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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Block copolymer self-assembly derived mesoporous magnetic materials with three-dimensionally (3D) co-continuous gyroid nanostructure

Magnetic nanomaterials are gaining interest for their many applications in technological areas from information science and computing to next-generation quantum energy materials. While magnetic materials have historically been nanostructured through techniques such as lithography and molecular beam epitaxy, there has recently been growing interest in using soft matter self-assembly. In this work, a triblock terpolymer, poly(isoprene-block-styrene-block-ethylene oxide) (ISO), is used as a structure directing agent for aluminosilicate sol nanoparticles and magnetic material precursors to generate organic–inorganic bulk hybrid films with co-continuous morphology. After thermal processing into mesoporous materials, results from a combination of small angle X-ray scattering (SAXS) and scanning electron microscopy (SEM) are consistent with the double gyroid morphology. Nitrogen sorption measurements reveal a type IV isotherm with H1 hysteresis, and yield a specific surface area of around 200 m 2 g −1 and an average pore size of 23 nm. The magnetization of the mesostructured material as a function of applied field shows magnetic hysteresis and coercivity at 300 K and 10 K. Comparison of magnetic measurements between the mesoporous gyroid and an unstructured bulk magnetic material, derived from the identical inorganic precursors, reveals the structured material exhibits a coercivity of 250 Oe, opposed to 148 Oe for the unstructured at 10 K, and presence of remnant magnetic moment not conventionally found in bulk hematite; both of these properties are attributed to the mesostructure. This scalable route to mesoporous magnetic materials with co-continuous morphologies from block copolymer self-assembly may provide a pathway to advanced magnetic nanomaterials with a range of potential applications.

Chemistry↗
DOE OSTI2024

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗
DOE OSTI2024

Gradient Coding With Iterative Block Leverage Score Sampling

Gradient coding is a method for mitigating straggling servers in a centralized computing network that uses erasure-coding techniques to distributively carry out first-order optimization methods. Randomized numerical linear algebra uses randomization to develop improved algorithms for large-scale linear algebra computations. In this study, we propose a method for distributed optimization that combines gradient coding and randomized numerical linear algebra. The proposed method uses a randomized ℓ 2 -subspace embedding and a gradient coding technique to distribute blocks of data to the computational nodes of a centralized network, and at each iteration the central server only requires a small number of computations to obtain the steepest descent update. The novelty of our approach is that the data is replicated according to importance scores, called block leverage scores, in contrast to most gradient coding approaches that uniformly replicate the data blocks. Furthermore, we do not require a decoding step at each iteration, avoiding a bottleneck in previous gradient coding schemes. We show that our approach results in a valid ℓ 2 -subspace embedding, and that our resulting approximation converges to the optimal solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗
DOE OSTI2025

Stripline Block Sensor System

The Long Baseline Neutrino Facility requires a secondary sensor system to aid in the installation and replacement of the stripline blocks. These blocks are responsible for delivering large amounts of current to the horn and must be installed with high precision to avoid possible physical damage. There are many constraints due to the modules' surroundings, such as small clearances and a highly radioactive environment. Existing systems have already been implemented within the process; however, these systems offer limited information, leaving much risk during operations. This calls for a sufficiently accurate sensor system, which has a small space requirement and provides valuable information throughout the replacement period. A variety of methods and technologies were explored to provide an applicable approach to the issue. The proposed solution consisted of the use of retroreflective and target, however, it cannot provide positional feedback throughout the entire process. A proposed alternative utilizes a three-dimensional indoor positioning system to provide the operator with real-time positioning and rotational information. Sensors placed on the module and stripline would communicate with fixed receivers surrounding the target hall to provide precise positional feedback. However, this solution may still contain line-of-sight issues as well as installation complications due to the radioactive environment. Future work would consist of finding vendors capable of providing technology that fits our constraints, proof of concept tests for both solutions, implementation planning, and trials within the target hall itself. Due to its ability to provide continuous positional and rotational feedback, the indoor positioning system is the most suitable solution for accurately installing the stripline block.

Espinoza, David [Unlisted, US]↗
DOE OSTI2025

Self‐Assembled Membranes for High Ion Selectivity and Proton Blocking in Electrochemical Applications

Anion-exchange membranes (AEMs) with high anion/cation selectivity and exceptional proton-blocking ability are critical for applications such as bipolar membrane electrodialysis and electrochemical acid recovery. However, existing AEMs are constrained by a trade-off between ionic conductivity and selectivity, largely due to the intrinsic coupling between charge density and water content, and they suffer from excessive proton leakage facilitated by the Grotthuss hopping mechanism. In this work, poly(vinylimidazolium) membranes functionalized with long alkyl side chains that self-assemble into well-defined microphase-separated morphologies stabilized by hydrophobic and electrostatic interactions are reported. These unique structures localize the charge density along the polymer backbone to promote fast and selective ion transport. As a result, these membranes exhibit ionic conductivities and counter-ion diffusivities surpassing those of conventional homogeneous membranes, along with unprecedented counter-ion/co-ion selectivity and proton-blocking ability. These results establish a new design paradigm for high-performance, phase separated charged polymer membranes that overcome the limitations of homogeneous membranes, with broad implications for advanced electrochemical technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fabrication of nanoporous doped metal oxide coatings via selective infiltration of a block copolymer template: The case of Al-doped zinc oxide

Conductive nanoporous conformal coatings are important for various applications including touchscreens, displays, and electrochromic windows, though design of such coating with controlled porosity and composition remains challenging. We propose a sequential infiltration synthesis (SIS) method for the fabrication of nanoporous conductive aluminum-doped zinc oxide (AZO) films by infiltrating block copolymer (BCP) templates, specifically polystyrene-block-polyvinyl pyridine (PS-b-P4VP), with diethyl zinc and trimethyl aluminum precursors. Tunability of both porosity and electrical conductivity is achieved by precisely controlling the swelling behavior of the polymer templates and adjusting the number of SIS cycles. Further, our results reveal that porosity levels can reach up to 80 %, with resistivity as low as ~7.83 Ωcm. Using conductive atomic force microscopy (C-AFM) and Hall effect measurements, we show that lower concentrations of aluminum doping relative to zinc (around 1: 17) results in higher conductivity of the AZO films. Additionally, AZO is based on zinc oxide (ZnO) which is cost-efficient, abundant and less toxic than commonly used transparent conductive oxides such as indium tin oxide (ITO) and fluorine-doped tin oxide (FTO). Therefore, this novel approach opens new possibilities for creating highly porous, conformal, conductive AZO coatings with customizable porosity and composition, making them ideal candidates for diverse optoelectronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Synthetic Band Structure Engineering of Graphene Using Block Copolymer-Templated Dielectric Superlattices

Engineering the electronic band structure of two-dimensional (2D) materials by imposing spatially periodic superlattice (SL) potentials opens a pathway to unconventional electronics. Nanopatterning the gate electrode or surface dielectric near 2D crystals provides a powerful strategy for realizing electrostatically tunable “remote” SLs with flexibility in lattice design. Here, we demonstrate the effectiveness of block copolymer (BCP)-templated dielectric nanopatterns for fabricating etch-free high-grade metal oxide SLs. Alumina (AlO x ) nanopatterns with hexagonal symmetry and a 38 nm SL wavelength are produced as a model material by directly converting a self-assembled BCP film via block-selective vapor phase infiltration. Despite micrometer-scale rotational disorder inherent to BCP self-assembly, electronic transport measurements of graphene reveal replica Dirac points at zero field and Hofstadter mini-gaps under finite magnetic fields. These results indicate the successful formation of remote SL potentials in graphene resulting from optimized AlO x nanopattern fabrication to achieve consistent lattice symmetry and periodicity at a macroscopic scale. The findings of this study, combined with the versatile, scalable, and cost-effective nature of BCP nanopatterning, highlight the potential of BCP-templated nanostructures for remote SL engineering in 2D crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of pattern transfer process on roughness of block copolymer patterns from directed self-assembly

Block copolymer-directed self-assembly (DSA) remains promising for improving pattern quality and reducing the stochastic variations that challenge high numerical aperture extreme ultraviolet lithography. Equally critical is refining pattern transfer methods for accurately transferring the rectified DSA features to the underlying substrate. We compare two atomic layer deposition (ALD)-based techniques: sequential infiltration synthesis (SIS) and dry liftoff, applied to polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) DSA patterns. Both methods utilize aluminum oxide hard masks, with one synthesized through infiltration into the PMMA domains and the other through conformal ALD coating. High-resolution scanning electron micrographs were analyzed to measure line edge, width, and placement roughness for both the line (PMMA) and space (PS) features. Although both methods yielded similar overall 3σ rms roughness, they differed significantly in the frequency-dependent power spectral density (PSD) profiles. SIS reduced line placement roughness at length scales associated with the polymer pitch, but increased space width roughness at low frequencies, whereas dry liftoff mimicked the frequency content of the original guiding pattern. This study underscores the importance of PSD evaluation in selecting optimal pattern transfer strategies for specific applications.

Block copolymers↗
DOE OSTI2024

Scalable Multiphysics Block Preconditioning for Low Mach Number Compressible Resistive MHD with Application to Magnetic Confinement Fusion

This study investigates multiphysics block preconditioners that are critical in devising scalable Newton–Krylov iterative solvers for longer time-scale fully implicit fluid plasma models. The specific model of interest is the visco-resistive, low Mach number, compressible magnetohydrodynamics (MHD) model. This model describes the dynamics of conducting fluids in the presence of electromagnetic fields and can be used to study aspects of astrophysical phenomena, important science and technology applications, and basic plasma physics. The specific application of interest that motivates this study is the macroscopic simulation of longer time-scale stability and disruptions of magnetic confinement fusion devices, specifically the ITER Tokamak. The computational solution of the governing balance equations for mass, momentum, heat transfer, and magnetic induction for resistive MHD systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena as well as the significant range of time and length scales that the interactions of these physical mechanisms produce. To handle the range of time and spatial scales of interest, a fully implicit unstructured variational multiscale finite element formulation is employed. For the scalable solution of the Newton linearized systems, fully coupled block preconditioners are designed to leverage algebraic multigrid subsolves. In conclusion, results are presented for the strong and weak scaling of the method as well as the robustness of these techniques for a large range of Lundquist numbers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Synthesis of multicomponent oxygen evolution reaction coatings via block copolymer templating with vapor- and solution-phase precursors

Porous mixed transition metal oxide heterostructures are promising electrocatalysts due to their high surface area. However, achieving conformal multicomponent oxide coatings with controlled nanoscale architectures remains challenging. Here, we report a synthesis strategy that integrates solution-based swelling infiltration (SBI) with gas-phase sequential infiltration synthesis (SIS) in a block copolymer template to fabricate porous, high-surface-area, conformal mixed-oxide electrocatalytic coatings. In this approach, a PS75-P4VP25 block copolymer (BCP) film is first infiltrated with transition metal acetylacetonate precursors via SBI, followed by exposure to gas phase precursors of ZnO via SIS process. Thermal annealing of the infiltrated BCP films converts them into all-inorganic Fe–ZnO, Fe–Co–ZnO, and Fe–Ni–ZnO coatings. Electrochemical testing on 70 nm thick conformal coatings demonstrates promising oxygen evolution reaction (OER) activity in alkaline media, with mass-specific current densities up to 1.0 × 10 5 mA/g at an overpotential of 330 mV (vs. RHE) at ultralow loading (~0.005 g/cm 2 ). Among the compositions, Fe–Co–ZnO and amorphous Fe–Ni–ZnO show the best OER performance, delivering current densities of 2.00 and 3.04 mA/cm 2 , respectively, compared to 1.52 mA/cm 2 for Fe–ZnO.. This work establishes SBI–SIS as a versatile route for fabricating nm-thin, high-performance multicomponent oxide heterostructures on cost-efficient supports, enabling efficient catalyst utilization in electrochemical energy conversion application.

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

A block-spectral adaptive H-/$p$-refinement strategy for shock-dominated problems

An adaptive H-/p-refinement strategy using a novel sensor is devised and tested in a block-spectral compressible Euler code equipped with adaptive-mesh refinement (AMR) and high-order flux-reconstruction numerics. At each Gauss quadrature point (or solution point) within each spectral block (or mesh element) the discrete velocity jump ΔU = ∂U/∂y 1 Δy 1 + ∂V/∂y 2 Δy 2 + ∂W/∂y 3 Δy 3 is calculated and normalized by the local speed of sound, a. Here, the grid spacing, Δx i , is calculated in each direction as the distance between auxiliary Gauss-Lobatto points, staggered relative to the solution points. The polynomial order is increased from p = 0 to p = p max in regions of weak compression, (ΔU/a) crit < ΔU/a < 0 and kept at p = p max in regions of flow expansion ΔU/a ≥ 0, while staying at the H = 0 base mesh level. Regions experiencing strong compressions, i.e. ΔU/a < (ΔU/a) crit , are H-refined up to H = H max where H max is applied at the location of maximum compression, ΔU/a = min(ΔU/a) in the domain, while keeping p = 0 to guarantee robustness and monotonicity of the solution in the H refined region. The critical value of (ΔU/a) crit = -0.06 is found to effectively separate smooth and non-smooth solution regions, supported by a 1D detonation initiation test case in ideal gas and a shock-to-detonation transition in high explosives. Using this value, the Sod shock tube, Shu-Osher problem, double Mach reflection and a 2D detonation in a high-explosive are simulated with the proposed adaptive H-/p-refinement. In the Sod shock tube case, p-refinement resolves the (weak) contact discontinuity while H-refinement enhances the grid resolution in the shock exploiting the monotonicity of the p = 0 reconstruction. For the Shu-Osher problem, p-refinement captures the small-scale oscillations trailing the shock that would be otherwise attenuated, while H-refinement triggered by the ΔU-sensor appropriately tracks the shock. In the double Mach reflection problem, H-refinement confines the numerical diffusion around the reflected shock while p-refinement recaptures many physical features trailing the shock. Finally, in the 2D high-explosive detonation case, H-refinement follows the leading shock and resolves the curvature of the detonation wave, while p-refinement adds resolution to the trailing reaction zone. Finally, the proposed methodology is tested in a detonation-wave propagation test case in high-explosives with numerical predictions comparing favorably against experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part II: linesweep ALE rezoning for nonconformal block-structured AMR meshes

The simulation of flows presenting contact discontinuities, vorticity, and large variations in spatial scales can be performed in a framework coupling Arbitrary Lagrangian Eulerian (ALE) algorithms and Adaptive Mesh Refinement (AMR). This coupling requires adaptation of ALE rezoning techniques to meshes containing nonconformal nodes arising from both the AMR topology and the junction of mesh blocks. Here, in this paper, we present an ALE rezoning strategy that is compatible with such meshes, and that can also act as a disentangling algorithm. Emphasis is put on an algorithm that respects intrinsic Lagrangian mesh properties in order to preserve accuracy around discontinuities. To that end, we adapt the weighted linesweep algorithm to nonconformal block-structured AMR meshes. Then, we present control parameters introduced in the method for it to be applicable in practical situations. Notably, the method is coupled to a specific metric optimization in order to palliate some shortcomings of the linesweep method. Finally, numerical test cases are presented that feature the capabilities of the ALE-AMR algorithm for flows that present discontinuities, vorticity, and a variety of scales. Notably, we show that our ALE-AMR algorithm gives results at least similar to Euler-AMR, but provides better accuracy in cases where discontinuities are involved, thanks to a method that respects the Lagrangian features of the mesh. Additionally, it enables Euler-AMR-like computations on domains with temporally varying domain boundaries.

Adaptive mesh refinement↗
DOE OSTI2026

Engineering Assembly Kinetics and Line Roughness in Solvent Vapor-Annealed Block Copolymer/Homopolymer Blends

Block copolymer (BCP) directed self-assembly (DSA) is a promising route to enhance lithography resolution by multiplying nanopattern density and reducing feature roughness. Eliminating kinetically trapped self-assembly defects requires fast self-assembly. However, acceleration strategies like solvent vapor annealing or homopolymer blending broaden domain interfaces, implying a trade-off in increased feature roughness. In this work, we experimentally investigate this apparent dilemma between self-assembly kinetics and line roughness for solvent vapor-annealed thin films of a lamellar poly(styrene-block-2-vinylpyridine) (PS-b-P2VP) BCP blended with PS and P2VP homopolymers. Binary blends with PS or P2VP homopolymers and ternary blends incorporating both in equal weight fractions were solvent vapor annealed using acetone, a near-neutral solvent for PS and P2VP, followed by P2VP-selective vapor-phase infiltration with alumina (AlOx) and polymer etching. Binary blends with P2VP exhibit a modest kinetic enhancement but also higher line-edge and -width roughness due to the increased frequency of P2VP protrusions and bridge defects in the alumina line patterns. In contrast, binary blends with PS self-assemble noticeably faster, while domain asymmetry from the added PS homopolymer reduces roughness by curbing the number of alumina protrusions and bridge defects. Ternary blends maintain DSA line patterns across a wider composition window and, at higher homopolymer loadings, reduce roughness at length scales near the lamellar period, consistent with a reduced impact of intradomain compositional fluctuations. These findings provide important insights for codesigning blend compositions and process flows to achieve high-resolution, defect free patterns with minimal roughness through BCP DSA.

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

Morphology of poly-3-hexyl-thiophene blends with styrene–isoprene–styrene block-copolymer elastomers from X-ray and neutron scattering

The nano- and micron scale morphology of poly(3-hexylthiophene) (P3HT) and polystyrene-block-polyisoprene-block-polystyrene (PS–PI–PS) elastomeric blends is investigated through the use of ultra-small and small angle X-ray and neutron scattering (USAXS, SAXS, SANS). It is demonstrated that loading P3HT into elastomer matrices is possible with little distortion of the elastomeric structure up to a loading of ~5 wt%. Increased loadings of conjugated polymer is found to significantly distort the matrix structure. Changes in processing conditions are also found to affect the blend morphology with especially strong dependence on processing temperature. Processing temperatures above the glass transition temperature (T g ) of polystyrene and the melting temperature (T m ) of the conjugated polymer additive (P3HT) creates significantly more organized mesophase domains. P3HT blends with PS–PI–PS can also be flow-aligned through processing, which results in an anisotropic structure that could be useful for the generation of anisotropic properties (e.g. conductivity). Moreover, the extent of flow alignment is significantly affected by the P3HT loading in the PS–PI–PS matrix. The work adds insight to the morphological understanding of a complex P3HT and PS–PI–PS polymer blend as conjugated polymer is added to the system. Here, we also provide studies isolating the effect of processing changes aiding in the understanding of the structural changes in this elastomeric conjugated polymer blend.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Scalable quantum computational science: A perspective from block-encodings and polynomial transformations

Significant developments made in quantum hardware and error correction recently have been driving quantum computing toward practical utility. However, gaps remain between abstract quantum algorithmic development and practical applications in computational sciences. In this perspective article, we propose several properties that scalable quantum computational science methods should possess. We further discuss how block-encodings and polynomial transformations can potentially serve as a unified framework with the desired properties. Recent advancements on these topics are presented, including the construction and assembly of block-encodings, and various generalizations of quantum signal processing (QSP) algorithms to perform polynomial transformations. The scalability of QSP methods on parallel and distributed quantum architectures is also highlighted. Promising applications in simulation and observable estimation in chemistry, physics, and optimization problems are presented. We hope this perspective serves as a gentle introduction to state-of-the-art quantum algorithms for the computational science community and inspires future development of scalable quantum computational science methodologies that bridge theory and practice.

Bayesian inference↗
DOE OSTI2025

Blocking C-terminal processing of KRAS4b via a direct covalent attack on the CaaX-box cysteine

RAS is the most frequently mutated oncogene in cancer. RAS proteins show high sequence similarities in their G-domains but are significantly different in their C-terminal hypervariable regions (HVR). These regions interact with the cell membrane via lipid anchors that result from posttranslational modifications (PTM) of cysteine residues. KRAS4b is unique as it has only one cysteine that undergoes PTM, C185. Small molecule covalent modification of C185 would block any form of prenylation and subsequently inhibit attachment of KRAS4b to the cell membrane, blocking its biological activity. We translated this concept to the discovery and development of disulfide tethering screen hits into irreversible covalent modifiers of C185. These compounds inhibited proliferation of KRAS4b-driven mouse embryonic fibroblasts, but not cells driven by N-myristoylated KRAS4b that harbor a C185S mutation and are not dependent on C185 prenylation. Top–down proteomics was used to confirm target engagement in cells. These compounds bind in a pocket formed when the HVR folds back between helix 3 and 4 in the G-domain (HVR-α3-α4). This interaction can happen in the absence of small molecules as predicted by molecular dynamics simulations and is stabilized in the presence of C185 binders as confirmed by small-angle X-ray scattering and solution NMR. NOESY-HSQC, an NMR approach that measures internuclear distances of 6 Å or less, and structure analysis identified the critical residues and interactions that define the HVR-α3-α4 pocket. Further development of compounds that bind to this pocket could be the basis of a new approach to targeting KRAS cancers.

C185↗
DOE OSTI2025

Classical optimization with imaginary-time block encoding on quantum computers: The MaxCut problem

Optimization problems in finance, physics, and computer science are typically very hard to tackle in classical computing; quantum computing could help speed up computations and provide efficient methods for tackling large problems. Typically, to treat a problem with a quantum computer, the optimal solution is cast as the ground state of a diagonal Hamiltonian. Here, we develop a method, called imaginary-time evolution block encoding (ITE-BE), based on a recent imaginary-time algorithm, which requires no variational parameter optimization, as all parameters can be derived analytically from the target Hamiltonian. We also demonstrate that our method can be successfully combined with other quantum algorithms such as the quantum approximate optimization algorithm (QAOA). For illustration, here we study the MaxCut problem. We find that the QAOA ansatz increases the postselection success of ITE-BE, and shallow QAOA circuits, when boosted with ITE-BE, achieve better performance than deeper QAOA circuits. For the special case of the transverse initial state, we adapt our block-encoding scheme to allow for a deterministic application of the first layer of the circuit.

Zhong, Dawei [University of Southern California, L↗