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At least 307 records · Page 17

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DOE OSTI2020

Crystallizing Atomic Xenon in a Flexible MOF to Probe and Understand Its Temperature-Dependent Breathing Behavior and Unusual Gas Adsorption Phenomenon

Flexible metal–organic frameworks (MOFs) hold great promise as smart materials for specific applications such as gas separation. These materials undergo interesting structural changes in response to guest molecules, which is often associated with unique adsorption behavior not possible for rigid MOFs. Understanding the dynamic behavior of flexible MOFs is crucial yet challenging as it involves weak host–guest interactions and subtle structural transformation not only at the atomic/molecular level but also in a nonsteady state. Here we report an in-depth study on the adsorbate- and temperature-dependent adsorption in a flexible MOF by crystallizing atomic gases into its pores. Mn(ina)2 shows an interesting temperature-dependent response toward noble gases. Its nonmonotonic, temperature-dependent adsorption profile results in an uptake maximum at a temperature threshold, a phenomenon that is unusual. Full characterization of Xe-loaded MOF structures is performed by in situ single-crystal and synchrotron X-ray diffraction, IR spectroscopy, and molecular modeling. The X-ray diffraction analysis offers a detailed explanation into the dynamic structural transformation and provides a convincing rationalization of the unique adsorption behavior at the molecular scale. The guest and temperature dependence of the structural breathing gives rise to an intriguing reverse of Xe/Kr adsorption selectivity as a function of temperature. The presented work may provide further understanding of the adsorption behavior of noble gases in flexible MOF structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Rationally Programming Nanomaterials with DNA for Biomedical Applications

Abstract DNA is not only a carrier of genetic information, but also a versatile structural tool for the engineering and self‐assembling of nanostructures. In this regard, the DNA template has dramatically enhanced the scalability, programmability, and functionality of the self‐assembled DNA nanostructures. These capabilities provide opportunities for a wide range of biomedical applications in biosensing, bioimaging, drug delivery, and disease therapy. In this review, the importance and advantages of DNA for programming and fabricating of DNA nanostructures are first highlighted. The recent progress in design and construction of DNA nanostructures are then summarized, including DNA conjugated nanoparticle systems, DNA‐based clusters and extended organizations, and DNA origami‐templated assemblies. An overview on biomedical applications of the self‐assembled DNA nanostructures is provided. Finally, the conclusion and perspectives on the self‐assembled DNA nanostructures are presented.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

The striking influence of oxophilicity differences in heterometallic Mo–Mn oxide cluster reactions with water

Mixed-metal oxides have proven to be effective catalysts for the hydrogen evolution reaction, often outperforming either of the binary metal oxides. The reactivity of Mn x MoO y - (x = 1, 2; y = 3, 4) clusters toward H 2 O was investigated via time-of-flight mass spectrometry with clear evidence of cluster oxidation and corresponding H 2 production, specifically for Mn x MoO 3 - (x = 1, 2) clusters. Unlike previously studied MoxOy- clusters, which assumed a broad distribution of stoichiometries (typically x ≤ y ≤ 3x), both MnMoOy- and Mn 2 MoO y - preferentially formed y = 3 and 4 compositions in significant quantities under our source conditions. The electronic and molecular structures of the Mn x MoO y (x = 1, 2; y = 3, 4) anion and neutral clusters were probed with anion photoelectron spectroscopy and analyzed with supporting density functional theory calculations. Our studies suggest that both metal centers are involved in initial cluster–water complex formation, while Mo is the center that undergoes oxidation; hence, reactivity terminates when Mo is saturated in its highest oxidation state of +6. Across these four clusters, Mn remains relatively reduced and is stable in a high-spin electronic configuration. The preferential reactivity of water molecules toward the Mo center rather than Mn is rationalized by the much lower relative oxophilicity of Mn.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Designer Nanomaterials through Programmable Assembly

Nanoparticles have long been recognized for their unique properties, leading to exciting potential applications across optics, electronics, magnetism, and catalysis. These specific functions often require a designed organization of particles, which includes the type of order as well as placement and relative orientation of particles of the same or different kinds. DNA nanotechnology offers the ability to introduce highly addressable bonds, tailor particle interactions, and control the geometry of bindings motifs. Here, we discuss how developments in structural DNA nanotechnology have enabled greater control over 1D, 2D, and 3D particle organizations through programmable assembly. This Review focuses on how the use of DNA binding between nanocomponents and DNA structural motifs has progressively allowed the rational formation of prescribed particle organizations. Here, we offer insight into how DNA-based motifs and elements can be further developed to control particle organizations and how particles and DNA can be integrated into nanoscale building blocks, so-called “material voxels”, to realize designer nanomaterials with desired functions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Phase Boundary Mapping of Tin-Doped ZnSb Reveals Thermodynamic Route to High Thermoelectric Efficiency

Not provided.

Chemistry↗

DOE OSTI2021

Symbol alphabets from plabic graphs III: n = 9

Symbol alphabets of n-particle amplitudes in N = 4 super-Yang-Mills theory are known to contain certain cluster variables of G(4, n) as well as certain algebraic functions of cluster variables. In this paper we solve the C Z = 0 matrix equations associated to several cells of the totally non-negative Grassmannian, combining methods of arXiv:2012.15812 for rational letters and arXiv:2007.00646 for algebraic letters. We identify sets of parameterizations of the top cell of G + (5, 9) for which the solutions produce all of (and only) the cluster variable letters of the 2-loop nine-particle NMHV amplitude, and identify plabic graphs from which all of its algebraic letters originate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

From Cation Order to Disorder: Unlocking Ion Transport Pathways in Li–Zn–Zr–Cl Halospinels

Lithium metal chloride halospinels of the general formula Li 2 MCl 4 are a promising class of earth-abundant ion conductors for all-solid-state batteries. However, poor roomtemperature ionic conductivity has historically limited their use in practical applications. Here, we substitute Zr 4+ into Li 2 ZnCl 4 along the series Li 2−2x/3 Zn 1−x Zr 2x/3 Cl 4 (x = 0, 0.1, 0.3, 0.4, 0.6, 0.9, and 1.0) to understand how cation disorder and vacancy tuning impact ion transport in “normal” halospinels. Aliovalent Zr 4+ substitution increases ionic conductivity by nearly 5 orders of magnitude, from 1.320(3) × 10 −9 S cm −1 in Li 2 ZnCl 4 to 6.74(1)× 10 −5 S cm −1 for x = 0.6. Average and local structure characterization through synchrotron X-ray diffraction (SXRD) and neutron pair distribution function (nPDF) analysis reveal that Zr 4+ redistributes the Zn 2+ and Li + sublattices into previously unoccupied interstitial sites, which form new low-energy hopping pathways that facilitate ion transport. We rationalize the dramatic rearrangement of the cation local structure by considering the coordination preferences of the cations and the potential electrostatic penalties incurred by the higher-valent Zr 4+ cations. This work delivers an atomistic understanding of substitution-induced cation disorder and ion transport properties in a new family of earth-abundant halospinels.

Cardoza, Abby M. [Colorado School of Mines, Golden↗

DOE OSTI2025

Unravelling the dynamics of the maturation protein in MS2 bacteriophage via molecular simulations

The MS2 bacteriophage capsid serves as a model system for studying viral structure and function. Mature MS2 virus consists of 178 capsid proteins and a single maturation protein (MP), which is essential for host receptor binding and infection initiation. Despite its critical role, the dynamic behavior of the capsid with the MP remains poorly understood. To address this, we conducted 0.5 µs all-atom molecular dynamics (MD) simulations of the MS2 capsid with and without the MP, revealing key insights into its structural dynamics. Our simulations showed that MP exhibits high flexibility, particularly in the “tip” and “side-loop” regions, which undergo significant motions that likely enhance its ability to engage with the F-pilus receptor. Detailed analysis of MP conformational states revealed that loop rearrangements around H357 enable transient switching between “semi-closed” and “open” conformations, suggesting a conformational selection mechanism for pilus binding. Additionally, ion interaction analyses revealed distinct sodium and chloride binding patterns, where sodium ions were mostly found at the outer capsid shell, while chloride ions interacted with the basic residues on the RNA-facing side. We also found that the presence of the MP enhances salt-bridge interactions, contributing to increased capsid stability, yet it does not significantly alter the pore sizes of pentameric and hexameric units. Together, these findings provide new insights into the functional role of the MP, highlighting its contribution to capsid stability and host receptor engagement. This study offers a foundation for understanding capsid dynamics relevant to viral infectivity and may guide future rational strategies aimed at disrupting host-virus interactions.

Capsid stability↗

DOE OSTI2020

Design principles for the ultimate gas deliverable capacity material: nonporous to porous deformations without volume change

Understanding the fundamental limits of gas deliverable capacity in porous materials is of critical importance as it informs whether technical targets (e.g., for on-board vehicular storage) are feasible. High-throughput screening studies of rigid materials, for example, have shown they are not able to achieve the original ARPA-E methane storage targets, yet an interesting question remains: what is the upper limit of deliverable capacity in flexible materials? In this work we develop a statistical adsorption model that specifically probes the limit of deliverable capacity in intrinsically flexible materials. The resulting adsorption thermodynamics indicate that a perfectly designed, intrinsically flexible nanoporous material could achieve higher methane deliverable capacity than the best benchmark systems known to date with little to no total volume change. Density functional theory and grand canonical Monte Carlo simulations identify a known metal–organic framework (MOF) that validates key features of the model. Therefore, this work (1) motivates a continued, extensive effort to rationally design a porous material analogous to the adsorption model and (2) calls for continued discovery of additional high deliverable capacity materials that remain hidden from rigid structure screening studies due to nominal non-porosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non‐Covalent Interactions in a Uranyl Tetrahalide Model System

Abstract Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO 2 X 4 ] 2− (X=Cl − and Br − ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔH f ) and observed vibrational signatures. Δ H f values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [ ]) were assessed as descriptors for trends in Δ H f . Results demonstrated a strong correlation between and Δ H f , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid‐state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid‐state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red‐shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular‐level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non‐Covalent Interactions in a Uranyl Tetrahalide Model System

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A Perspective into Operando Methods for Probing Catalytic Interfaces

Rational design of electrocatalysts for (photo)electrochemical (PEC) processes like hydrogen and oxygen evolution and CO2 reduction reactions is aided by the recent improvements in capabilities of operando measurements, where morphology, composition, and/or function are probed during active catalysis. Through operando microscopy and spectroscopy, structure, catalytic microenvironment, oxidation state, adsorbates, and products can be measured to gain a better understanding of catalyst behavior and suggest possible improvements. Visualizing evolving catalyst morphologies, surface compositions, and electrochemical behavior also helps address many fundamental research questions for a better understanding of catalytic mechanisms. Correlating morphology with chemical identity or functional behavior using a variety of innovative microscopy methods is particularly promising for guiding development of next generation catalysts, and there are also many recent examples of using AI and robotics tools to innovate and speed development. In this Perspective, advances made over the past few years in operando imaging of catalysts relevant to solar fuels will be explored, followed by an outlook on technological developments in instrumentation, sample design, and computational power that may be applied to this field.

Catalysts↗

DOE OSTI2021

Plasma-catalyst modeling for materials selection: challenges and opportunities in nitrogen oxidation

Reliable kinetic models are essential to rationalize observations and to guide the selection of appropriate plasma-catalyst combinations. Kinetic models coupling plasma- and heterogeneous-catalytic-chemistries, however, are primitive. Here, we combine reduced plasma chemistries and density functional theory parameterized surface reactions to model NO formation from N2 oxidation, an alternative nitrogen fixation process. We first show plasma excited species can enhance turnover frequencies of both Pt and Au. The enhancing potential is a function of plasma species and their densities. We then compare NO production between plasma/Pt and plasma/Au with an integral reactor model and explore the dependence of NO production as a function of plasma conditions, reactor configurations and chemical compositions. Plasma/Pt generates more NO than plasma/Au under most thermal and plasma parametric conditions. Plasma/Au outperforms plasma/Pt under high plasma excitations at low temperatures. Furthermore, these results highlight that selection of plasma-catalyst combinations should consider the properties of plasmas, materials and the coupling of the two.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Accelerating the Discovery of New, Single Phase High Entropy Ceramics via Active Learning

High-entropy ceramics have garnered interest due to their remarkable hardness, compressive strength, thermal stability, and fracture toughness; yet the discovery of new high-entropy ceramics (out of a tremendous number of possible elemental permutations) still largely requires costly, inefficient, trial-and-error experimental and computational approaches. The entropy forming ability (EFA) factor was recently proposed as a computational descriptor that positively correlates with the likelihood that a 5-metal high-entropy carbide (HECs) will form the desired single phase, homogeneous solid solution; however, discovery of new compositions is computationally expensive. If you consider 8 candidate metals, the HEC EFA approach uses 49 optimizations for each of the 56 unique 5-metal carbides, requiring a total of 2744 costly density functional theory calculations. Here, we describe an orders-of-magnitude more efficient active learning (AL) approach for identifying novel HECs. To begin, we compared numerous methods for generating composition-based feature vectors (e.g., magpie and mat2vec), deployed an ensemble of machine learning (ML) models to generate an average and distribution of predictions, and then utilized the distribution as an uncertainty. Here we then deployed an AL approach to extract new training data points where the ensemble of ML models predicted a high EFA value or was uncertain of the prediction. Our approach has the combined benefit of decreasing the amount of training data required to reach acceptable prediction qualities and biases the predictions toward identifying HECs with the desired high EFA values, which are tentatively correlated with the formation of single phase HECs. Using this approach, we increased the number of 5-metal carbides screened from 56 to 15,504, revealing 4 compositions with record-high EFA values that were previously unreported in the literature. Our AL framework is also generalizable and could be modified to rationally predict optimized candidate materials/combinations with a wide range of desired properties (e.g., mechanical stability, thermal conductivity).

36 MATERIALS SCIENCE↗

DOE OSTI2022

Combining Experimental and Theoretical Techniques to Gain an Atomic Level Understanding of the Defect Binding Mechanism in Hard Carbon Anodes for Sodium Ion Batteries

Sodium ion batteries (NIBs) are an attractive alternative to lithium–ion batteries in applications that require large–scale energy storage due to sodium's high natural abundance and low cost. Hard carbon (HC) is the most promising anode material for NIBs; however, there is a knowledge gap in the understanding of the sodium binding mechanism that prevents a rational design of HC. This study tunes sucrose–derived HC via synthesis temperature then evaluates the structural, physical, and electrochemical properties. Neutron total scattering is used to generate structural models by fitting pair distribution functions (PDF) with a combination of molecular dynamics and reverse Monte Carlo methods. From this model, the number and type of structural features are identified, quantified, and correlated to the galvanostatic charge/discharge. A method of PDF “fingerprinting” binding sites using Na probe atoms is developed and analyzing these PDFs reveals an atomistic view of ion binding sites responsible for “defect” storage mechanisms. Combining these techniques results in an atomic–level study that provides a big picture of the Na–binding mechanism in NIBs, which allows for more precise tuning of the structure–property relationships in the future. Finally, the methodologies developed will also enable new strategies for the analysis of amorphous functional materials.

25 ENERGY STORAGE↗

DOE OSTI2026

Structure of Layers Formed by [2-(3,6-Disubstituted-9 H -carbazol-9-yl)ethyl]phosphonic Acids on Metal Oxides

[2-(9 H -Carbazol-9-yl)ethyl]phosphonic acid (2PACz) and its derivatives are being used extensively as hole-transport layers in organic and perovskite solar cells due to their ability to modify electrode work function, surface wettability, and in some cases, to improve active-layer adhesion, while minimizing interfacial energy losses. The orientation and coverage of surface modifiers significantly impact these functional properties; however, the detailed structure and packing in these overlayers are challenging to investigate, leading to a lack of understanding of how this structure and packing influence performance and limiting the ability to rationally design molecular modifiers. Here, we investigate monolayers of 2-(9 H -carbazol-9-yl)ethyl phosphonic acid derivatives (from here on referred to as X-2PACz) on indium tin oxide (ITO) and alpha phase aluminum oxide (α-Al 2 O 3 ) using a combination of X-ray photoelectron spectroscopy (XPS), near-edge X-ray absorption fine structure (NEXAFS) spectroscopy, and X-ray reflectivity (XRR). By correlating elemental ratios, molecular orientation, and electron density profiles, we directly quantify surface coverage, layer thickness, and molecular tilt across a series of chemically related monolayers. We find that 2PACz and the X-2PACz derivatives form dense monolayers on α-Al 2 O 3 and ITO, with similar surface coverages on either substrate that are inversely proportional to molecular steric bulk. These surface coverage results indicate that X-2PACz is sterically limited in its monolayer surface packing density, as opposed to site limited. Despite surface packing density differences between molecules, the NEXAFS data show a constant average molecular orientation of 61° to 65° between the plane of the carbazole and the substrate for all the molecules on both substrates. These results increase our general understanding of 2PACz derivatives as they become increasingly useful in high performance solar cells.

NEXAFS↗

DOE OSTI2020

Deep Understanding of Strong Metal Interface Confinement: A Journey of Pd/FeO x Catalysts

Tuning the atomic interface configuration of noble metals (NMs) and transition-metal oxides is an effective straightforward yet challenging strategy to modulate the activity and stability of heterogeneous catalysts. Herein, Pd supported on mesoporous Fe 2 O 3 with a high specific surface area was rationally designed and chosen to construct the Pd/iron oxide interface. As a versatile model, the physicochemical environments of Pd nanoparticles (NPs) could be precisely controlled by taming the reduction temperature. The experimental and density functional theory calculation results unveiled that the catalyst in the support–metal interface confinement (SMIC) state showed significantly enhanced catalytic activity and sintering resistance for CO oxidation. The constructed Fe sites at the interfaces between FeO x overlayers and Pd NPs not only provided additional coordinative unsaturated ferrous sites for the adsorption and activation of O 2 , thereby facilitating the activation efficiency of O 2 , but also impressively changed the reaction pathway of CO oxidation. As a result, the catalyst followed the Pd/Fe dual-site mechanism instead of the classical Mars–van Krevelen mechanism. For the catalyst in the strong metal–support interaction (SMSI) state, its catalytic activity was seriously suppressed because of the excessive encapsulation of the active Pd sites by FeO x overlayers. Thus, the present study therefore provides detailed insights into the SMIC and SMSI in ferric oxide-supported Pd catalysts, which could guide the preparation of highly efficient supported catalysts for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

An anti-PD-1–GITR-L bispecific agonist induces GITR clustering-mediated T cell activation for cancer immunotherapy

Costimulatory receptors such as glucocorticoid-induced tumor necrosis factor receptor–related protein (GITR) play key roles in regulating the effector functions of T cells. In human clinical trials, however, GITR agonist antibodies have shown limited therapeutic effect, which may be due to suboptimal receptor clustering-mediated signaling. To overcome this potential limitation, a rational protein engineering approach is needed to optimize GITR agonist-based immunotherapies. Here we show a bispecific molecule consisting of an anti-PD-1 antibody fused with a multimeric GITR ligand (GITR-L) that induces PD-1-dependent and FcγR-independent GITR clustering, resulting in enhanced activation, proliferation and memory differentiation of primed antigen-specific GITR + PD-1 + T cells. The anti-PD-1–GITR-L bispecific is a PD-1-directed GITR-L construct that demonstrated dose-dependent, immunologically driven tumor growth inhibition in syngeneic, genetically engineered and xenograft humanized mouse tumor models, with a dose-dependent correlation between target saturation and Ki67 and TIGIT upregulation on memory T cells. Anti-PD-1–GITR-L thus represents a bispecific approach to directing GITR agonism for cancer immunotherapy.

60 APPLIED LIFE SCIENCES↗