a Galerkin based fast Fourier transform (FFT) formulation was enhanced to deal with high phase contrast materials. In addition, GPU parallelization was employed in solving the governing equation for strain fluctuations using a Krylov iterative solver. Emphasis is laid on the conditions under which percolation of plastically non-deforming zones through the porous network emerge, a regime termed unhomogeneous yielding. By way of contrast, the regime where the plastic strain fluctuations (associated with the heterogeneous void-matrix aggregate) fall below the percolation threshold is defined as homogeneous yielding. Here, we find that nonuniform pore distributions only affect unhomogeneous yielding and have a universal softening effect. The extent of this distribution softening is analyzed as a function of porosity, cell size and number of realizations. Whether the uncovered universal distribution softening has direct implications on failure resistance of porous materials is discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗
DOE OSTI2024

Effect of plasma treatment on LMPAEK/CF tape and composites manufactured by automated tape placement (ATP)

Automated tape placement (ATP) process is widely used in aerospace for its advanced process control and multi-axis capabilities but faces issues like limited choice of materials and suboptimal tape consolidation. This study investigates air plasma treatment on ATP carbon fiber thermoplastic feedstock tape to address these challenges. The effects on low melt Polyaryletherketone/carbon fiber unidirectional tape (LMPAEK/CF UD tape) were analyzed. Treated and untreated tapes were used to fabricate composites and evaluated for physical, thermal, mechanical, and interfacial properties. Atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) analyses revealed surface roughness changes (on LMPAEK), extent of oxidation, and the presence of hydroxyl/carboxyl groups. Composites from plasma-treated tapes showed a 7.6% increase in tensile strength, 8% in tensile modulus, 18% in flexural strength, and 8.3% in flexural modulus. Further, the interlaminar shear strength improved by 18.7%. Failure analysis showed untreated composites failed via inter-ply and fiber-matrix delamination, while treated composites experienced matrix cracking and fiber breakage. This study highlights atmospheric plasma treatment as a solution to ATP’s limitations, significantly enhancing LMPAEK/CF UD tape composites’ properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Influence of plasticizers on thermal and mechanical properties of biocomposite filaments made from lignin and polylactic acid for 3D printing

Polylactic acid (PLA) and organosolv lignin were mixed at different ratios and extruded to obtain PLA-lignin composite filaments. PLA was replaced with lignin up to 20 wt%. Two plasticizers (polyethylene glycol (PEG) 2000 and struktol TR451) were added in varying concentrations to enhance the properties of PLA_L20 (20% lignin in PLA) composite filaments. Furthermore, the effect of lignin in PLA, and PEG, and struktol in PLA_L20 composites was investigated via tensile test, differential scanning calorimetry, thermogravimetric analysis, scanning electron microscopy, Fourier transform infrared spectroscopy of the filaments, and dynamic mechanical analysis of 3D printed samples. A 2 wt% PEG was able to enhance both tensile stress and elongation at maximum load of PLA_L20 composite by 19% and 35%, respectively, whereas struktol TR451 was able to improve elongation at maximum load by 24%.

3D printing↗
DOE OSTI2024

QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Understanding the p-doping of spiroOMeTAD by tris(pentafluorophenyl)borane

The solid-state organization of photoabsorber, hole and electron transporting layers, and interfaces between them plays an important role in governing the performance and stability of emerging optoelectronic devices such as perovskite solar cells (PSCs). The molecular organic semiconductor (OSC) 2,2' ,7,7' -tetrakis [N,N-di(4-methoxyphenyl)amino]-9,9'-spirobifluorene (spiroOMeTAD) is a promising hole-transporting material (HTM) for PSCs, which is p-doped by molecular dopants to augment the charge carrier mobility. Here, the p-type doping of spiroOMeTAD by tris(pentafluorophenyl)borane (BCF) is investigated by a combination of techniques including optical spectroscopy, X-ray diffraction, Fourier transform infrared (FTIR), solid-state (ss)NMR, and electron paramagnetic resonance (EPR) spectroscopy. BCF molecules interact with traces of water molecules to form BCF-water complexes. Optical spectroscopy analysis suggests that the BCF/BCF-water complexes oxidize spiroOMeTAD molecules and facilitate p-type doping of spiroOMeTAD molecules. The different distributions of BCF and BCF-water molecules in doped spiroOMeTAD are characterized by FTIR and 11B NMR spectroscopy. An NMR crystallography approach which combines two-dimensional (2D) ssNMR and crystallography modeling is employed to unravel the packing interactions in spiroOMeTAD, and this analysis is extended to probe the morphological and structural changes in spiroOMeTAD:BCF blends. The hyperfine interactions are characterized by 2D hyperfine sub-level correlation (HYSCORE) spectroscopy. In this way, insight into the complex spiroOMeTAD:BCF blend morphology is obtained and compared for different dopant concentrations. Further, molecular-level analysis of doped HTMs enabled by this study has much wider relevance for further investigation, for example, chemical design and interfacial engineering of p-type doped HTMs for stable and efficient hybrid perovskite photovoltaics.

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

Characterizing Hazardous Gases from NMC811 Materials and Coin Cells with TGA and Tube-Furnace FTIR-MS Evolved-Gas-Analysis

Abuse testing is useful for informing the risks of different battery chemistries but has been limited to larger formats. This paper conducted thermal abuse tests at the smaller coin cell level to determine its relevance in specifying vent gas flammability and toxicity. A nitrogen purge carried the evolved gases into a parallel Fourier-transform infrared spectrometer (FTIR) and a mass spectrometer (MS) downstream of the tube furnace. The experimental system was validated by comparing evolved gas data for single components between the tube furnace system and a thermogravimetric analysis (TGA) instrument. Multiple samples were tested during validation, including CaCO3, electrolyte, delithiated NMC 811 cathode, and lithiated graphite anode. Temperature-resolved gas evolution of HF, CO2, CO, H2, and hydrocarbons from isolated components helped to characterize the emission sources. A previously unreported H2 generation mechanism was found. It was shown that the reduced NMC cathode acts as a catalyst to crack polypropylene-decomposed hydrocarbons into H2 at around 450 degrees C. It was also shown, while studying LiPF6 thermal decomposition, that using the tube furnace with a coin cell casing as the sample holder has some advantages for evolved-gas analysis of environmentally sensitive samples relative to testing in TGA instruments. After validation with single components, a fully charged NMC 811 coin cell was failed in the tube furnace. The measured evolved gases were found to be a combination of the species measured from the single component tests. H2 formation related to the reduced cathode was found to have greater abundance than H2 formed from the anode. Hydrogen fluoride emission factors and diethyl carbonate conversion emission factors assist in understanding the gaseous hazards for larger format cells.

25 ENERGY STORAGE↗
DOE OSTI2025

Soil porous microstructure control over soil organic matter mobility: A multimethod workflow for understanding chemistry-dependent organic matter binding in soil

Soil organic matter (SOM) has attracted a great deal of interest; particularly for its potential to mitigate human derived CO 2 emissions. Studies have demonstrated that SOM plays a critical role in carbon storage and CO 2 sequestration. However, the sorption properties of SOM, which influence its transport in pore water and stabilization within the soil, remain poorly understood. This study develops a workflow to: (1) examine compound-specific advective and diffusive transport and desorption behaviors, (2) quantify desorption rates through stop-flow and continuous-flow column experiments, and (3) evaluate the impact of soil microporosity on SOM mobility using high-resolution imaging and extractions. Intact core column experiments were conducted on Uncultivated (Natural) and Cultivated soil samples, both were arid soils, collected in Washington State. X-ray computed tomography was employed to measure porosity and pore connectivity, while Fourier-transform ion cyclotron resonance mass spectrometry was used to analyze SOM composition. The findings revealed that cultivation increased total carbon and nitrogen levels due to irrigation and fertilization, enhancing carbon capture potential in arid soils. In contrast, the Natural soil, characterized by higher porosity and connectivity, contained more oxidized carbon. Pore network analysis indicated that soil compaction in the Cultivated soil may lead to longer diffusion pathways, significantly influencing SOM transport and stability.

Hydraulic Properties↗
DOE OSTI2021

Heat accelerates degradation of β -lactoglobulin fibrils at neutral pH

Fibrous aggregates of β-lactoglobulin display superior mechanical and interfacial properties compared to the native protein. These properties directly link to the protein morphology and structure. When incorporated into food matrices, during processing protein fibrils are exposed to pH shifts and high temperature conditions, which accelerate their degradation. In the present study, neutralized β-lactoglobulin fibrils were heated at 100 °C and 121 °C for various times to assess their degradation. Fibril morphology, structure, and viscosity in solution were examined by microscopy, scattering, spectroscopy, and rheology. Atomic force microscopy showed the contour length of the protein fibrils decreased gradually with heating at 100 °C and 121 °C, with greater decreases at 121 °C. Increased fibril diameters (~15–25 nm) were observed at 121 °C for 5–15 min heating and were disrupted upon further heating. Small-angle x-ray scattering indicated an increase in fibril radius with heating at pH 7 followed by a decrease at prolonged heating, whereas fibril length decreased continuously with heating. Thioflavin T fluorescence, circular dichroism and Fourier transform infrared spectroscopy confirmed the conversion of β-sheet to random coils as fibrils were degraded during thermal treatment at pH 7. Surface hydrophobicity of fibrils decreased with increase in heating temperature and time, coinciding with an increase in the content of non-aggregated proteins. Viscosity of fibril solutions increased when fibrils were heated at 100 °C, whereas at 121 °C their viscosity first increased and then decreased. Furthermore, these findings imply heating at 100 °C and 121 °C facilitates degradation and depolymerisation of β-lactoglobulin fibrils with aggregation as an intermediate step.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Experimental and theoretical analysis of carbon driven detonation waves in a heterogeneously premixed Rotating Detonation Engine

Coal dust explosions can be hazardous; however, they can also generate a significant rise in stagnation pressure if adequately harnessed. Rotating detonation combustors seek to take advantage of the stagnation pressure rise phenomenon in a more sustained and controlled manner via confinement to a physical annulus, leading to increased overall thermodynamic efficiency. Here this investigation presents an analysis of detonations fueled by Carbon Black, a solid particulate consisting of virtually pure carbon molecules and lean Hydrogen-Air mixtures. It is realized that with the addition of Carbon Black, an increase of lean mixture detonability and detonation velocities extending the operating limit over that of a pure hydrogen-air mixture is experienced. For all testing conditions, the total equivalence ratio is held at φ = 1, while the fuel mixture's carbon mass fraction is increased from 0 to 0.7 while the hydrogen is decreased. Detonation wave velocities are extracted from high-speed imaging through applying a Discrete Fourier Transform algorithm to determine changes to the wave speed as Carbon Black particles are introduced. As a result, due to the addition of Carbon Black as an auxiliary fuel source, detonations were formed instead of deflagrations in operating conditions where one would expect deflagrations at the same hydrogen-air equivalence ratios without Carbon Black addition. The detonation formation provides evidence that the coal particles are reacting within the detonation wave in a large enough capacity to support a detonation wave within the annulus. Furthermore, the wave speed is shown to increase with the additional of carbon particles. At a constant global equivalence ratio, the detonation wave velocities were found to decrease with hydrogen's incremental replacement with coal particles. Whereby, through a theoretical comparison of the heat of combustion as computed from the experimentally derived detonation wave velocities, a linear relationship of the two was shown to exist. Therefore, the heat of combustion has the potential to describe an operational limit to sustaining a detonation wave.

42 ENGINEERING↗
DOE OSTI2022

Demonstration of low-level biogenic fuel content using quench curve and direct liquid scintillation counting (LSC) methods

In this work, an investigation into the direct method for liquid scintillation counting (LSC) quantification of biogenic fuel content in fuel blendstock is presented. This method development intentionally used a colored matrix (~99 wt%), fossil diesel fraction, and low-level biogenic fractions (~1 wt%) to determine the applicability of the LSC technique in colored blend mixtures. LSC procedures for quench correction, including the use of an instrument internal standard (Quantulus SQP values), color quench curves, and an internal 14 C standard spike on samples containing low-level amounts of biogenic gasoline, jet, and diesel mixed with fossil fuel, were compared. Samples were analyzed on both Perkin-Elmer Quantulus and Tri-Carb instruments, and the 14 C contents were compared with those determined by accelerator mass spectrometry (AMS). Results from the Tri-Carb instrument showed that percent differences of <10 % compared to AMS-reported values are achievable at 5-hour count times despite colored samples. A comparison between the impact of chemical and color quenching in the fuel samples showed that color quenching in highly colored samples reduces efficiency significantly more than chemical quenching, indicating that chemical quench curves are not appropriate for highly colored biofuel/fossil-fuel blended samples. Results indicate that both the direct method with internal spike quench correction and the use of a color-quench curve provide accurate results for 1 % biogenic fuel blends. Additionally, we have explored the use of Fourier transform infrared (FTIR) spectroscopy in measuring the biogenic content of the colored blended fuel samples. Preliminary results show the presence of biogenic carbon-derived fingerprints that are absent in fossil-derived sample. However, further work is needed to develop an FTIR-based quantitative method.

09 BIOMASS FUELS↗
DOE OSTI2023

Position-specific carbon isotopes of Murchison amino acids elucidate extraterrestrial abiotic organic synthesis networks

The Murchison meteorite is a well-studied carbonaceous chondrite with relatively high concentrations of amino acids thought to be endogenous to the meteorite, in part because they are characterized by carbon isotope (δ 13 C) values higher than those typical of terrestrial amino acids. Past studies have proposed that extraterrestrial amino acids in the Murchison meteorite could have formed by Strecker synthesis (for α-amino acids), Michael addition (for β-amino acids), or reductive amination, but a lack of constraints have prevented confident discrimination among these possibilities, or assignment of specific formation pathways to each of several specific amino acids. Position-specific carbon isotope analysis differentiates amongst these mechanisms by relating molecular sites to isotopically distinct carbon sources and by constraining isotope effects associated with elementary chemical reactions. Prior measurements of the position-specific carbon isotopic composition of α-alanine from the Murchison CM chondrite demonstrated that alanine’s high δ 13 C VPDB value is attributable to the amine carbon (δ 13 C VPDB = +142 ± 20‰), consistent with Strecker synthesis drawing on 13 C-rich carbonyl groups in precursors (Chimiak et al., 2021). Here, we measured the δ 13 C composition of fragment ions generated by electron impact ionization of derivatized α-alanine, β-alanine, and aspartic acid from Murchison via gas chromatography-Fourier transform mass spectrometry. α-Alanine’s amine carbon yielded δ 13 C VPDB = +109 ± 21‰, which is consistent with the previously measured value and with formation from 13 C-rich precursors. β-Alanine’s amine carbon presents a lower δ 13 C VPDB = +33 ± 24‰, which supports formation from 13 C-rich precursors but potentially via a Michael addition mechanism rather than Strecker synthesis. Aspartic acid’s amine carbon has δ 13 C VPDB = -14 ± 5‰, suggesting synthesis from precursors distinct from those that generated the alanine isomers. Further, these measurements indicate that Murchison amino acids are a mixture of compounds made from different synthesis mechanisms, though some subsets likely drew on the same substrates; this conclusion highlights the complexity of extraterrestrial organic synthesis networks and the potential of emerging methods of isotope ratio analysis to elucidate the details of those networks.

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

Annealing temperature variation and its influence on the self-cleaning properties of TiO 2 thin films

Titanium dioxide (TiO 2 ) is an important material in science and engineering because of its basic and synthetic properties. Nevertheless, there is a dearth of reports in the open literature focusing on its ability to self-clean under temperature changes. In this study, we used the spin coating technique to produce TiO 2 thin films to evaluate its self-cleaning ability after annealing at different temperatures. The TiO 2 sol was obtained through an endothermal sol-gel process, and the gel was coated on a glass substrate using a spin coater. The deposited films were then annealed at 400 °C, 600 °C, and 800 °C for 1 h. The influence of annealing temperature variation on the self-cleaning properties of the thin film was characterized using X-ray diffraction, scanning electron microscope; Fourier transformed infrared spectrometric analysis and UV-vis spectrophotometer. A test to ascertain self-cleaning was conducted using the degradation of methylene blue, and the different films were tested for durability. The durability test confirmed the connection between solid coating and substrate at all annealing temperatures. Thin films annealed at 600 °C revealed the best self-cleaning properties. The morphological analysis revealed snowflake shapes uniformly distributed over the substrate at 400 °C, and agglomeration improved as the annealing temperature increased. Structural analysis showed an increase in crystallinity with an increase in annealing temperature for both rutile and anatase phases. At three different temperatures, the chemical bond and the absorption band pattern followed the same path, although the peak intensity declined with temperature rise. Finally, the optical bandgap of the thin coated TiO 2 declined from 3.39 eV to 3.20 eV as the binding temperature increased from 400 to 800 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A green degumming approach for lignocellulosic kenaf bast using ethanolamine deep eutectic solvent

Traditional chemical degumming methods for lignocellulosic bast fibers pose substantial challenges, especially when dealing with kenaf bast, which has a high lignin content. Here, these challenges include severe pollution and low efficiency, etc. Therefore, this study developed a novel, green, and efficient degumming approach for lignocellulosic kenaf bast, leveraging choline chloride-ethanolamine (ChCl-ETA) alkaline deep eutectic solvent (DES). The efficacy of the ChCl-ETA DES based degumming method was validated through comprehensive chemical composition analysis, scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), thermogravimetric analysis (TG), and two-dimensional (2D) nuclear magnetic resonance (NMR) spectroscopy. Subsequently, the optimal degumming conditions, with a choline chloride to ethanolamine ratio of 1:6 and a degumming temperature of 120 °C, were determined based on the results of the residual gum content. Significantly, the recycled ChCl-ETA DES mixtures could maintain a degumming capacity (revealed by the residual gum content of degummed fibers) comparable to that of the conventional double-boiling method for at least five degumming cycles without purification. Given its low-pollution process and high efficiency, this developed method holds great potential for industrial-scale applications of lignocellulosic bast fibers.

Choline chloride↗