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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Charge Transport in Solvated Donor–Acceptor Functionalized Peptoids: Molecular Dynamics and Rate Theory

Scalable solar-energy conversion requires photoactive materials that combine the efficiency of natural photosynthetic systems with the stability and processability needed for practical applications. Achieving reliable charge transport in soft, self-assembled organic materials remains challenging, as structural fluctuations and environmental effects strongly influence charge-transfer (CT) rates. Here, we present a broadly applicable computational framework for evaluating CT rates in the condensed phase, combining Fermi’s golden rule rate theory with inputs from all-atom molecular dynamics (MD) simulations and first-principles electronic-structure calculations. The approach does not rely on system-specific parametrization and is applicable to a wide range of soft and disordered materials. We demonstrate the applicability and usefulness of the framework on redox-active peptoids functionalized with iron–porphyrin (Fe–P) complexes, a bioinspired platform with programmable donor–acceptor units and tunable three-dimensional organization. The calculated CT rates exhibit strong sensitivity to molecular conformation, with variations spanning several orders of magnitude. This dependence is shown to arise from the pronounced variation in diabatic electronic coupling with the relative orientations and separations of the Fe–P complexes across the conformational ensemble. The framework provides a consistent route for connecting atomistic structure to CT kinetics in the condensed phase and enables analysis of structure–rate relations in organic semiconducting systems.

Charge transfer↗
DOE OSTI2023

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure–function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Finally, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Understanding the phase transformation mechanisms that affect the dynamic response of Fe-based microstructures at the atomic scales

Large-scale molecular dynamics (MD) simulations were carried out to investigate the shock-induced evolution of microstructure in Fe-based systems comprising single-crystal and layered Cu/Fe alloys with a distribution of interfaces. The shock compression of pure single-crystal Fe oriented along [110] above a threshold pressure results in a BCC (α)→HCP (ε) phase transformation behavior that generates a distribution of ε phase variants in the phase transformed region of the microstructure behind the shock front. The propagation of the release wave through a phase transformed ε phase causes a reverse ε→α phase transformation and renders a distribution of twins for the [110] oriented Fe that serve as void nucleation sites during spall failure. The simulations reveal that the α→ε→α transformation-induced twinning for shock loading along the [110] direction is due to a dominant ε phase variant formed during compression that rotates on the arrival of the release wave followed by a reverse phase transformation to twins in the α phase. The modifications in the evolution of the ε phase variants and twins in Fe behavior are also studied for Cu–Fe layered microstructures due to the shock wave interactions with the Cu/Fe interfaces using a newly constructed Cu–Fe alloy potential. Here, the MD simulations suggest that interfaces affect the observed variants during shock compression and, hence, distributions of twins during shock release that affects the void nucleation stresses in the Fe phase of Cu/Fe microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effects of sodium and calcium chloride ionic stresses on model yeast membranes revealed by molecular dynamics simulation

As efforts to move a renewable economy grow, it will be necessary to make use of microbial conversion strategies for the production of novel materials or the upgrading of waste to high-value products. One critical technical challenge currently limiting waste upgrading remains the difficulty in obtaining single-pot conversion techniques where physical, chemical, and biological conversion are performed in a single step. To overcome this challenge, a detailed understanding of how different stresses impact microbial membrane stability will be necessary. In this work, using all-atom molecular dynamics simulations, we examine the impacts of moderate concentrations of NaCl and CaCl 2 on a model yeast plasma membrane. Weak, though statistically significant, changes in membrane morphology and dynamics functions are observed that are consistent with swelling and stiffening. Additionally, an examination of the ion-lipid contacts and the behavior of water at the water-membrane interface suggests that the impacts of these common salts may, in part, be mediated through changes to water-membrane hydrogen-bonding and hydration water dynamics.

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

Ethanol-Induced Condensation and Decondensation in DNA-Linked Nanoparticles: A Nucleosome-like Model for the Condensed State

Inspired by the conventional use of ethanol to induce DNA precipitation, ethanol condensation has been applied as a routine method to dynamically tune “bond” lengths (i.e., the surface-to-surface distances between adjacent nanoparticles that are linked by DNA) and thermal stabilities of colloidal crystals involving DNA-linked nanoparticles. However, the underlying mechanism of how the DNA bond that links gold nanoparticles changes in this class of colloidal crystals in response to ethanol remains unclear. Here, we conducted a series of all-atom molecular dynamic (MD) simulations to explore the free energy landscape for DNA condensation and decondensation. Our simulations confirm that DNA condensation is energetically much more favorable under 80% ethanol conditions than in pure water, as a result of ethanol’s role in enhancing electrostatic interactions between oppositely charged species. Moreover, the condensed DNA adopts B-form in pure water and A-form in 80% ethanol, which indicates that the higher-order transition does not affect DNA’s conformational preferences. We further propose a nucleosome-like supercoiled model for the DNA condensed state, and we show that the DNA end-to-end distance derived from this model matches the experimentally measured DNA bond length of about 3 nm in the fully condensed state for DNA where the measured length is 16 nm in water. Altogether, this study provides an atomistic understanding of the mechanism underlying ethanol-induced condensation and water-induced decondensation, while our proposed nucleosome-like model allows the design of new strategies for interpreting experimental studies of DNA condensation.

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

Dynamic Copper Site Redispersion through Atom Trapping in Zeolite Defects

Single-site copper-based catalysts have shown remarkable activity and selectivity for a variety of reactions. However, deactivation by sintering in high-temperature reducing environments remains a challenge and often limits their use due to irreversible structural changes to the catalyst. Here, we report zeolite-based copper catalysts in which copper oxide agglomerates formed after reaction can be repeatedly redispersed back to single sites using an oxidative treatment in air at 550 °C. Under different environments, single-site copper in Cu–Zn–Y/deAlBeta undergoes dynamic changes in structure and oxidation state that can be tuned to promote the formation of key active sites while minimizing deactivation through Cu sintering. For example, single-site Cu 2+ reduces to Cu 1+ after catalyst pretreatment (270 °C, 101 kPa H 2 ) and further to Cu0 nanoparticles under reaction conditions (270–350 °C, 7 kPa EtOH, 94 kPa H 2 ) or accelerated aging (400–450 °C, 101 kPa H 2 ). After regeneration at 550 °C in air, agglomerated CuO was dispersed back to single sites in the presence and absence of Zn and Y, which was verified by imaging, in situ spectroscopy, and catalytic rate measurements. Ab initio molecular dynamics simulations show that solvation of CuO monomers by water facilitates their transport through the zeolite pore, and condensation of the CuO monomer with a fully protonated silanol nest entraps copper and reforms the single-site structure. Importantly, the capability of silanol nests to trap and stabilize copper single sites under oxidizing conditions could extend the use of single-site copper catalysts to a wider variety of reactions and allows for a simple regeneration strategy for copper single-site catalysts.

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

Permeability of the HIV-1 capsid to metabolites modulates viral DNA synthesis

Reverse transcription, an essential event in the HIV-1 life cycle, requires deoxynucleotide triphosphates (dNTPs) to fuel DNA synthesis, thus requiring penetration of dNTPs into the viral capsid. The central cavity of the capsid protein (CA) hexamer reveals itself as a plausible channel that allows the passage of dNTPs into assembled capsids. Nevertheless, the molecular mechanism of nucleotide import into the capsid remains unknown. Employing all-atom molecular dynamics (MD) simulations, we established that cooperative binding between nucleotides inside a CA hexamer cavity results in energetically favorable conditions for passive translocation of dNTPs into the HIV-1 capsid. Furthermore, binding of the host cell metabolite inositol hexakisphosphate (IP 6 ) enhances dNTP import, while binding of synthesized molecules like benzenehexacarboxylic acid (BHC) inhibits it. The enhancing effect on reverse transcription by IP 6 and the consequences of interactions between CA and nucleotides were corroborated using atomic force microscopy, transmission electron microscopy, and virological assays. Collectively, our results provide an atomistic description of the permeability of the HIV-1 capsid to small molecules and reveal a novel mechanism for the involvement of metabolites in HIV-1 capsid stabilization, nucleotide import, and reverse transcription.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Combined Machine Learning and Molecular Dynamics Reveal Two States of Hydration of a Single Functional Group of Cationic Polymeric Brushes

The state of hydration of a macromolecular system regulates a plethora of different properties of such a system. In this article, we develop a novel machine learning (ML) approach, based on the unsupervised clustering algorithm, for probing the hydration behavior of the {N(CH 3 ) 3 } + functional group of the PMETAC [Poly(2-(methacryloyloxy)ethyl trimethylammonium chloride] polyelectrolyte (PE) brush system. The PE brushes and the brush-supported water molecules and counterions (chloride ions) are first described using all-atom molecular dynamics (MD) simulations. The simulation data is subsequently used in our ML framework to identify that (1) the {N(CH 3 ) 3 } + functional groups of the PMETAC brushes have two distinct hydration states with one state (state 1) being characterized by less structured water molecules and the other state (state 2) being characterized by more structured water molecules and (2) an enhancement in the brush grafting density leads to the progressive dissapparenace of state 2. An increase in the grafting density increases the number of chloride counterions in a given volume around the {N(CH 3 ) 3 } + functional group and increases the number of shared water molecules between the {N(CH 3 ) 3 } + and Cl - . The chloride counterions are associated with a hydration layer with much less structured water molecules. Therefore, with an increase in the grafting density, an increase in the percentage of shared water molecules leads to the prevalence of the hydration state [of the {N(CH 3 ) 3 } + moiety] with less structured water molecules. Finally, we explain how the present findings are commensurate with two key previous related results, namely a significantly large chloride ion mobility inside the PMETAC brush layer and the {N(CH 3 ) 3 } + -Cl - average distance remaining independent of the PMETAC brush grafting density. Furthermore, we anticipate that the combined ML-MD-simulation approach proposed in this study can be adapted to probe other soft matter systems to reveal new insights of the underlying mechanisms of emergent phenomenon.

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

Kibble–Zurek scaling of nonequilibrium phase transition in barium titanate

Far-from-equilibrium phase transition dynamics is one of the grand challenges in modern materials science. A theoretical landmark is the Kibble–Zurek (KZ) scaling to describe the relationship between the temperature quenching rate and the resulting defect density in the vicinity of symmetry-breaking phase transformations. Despite the confirmation of the KZ scaling in ferroic perovskite materials and macroscopic simulations, its atomistic mechanisms remain elusive. Here, we demonstrate the KZ scaling using all-atom molecular dynamics simulations for a prototypical ferroelectric perovskite, barium titanate, with the scaling exponent corresponding to the theoretical prediction for rapid quenching. Simulated diffuse neutron scattering data are presented to guide future experiments.

Physics↗
DOE OSTI2023

Atomistic structure of the SARS-CoV-2 pseudoknot in solution from SAXS-driven molecular dynamics

SARS-CoV-2 depends on -1 programmed ribosomal frameshifting (-1 PRF) to express proteins essential for its replication. The RNA pseudoknot stimulating -1 PRF is thus an attractive drug target. However, the structural models of this pseudoknot obtained from cryo-EM and crystallography differ in some important features, leaving the pseudoknot structure unclear. We measured the solution structure of the pseudoknot using small-angle X-ray scattering (SAXS). The measured profile did not agree with profiles computed from the previously solved structures. Beginning with each of these solved structures, we used the SAXS data to direct all atom molecular dynamics (MD) simulations to improve the agreement in profiles. In all cases, this refinement resulted in a bent conformation that more closely resembled the cryo-EM structures than the crystal structure. Applying the same approach to a point mutant abolishing -1 PRF revealed a notably more bent structure with reoriented helices. This work clarifies the dynamic structures of the SARS-CoV-2 pseudoknot in solution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Resonant inelastic x-ray scattering in warm-dense Fe compounds beyond the SASE FEL resolution limit

Resonant inelastic x-ray scattering (RIXS) is a widely used spectroscopic technique, providing access to the electronic structure and dynamics of atoms, molecules, and solids. However, RIXS requires a narrow bandwidth x-ray probe to achieve high spectral resolution. The challenges in delivering an energetic monochromated beam from an x-ray free electron laser (XFEL) thus limit its use in few-shot experiments, including for the study of high energy density systems. Here we demonstrate that by correlating the measurements of the self-amplified spontaneous emission (SASE) spectrum of an XFEL with the RIXS signal, using a dynamic kernel deconvolution with a neural surrogate, we can achieve electronic structure resolutions substantially higher than those normally afforded by the bandwidth of the incoming x-ray beam. We further show how this technique allows us to discriminate between the valence structures of Fe and Fe2O3, and provides access to temperature measurements as well as M-shell binding energies estimates in warm-dense Fe compounds.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Molecular Dynamical and Quantum Mechanical Exploration of the Site-Specific Dynamics of Cy3 Dimers Internally Linked to dsDNA

Performing spectroscopic measurements on biomolecules labeled with fluorescent probes is a powerful approach to locating the molecular behavior and dynamics of large systems at specific sites within their local environments. The indocarbocyanine dye Cy3 has emerged as one of the most commonly used chromophores. The incorporation of Cy3 dimers into DNA enhances experimental resolution owing to the spectral characteristics influenced by the geometric orientation of excitonically coupled monomeric units. Various theoretical models and simulations have been utilized to aid in the interpretation of the experimental spectra. In this study, we employ all-atom molecular dynamics simulations to study the structural dynamics of Cy3 dimers internally linked to the dsDNA backbone. We used quantum mechanical calculations to derive insights from both the linear absorption spectra and the circular dichroism data. Furthermore, we explore potential limitations within a commonly used force field for cyanine dyes. The molecular dynamics simulations suggest the presence of four possible Cy3 dimeric populations. The spectral simulations on the four populations show one of them to agree better with the experimental signatures, suggesting it to be the dominant population. Furthermore, the relative orientation of Cy3 in this population compares very well with previous predictions from the Holstein–Frenkel Hamiltonian model.

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

High Dynamic Range AFM Cantilever With a Collocated Piezoelectric Actuator-Sensor Pair

We present a novel approach to fundamentally eliminate electrical feedthrough (cross-talk) signal in self-sensing piezoelectric microcantilevers, used in dynamic mode atomic force microscopy (AFM). The probe is an Si microcantilever on which a two-layer piezoelectric stack transducer is microfabricated. The top transducer in the stack functions as an actuator, while the bottom transducer is used as a deflection sensor. This arrangement leads to a collocated actuator-sensor pair that co-exist on the same surface area. We report experimental results that establish the sensor's ability to capture the full dynamic range of the cantilever with minimal feedthrough from the actuator.

42 ENGINEERING↗
DOE OSTI2022

Uncovering the role of nanoscale precipitates on martensitic transformation and superelasticity

Here we characterize the role of coherent nanoscale B2 Ni 50 Al 50 precipitates on the temperature- and stress-induced martensitic phase transformation in nanocrystalline Ni 63 Al 37 shape memory alloys using multi-million-atoms molecular dynamics (MD) simulations. We studied two types of precipitates: one with single crystal precipitates (SXP) and a second where grain boundaries cut through precipitates (PXP). Simulations reveal that the presence of B2 precipitates stabilizes the cyclic flag-shaped stress-strain response, characteristic of superelasticity, and reduces remnant strain. In contrast, single-phase nanocrystalline Ni 63 Al 37 exhibits degradation of the reverse transformation during cyclic loading and, eventually, incomplete reversible transformation within a few cycles. This is consistent with previous experimental findings of ultra-low fatigue in Ni-Ti-Cu alloys with Ti 2 Cu precipitates. The simulations reveal that the presence of precipitates significantly improves the reversibility of the transformation by acting as elastic zones that partially shield the martensitic transformation and drive the reverse transformation. A detailed analysis of the MD trajectories reveals that the martensitic transformation of the matrix induces ultra-large elastic deformation in some of the B2 precipitates (approximately 12%) to the point of resulting in a martensite-like atomic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Challenges of conventional iterative all-atom and coarse-grained multiscale molecular dynamics

In this work, we evaluate the biomolecular dynamics behaviors when conventionally iterating between all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations over multiple cycles. We implemented the workflow to iterate between AA and CG in OpenMM, namely the iterative multiscale MD (iMMD) simulation workflow. In particular, we aim to identify practical applications for iterating between AA and CG simulations in a conventional manner without any constraints or model modifications. We evaluate the iMMD workflow on four representative systems, spanning folding of two soluble proteins and protein-protein as well as protein-lipid interactions of two membrane proteins. We observe that iteration between AA and CG representations could help the soluble proteins exit undesirable metastable states to fold, resulting from random protein structural distortions due to cycling. Consequently, the most reliable use of iterative AA and CG simulations appears to be to accelerating complex lipid mixing for membrane-bound protein systems rather than sampling protein conformational space. Our work explores the practical usages and limitations for iterative AA and CG simulations using readily available AA and CG force fields. The evaluated iMMD workflow in OpenMM is made available at https://github.com/lanl/iMMD.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Quantifying Membrane Structure and Dynamics during Bioproduct Production in Zymomonas mobilis by Molecular Simulation

The conversion of lignocellulosic biomass into biofuels and bioproducts by microbial biorefineries is central to a sustainable chemical industry. Zymomonas mobilis is one such biorefinery chassis and is resistant to ethanol stress, leading to its use in biomass conversion to biofuels and bioproducts. However, Z. mobilis growth is often inhibited by organic acids, aldehydes, alcohols, ketones, and amides found in biomass hydrolysate. The resulting slow growth inhibits production and as a result drives up the price for the resulting products. One hypothesis is that these molecules interact with or disrupt the bacterial membrane, triggering stress responses and hindering growth. To test this hypothesis at the molecular level, we employ all-atom molecular dynamics (MD) simulations to investigate lignocellulose-derived small molecules and their impact on a biologically relevant Z. mobilis membrane model. Simulations were conducted across a range of inhibitor concentrations from 0 to 2.5 mol %, analyzing key membrane properties such as area per lipid (APL), membrane thickness, lipid-order parameter (−S CH ), lateral diffusion coefficient (D xy ), and permeability coefficient (Pm). From simulation, we observed altered membrane structure and dynamics at these modest small molecule concentrations commonly found in hydrolysates. Generally, the membranes become thinner, with a higher area per lipid and lower-order parameter as the small molecule concentration increases. These trends are stronger for more hydrophobic molecules with greater hydrophobic bulk, as isobutanol, propanol, and propanoic acid showed greater membrane perturbations as the concentration increased compared to other small molecules. Tracking small molecule distributions directly in our equilibrium simulations allows us to determine concentration-dependent free energy profiles for these molecules. While the trends are noisy, generally the barriers to crossing the membrane decrease as the concentration increases, indicating that the membranes become leakier as small molecule concentrations rise. Comparing between native Z. mobilis membranes with hopanoids and membranes sharing the same phospholipid composition but without hopanoids, hopanoids stabilize and order the membrane for smaller molecules to maintain membrane structure but appear insufficient for larger hydrophobic molecules like isobutanol. These findings provide a mechanistic understanding of how small molecules found in biomass degradation streams interact with the Z. mobilis membrane, offering valuable insights for future strain engineering efforts to optimize biofuel and bioproduct synthesis from biomass feedstocks by highlighting limits to small molecule tolerance. This knowledge can guide the modification of membrane composition to develop more robust microbes, thereby improving microbial survival and yields in industrial contexts.

Singh, Nitin Kumar [Michigan State Univ., East Lan↗
DOE OSTI2022

Hierarchical Self-Assembly Pathways of Peptoid Helices and Sheets

Peptoids (N-substituted glycines) are a class of tailorable synthetic peptidomic polymers. Amphiphilic diblock peptoids have been engineered to assemble 2D crystalline lattices with applications in catalysis and molecular separations. Assembly is induced in an organic solvent/water mixture by evaporating the organic phase, but the assembly pathways remain uncharacterized. We conduct all-atom molecular dynamics simulations of Nbrpe6Nc6 as a prototypical amphiphilic diblock peptoid comprising an NH 2 -capped block of six hydrophobic N-((4-bromophenyl)ethyl)glycine residues conjugated to a polar NH 3 (CH 2 ) 5 CO tail. We identify a thermodynamically controlled assembly mechanism by which monomers assemble into disordered aggregates that self-order into 1D chiral helical rods then 2D achiral crystalline sheets. We support our computational predictions with experimental observations of 1D rods using small-angle X-ray scattering, circular dichroism, and atomic force microscopy and 2D crystalline sheets using X-ray diffraction and atomic force microscopy. Furthermore, this work establishes a new understanding of hierarchical peptoid assembly and principles for the design of peptoid-based nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗