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At least 433 records · Page 24

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DOE OSTI2026

Structural Mechanism of an Efficacy Photoswitch Targeting the β 2 ‐adrenergic Receptor

The field of photopharmacology develops light-responsive drugs that can modulate protein activity, enabling precise and dynamic investigations of their roles in health and disease. Adrenergic receptors are prominent targets for this approach because they are prototypical G protein-coupled receptors with high clinical relevance in bronchial and cardiovascular diseases. Here, we employed the azobenzene-based compound photoazolol-1 in combination with time-resolved serial crystallography at X-ray free-electron lasers to resolve the molecular mechanisms by which photoswitchable β-blockers modulate activity of the β 2 -adrenoceptor (β 2 AR). Time-resolved structures of the receptor bound to trans-photoazolol-1 (pre-photoconversion), a strained intermediate in the nanosecond range, and the fully photoisomerized cis-photoazolol-1 reveal how isomerization of the azobenzene moiety induces distinct conformational changes within the orthosteric ligand binding pocket. Within seconds, light-excited photoazolol-1 adopts a new binding pose, altering interactions with extracellular loop 2 and shifting the positions of transmembrane helices 5, 6, and 7. Functional assays of β 2 AR in cellular membranes show that photoazolol-1 acts as an efficacy photoswitch, changing from an inverse agonist to a neutral antagonist upon isomerization without leaving the binding pocket. In combination, these findings suggest a molecular mechanism for activity modulation via efficacy photoswitches and provide a framework for designing ligands that exploit light-driven transitions within the binding pocket to achieve spatiotemporal control of receptor function.

G protein-coupled receptors↗

DOE OSTI2026

pH‐Mediated Strong Metal‐Support Interaction Construction Through Dynamic Fermi Level Tuning

The metal–support interface is central to governing catalytic transformations. While strong metal–support interaction (SMSI) is an established strategy to tailor the morphology and electronic properties of supported metal catalysts, the role of interfacial charge redistribution in SMSI formation remains poorly understood and rarely leveraged. Here, in this study, we report a dual-stimuli approach that combines pH modulation with ultrasonication to mediate SMSI construction in aqueous solution through dynamic Fermi level tuning. By leveraging in situ pH-driven charge redistribution at the metal–support interface, we achieve controllable SMSI encapsulation of metal nanoparticles, as verified by electrochemical analysis, work function measurements, and x-ray-based techniques. The resulting catalysts exhibit tunable SMSI features and deliver enhanced activity and selectivity in hydrogenation reactions. This work establishes a facile strategy to modulate catalyst structure and electronic properties by exploiting Fermi level variation as a driving force, thereby advancing rational SMSI design and catalytic performance across diverse environments.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2024

A One‐Pot Biocatalytic Cascade to Access Diverse l ‐Phenylalanine Derivatives from Aldehydes or Carboxylic Acids

Abstract Nonstandard amino acids (nsAAs) that are l ‐phenylalanine derivatives with aryl ring functionalization have long been harnessed in natural product synthesis, therapeutic peptide synthesis, and diverse applications of genetic code expansion. Yet, to date, these chiral molecules have often been the products of poorly enantioselective and environmentally harsh organic synthesis routes. Here, we reveal the broad specificity of multiple natural pyridoxal 5′‐phosphate (PLP)‐dependent enzymes, specifically an l ‐threonine transaldolase, a phenylserine dehydratase, and an aminotransferase, toward substrates that contain aryl side chains with diverse substitutions. We exploit this tolerance to construct a one‐pot biocatalytic cascade that achieves high‐yield synthesis of 18 diverse l ‐phenylalanine derivatives from aldehydes under mild aqueous reaction conditions. We demonstrate the addition of a carboxylic acid reductase module to this cascade to enable the biosynthesis of l ‐phenylalanine derivatives from carboxylic acids that may be less expensive or less reactive than the corresponding aldehydes. Finally, we investigate the scalability of the cascade by developing a lysate‐based route for preparative‐scale synthesis of 4‐formyl‐ l ‐phenylalanine, a nsAA with a bio‐orthogonal handle that is not readily market‐accessible. Overall, this work offers an efficient, versatile, and scalable route with the potential to lower manufacturing costs and democratize synthesis for many valuable nsAAs.

Anderson, Shelby R. [Department of Chemical and Bi↗

DOE OSTI2025

Nonadditive CO 2 Uptake of Type II Porous Liquids Based on Imine Cages

Type II porous liquids can potentially exploit the fluidity of liquids and sorption properties of porous sorbents, yet CO 2 uptake in porous liquids is still poorly understood. Molecular simulations and experiments are used to examine CO 2 uptake by a prototypical porous liquid composed of porous organic cages (CC13) in 2′-hydroxyacetophenone (2′-HAP). The simulations are in reasonable agreement with experimental measurements of CO 2 solubility and provide unambiguous information on the partitioning of CO 2 within microenvironments in the liquid. Analysis of CO 2 dynamics is performed using these simulations, including assessing the self-diffusivity of CO 2 in both the neat solvent and porous liquid. This offers insights into the kinetics of CO 2 uptake and transport in type II porous liquids based on imine cages. Experiments with type II porous liquids formed by dissolving CC13 in three different size-excluded solvents show nonadditive CO 2 absorption relative to predictions based on ideal volume additivity. This nonadditive absorption behavior is also observed in simulations. Nonadditive CO 2 uptake is also demonstrated in type II porous liquids based on another imine-based porous cage, CC19.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Designing Spin‐Crossover Systems to Enhance Thermopower and Thermoelectric Figure‐of‐Merit in Paramagnetic Materials

Thermoelectric materials, capable of converting temperature gradients into electrical power, have been traditionally limited by a trade‐off between thermopower and electrical conductivity. This study introduces a novel, broadly applicable approach that enhances both the spin‐driven thermopower and the thermoelectric figure‐of‐merit (zT) without compromising electrical conductivity, using temperature‐driven spin crossover. Our approach, supported by both theoretical and experimental evidence, is demonstrated through a case study of chromium doped‐manganese telluride, but is not confined to this material and can be extended to other magnetic materials. By introducing dopants to create a high crystal field and exploiting the entropy changes associated with temperature‐driven spin crossover, we achieved a significant increase in thermopower, by approximately 136 μV K −1 , representing more than a 200% enhancement at elevated temperatures within the paramagnetic domain. Our exploration of the bipolar semiconducting nature of these materials reveals that suppressing bipolar magnon/paramagnon‐drag thermopower is key to understanding and utilizing spin crossover‐driven thermopower. These findings, validated by inelastic neutron scattering, X‐ray photoemission spectroscopy, thermal transport, and energy conversion measurements, shed light on crucial material design parameters. We provide a comprehensive framework that analyzes the interplay between spin entropy, hopping transport, and magnon/paramagnon lifetimes, paving the way for the development of high‐performance spin‐driven thermoelectric materials.

magnons↗

DOE OSTI2025

A Scalable Interior‐Point Gauss–Newton Method for PDE‐Constrained Optimization With Bound Constraints

Here, we present a scalable approach to solve a class of partial differential equation (PDE)‐constrained optimization problems with bound constraints. This approach utilizes a robust full‐space interior‐point (IP)‐Gauss–Newton optimization method. To cope with the poorly‐conditioned IP‐Gauss–Newton saddle‐point linear systems that need to be solved approximately, once per optimization step, we propose two spectrally related preconditioners. These preconditioners leverage the limited informativeness of data in regularized PDE‐constrained optimization problems. A block Gauss–Seidel preconditioner is proposed for the GMRES‐based solution of the IP‐Gauss–Newton linear systems. It is shown, for a large‐class of PDE‐ and bound‐constrained optimization problems, that the spectrum of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix is asymptotically independent of discretization and is not impacted by the ill‐conditioning that notoriously plagues interior‐point methods. We exploit symmetry of the IP‐Gauss–Newton linear systems and propose a regularization and log‐barrier Hessian preconditioner for the preconditioned conjugate gradient (PCG)‐based solution of the equivalent IP‐Gauss–Newton–Schur complement linear systems. The eigenvalues of the block Gauss–Seidel preconditioned IP‐Gauss–Newton matrix, that are not equal to one, are identical to the eigenvalues of the regularization and log‐barrier Hessian preconditioned Schur complement matrix. The scalability of the approach is demonstrated on two example problems. The numerical solution of these optimization problems is shown to require a discretization independent number of IP‐Gauss–Newton linear solves. Furthermore, the linear systems are solved in a discretization and IP ill‐conditioning independent number of preconditioned Krylov subspace iterations. The parallel scalability of the preconditioner, achieved via algebraic multigrid component solvers when applicable, and the aforementioned algorithmic scalability permits a parallel scalable means to compute solutions of a large class of PDE‐ and bound‐constrained problems.

PDE-constrained optimization↗

DOE OSTI2025

The structural basis for the broad aldehyde specificity of the aminoaldehyde dehydrogenase PauC from the human pathogen Pseudomonas aeruginosa

Abstract Despite significant differences in size and formal charge, the aldehyde dehydrogenasePaPauC (PA5312) fromPseudomonas aeruginosaPAO1 efficiently catalyzes the NAD + ‐dependent oxidation of the aminoaldehydes formed in polyamines degradation. We report here thatPaPauC also oxidizes 4‐guanidinebutyraldehyde, formed in one arginine degradation pathway, trimethylaminobutyraldehyde, of unknown metabolic origin, and indole‐3‐acetaldehyde, a precursor of the plant growth‐promoting hormone indoleacetic acid.PaPauC has been proposed as a potential target for combatingP. aeruginosa. However, understanding its structure–function relationships, crucial for developing specific inhibitors, is lacking. Using X‐ray crystallography, we identified the structural characteristics that determinePaPauC broad aldehyde specificity: a spacious aldehyde‐entrance tunnel and six active‐site residues. Docking simulations, site‐directed mutagenesis, and kinetic analyses support the interactions of Lys479 with glutamylated aminoaldehydes; Phe169, Trp176, and Phe467 with amino and guanidinium groups through cation–π interactions and with the indole group via NH–π and CH–π interactions; Asp459 with amino and indole groups; and Thr303 with amide and guanidinium groups. Exploiting the distinctive structural features of thePaPauC active site could aid in developing specific inhibitors to combatP. aeruginosainfections in humans and animals, as well as in preventing its colonization of plants, which are abundantP. aeruginosareservoirs and, therefore, a significant source of human infections.

Biochemistry & Molecular Biology↗

DOE OSTI2025

Structures of a synthetic antibody selected against and bound to the C‐terminal domain of Clostridium perfringens enterotoxin

Abstract Clostridium perfringensenterotoxin (CpE) causes cytotoxic gastrointestinal disease in mammalian epithelium by binding membrane protein receptors called claudins. Claudins direct the formation of cell/cell tight junctions through oligomerization and govern the transport of molecules between individual cells. CpE binds claudins through its C‐terminal domain (cCpE) and induces cytotoxicity through its N‐terminal domain. The non‐toxic cCpE is a useful tool to study claudins, tight junctions, and for translational applications, such as increasing the permeability of restrictive tissues like the blood–brain barrier or selective targeting of claudin overexpressing cancers. Conversely, there are no specialized molecular tools to study CpE or cCpE, or to modulate or inhibit their functions. We previously reported the development of synthetic antigen‐binding fragments (sFabs) that bind cCpE, and low‐resolution structures of them bound to claudin/cCpE complexes. Here, we determine high‐resolution structures of sFab COP‐2 bound to cCpE using X‐ray crystallography and cryogenic electron microscopy. The structures and biophysical findings provide the mechanism of COP‐2 binding to cCpE and the molecular determinants driving their interactions. These insights can advance the design of new antibody‐based tools from our COP‐2 scaffold to study or alter cCpE function and give rise to a “Trojan horse” strategy that exploits cCpE's tight junction barrier disrupting function to selectively deliver conjugated therapeutics through normally impermeable tissues.

Biochemistry & Molecular Biology↗

DOE OSTI2025

Efficient Simulation of Open Quantum Systems on NISQ Trapped‐Ion Hardware

Abstract Simulating open quantum systems, which interact with external environments, presents significant challenges on noisy intermediate‐scale quantum (NISQ) devices due to limited qubit resources and noise. In this study, an efficient framework is proposed for simulating open quantum systems on NISQ hardware by leveraging a time‐perturbative Kraus operator representation of the system's dynamics. This approach avoids the computationally expensive Trotterization method and exploits the Lindblad master equation to represent time evolution in a compact form, particularly for systems satisfying specific commutation relations. The efficiency of this method is demonstrated by simulating quantum channels, such as the continuous‐time Pauli channel and damped harmonic oscillators, on NISQ trapped‐ion hardware, including IonQ Harmony and Quantinuum H1‐1. Additionally, hardware‐agnostic error mitigation techniques are introduced, including Pauli channel fitting and quantum depolarizing channel inversion, to enhance the fidelity of quantum simulations. These results show strong agreement between the simulations on real quantum hardware and exact solutions, highlighting the potential of Kraus‐based methods for scalable and accurate simulation of open quantum systems on NISQ devices. This framework opens pathways for simulating more complex systems under realistic conditions in the near term.

Burdine, Colin [Department of Electrical and Compu↗

DOE OSTI2024

Towards accelerating particle-resolved direct numerical simulation with neural operators

In this paper, we present our ongoing work aimed at accelerating a particle-resolved direct numerical simulation model designed to study aerosol–cloud–turbulence interactions. The dynamical model consists of two main components—a set of fluid dynamics equations for air velocity, temperature, and humidity, coupled with a set of equations for particle (i.e., cloud droplet) tracing. Rather than attempting to replace the original numerical solution method in its entirety with a machine learning (ML) method, we consider developing a hybrid approach. We exploit the potential of neural operator learning to yield fast and accurate surrogate models and, in this study, develop such surrogates for the velocity and vorticity fields. We discuss results from numerical experiments designed to assess the performance of ML architectures under consideration as well as their suitability for capturing the behavior of relevant dynamical systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

2D Nitrogen‐Doped Graphene Materials for Noble Gas Separation

Abstract Noble gases, notably xenon, play a pivotal role in diverse high‐tech applications. However, manufacturing xenon is an inherently challenging task, due to its unique properties and trace abundance in the Earth's atmosphere. Consequently, there is a pressing need for the development of efficient methods for the separation of noble gases. Using mild fluorographene chemistry, nitrogen‐doped graphene (GNs) materials are synthesized with abundant aromatic regions and extensive nitrogen doping within the vacancies and holes of the aromatic lattice. Due to the organized interlayer “nanochannels”, nitrogen functional groups, and defects within the two‐dimensional (2D) structures, GNs exhibits effective selectivity for Xe over Kr at low pressure. This enhanced selectivity is attributed to the stronger binding affinity of Xe to GN compared to Kr. The adsorption is governed by London dispersion forces, as revealed by theoretical calculations using symmetry‐adapted perturbation theory (SAPT). Investigation of other GNs differing in nitrogen content, surface area, and pore sizes underscores the significance of nitrogen functional groups, defects, and interlayer nanochannels over the surface area in achieving superior selectivity. This work offers a new perspective on the design and fabrication of functionalized graphene derivatives, exhibiting superior noble gas storage and separation activity exploitable in gas production technologies.

Šedajová, Veronika↗

DOE OSTI2025

Decoding Antenna Behavior in Metal—Organic Frameworks

Metal–organic frameworks (MOFs) define a solid-state platform for developing artificial photosystems. Efficient anisotropic exciton migrations in these frameworks entail “antenna behavior” that can power up the distal interior reaction centers (RC), driving charge separation between donor-acceptor pairs. Reminiscent of the natural light-harvesting complex, such processes can achieve high quantum yield by exploiting the vast interior surface of the porous crystallites. It is important to understand the optimum positioning of the RC site relative to the anisotropic exciton migration path within these frameworks. The efficiency of such antenna behavior is probed here through Stern–Volmer (SV) type analysis with a series of node-anchored redox quenchers, ferrocene-carboxylate, ferrocene acetate, and dinitrobenzoate. Decoding various intrinsic processes, this work constructs a revised SV formalism in solid assembly that hosts ultrafast anisotropic exciton migration to account for the intrinsic exciton hopping rate from the extrinsic electron transfer rate, and the dimension of effective quenching. In conclusion, this transformative understanding can be applied to other relevant solid-state assemblies.

Saha, Bapan [Southern Illinois University, Carbond↗

DOE OSTI2024

Genome‐wide association studies on resistance to powdery mildew in cultivated emmer wheat

Abstract Powdery mildew, caused by the fungal pathogenBlumeria graminis(DC.) E. O. Speer f. sp.triticiEm. Marchal (Bgt), is a constant threat to global wheat (Triticum aestivumL.) production. Although ∼100 powdery mildew (Pm) resistance genes and alleles have been identified in wheat and its relatives, more is needed to minimizeBgt’s fast evolving virulence. In tetraploid wheat (Triticum turgidumL.), wild emmer wheat [T. turgidumssp.dicoccoides(Körn. ex Asch. & Graebn.) Thell.] accessions from Israel have contributed manyPmresistance genes. However, the diverse genetic reservoirs of cultivated emmer wheat [T. turgidumssp.dicoccum(Schrank ex Schübl.) Thell.] have not been fully exploited. In the present study, we evaluated a diverse panel of 174 cultivated emmer accessions for their reaction toBgtisolateOKS(14)‐B‐3‐1and found that 66% of accessions, particularly those of Ethiopian (30.5%) and Indian (6.3%) origins, exhibited high resistance. To determine the genetic basis ofBgtresistance in the panel, genome‐wide association studies were performed using 46,383 single nucleotide polymorphisms (SNPs) from genotype‐by‐sequencing and 4331 SNPs from the 9K SNP Infinium array. Twenty‐five significant SNP markers were identified to be associated withBgtresistance, of which 21 SNPs are likely novel loci, whereas four possibly represent emmer derivedPm4a,Pm5a,PmG16, andPm64. Most novel loci exhibited minor effects, whereas three novel loci on chromosome arms 2AS, 3BS, and 5AL had major effect on the phenotypic variance. This study demonstrates cultivated emmer as a rich source of powdery mildew resistance, and the resistant accessions and novel loci found herein can be utilized in wheat breeding programs to enhanceBgtresistance in wheat.

Genetics & Heredity↗

DOE OSTI2026

Sparsity Applications for Gradient‐Based Optimization of Wind Farms

Optimizing wind farms is essential for designing efficient energy systems, especially as farms grow larger and span multiple sites. However, this optimization becomes increasingly challenging due to the rising computational cost associated with more turbines. Gradient‐based optimization methods scale better than gradient‐free approaches for large problems, but the most computationally expensive component remains the calculation of gradients for the objective function and constraint Jacobians. To address this, we propose leveraging sparsity to accelerate gradient evaluations and reduce the size of the constraint Jacobian. Wind farms naturally exhibit sparsity—many turbines do not influence each other under certain wind directions. However, unlike traditional sparse problems with fixed patterns, wind farm sparsity is dynamic, requiring new strategies to handle changing interactions efficiently. This paper presents a study of sparsity in wind farm optimization and introduces several methods to exploit it. These strategies are tested on multiple farms using the analytic Cumulative Curl model, with gradients computed via automatic differentiation (AD). The same sparsity‐aware techniques are also applicable to finite difference (FD) methods, where they can yield even greater speedups due to the high cost of directional evaluations. Results show that sparse methods achieve up to a 10x speedup with less than ± 5% variance in optimized wake losses compared to traditional methods. These findings suggest that sparsity‐aware optimization not only maintains solution quality but also scales efficiently with farm size, enabling more comprehensive design exploration at reduced computational cost.

17 WIND ENERGY↗

DOE OSTI2025

Towards Automated Assessment of Vulnerability Exposures in Security Operations

Current approaches for risk analysis of software vulnerabilities using manual assessment and numeric scoring do not complete fast enough to keep pace with the maintenance work rate to patch and mitigate the vulnerabilities. This paper proposes a new approach to modeling software vulnerability risk in the context of the network environment and firewall configuration. In the approach, vulnerability features are automatically matched up with networking, target asset, and adversary features to determine whether adversaries can exploit a vulnerability. The ability of adversaries to reach a vulnerability is modeled by automatically identifying the network services associated with vulnerabilities through a pipeline of machine learning and natural language processing and automatically analyzing network reachability. Our results show that the pipeline can identify network services accurately. We also find that only a small number of vulnerabilities pose real risks to a system. However, if left unmitigated, adversarial reach to vulnerabilities may extend to nullify the effect of firewall countermeasures.

Huff, Philip↗

DOE OSTI2024

IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming

Task-based programming models are gaining traction in scientific computing. IRIS is a portable runtime system that exploits multiple heterogeneous programming systems and can discover available resources and manage multiple diverse programming systems (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, and OpenMP) simultaneously. It accounts for the constraints of task dependencies and provides customizable scheduling policies to map those tasks to heterogeneous devices. In this paper, we present new capabilities added to IRIS to improve its portability for heterogeneous programming, build-friendliness, and performance efficiency. The new additions include vendor-specific kernel support, a runtime system with a foreign function interface to eliminate writing wrapper or boilerplate code for heterogeneous kernels, an easy-to-use and configurable CMake-based build environment, automatic and efficient data transfers and orchestration, and the Hunter and DAGGER toolchains to evaluate IRIS’s task scheduling algorithms.

Miniskar, Narasinga Rao↗

DOE OSTI2024

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL

The clean energy transformation includes the integration of distributed energy resources with the power grid, which has led to a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Power grids infrastructure represents an operational technology environment that has become a system of systems, integrating heterogeneous devices which are both software-and hardware-intensive; as a result, there are increasing demands to exploit advances in the commodity of software-hardware infrastructures to improve energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, which leads to vulnerabilities and undesirable outcomes. The use of formal methods to characterize and prove system requirements removes ambiguity, increases automation, and provides high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system-level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗

DOE OSTI2025

Measurement of inclusive and differential cross sections of single top quark production in association with a W boson in proton-proton collisions at $\sqrt{s}$ = 13.6 TeV

The first measurement of the inclusive and normalised differential cross sections of single top quark production in association with a W boson in proton-proton collisions at a centre-of-mass energy of 13.6 TeV is presented. The data were recorded with the CMS detector at the LHC in 2022, and correspond to an integrated luminosity of 34.7 fb −1 . The analysed events contain one muon and one electron in the final state. For the inclusive measurement, multivariate discriminants exploiting the kinematic properties of the events are used to separate the signal from the dominant top quark-antiquark production background. A cross section of $82.3\pm 2.1{\left(\textrm{stat}\right)}_{-9.7}^{+9.9}\left(\textrm{syst}\right)\pm 3.3\left(\textrm{lumi}\right)$ pb is obtained, consistent with the predictions of the standard model. A fiducial region is defined according to the detector acceptance to perform the differential measurements. The resulting differential distributions are unfolded to particle level and show good agreement with the predictions at next-to-leading order in perturbative quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗