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Results for “structured dynamic model tuning”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cavity electrodynamics of van der Waals heterostructures

Van der Waals heterostructures host many-body quantum phenomena that are tunable in situ using electrostatic gates. Their constituent two-dimensional materials and gates can naturally form plasmonic self-cavities, confining light in standing waves of current density due to finite-size effects. The plasmonic resonances of typical graphite gates fall in the gigahertz to terahertz range, corresponding to the same microelectronvolt to millielectronvolt energy scale as the phenomena in van der Waals heterostructures that they electrically control. This raises the possibility that the built-in cavity modes of graphite gates are relevant for shaping the low-energy physics of these heterostructures. However, probing these cavity-coupled electrodynamics is challenging as devices are notably smaller than the diffraction limit at the relevant wavelengths. Here we report on the intrinsic cavity conductivity of gate-tunable graphene heterostructures. As the carrier density is tuned, we observe coupling and spectral weight transfer between graphene and graphite plasmonic cavity modes in the ultrastrong coupling regime. We present an analytical model to describe the results and provide general principles for cavity design. Our findings show that intrinsic cavity effects are important for understanding the low-energy electrodynamics of van der Waals heterostructures and open a pathway for useful functionality through cavity control.

Electronic properties and materials↗
DOE OSTI2025

In Situ/Operando Probing of Dynamic Phase Structures of Alumina‐Supported Ultrasmall Copper‐Gold Alloy Nanoparticles Under Reaction Conditions

Abstract The ability to control phase structures and surface sites of ultrasmall alloy nanoparticles under reaction conditions is essential for preparing catalysts by design. This is, however, challenging due to limited understanding of the atomic‐scale phases and their correlation with the ensemble‐averaged structures and activities of catalysts during catalytic reactions. We reveal here a dynamic structural stability of alumina‐supported ultrasmall and equiatomic copper‐gold alloy nanoparticles under reaction conditions as a model system in the in situ/operando study. In situ atomic‐scale morphological tracking under oxygen reveals temperature‐dependent dynamic crystalline‐amorphous dual‐phase structures, showing dynamic stability over an elevated temperature range. This atomic‐scale dynamic phase stability coincides with a “conversion plateau” observed for carbon monoxide oxidation on the catalyst. It is substantiated by the stable lattice ordering/disordering structures and surface sites with oscillatory characteristics shown by operando ensemble‐average structural tracking of the catalyst during the oxidation reaction. The understanding of the atomic‐scale dynamic phase structures in correlation with the ensemble‐average dynamic ordering/disordering phase structures and surface sites provides fresh insights into the unique synergy of the supported alloy nanoparticles. This understanding has implications for the design and structural tuning of active and stable ultrasmall alloy catalysts under elevated temperatures.

Chemistry↗
DOE OSTI2026

Domain-Dependent Electronic Properties of 2D Copper Boride Synthesized from Reversible Subsurface Diffusion on Cu(111)

Emerging boron-based 2D materials hold properties with potential applications ranging from electronic devices to catalysis and energy storage. Using physical vapor deposition, 2D copper borides are formed on Cu(111) at elevated temperatures. However, the as-prepared surfaces often contain boron clusters that compromise structural homogeneity, and the dynamics of their formation is not yet fully understood. Through in situ low-energy electron microscopy (LEEM), Auger electron spectroscopy (AES), and scanning tunneling microscopy/spectroscopy (STM/STS), we show that cluster-free 2D CuB x is synthesized via reversible subsurface diffusion of boron atoms. The resolved regular atomic structure aligns with the previously calculated Cu 8 B 14 model. In a rare case, possibly due to surface strain and a change of orientation, a second domain of CuB x was observed with a pronounced change in electronic properties, yet electronic states remain delocalized in both domains. In conclusion, these findings demonstrate the sensitivity of electronic properties to domain structure and highlight a potential opportunity to tune 2D CuB x for diverse applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

In situ scanning transmission electron microscopy enables observation of the domain dynamics in ferroelectric materials as a function of externally applied bias and temperature. The resultant data sets contain a wealth of information on polarization switching and phase transition mechanisms. However, identification of these mechanisms from observational data sets has remained a problem due to a large variety of possible configurations, many of which are degenerate. Here, an approach based on a combination of deep learning-based semantic segmentation, rotationally invariant variational autoencoder (VAE), and non-negative matrix factorization to enable learning of a latent space representation of the data with multiple real-space rotationally equivalent variants mapped to the same latent space descriptors is introduced. By varying the size of training sub-images in the VAE, the degree of complexity in the structural descriptors is tuned from simple domain wall detection to the identification of switching pathways. Importantly, this yields a powerful tool for the exploration of the dynamic data in mesoscopic electron, scanning probe, optical, and chemical imaging. Moreover, this work adds to the growing body of knowledge of incorporating physical constraints into the machine and deep-learning methods to improve learned descriptors of physical phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Revealing multiscale competing processes in the solid-state synthesis of single-crystalline layered oxide positive electrodes

Solid-state synthesis involves a web of coupled chemical reactions and physical changes that unfold across multiple scales. Efforts to fine-tune its parameters have historically followed heuristic, trial-driven workflows that demand significant time and resources. In this study, we aimed to open this black box by employing multiscale in situ synchrotron imaging and diffraction. Using LiNi 0.5 Mn 0.3 Co 0.2 O 2 battery positive electrode material as a model system and Ba-based sintering aids, we reveal dopant segregation, intergranular mass transport, and porosity evolution as key drivers of single-crystalline particle formation. Notably, we uncovered a dynamic competition between particle-level grain coalescence and atomic-scale cation disordering, both of which are thermally activated yet have opposing impacts on battery performance. These findings highlight the coupled, multiscale nature of structure development and offer a mechanistic basis for optimizing the solid-state synthesis process. This framework provides a path toward more controlled, efficient, and scalable production of high-performance battery positive electrode materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

OC6 Phase Ib: Validation of the CFD predictions of difference-frequency wave excitation on a FOWT semisubmersible

During the previous OC5 11 project, state-of-the-art mid-fidelity engineering tools for floating wind systems were found to consistently underpredict the nonlinear, low-frequency responses of semisubmersible offshore wind platforms, leading to substantial errors in the structural loads because of low-frequency surge and pitch resonance. To examine this underprediction, a coordinated investigation with computational fluid dynamics (CFD) simulations and model-basin experiments was carried out. Both investigations involved a fixed and simplified OC5-DeepCwind semisubmersible in bichromatic waves. The wave excitations - especially the nonlinear, difference-frequency excitation - on the structure from the CFD simulations were compared to the experimental measurements for validation, with uncertainty analyses for both the experimental and the CFD results. Furthermore, the wave excitations on each column of the semisubmersible were measured separately in the experiment, allowing the validation of the CFD results to be done on a per-column basis. Overall, the CFD predictions of the difference-frequency excitations agree with the experimental measurements, suggesting the CFD solutions can be used as a reference for tuning and improving the engineering-level tools and can provide a means to better understand the underprediction at low frequencies.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗
DOE OSTI2022

Analysis of HolosGen Sub-Scale Simulator with Plant Dynamics Code

The Subcritical Power Module Sub-scale Simulator (SPM-SS) has been designed and constructed by HolosGen LLC under the ARPA-E MEITNER program to simulate the thermal-hydraulic and heat transfer behavior of the full-scale Holos-Quad Subcritical Power Modules (SPMs). Four coupled SPMs, each rated at 5.5MW, form the Holos-Quad gas-cooled microreactor design. The SPM-SS represents a substantially scaled-down system with a power rating less than 40 kW, equipped with an electrically heated fuel cartridge heat exchanger, an electrically heated compressor heat exchanger, and a valve actuated turbine heat exchanger, in addition to a recuperator and a cooler heat exchanger. The fuel cartridge represents a portion of the full-scale SPM core, the compressor heat exchanger mimics the temperature changes resulting from the compressor’s turbomachinery inefficiencies, the turbine heat exchanger mimics the expansion process normally occurring through the turbine, while the recuperator and cooler heat exchangers complete the subscale simulator loop. The heaters equipping the fuel cartridge and the compressor heat exchangers are electronically controlled to simulate normal and off-normal SPM operating conditions. The full-scale Holos-Quad SPM design eliminates the traditional balance of plant and executes thermal-to-electric energy conversion by means of an intercooled Brayton cycle with decoupled compressor-turbine turbomachinery. The Holos-Quad full-scale design is equipped with a multi-stage axial Low- and High-Pressure compressor, and a multistage axial turbine. The SPM-SS is designed for testing and validation of selected components which are instead coupled by a traditional balance of plant. The SPMSS is not equipped with turbo-machinery (compressor and turbine) as the development of these components were excluded from the scope of work under the ARPA-E MEITNER funding program. The SPM-SS balance of plant enables modifications, replacement and testing of individual components with different working fluids and is designed to include the turbo-machinery components that will be developed in future research . The SPM-SS can be operated with different gases, variable mass-flow-rates, pressures, and temperatures to obtain test data for selected components, whose performance can be scaled to validate the computer model of the full-scale SPM at various conditions (e.g., start-up, transients conditions). The SPM-SS can operate at the maximum Holos-Quad design pressure of 7 MPa, and a maximum temperature limited to 650 °C by the electrical heaters. Several SPM-SS tests have been conducted and analyzed with the Plant Dynamics Code (PDC) developed at the Argonne National Laboratory (ANL). These tests aimed at validating the PDC modeled predictions of the full-scale Holos-Quad design with data from selected SPM-SS components. In order to address SPM-SS specific characteristics, such as components heat losses and absence of turbomachinery components, some modifications to the PDC have been implemented to factor the design differences from the full-scale Holos-Quad SPM to the SPM-SS. As the PDC offers capabilities to analyze systems with different working fluids, air, nitrogen, and helium were utilized as the SPM-SS working fluids. Air was utilized to fine-tune the SPM-SS Systems Structures and Components (SSCs), nitrogen was utilized to pressure test the SPM-SS loop at the SPMs design maximum pressure of 7MPa. Helium was utilized as the working fluid circulating through the SPM-SS SSCs for specific tests to validate the PDC predictions of the fuel cartridge heat exchanger. SPM-SS tests data were also analyzed with both the steady-state and transient analysis capabilities offered by the PDC. This report describes the PDC analysis of the SPM-SS tests data, including the necessary code modifications and comparison of the code results with the experimental data. Based on the results, a discussion is presented on how the analysis supports design and transient calculations of the full-scale Holos-Quad microreactor. Also based on the results of this work, recommendations are made for future optimizations of the SPM-SS components and PDC model development needs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Experimental modal analysis of SSR1 cryomodule for numerical model tuning and validation

The present activity aims to test the Cryomodule SSR1 to validate the corresponding mixed multibody-finite element numerical model and to determine the range of frequencies in which the first natural modes of the structure lie. The experimental activity consisted of a hammer test of the cryomodule at an early assembly stage at which the internal parts, constituting the cold mass, are accessible and, thus, many accelerometers can be attached to the beam string. The comparison between the experimental results obtained for the sub-assembly and the numerical results obtained for the corresponding sub-model, derived from the previously developed complete model, allowed to assess the validity of the numerical model and to get feedback on the effectiveness of the placement of the sensors in capturing the dynamic response of the system during transportation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Field-tuned quantum renormalization of spin dynamics in the honeycomb lattice Heisenberg antiferromagnet YbCl 3

The basis for our understanding of quantum magnetism has been the study of elegantly simple model systems. However, even for the antiferromagnetic honeycomb lattice with isotropic spin interactions–one of the simplest model systems–a detailed understanding of quantum effects is still lacking. Here, using inelastic neutron scattering measurements of the honeycomb lattice material YbCl 3 , we elucidate how quantum effects renormalize the single-magnon and multimagnon excitations and how this renormalization can be tuned and ultimately driven to the classical limit by applying a magnetic field. Additionally, our work reveals that the quantum effects tuned by the magnetic field not only renormalize the magnetic excitations but also induce a distinctive sharp feature inside the multimagnon continuum. From a more general perspective, this result demonstrates that structures within magnetic continua can occur over a wide experimental parameter space and can be used as a reliable means of identifying quantum phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Is Betelgeuse the Outcome of a Past Merger?

We explore the possibility that the star α Orionis (Betelgeuse) is the outcome of a merger that occurred in a low-mass-ratio (q= $\mathcal{M}$ 2 /$\mathcal{M}$ 1 = 0.07–0.25) binary system some time in the past hundreds of thousands of years. To that goal, we present a simple analytical model to approximate the perturbed internal structure of a post-merger object following the coalescence of a secondary in the mass range 1–4 M ⊙ into the envelope of a 15–17 M ⊙ primary. We then compute the long-term evolution of post-merger objects for a grid of initial conditions and make predictions about their surface properties for evolutionary stages that are consistent with the observed location of Betelgeuse in the Hertzsprung–Russell diagram. We find that if a merger occurred after the end of the primary’s main-sequence phase, while it was expanding toward becoming a red supergiant star and typically with radius ∼200–300 R ⊙ , then its envelope is spun up to values that remain in a range consistent with Betelgeuse observations for thousands of years of evolution. We argue that the best scenario that can explain both the fast rotation of Betelgeuse and its observed large space velocity is one where a binary was dynamically ejected by its parent cluster a few million years ago and then subsequently merged. An alternative scenario in which the progenitor of Betelgeuse was spun up by accretion in a binary and released by the supernova explosion of the companion requires a finely tuned set of conditions but cannot be ruled out.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Reconfigurable structure and tunable transport in synchronized active spinner materials

Ensembles of actuated colloids are excellent model systems to explore emergent out-of-equilibrium structures, complex collective dynamics, and design rules for the next generation materials. Here, we demonstrate that ferromagnetic microparticles suspended at an air-water interface and energized by an external rotating magnetic field spontaneously form dynamic ensembles of synchronized spinners in a certain range of the excitation field parameters. Each spinner generates strong hydrodynamic flows, and collective interactions of the multiple spinners promote a formation of dynamic lattices. On the basis of experiments and simulations, we reveal structural transitions from liquid to nearly crystalline states in this novel active spinner material and demonstrate that dynamic spinner lattices are reconfigurable, capable of self-healing behavior and that the transport of embedded inert cargo particles can be remotely tuned by the parameters of the external excitation field. Our findings provide insights into the behavior of active spinner materials with reconfigurable structural order and tunable functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Spin-Transfer-Torque Oscillator with an Antiferromagnetic Exchange-Coupled Composite Free Layer

We present an antiferromagnetically exchange-coupled composite (soft and hard layers) spin torque oscillator (AF-ECC STO) and demonstrate its operation via both analytical and micromagnetic modeling. The operation exploits the exchange field due to the antiferromagnetic coupling between soft and hard sublayers of the free layer as well as on the easy-plane anisotropy of the soft sublayer. Optimized AF-ECC STO structures can generate large-amplitude magnetization oscillations, which can be tuned over a broad frequency range with precessions mostly generated by the soft layer. We demonstrate that the AF-ECC STO structure offers flexibility in current control of the oscillation frequency and magnetization angle for realistic material parameters.

42 ENGINEERING↗
DOE OSTI2023

Dark matter trigger for early dark energy coincidence

Current cosmological measurements present a persistent tension in the value of the current cosmic expansion rate, the Hubble constant, as inferred from cosmic microwave background (CMB) and large-scale structure (LSS) data compared to that inferred from the classical distance ladder. Early dark energy (EDE), whose cosmological role is localized in time around the epoch of matter-radiation equality just prior to the release of the CMB photons, is designed to resolve this "Hubble tension". However, the model introduces a new coincidence problem: Why should the EDE dynamics occur near matter-radiation equality if EDE is decoupled from both matter and radiation? The resolution of this problem may lie in an early dark sector (EDS), wherein the dark matter mass is dependent on the EDE scalar field. In this work, we construct such an EDS model and show that it naturally resolves the EDE coincidence problem at the background level without any fine-tuning of the coupling to dark matter or of the initial conditions. When fitting to current cosmological data, including that from the local distance ladder, CMB, and LSS, our EDS maximum-likelihood model performs comparably to EDE for resolving the Hubble tension. However, fitting the Planck CMB data requires a specific range of initial field positions to balance the scalar field fluctuations that drive acoustic oscillations, providing testable differences with other EDE models and a platform for future model-building.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effect of surface steps on chemical ordering in the subsurface of Cu(Au) solid solutions

Atomic steps are typically assumed to only influence surface phenomena of solids. In contrast, in this paper we show, using in-situ atomic-resolution electron microscopy observations and atomistic modeling, the pronounced effect from surface stepsin inducing compositional and structural evolution in the subsurface of a Cu(Au) solid solution. We find that Au surface segregation results in a stacked sequence of Cu-Au ordered phases in the subsurface. The presence of a monatomic step at the surface induces the formation of an anti-phase boundary that extends from the surface step to deeper layers by maintaining the same composition profile associated with each terrace. The bunching of surface steps induces chemical disordering of the Cu-Au ordered phases in the subsurface region of the bunched steps. These results demonstrate the instant propagation of surface dynamics of atomic steps into the subsurface region and can find broader applicability in utilizing surface defects to tune the composition and structure in the subsurface of alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure

Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1–1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Furthermore, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Transfer Learning Meets Embedded Correlated Wavefunction Theory for Chemically Accurate Molecular Simulations: Application to Calcium Carbonate Ion Pairing

Achieving chemical accuracy for molecular simulations remains a central challenge in computational chemistry. Here, we present an embedded correlated wavefunction transfer learning (ECW-TL) framework for accurately simulating molecular dynamics in the condensed phase. ECW-TL incorporates high-level electron exchange and correlation effects in ECW theory while preserving the training and computational efficiency of machine-learned interatomic potentials. We demonstrate the framework on Ca 2+ –CO 3 2– ion pairing in aqueous solution, a key process underlying CO 2 mineralization in seawater. As proof of principle, we first show that fine-tuning a DFT-revPBE-D3(BJ) baseline model with embedded-DFT-SCAN data reproduces the DFT-SCAN free-energy surface within 1 kcal/mol across all solvation states. Extending the framework to embedded MP2 and localized natural-orbital CCSD(T) further refines the free-energy profile, revealing the crucial role of exact electron exchange and correlation in determining ion-pair stability and structure. The computed ion-pair association free energy is in quantitative agreement with experimental measurements, further validating the accuracy of the ECW-TL framework. ECW-TL thus provides a general, data-efficient route for transferring CW accuracy to efficient simulations of complex aqueous and interfacial chemical processes.

cluster chemistry↗
DOE OSTI2024

De novo design of pH-responsive self-assembling helical protein filaments

Abstract Biological evolution has led to precise and dynamic nanostructures that reconfigure in response to pH and other environmental conditions. However, designing micrometre-scale protein nanostructures that are environmentally responsive remains a challenge. Here we describe the de novo design of pH-responsive protein filaments built from subunits containing six or nine buried histidine residues that assemble into micrometre-scale, well-ordered fibres at neutral pH. The cryogenic electron microscopy structure of an optimized design is nearly identical to the computational design model for both the subunit internal geometry and the subunit packing into the fibre. Electron, fluorescent and atomic force microscopy characterization reveal a sharp and reversible transition from assembled to disassembled fibres over 0.3 pH units, and rapid fibre disassembly in less than 1 s following a drop in pH. The midpoint of the transition can be tuned by modulating buried histidine-containing hydrogen bond networks. Computational protein design thus provides a route to creating unbound nanomaterials that rapidly respond to small pH changes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗