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DOE OSTI2016

Topological defect formation in rotating binary dipolar Bose–Einstein condensate

We investigate the topological defects and spin structures of a rotating binary Bose–Einstein condensate, which consists of both dipolar and scalar bosonic atoms confined in spin-dependent optical lattices, for an arbitrary orientation of the dipoles with respect to their plane of motion. Our results show that the tunable dipolar interaction, especially the orientation of the dipoles, can be used to control the direction of stripe phase and its related half-vortex sheets. In addition, it can also be used to obtain a regular arrangement of various topological spin textures, such as meron, circular and cross disgyration spin structures. We point out that such topological defects and regular arrangement of spin structures arise primarily from the long-range and anisotropic nature of dipolar interaction and its competition with the spin-dependent optical lattices and rotation. - Highlights: • Effects of both strength and orientation of the dipoles are discussed. • Various topological defects can be formed in different parameter regions. • Present one possible way to obtain regular arrangements of spin textures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Techno-economic assessment of pellets produced from steam pretreated biomass feedstock

Minimum production cost and optimum plant size are determined for pellet plants for three types of biomass feedstock e forest residue, agricultural residue, and energy crops. The life cycle cost from harvesting to the delivery of the pellets to the co-firing facility is evaluated. The cost varies from 95 to 105 t -1 for regular pellets and 146–156 t -1 for steam pretreated pellets. The difference in the cost of producing regular and steam pretreated pellets per unit energy is in the range of 2e3 GJ -1 . The economic optimum plant size (i.e., the size at which pellet production cost is minimum) is found to be 190 kt for regular pellet production and 250 kt for steam pretreated pellet. Furthermore, sensitivity and uncertainty analyses were carried out to identify sensitivity parameters and effects of model error.

09 BIOMASS FUELS↗

DOE OSTI2011

Numerical homogenization of concrete microstructures without explicit meshes

Life management of electric hydro or nuclear power plants requires to estimate long-term concrete properties on facilities, for obvious safety and serviceability reasons. Decades-old structures are foreseen to be operational for several more decades. As a large number of different concrete formulations are found in EDF facilities, empirical models based on many experiments cannot be an option for a large fleet of power plant buildings. To build predictive models, homogenization techniques offer an appealing alternative. To properly upscale creep, especially at long term, a rather precise description of the microstructure is required. However, the complexity of the morphology of concrete poses several challenges. In particular, concrete is formulated to maximize the packing density of the granular skeleton, leading to aggregates spanning several length scales with small inter particle spacings. Thus, explicit meshing of realistic concrete microstructures is either out of reach of current meshing algorithms or would produce a number of degrees of freedom far higher than the current generic FEM codes capabilities. This paper proposes a method to deal with complex matrix-inclusions microstructures such as the ones encountered at the mortar or concrete scales, without explicitly meshing them. The microstructure is superimposed to an independent mesh, which is a regular Cartesian grid. This inevitably yields so called 'gray elements', spanning across multiple phases. As the reliability of the estimate of the effective properties highly depends on the behavior affected to these gray elements, special attention is paid to them. As far as the question of the solvers is concerned, generic FEM codes are found to lack efficiency: they cannot reach high enough levels of discretization with classical free meshes, and they do not take advantage of the regular structure of the mesh. Thus, a specific finite differences/finite volumes solver has been developed. At first, generic off-the-shelf linear system solvers were used. To further improve the efficiency in terms of memory requirements, specific variants of the preconditioned conjugate gradient were implemented. This allowed to homogenize the conductivity of a concrete-like microstructure using more than 10{sup 9} degrees of freedom on a rather common hardware for 2010 (a PC embedding 48 GB of RAM). Taking benefit of the properties of the regular Cartesian grid we have also investigated a multi-level method to improve the CPU efficiency of the code.

36 MATERIALS SCIENCE↗

DOE OSTI2023

An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments' dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments' characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSCKSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e. g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures.

58 GEOSCIENCES↗

DOE OSTI2024

A robust spectral element implementation of the $k - τ$ RANS model in Nek5000/NekRS

The $k - ω$ Reynolds Averaged Navier Stokes (RANS) model is one of the industry standard approaches for modeling of turbulent flows. It performs better than the $k - ϵ$ model for low Reynolds number flows and is also more suitable for boundary layers with adverse pressure gradients. Major drawback of the model, however, is that the asymptotic value of $ω$ at the walls is singular, necessitating the use of a contrived “sufficiently” large value for $ω$ as the boundary condition for its transport equation. Here, this invariably leads to the solution being sensitive to near wall grid spacing. While an acceptable solution for low order (finite volume) methods, the excessive near wall gradients lead to persistent numerical stability issues in high order codes. To alleviate the problem, specifically in the context of the high order spectral element code Nek5000, a regularized $k - ω$ approach was formulated in our prior work (Tomboulides et al., 2018). The formulation, however, relies on the use of wall distance and its gradients for modeling the closure terms and can pose problems for simulations in complex geometries. This work presents a novel implementation of the $k - τ$ RANS model in Nek5000, where $τ = 1/ω$, eliminating the need for regularization, owing to the asymptotically bounded behavior of the source terms in the $τ$ transport equation, and also eliminating dependence on wall distance. Robustness and stability of the $k - τ$ model is ensured through implicit treatment of the source terms and their careful numerical implementation and demonstrated through several cases aimed at verification and validation. Studies include both canonical and engineering relevant problems, viz., turbulent channel flow, pipe flow, backward facing step, flow over NACA 0012 airfoil and flow in a T-junction. Results from the $k - τ$ model are shown to be consistent with regularized $k - ω$ model and also with the $k - ω$ SST model in OpenFOAM (for select studies). Comparison with experimental data is also shown, where available, to bolster validation efforts for the $k - τ$ model implementation through prediction of key turbulent quantities of interest.

Nek5000↗

DOE OSTI2015

Identification of subsurface structures using electromagnetic data and shape priors

We consider the inverse problem of identifying large-scale subsurface structures using the controlled source electromagnetic method. To identify structures in the subsurface where the contrast in electric conductivity can be small, regularization is needed to bias the solution towards preserving structural information. We propose to combine two approaches for regularization of the inverse problem. In the first approach we utilize a model-based, reduced, composite representation of the electric conductivity that is highly flexible, even for a moderate number of degrees of freedom. With a low number of parameters, the inverse problem is efficiently solved using a standard, second-order gradient-based optimization algorithm. Further regularization is obtained using structural prior information, available, e.g., from interpreted seismic data. The reduced conductivity representation is suitable for incorporation of structural prior information. Such prior information cannot, however, be accurately modeled with a gaussian distribution. To alleviate this, we incorporate the structural information using shape priors. The shape prior technique requires the choice of kernel function, which is application dependent. We argue for using the conditionally positive definite kernel which is shown to have computational advantages over the commonly applied gaussian kernel for our problem. Numerical experiments on various test cases show that the methodology is able to identify fairly complex subsurface electric conductivity distributions while preserving structural prior information during the inversion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

An extension of the localized artificial diffusivity method for immiscible and high density ratio flows

The localized artificial diffusivity (LAD) method is widely regarded as the preferred multi-material regularization scheme for the compact finite difference method, because it is conservative, easy to implement, and generally robust for a wide range of multi-material problems. However, traditional LAD methods face significant challenges when applied to flows with large density ratios and when maintaining thermodynamic equilibrium across material interfaces. These limitations arise from the formulation of the artificial diffusivity flux and the reliance on enthalpy diffusion for interface regularization. Additionally, traditional LAD methods struggle to ensure stability under large density ratio conditions, fail to maintain a finite interface thickness, and are therefore unsuitable for modeling immiscible interfaces. Here, in this work, we discuss the origins of these issues in traditional LAD methods and propose modifications which enable the simulation of large density ratio and immiscible flows. The proposed method targets the artificial diffusion fluxes at gradients and ringing in the volume fraction, rather than the mass fraction in traditional methods, to consistently regularize large density ratio interfaces. Furthermore, the proposed method introduces an artificial bulk density diffusion term to enforce equilibrium conditions across interfaces. To address the challenge of modeling immiscible flows, a conservative diffuse interface term is incorporated into the formulation to ensure a finite interface thickness. Specific consideration is taken in the design of the method to ensure that these crucial properties are maintained for N -material flows. The effectiveness of the proposed method is demonstrated through a series of canonical test cases, and its accuracy is validated by comparison with experimental data on micro-bubble collapse in water. These results highlight the method’s robustness and its ability to overcome the limitations of traditional LAD approaches.

Artificial diffusivity↗

DOE OSTI2013

Mechano-hydrothermal synthesis of Mg{sub 2}Al–NO{sub 3} layered double hydroxides

A mechano-hydrothermal method was developed to synthesize Mg{sub 2}Al–NO{sub 3} layered double hydroxide (LDH) from MgO, Al{sub 2}O{sub 3} and NaNO{sub 3} as starting materials. A two-step synthesis was conducted, that is, a mixture of MgO and Al{sub 2}O{sub 3} was milled for 1 h, followed by hydrothermal treatment with NaNO{sub 3} solution. The resulting LDHs were characterized by X-ray diffraction, transmission electron microscopy, scanning electron microscopy, Fourier transform infrared and elemental analyses. Pre-milling played a key role in the LDH formation during subsequent hydrothermal treatment. The process is advantageous in terms of low reaction temperature and short reaction time compared with the conventional hydrothermal method, and the target products are of high crystallinity, good dispersion and regular shape compared with the conventional mechanochemical method. - Graphical abstract: The novel mechano-hydrothermal route to synthesize LDH has advantages in low reaction temperature and short reaction time, and the target product was of high crystallinity, good dispersion and regular shape. Display Omitted - Highlights: • A mechano-hydrothermal route was developed for layered double hydroxide synthesis. • Synthesis could be achieved at low temperature and in a short time. • Resulting layered double hydroxide samples were well dispersed and of regular shape. • A dissolution–recrystallization mechanism was proposed for the formation process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

J-aggregation in porphyrin nanoparticles induced by diphenylalanine

In this report, L-diphenylalanine-decorated tetraphenylporphyrin (TPPtFF{sub C}) was synthesized and self-assembled into regular nano-architechtures. The morphology of the assemblies varied with the concentration of TPPtFF{sub C}. The absorption spectra of the nanoparticles show the Soret band merges with the Q bands and redistributes with great red-shift, indicative of the formation of J-aggregates of the porphyrin molecules. The fluorescence emission of the nanoparticles is merged and red-shifted to near-infrared region. Studies of absorption and fluorescence spectra reveal an indispensible role of diphenylalanine group in the formation of J-aggregates. The Raman spectra disclose that diprotonation of the porphyrin core contributes to delocalized coherent excited states in the nanoparticles. The positive cotton effect in circular dichroism spectra corresponding to the Soret band of TPPtFF{sub C} in solution confirms the formation of J-aggregates with right-handed chirality of the dipole moment. This report will shed light on the rational design of porphyrin-peptide conjugates to mimic naturally light-harvesting complexes. - Graphical abstract: TPPtFF{sub C} was synthesized and self-assembled into regular nano-architectures. Photophysical property studies of the nanoparticles indicate the porphyrin molecules form typical J-aggregates. The diprotonation of the porphyrin core and the FF group play an indispensible role in the formation of J-aggregates. - Highlights: • Porphyrin-peptide conjugates were self-assembled into regular nanostructures. • The photophysical properties of the nanoparicles indicate formation of typical J-aggregates. • The Raman spectra confirm that diprotonation of the porphyrin core contributes to exciton coherence in the nanoparticles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

An experimental comparison of various methods of nearfield acoustic holography

An experimental comparison of four different methods of nearfield acoustic holography (NAH) is presented in this study for planar acoustic sources. The four NAH methods considered in this study are based on: (1) spatial Fourier transform, (2) equivalent sources model, (3) boundary element methods and (4) statistically optimized NAH. Two dimensional measurements were obtained at different distances in front of a tonal sound source and the NAH methods were used to reconstruct the sound field at the source surface. Reconstructed particle velocity and acoustic pressure fields presented in this study showed that the equivalent sources model based algorithm along with Tikhonov regularization provided the best localization of the sources. Reconstruction errors were found to be smaller for the equivalent sources model based algorithm and the statistically optimized NAH algorithm. Effect of hologram distance on the performance of various algorithms is discussed in detail. The study also compares the computational time required by each algorithm to complete the comparison. Four different regularization parameter choice methods were compared. The L-curve method provided more accurate reconstructions than the generalized cross validation and the Morozov discrepancy principle. Finally, the performance of fixed parameter regularization was comparable to that of the L-curve method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Effects of porosity on corrosion resistance of Mg alloy foam produced by powder metallurgy technology

Magnesium alloy foams have the potential to serve as structural material for regular light-weight applications as well as for biodegradable scaffold implants. However, their main disadvantage relates to the high reactivity of magnesium and consequently their natural tendency to corrode in regular service conditions and in physiological environments. The present study aims at evaluating the effect of porosity on the corrosion resistance of MRI 201S magnesium alloy foams in 0.9% NaCl solution and in phosphate buffer saline solution as a simulated physiological electrolyte. The magnesium foams were produced by powder metallurgy technology using space-holding particles to control the porosity content. Machined chips were used as raw material for the production of Mg alloy powder by milling process. The microstructure of the foams was examined using optical and scanning electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy analysis. The corrosion behavior was evaluated by immersion test and potentiodynamic polarization analysis. The results obtained clearly demonstrate that the porosity has a significant effect on the corrosion resistance of the tested foams. Foams with 14–19% porosity have a corrosion rate of 4–10 mcd and 7–15 mcd in NaCl and phosphate buffer saline solution, respectively, compared to only 0.10 mcd for the same alloy in as cast conditions. This increased corrosion degradation of the Mg foams by more than one order of magnitude compared to the cast alloy may limit their potential application in regular and physiological environments. - Highlights: • Porosity has a detrimental effect on corrosion resistance of MRI 201S Mg foams. • 14–19% porosity increases the corrosion rate by more than one order of magnitude. • Accelerated corrosion limits the use of foams in regular/physiological environments.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Surface defects on the Gd{sub 2}Zr{sub 2}O{sub 7} oxide films grown on textured NiW technical substrates by chemical solution method

Epitaxial growth of oxide thin films has attracted much interest because of their broad applications in various fields. In this study, we investigated the microstructure of textured Gd{sub 2}Zr{sub 2}O{sub 7} films grown on (001)〈100〉 orientated NiW alloy substrates by a chemical solution deposition (CSD) method. The aging effect of precursor solution on defect formation was thoroughly investigated. A slight difference was observed between the as-obtained and aged precursor solutions with respect to the phase purity and global texture of films prepared using these solutions. However, the surface morphologies are different, i.e., some regular-shaped regions (mainly hexagonal or dodecagonal) were observed on the film prepared using the as-obtained precursor, whereas the film prepared using the aged precursor exhibits a homogeneous structure. Electron backscatter diffraction and scanning electron microscopy analyses showed that the Gd{sub 2}Zr{sub 2}O{sub 7} grains present within the regular-shaped regions are polycrystalline, whereas those present in the surrounding are epitaxial. Some polycrystalline regions ranging from several micrometers to several tens of micrometers grew across the NiW grain boundaries underneath. To understand this phenomenon, the properties of the precursors and corresponding xerogel were studied by Fourier transform infrared spectroscopy and coupled thermogravimetry/differential thermal analysis. The results showed that both the solutions mainly contain small Gd−Zr−O clusters obtained by the reaction of zirconium acetylacetonate with propionic acid during the precursor synthesis. The regular-shaped regions were probably formed by large Gd−Zr−O frameworks with a metastable structure in the solution with limited aging time. This study demonstrates the importance of the precise control of chemical reaction path to enhance the stability and homogeneity of the precursors of the CSD route. - Highlights: •We investigate microstructure of Gd{sub 2}Zr{sub 2}O{sub 7} films grown by a chemical solution route. •The aging effect of precursor solution on formation of surface defect was thoroughly studied. •Gd−Zr−O clusters are present in the precursor solutions.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Fragmentation analysis of a bar with the Lip-field approach

The Lip-field approach was introduced in Moës and Chevaugeon (2021) as a new way to regularize softening material models. It was tested in 1D quasistatic in Moës and Chevaugeon (2021) and 2D quasistatic in Chevaugeon and Moës (2021): this paper extends it to 1D dynamics, on the challenging problem of dynamic fragmentation. The Lip-field approach formulates the mechanical problem to be solved as an optimization problem, where the incremental potential to be minimized is the non-regularized one. Spurious localization is prevented by imposing a Lipschitz constraint on the damage field. Here, the displacement and damage field at each time step are obtained by a staggered algorithm, that is the displacement field is computed for a fixed damage field, then the damage field is computed for a fixed displacement field. Indeed, these two problems are convex, which is not the case of the global problem where the displacement and damage fields are sought at the same time. The incremental potential is obtained by equivalence with a cohesive zone model, which makes material parameters calibration simple. A non-regularized local damage equivalent to a cohesive zone model is also proposed. It is used as a reference for the Lip-field approach, without the need to implement displacement jumps. These approaches are applied to the brittle fragmentation of a 1D bar with randomly perturbed material properties to accelerate spatial convergence. Both explicit and implicit dynamic implementations are compared. Favorable comparison to several analytical, numerical and experimental references serves to validate the modeling approach.

36 MATERIALS SCIENCE↗

DOE OSTI2013

Evaluation of radiosurgery techniques–Cone-based linac radiosurgery vs tomotherapy-based radiosurgery

Performances of radiosurgery of intracranial lesions between cone-based Linac system and Tomotherapy-based system were compared in terms of dosimetry and time. Twelve patients with single intracranial lesion treated with cone-based Linac radiosurgery system from 2005 to 2009 were replanned for Tomotherapy-based radiosurgery treatment. The conformity index, homogeneity index (HI), and gradient score index (GSI) of each case was calculated. The Wilcoxon matched-pair test was used to compare the 3 indices between both systems. The cases with regular target (n = 6) and those with irregular target (n = 6) were further analyzed separately. The estimated treatment time between both systems was also compared. Significant differences were found in HI (p = 0.05) and in GSI (p = 0.03) for the whole group. Cone-based radiosurgery was better in GSI whereas Tomotherapy-based radiosurgery was better in HI. Cone-based radiosurgery was better in conformity index (p = 0.03) and GSI (p = 0.03) for regular targets, whereas Tomotherapy-based radiosurgery system performed significantly better in HI (p = 0.03) for irregular targets. The estimated total treatment time for Tomotherapy-based radiosurgery ranged from 24 minutes to 35 minutes, including 15 minutes of pretreatment megavoltage computed tomography (MVCT) and image registration, whereas that for cone-based radiosurgery ranged from 15 minutes for 1 isocenter to 75 minutes for 5 isocenters. As a rule of thumb, Tomotherapy-based radiosurgery system should be the first-line treatment for irregular lesions because of better dose homogeneity and shorter treatment time. Cone-based Linac radiosurgery system should be the treatment of choice for regular targets because of the better dose conformity, rapid dose fall-off, and reasonable treatment time.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2018

How Accurate Is Density Functional Theory at Predicting Dipole Moments? An Assessment Using a New Database of 200 Benchmark Values

We present that dipole moments are a simple, global measure of the accuracy of the electron density of a polar molecule. Dipole moments also affect the interactions of a molecule with other molecules as well as electric fields. To directly assess the accuracy of modern density functionals for calculating dipole moments, we have developed a database of 200 benchmark dipole moments, using coupled cluster theory through triple excitations, extrapolated to the complete basis set limit. This new database is used to assess the performance of 88 popular or recently developed density functionals. The results suggest that double hybrid functionals perform the best, yielding dipole moments within about 3.6-4.5% regularized RMS error versus the reference values - which is not very different from the 4% regularized RMS error produced by coupled cluster singles and doubles. Many hybrid functionals also perform quite well, generating regularized RMS errors in the 5-6% range. Lastly, some functionals, however, exhibit large outliers, and local functionals in general perform less well than hybrids or double hybrids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Where Are White Roofs More Effective in Cooling the Surface?

Solar reflective roofs (also called white or cool roofs) are a common heat mitigation strategy. By reflecting more sunlight than regular roofs, cool roofs experience lower surface temperatures and produce less heating of the surrounding air. The effectiveness of cool roofs, quantified by the surface temperature difference between cool roofs and regular roofs ??????, is known to vary spatially. A common perception is that ?????? is controlled by solar radiation that reaches the roof surface. Here we use an Earth System Model and a surface energy balance model to show that the spatial variability of ??????, when normalized by the albedo difference between cool roofs and regular roofs (????), is in fact more controlled by an energy distribution factor that encodes the efficiencies of surface energy balance components in dissipating heat. Our results suggest that painting the roof white is more effective in reducing the roof surface temperature when the roof has less water holding capacity and smaller thermal admittance and is located in places with more solar radiation, less precipitation, and lower wind speed.

Wang, Linying↗

DOE OSTI2025

Space‐Time Causal Discovery in Earth System Science: A Local Stencil Learning Approach

Causal discovery tools enable scientists to infer meaningful relationships from observational data, spurring advances in fields as diverse as biology, economics, and climate science. Despite these successes, the application of causal discovery to space-time systems remains immensely challenging due to the high-dimensional nature of the data. For example, in climate sciences, modern observational temperature records over the past few decades regularly measure thousands of locations around the globe. To address these challenges, we introduce Causal Space-Time Stencil Learning (CaStLe), a novel meta-algorithm for discovering causal structures in complex space-time systems. CaStLe leverages regularities in local space-time dependencies to learn governing global dynamics. This local perspective eliminates spurious confounding and drastically reduces sample complexity, making space-time causal discovery practical and effective. For causal discovery, CaStLe flexibly accepts any appropriately adapted time series causal discovery algorithm to recover local causal structures. These advances enable causal discovery of geophysical phenomena that were previously unapproachable, including non-periodic, transient phenomena such as volcanic eruption plumes. Regularities in local space-time dependencies are transformed into informative spatial replicates, which actually improve CaStLe's performance when applied to ever-larger spatial grids. We successfully apply CaStLe to discover the atmospheric dynamics governing the climate response to the 1991 Mount Pinatubo volcanic eruption. We provide validation experiments to demonstrate the effectiveness of CaStLe over existing causal-discovery frameworks on a range of geophysics-inspired benchmarks while identifying the method's limitations and domains where its assumptions may not hold.

Nichol, J. Jake [Univ. of New Mexico, Albuquerque,↗

DOE OSTI2025

Bond-centric modular design of protein assemblies

Directional interactions that generate regular coordination geometries are a powerful means of guiding molecular and colloidal self-assembly, but implementing such high-level interactions with proteins remains challenging due to their complex shapes and intricate interface properties. Here we describe a modular approach to protein nanomaterial design inspired by the rich chemical diversity that can be generated from the small number of atomic valencies. We design protein building blocks using deep learning-based generative tools, incorporating regular coordination geometries and tailorable bonding interactions that enable the assembly of diverse closed and open architectures guided by simple geometric principles. Experimental characterization confirms the successful formation of more than 20 multicomponent polyhedral protein cages, two-dimensional arrays and three-dimensional protein lattices, with a high (10%–50%) success rate and electron microscopy data closely matching the corresponding design models. Due to modularity, individual building blocks can assemble with different partners to generate distinct regular assemblies, resulting in an economy of parts and enabling the construction of reconfigurable networks for designer nanomaterials.

Biomaterials – proteins↗