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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 343 records · Page 19

ν-point energy correletors with F AST EEC: Small-x physics from LHC jets

In recent years, energy correlators have emerged as a powerful tool for studying jet substructure, with promising applications such as probing the hadronization transition, analyzing the quark-gluon plasma, and improving the precision of top quark mass measurements. The projected N-point correlator measures correlations between N final-state particles by tracking the largest separation between them, showing a scaling behavior related to DGLAP splitting functions. These correlators can be analytically continued in N, commonly referred to as ν-correlators, allowing access to non-integer moments of the splitting functions. Of particular interest is the ν → 0 limit, where the small momentum fraction behavior of the splitting functions requires resummation. Originally, the computational complexity of evaluating ν-correlators for M particles scaled as 2 2M , making it impractical for real-world analyses. However, by using recursion, we reduce this to M 2M , and through the FastEEC method of dynamically resolving subjets, M is replaced by the number of subjets. This breakthrough enables, for the first time, the computation of ν-correlators for LHC data. In practice, limiting the number of subjets to 16 is sufficient to achieve percent-level precision, which we validate using known integer-ν results and convergence tests for non-integer ν. We have implemented this in an update to FastEEC and conducted an initial study of power-law scaling in the perturbative regime as a function of ν, using CMS Open Data on jets. The results agree with DGLAP evolution, except at small ν, where the anomalous dimension saturates to a value that matches the BFKL anomalous dimension.

Energy correlators↗

CO 2 capture from wet flue gas using a water-stable and cost-effective metal-organic framework

We report the use of MIL-120 as a water-stable and cost-effective metal-organic framework (MOF) for selectively capturing CO 2 from wet flue gas. Synthesized using inexpensive and environmentally benign reagents in water, MIL-120 possesses one-dimensional pores decorated with hydroxyl-bridged Al(III) ions and benzene rings with an interstitial spacing of 4.78 Å. Carbon dioxide isotherms show steep uptake at low pressure, and the affinity of MIL-120 for CO 2 is 44 kJ mol –1 . CO 2 -loading 13 C solid-state nuclear magnetic resonance and Fourier transform infrared spectra tracking the sorption of CO 2 into MIL-120 revealed that the interplay of pore size, functionality, and dimensionality is vital for CO 2 restriction within the pores of MIL-120. Breakthrough experiments reveal that MIL-120 can capture CO 2 from dry and wet flue gas with uptake capacities of 1.215 and 1.118 mmol g –1 , respectively. Our work highlights the synthetic benefits of MIL-120 and elucidates its selective capture of CO 2 from wet flue gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of liquid cells for high resolution imaging and chemical analysis in situ with Transmission Electron Microscopy

The development of liquid cells for transmission electron microscopy (TEM) have enabled breakthroughs in the study of nanoscale structural, morphological, or chemical changes during materials growth and applications [1]. The challenges of achieving high resolution imaging and chemical analysis through liquids often arise from the liquid cells being too thick. Making ultra-thin freestanding membranes and controlling the liquid thickness are some of the key attributes to the recent liquid cell developments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics

Abstract Artificial intelligence (AI) promises to reshape scientific inquiry and enable breakthrough discoveries in areas such as energy storage, quantum computing, and biomedicine. Scanning transmission electron microscopy (STEM), a cornerstone of the study of chemical and materials systems, stands to benefit greatly from AI-driven automation. However, present barriers to low-level instrument control, as well as generalizable and interpretable feature detection, make truly automated microscopy impractical. Here, we discuss the design of a closed-loop instrument control platform guided by emerging sparse data analytics. We hypothesize that a centralized controller, informed by machine learning combining limited a priori knowledge and task-based discrimination, could drive on-the-fly experimental decision-making. This platform may unlock practical, automated analysis of a variety of material features, enabling new high-throughput and statistical studies.

47 OTHER INSTRUMENTATION↗

Rational Design of Novel Biomimetic Sequence-Defined Polymers for Mineralization Applications

Silica biomineralization is a naturally occurring process, wherein organisms use proteins and other biological structures to direct the formation of complex, hierarchical nanostructures. Discovery and characterization of such proteins and their underlying mechanisms spurred significant efforts to identify routes for biomimetic mineralization that reproduce the exquisite shapes and size selectivities found in nature. A common strategy has been the use of short peptide sequences with chemistry mimicking those found in natural systems, such as the use of the silaffin-derived R5 peptide. While progress has been made using this approach, there are many limitations that have prevented breakthroughs in biomimicry. To advance our ability to use charged macromolecules for silica formation, we propose to use sequence-defined synthetic polymers known as peptoids, or N-substituted polyglycines, which present significant capability for the precise tuning of sequence and structure beyond what can often be achieved with peptides alone. This study presents a computationally predicted design of these polymers that leads to the controlled formation of silica nanomaterials. We investigate surface adsorption and the mineralization process through analysis of binding mechanisms and energetics of the R5 system. Next, we synthesized two R5-inspired peptoids and validated our prediction in the design of mineralization polymers through characterization using surface plasmon resonance and electron microscopy. Here, this computationally guided study holds great promise for designing new sequences with unprecedented control of the placement of chemical functional groups, thus allowing for further unraveling of silicification mechanisms and the eventual design of sequence-defined synthetic polymers leading to the predictive synthesis of nanostructured functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding How Ligand Functionalization Influences CO2 and N2 Adsorption in a Sodalite Metal–Organic Framework

In this work, a detailed study is conducted to understand how ligand substitution influences the CO2 and N2 adsorption properties of two highly crystalline sodalite metal–organic frameworks (MOFs) known as Cu–BTT (BTT–3 = 1,3,5-benzenetristetrazolate) and Cu–BTTri (BTTri–3 = 1,3,5-benzenetristriazolate). The enthalpy of adsorption and observed adsorption capacities at a given pressure are significantly lower for Cu–BTTri compared to its tetrazole counterpart, Cu–BTT. In situ X-ray and neutron diffraction, which allow visualization of the CO2 and N2 binding sites on the internal surface of Cu–BTTri, provide insights into understanding the subtle differences. As expected, slightly elongated distances between the open Cu2+ sites and surface-bound CO2 in Cu–BTTri can be explained by the fact that the triazolate ligand is a better electron donor than the tetrazolate. The more pronounced Jahn–Teller effect in Cu–BTTri leads to weaker guest binding. The results of the aforementioned structural analysis were complemented by the prediction of the binding energies at each CO2 and N2 adsorption site by density functional theory calculations. In addition, variable temperature in situ diffraction measurements shed light on the fine structural changes of the framework and CO2 occupancies at different adsorption sites as a function of temperature. Finally, simulated breakthrough curves obtained for both sodalite MOFs demonstrate the materials’ potential performance in dry postcombustion CO2 capture. The simulation, which considers both framework uptake capacity and selectivity, predicts better separation performance for Cu–BTT. The information obtained in this work highlights how ligand substitution can influence adsorption properties and hence provides further insights into the material optimization for important separations.

adsorption capacities↗

Isotherm, Kinetic, Process Modeling, and Techno-Economic Analysis of a Diamine-Appended Metal-Organic Framework for CO 2 Capture Using Fixed Bed Contactors

In this report, diamine-appended metal-organic frameworks exhibiting step-shaped CO 2 adsorption are exceptional candidates for energy-efficient carbon capture. However, there are few studies examining their performance in real-world capture scenarios, in part due to the challenge inherent in modeling their CO 2 uptake behavior. Here, we develop a dual-site Sips model to fit experimental CO 2 adsorption data for dmpn-Mg 2 (dobpdc) (dmpn = 2,2-dimethyl-1,3-diaminopropane; dobpdc 4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) and develop a linear driving force model for the adsorption kinetics based on available experimental data. These models are used to develop a dynamic, fixed bed, nonisothermal contactor model using shaped particles of the material, which is validated with experimental breakthrough data. We also examine the effects of the high heat of adsorption of the material on CO 2 uptake performance and find that heat removal is essential to maximize capture performance. We finally investigate "basic"(no bed cooling during adsorption) and "modified"(bed cooling during adsorption) temperature swing adsorption (TSA) processes using dmpn-Mg 2 (dobpdc), and their process economics are compared to a state-of-the-art monoethanolamine (MEA) capture system with and without heat recovery. In the absence of heat recovery, the adsorbent systems are more costly than established technology. However, with 85% heat recovery, both adsorbent-based TSA processes are projected to cost less than the MEA system. This work highlights that thermal management is vital for implementation of dmpn-Mg 2 (dobpdc) as a viable CO 2 capture technology. Investigation of other contactor technologies that can provide unique ways to manage system heat represent promising future areas of study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiscale Catalytic Fast Pyrolysis of Grindelia Reveals Opportunities for Generating Low Oxygen Content Bio-Oils from Drought Tolerant Biomass

Grindelia squarrosa (curlycup gumweed) biomass possesses unique biochemistry, cell wall composition, and leaf architecture tailored for prolific growth in arid and semiarid climates. Most notably, this plant has developed high levels of extractable resins that have high effective H/C eff ratios ((mol H - 2 x mol O)/mol C), which is hypothesized to lead to low coke formation during catalytic fast pyrolysis (CFP) over the ZSM-5 catalyst. In microscale experiments with high ZSM-5 loadings (biomass-to-catalyst mass ratio (B/C) ~ 0.1), in situ CFP generated high yields of aromatic hydrocarbons (30% carbon yield) while ex situ CFP favored aliphatic hydrocarbons (25% carbon yield). The difference between the two configurations was attributed to the constant catalyst temperature during ex situ CFP. Deactivation leading to partially deoxygenated vapor products occurred rapidly until B/C ≤ 0.5 by the adsorption of organic species blocking access to acid sites inside the micropores of the catalyst. This was followed by more gradual deactivation leading to primary vapor breakthrough, which we attribute to coke formation on acid sites on the external surface of ZSM-5 crystallites. Noncatalytic fast pyrolysis of Grindelia in a bench scale reactor produced oils with oxygen content (18 wt % on dry basis) and carbon yield (33%) comparable to those of CFP of woody biomass. The CFP of Grindelia further reduced the oxygen content to 7 wt % for in situ CFP and 4 wt % for ex situ CFP at B/C of 2-3. The good deoxygenation was attributed to a combination of a high H/C eff ratio and overall better quality of the pyrolysis vapors that were passed over the ZSM-5 catalyst. The high inorganic content of the Grindelia likely catalyzed pyrolysis to remove oxygenated coke precursors. This integrated CFP study demonstrated that Grindelia could be an important feedstock for generating stabilized noncatalytic and CFP oils for downstream processing into fuels and/or extraction of high-value chemicals. The preprocessing of this feedstock will be required to remove inorganics, which cause an irreversible deactivation of ZSM-5.

BIOMASS FUELS↗

Unsteady- and Steady-State Relative Permeability Study with X-ray and Acoustic Monitoring for CO 2 Storage in Deep Saline Aquifers

In this study, we link the multiphase flow measurements with controls of sedimentary structures (e.g., heterogeneity and anisotropy) on relative permeability to variations in ultrasonic velocities for two deep saline aquifer formations (Entrada and Bluff Sandstones) in the San Juan Basin of the Southwestern USA. The rock specimens were extracted from outcrop sites near Durango, CO, USA. They have distinct differences in grain size, cementation composition, and individual chemical amounts, despite both formations being eolian sandstones. We performed a series of unsteady- and steady-state CO 2 -brine relative permeability experiments under capillary-controlled displacement rates. Unsteady-state experiments were conducted at 71 °C and 9.65 MPa; steady-state experiments were conducted at 85 °C and 22.8 MPa and 89 °C and 24.1 MPa for the Bluff and Entrada Sandstones, respectively. During the unsteady experiments, X-ray computed tomography was used to visualize multiphase flow in porous media and quantify saturations during brine drainage under various flow rates. Scan images and saturation profiles indicate that the CO 2 distribution in the pore volume was strongly impacted by the presence of high-angle cross-laminations, heterogeneous rock structure, and direction of bedding orientation. Those factors contribute to dramatic and quick initial breakthroughs and affect the overall saturation dynamics. Steady-state relative permeability tests were conducted at net flow rates of 1 mL/min for both brine drainage and imbibition. During the experimental steps, the CO 2 fractional flow was increased and decreased for both drainage and imbibition scenarios to mimic the front when CO 2 contacts brine and behind the front when brine enters space previously occupied by CO 2 . It was found that compressional velocity decreased, while shear waves slightly increased as brine saturation decreased. The hysteresis effects for the relative permeability and acoustic velocities were distinct. Furthermore, the CO 2 /brine front stability is quantified by applying a mobility ratio approach to spot saturations at which the boundary line between fluids becomes uneven. The results presented in this work can potentially boost the quality and precision of forecasts for the CO 2 storage projects in which the vertical and horizontal core-scale heterogeneity and anisotropy impact the plume migration within host reservoirs.

carbon dioxide (CO2)↗

Microbe-Encapsulated Silica Gel Biosorbents for Selective Extraction of Scandium from Coal Byproducts

Establishing an inexpensive and environmentally friendly scandium (Sc) supply is critical for the development of clean energy technologies. However, refining Sc from Sc-bearing sources using current technologies poses economic and environmental challenges due to its low concentration relative to base metals and chemically similar lanthanides. In this work, we developed a biosorption-based flow-through process for extraction of Sc from low-grade feedstocks. A novel biosorbent material was synthesized by encapsulating Arthrobacter nicotianae, a bacterium that selectively adsorbs Sc, within a porous silica matrix. Through the use of several complementary microscopy techniques, we demonstrated a highly porous biosorbent structure with a high cell-loading density and a homogenous cell distribution. Batch adsorption assays revealed selective Sc adsorption over lanthanides and common based metals, with the exception of Fe(III), as evidenced by separation factors greater than 50. The MESG particles were packed into fixed-bed columns to enable adsorption under flow-through conditions, which demonstrated effective Sc extraction at flow rates up to 0.08 cm/s and high stability for reuse; greater than 95% of the adsorption capacity was maintained after 10 consecutive adsorption/desorption cycles. When applied to a lignite coal leachate, whose Fe content was depleted through pH-mediated precipitation, the MESG particles yielded Sc breakthrough at 30 bed volumes, whereas all other metals broke through after only a few bed volumes. Following desorption, an eluate with a 124-fold increase in Sc purity was achieved relative to the lignite leachate with Sc constituting 96.4% of the total REEs. This study established a rapid, facile, and scalable cell immobilization approach that enables the use of microbial biomass for Sc recovery from low-grade sources.

Dong, Ziye↗

Structurally Driven Selective Adsorption of Hydrocarbons by Metal Substitution in Isostructural Rare-Earth Metal–Organic Frameworks

The design and realization of highly selective nanoporous materials are necessary to target critical separations across industries. By leveraging pore size, pore shape, and linker functionalization, the design of nanoporous solid adsorbents will enable the rapid production of energy efficient separation materials for high-value gas mixtures. This study uses a combination of modeling, synthesis, and gas adsorption testing to investigate a new class of small-pore isostructural rare-earth (RE) 2,5-dihydroxyterephthalic acid (DOBDC) metal–organic frameworks (MOFs) (RE: Pr-, Gd-, Er-, Yb; DOBDC = 2,5-dihydroxyterephthalic acid) and their adsorption selectivity for acetylene/ethylene mixtures. Density functional theory simulations identified that selective binding of acetylene over ethylene in the Gd-, Er-, and Yb-DOBDC MOFs was due to hydrogen-bonding between acetylene and the linker hydroxyl. Adsorption experiments validated the computational results by identifying mechanisms that control the acetylene/ethylene adsorption selectivity and high acetylene adsorption. Furthermore, dynamic column breakthrough experiments with the Gd-DOBDC MOF validated the simulations and indicated that ethylene can be separated from acetylene in a mixture containing 1 vol % acetylene and 39 vol % ethylene (balance argon). In conclusion, the results highlight the complexity of gas binding in functional porous materials and how combining modeling and experiment enables a fundamental understanding of gas–framework interactions that can be leveraged for the design of future separation materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

UV–Vis–NIR Reflectance Spectroscopy and Chemometrics for Monitoring Pu Directly on an Ion Exchange Column

Here, we present a fiber-optic UV–vis–NIR reflectance spectroscopy method for direct, noninvasive monitoring of Pu(IV) in a glass ion exchange column during dynamic loading and elution in a glovebox. A movable probe enables spatially resolved spectral acquisition along the column axis, capturing distinct features associated with Pu(IV) nitrate complexes during loading and free ions during elution. Principal component analysis was applied to extract the dominant spectral variance and resolve relative concentration profiles without requiring precise knowledge of optical penetration depth or species identity. This in situ approach reveals spatial gradients and speciation dynamics in real time, which provides actionable insight into Pu(IV) ion migration, resin saturation, and breakthrough behavior under evolving flow conditions. The method offers a practical, fiber-compatible strategy to monitor glass column–based separations for Pu and other lanthanides or actinides and to characterize metal–resin interactions in flow-through systems.

actinide↗

Comparative Analysis of TCR and TCR-pMHC Complex Structure Prediction Tools

The rapid development of computational approaches for predicting the structures of T cell receptors (TCRs) and TCR-peptide-major histocompatibility (TCR-pMHC) complexes, accelerated by AI breakthroughs such as AlphaFold, has made it feasible to calculate these structures with increasing accuracy. Although these tools show great potential, their relative accuracy and limitations remain unclear due to the lack of standardized benchmarks. Here, we systematically evaluate seven tools for predicting isolated TCR structures together with six tools for predicting TCR-pMHC complex structures. The methods include homology-based approaches, general prediction tools using AlphaFold, TCR-specific tools derived from AlphaFold2, and the newly developed tFold-TCR model. The evaluation uses a post-training data set comprising 40 αβ TCRs and 27 TCR-pMHC complexes (21 Class I and 6 Class II). Model accuracy is assessed at global, local, and interface levels using a variety of metrics. We find that each tool offers distinct advantages in various aspects of its predictions. AlphaFold2, AlphaFold3, and tFold-TCR excel in overall accuracy of TCR structure prediction, and TCRmodel2 and AlphaFold2 perform well in overall accuracy of TCR-pMHC structure prediction. However, TCR-specific tools derived from AlphaFold2 show lower accuracy in the framework region than both homology-based methods and general-purpose tools such as AlphaFold, and challenges remain for all in modeling CDR3 loops, docking orientations, TCR-peptide interfaces, and Class II MHC-peptide interfaces. Furthermore, these findings will guide researchers in selecting appropriate tools, emphasize the importance of using multiple evaluation metrics to assess model performance, and offer suggestions for improving TCR and TCR-pMHC structure prediction tools.

Chemical structure↗

Self-Organization and Nitrogen Incorporation in Diamond-Like Carbon Microstructures Synthesized by Nonthermal Plasma

Nonthermal plasma activation of light alkanes is an encouraging decarbonization strategy to produce chemicals or fuels from abundant and/or flared carbon sources. However, prolific carbon growth on both the catalyst and electrode has limited its practicality, requiring additional knowledge of the carbon structure and growth mechanism before breakthroughs are realized. Furthermore, visual evidence is provided for nonuniform diamond-like carbon (DLC) microstructures that materialize in a coaxial dielectric barrier discharge (DBD) reactor flowing ethane and He at 278 K. Through a connection to known behaviors of DBD microdischarge patterns, the microstructure spacing was controlled by altering the applied voltage (ΔV) of the plasma or the burning voltage (U b ). Additionally, carbon valorization through nitrogen incorporation from N 2 was explored as an orthogonal solution to carbon mitigation, with N/C values >0.25 achieved and both sp 2 and sp 3 C–N bonding observed in the microstructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Protein–Protein Interaction Networks Derived from Classical and Machine Learning-Based Natural Language Processing Tools

The study of protein-protein interactions (PPIs) provides insight into various biological mechanisms, including the binding of antibodies to antigens, enzymes to inhibitors or promoters, and receptors to ligands. Recent studies of PPIs have led to significant biological breakthroughs. For example, the study of PPIs involved in the human:SARS-CoV-2 viral infection mechanism aided in the development of the SARS-CoV-2 vaccines. Though several databases exist for the manual curation of PPI networks, text mining methods have been routinely demonstrated as useful alternatives for newly studied or understudied species where databases are incomplete. Here, the relationship extraction (RE) performance of several open-source classical text processing, machine learning (ML)-based natural language processing (NLP), and large language model (LLM)-based NLP tools were compared. Overall, our results indicated that networks derived from classical methods tend to have high true positive rates at the expense of having overconnected-networks, ML-based NLP methods have lower true positive rates but networks with the closest structures to the target network, and LLM-based NLP methods tend to exist in-between the two other approaches, with variable performances. Finally, the selection of a specific NLP approach should be tied to the needs of a study and text availability, as models varied in performance due to the amount of text provided.

59 BASIC BIOLOGICAL SCIENCES↗

Emerged Metallicity in Molecular Ferromagnetic Wires

Supramolecular engineering bridges molecular assembly with macromolecular charge-transfer salts, promising the design to construct supramolecular architectures that integrate cooperative properties difficult or impossible to find in conventional lattices. Here, we report the crystal engineering design and kinetic growth of one-dimensional supramolecular wires composed of bis(ethylenedithio)tetrathiafulvalene (ET + ) cation and polymeric Cu[N(CN) 2 ] 2 – anion. A bulk ferromagnetic order is discovered for filling up the gap where strong ferromagnetism is missing in such ET molecule-based charge-transfer salts. Metallicity is induced by electric current from the semiconducting wire, which is attributed to strain effect by tuning its close molecular contact. This structural feature is evidenced through the combination of various mechanistic spectroscopic studies. Further, electric dipole is established from the close molecular contacts and is suggestive to stabilize ferromagnetic spin interaction through anions bridging spin sites. The breakthrough shown here provides a pathway to explore low-dimensional supramolecular materials exhibiting strong electron correlation, metallicity, and ferromagnetism.

77 NANOSCIENCE AND NANOTECHNOLOGY↗