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At least 829 records · Page 46

Random coordinate descent: A simple alternative for optimizing parameterized quantum circuits

Variational quantum algorithms rely on the optimization of parameterized quantum circuits in noisy settings. The commonly used back-propagation procedure in classical machine learning is not directly applicable in this setting due to the collapse of quantum states after measurements. Thus, gradient estimations constitute a significant overhead in a gradient-based optimization of such quantum circuits. This paper introduces a random coordinate descent algorithm as a practical and easy-to-implement alternative to the full gradient descent algorithm. This algorithm only requires one partial derivative at each iteration. Motivated by the behavior of measurement noise in the practical optimization of parameterized quantum circuits, this paper presents an optimization problem setting that is amenable to analysis. Under this setting, the random coordinate descent algorithm exhibits the same level of stochastic stability as the full gradient approach, making it as resilient to noise. The complexity of the random coordinate descent method is generally no worse than that of the gradient descent and can be much better for various quantum optimization problems with anisotropic Lipschitz constants. Theoretical analysis and extensive numerical experiments validate our findings. Published by the American Physical Society 2024

Ding, Zhiyan (ORCID:000000018863403X)↗

Spatial Optimization of Multiscale Biorefinery Deployment for a Diversified Bioeconomy in the United States

Strategic biorefinery siting is critical for a diversified bioeconomy, yet industry, policy, and research often focus on either large-scale biofuel plants or smaller-scale specialty bioproduct facilities, with limited coordination across scales. We address this gap by modeling biorefinery deployment spanning a 28-fold difference in capacity. We developed an open-source, spatially explicit framework integrating techno-economic analysis with logistics and refinery cost surrogate models to evaluate multiscale miscanthus-derived biorefineries across the rainfed U.S. for the production of ethanol, succinic acid, lactic acid, potassium sorbate, and acrylic acid. Overall costs change little as feedstock density increases, while transport distances decrease by ∼30 to 67% (∼100 km) and siting flexibility improves. Specifically, a 5-fold feedstock density increase (2% to 10% of suitable land) reduces minimum selling prices by <10% (e.g., 0.27 USD·gal –1 for ethanol). This limited economic sensitivity suggests dense planting is not required for competitive deployment, particularly for smaller-scale facilities. Representing collection areas as irregular rather than circular expands the feasible space under low-density scenarios. While large-scale refineries anchor regional supply chains, smaller facilities retain spatial flexibility even when large refineries are established. These findings highlight the importance of spatial representation and multiscale coordination for robust, regionally tailored biomanufacturing networks to advance renewable carbon integration without extensive land conversion.

biorefinery siting↗

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Firesense: Supporting Operational Partners Through Co-Development

Fire is a natural disturbance and fundamental to many ecosystems, but, across the United States and many areas globally, fires have become more common, larger and more likely to occur at the same time. This has the potential to challenge resource allocation and response and requires coordinated integration of technology and tools at the spatial and temporal scales required by practitioners who make wildland fire management decisions. In the US wildfire is currently managed across state, federal, and tribal agencies who leverage various datasets to guide management decisions. FireSense, a NASA Science Mission Directorate project, aims to develop and deliver trailblazing technology and tools for use before, during, and after wildland fires by working together with land managers and practitioners. FireSense is focused on turning information into solutions by expanding partnerships and collaborations with operational agencies to inform and deliver data and technology to support decisions for wildland fire management. Through implementation across the US and with campaign activities in a variety of landscapes, coordinated research and development work will build upon adaptive and use-inspired approaches that can be put into operation. By leveraging and complementing partner activities through coordinated investment, we support a more comprehensive and cohesive response that can advance fire science to better understand fire behavior and effects through integrated measurement, monitoring and modeling. We present updates from in-progress technology development and field campaigns within the US which include sampling and application across scales with information from multiple sensors collocated with field measurements and highlighting the importance of cross-scale observations during the fire lifecycle. Coordinated investment in new science and technology for the complete fire lifecycle supports a comprehensive and cohesive fire response that help to overcome barriers and anticipate and manage the new reality of extreme fires in a warming world.

Jacquelyn Shuman↗

Method for Real-Time State Estimation of Structural Modes for an Aeroelastic Wind Tunnel Model

A method for estimating displacements, velocities, and accelerations of structural modes in generalized coordinates from measured sensor data in real time is developed and demonstrated. Data from conventional strain gauges and fiber optic strain sensors (FOSS) were combined with strain mode shapes to produce least-squares estimates of the structural mode displacements. Similarly, accelerometer data were combined with displacement mode shapes to estimate structural mode accelerations. Estimates were then combined using a Kalman filter to refine the displacement estimates and produce structural mode velocity estimates. The approach was demonstrated using simulation data for the NASA-Boeing collaboration called the Integrated Adaptive Wing Technology Maturation (IAWTM) project in both a stable open-loop condition and an unstable condition where estimated displacement and velocity states were used for feedback control. Results supported the feasibility of using this approach for feedback control and system identification applications for wind tunnel tests.

Aeroservoelasticity↗

FRMAC Laboratory Analysis Manual Volume 1, Revision 0

The Federal Radiological Monitoring and Assessment Center (FRMAC) is an operational center, available on request by the Department of Homeland Security (DHS) to respond to nuclear and radiological incidents as described in the National Response Framework (NRF). Under the Federal Interagency Operational Plan for Response and Recovery’s Nuclear/Radiological Annex, the U.S. Department of Energy (DOE) has the responsibility to maintain the operational readiness of the FRMAC during the emergency phase of an event. FRMAC is initially established and managed by the Nuclear Emergency Support Team (NEST) and serves as an interagency operations center with representatives from various federal, state, and local radiological response organizations. The purpose of the FRMAC is to assist state, local, tribal, and territorial governments (SLTT) in their mission to protect the health and well-being of their citizens with: • Verified radiation measurements. • Interpretations of radiation distributions based on Environmental Protection Agency (EPA), Food and Drug Administration (FDA), or local Protective Action Guidelines (PAGs). • Characterization of overall radiological conditions. Once a declaration to respond to a radiological emergency has been made, the National Nuclear Security Administration (NNSA) Headquarters will coordinate the response in consultation with the cognizant NNSA Regional Coordinating Office (RCO). Each of the eight RCOs maintain a 24-hour response capability for radiological emergencies that may occur in states served by its region. When a FRMAC is established, it operates under the parameters of the Incident Command System (ICS), as defined in the National Incident Management Systems (NIMS) construct. The Consequence Management Home Team (CMHT) will be activated immediately during normal business hours (Pacific Time Zone), and within two hours otherwise. The Consequence Management Response Team (CMRT) is prepared for deployment within six hours after activation. Along with the assets, FRMAC provides an operational framework for coordinating of all federal off-site radiological monitoring and assessment activities during a response to a radiological emergency to support the coordinating agency and SLTT governments. Potential radiological emergencies that fall within FRMAC vary widely in terms of the area affected, the nature of the contamination, and the scope of the government’s response. Detonation of a nuclear device, accidental release of radiation from a nuclear power plant, and a terrorist threat are just a few of the many possible scenarios FRMAC must be prepared to address. Through all this, supporting the state, local, and tribal organizations in the protection of the public remains the primary goal of the federal response.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Evolution of Palladium Single Atoms on Anatase Titania Support Determines the Reverse Water–Gas Shift Activity

Research interest in single-atom catalysts (SACs) has been continuously rising. However, the lack of understanding of the dynamic behaviors of SACs during applications hinder catalyst development and mechanistic understanding. Herein, we report on the evolution of active sites over Pd/TiO 2 -anatase SAC (Pd 1 /TiO 2 ) in the reverse water-gas shift (rWGS) reaction. Combining kinetics, in-situ characterization, and theory, we show that at T ≥ 350 °C, the reduction of TiO 2 by H 2 alters the coordination environment of Pd, creating Pd sites with partially cleaved Pd-O interfacial bonds and a unique electronic structure that exhibit high intrinsic rWGS activity through the carboxyl pathway. The activation by H 2 is accompanied by the partial sintering of single Pd atoms (Pd 1 ) into disordered, flat, ~1 nm diameter clusters (Pd n ). The highly active Pd sites in the new coordination environment under H 2 are eliminated by oxidation, which, when performed at high temperature, also re-disperses Pd n and facilitates the reduction of TiO 2 . In contrast, Pd 1 sinters into crystalline, ~5 nm particles (Pd NP ) during CO treatment, deactivating Pd 1 /TiO 2 . During the rWGS reaction, the two Pd evolution pathways co-exist. The activation by H 2 dominates, leading to the increasing rate with time-on-stream, and steady-state Pd active sites similar with the ones formed under H 2 . Finally, this work demonstrates how the coordination environment and nuclearity of metal sites on a SAC evolve during catalysis and pre-treatments, and how their activity is modulated by these behaviors. These insights on SAC dynamics and structure-function relationship are valuable to mechanistic understanding and catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Method and apparatus for autonomous, in-receiver prediction of GNSS ephemerides

Methods and apparatus for autonomous in-receiver prediction of orbit and clock states of Global Navigation Satellite Systems (GNSS) are described. Only the GNSS broadcast message is used, without need for periodic externally-communicated information. Earth orientation information is extracted from the GNSS broadcast ephemeris. With the accurate estimation of the Earth orientation parameters it is possible to propagate the best-fit GNSS orbits forward in time in an inertial reference frame. Using the estimated Earth orientation parameters, the predicted orbits are then transformed into Earth-Centered-Earth-Fixed (ECEF) coordinates to be used to assist the GNSS receiver in the acquisition of the signals. GNSS satellite clock states are also extracted from the broadcast ephemeris and a parameterized model of clock behavior is fit to that data. The estimated modeled clocks are then propagated forward in time to enable, together with the predicted orbits, quicker GNSS signal acquisition.

Bar-Sever, Yoaz E.↗

A Theory of Ultrafast Charge Transfer Relaxation with Non-Innocent Solvent Molecules

In this work we revisit the photodynamics of tetracyanoethylene-hexamethylbenzene (TCNE- HMB), the molecular complex studied by Hochstrasser et al. [J. Chem. Phys. 100, 4797–4810, 1994] that has long challenged the applicability of Marcus’s theory of elec- tron transfer for predicting photochemical reactions. Using a novel black-box electronic structure algorithm (time-dependent density functional theory with one double, TD- DFT-1D) to efficiently run molecular dynamics that can treat charge recombination, we run ab initio surface hopping molecular dynamics and confirm that, for a polar solvent, charge recombination rates can be incredibly fast (indeed faster than the sol- vent relaxation time); for non-polar solvents, the rate is much slower. We demonstrate that, although Marcus theory cannot be directly applied, these nonequilibrium (and sometimes incredibly fast) photoexcited dynamics can be effectively explained within a two-state model without any evidence of a transition through a conical intersection. Most importantly, for this paradigmatic model system, we are able to identify two nuclear coordinates of interest (rather than the single coordinate predicted by Marcus or a full set of internal quantum modes studied by Bixon and Jortner): the solvent relaxation in the first shell (that strongly modulates the energies of the charge trans- fer state and differentiates time scales for relaxation) and a nuclear displacement in the TCNE-HMB complex arising from a handful of vibrations that induces non-Born Oppenheimer motion and eventually facilitates an abrupt electronic transition to the ground state. Altogether, these findings suggest a tractable generalization of Marcus theory for future simulations of photochemistry with non-innocent solvent environ- ments in the spirit of a Hamiltonian suggested by Stuchebrukhov (J. Chem. Phys. 107, 3821, 1997).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Regulatory Coordination of Photophysical, Photochemical, and Biochemical Reactions in the Photosynthesis of Land Plants

Balance among the sequential photophysical, photochemical, and biochemical reactions of photosynthesis is needed for converting fleeting energy in light to stable energy in chemical bonds. Any imbalance acts as either a bottleneck for limiting photosynthetic efficiency or an agent for inducing structural and functional damage to photosynthetic apparatus. Not only must each reaction be carefully regulated, but regulatory processes must also be coordinated across the reactions. However, regulations of different stages of photosynthesis have rarely been studied jointly. Non-photochemical quenching (NPQ) and stomatal conductance (g s ) are key regulators of photophysical and biochemical reactions, respectively. Existing evidence suggests that the redox state of plastoquinone regulates g s and that the photochemical reactions are partially regulated by the ultrastructural dynamics of thylakoids induced by osmotic water fluxes in chloroplasts of land plants. To examine how these regulations are coordinated and feedback to each other, we simultaneously measured NPQ and gs and inferred the redox state of plastoquinone and the light-induced thylakoid swelling/shrinking on numerous C 3 and C 4 species. For all species measured, NPQ and gs covary with the redox states of the electron transport chain, particularly plastoquinone, and increase as thylakoid swelling is inferred. NPQ has the maximal sensitivity at the light intensity at which thylakoid is inferred to be fully swollen. Our findings suggest that plant energy and water use strategies are intimately linked by evolution, and studying the regulations of different photosynthetic stages as a whole can lead to new insights of the functioning of photosynthetic machinery in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗

SSAPy - Space Situational Awareness for Python

SSAPy is a fast and flexible orbit modeling and analysis tool for orbits spanning from low-Earth into the cislunar regime. Orbits can be flexibly specified from common input formats such as Keplerian elements or two-line element (TLE) data files. SSAPy allows users to model satellites and specify parameters such as satellite area, mass, and drag coefficients. SSAPy includes a customizable force-propagation with a range of Earth, Lunar, radiation, atmospheric, and maneuvering models. SSAPy makes use of various community integration methods and can calculate time-evolved orbital quantities, including satellite magnitudes and state vectors. Users can specify various space- and ground-based observation models with support for multiple coordinate and reference frames. SSAPy also supports orbit analysis and propagation methods such as multiple hypothesis tracking and has built-in uncertainty quantification. The majority of SSAPy’s methods are vectorized and parallelizable, allowing for effective use of high-performance computer (HPC) systems. Finally, SSAPy has plotting functionality, allowing users to visualize orbits and trajectories. Examples are shown in Figure 1 and Figure 2.

97 MATHEMATICS AND COMPUTING↗

A Vehicle-to-Grid planning framework incorporating electric vehicle user equilibrium and distribution network flexibility enhancement

The rapid surge in electric vehicle (EV) adoption, coupled with advancements in charging technologies, emphasizes the critical necessity for expanding EV recharging infrastructure. Simultaneously, the Distribution Network (DN) encounters escalating challenges in meeting charging demand during peak traffic periods. Consequently, there is a mounting demand for the deployment of innovative Vehicle-to-Grid (V2G) technologies to augment the DN’s flexibility in power dispatch and alleviate travel costs for EV users. Hence, this paper proposes an EV-user-equilibrium-(UE)-constrained V2G planning framework that enhances flexibility in the DN. The framework aims to ascertain the optimal placement and capacity of EV charging stations (EVCSs) and V2G charging piles within the Transportation Network (TN). It takes into account the equilibrium condition stemming from competitive EV charging and routing behaviors alongside the optimal expansion of DN energy resources to accommodate the electricity supplied by the V2G piles. This study commences by analyzing EV drivers’ travel decisions, considering the influence of charging and V2G pile locations and sizes. Subsequently, we tackle the Traffic Assignment Problem with User Equilibrium (TAP-UE) model to characterize the steady-state traffic flow distribution of EVs. Following this, we formulate the optimization model for the Coordinated Power and Transportation Network (CPTN), which encompasses the optimal expansion of DN facilities and traffic flow regulation under UE conditions. To mitigate the computational complexity associated with the V2G planning model, we introduce a series of linearization methods to obtain a manageable Mixed-Integer Linear Programming (MILP) solution. Finally, to validate the efficacy of our proposed planning framework, we apply it to two test systems, including a real-world case study. Through these case studies, we explore the necessity and potential benefits of V2G technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Identification of pressure points in modern power systems using transfer entropy

Power shortages disrupt daily life, economic activity, and essential services. In modern power systems, weather is an increasingly important driver of reliability: high temperatures raise demand and limit transmission capacity, and calm or cloudy periods reduce wind and solar supply. Using a data-driven analysis, this study identifies grid infrastructure whose operating patterns help predict power shortages. The results show that reliability risks often emerge from interacting stresses across generation, transmission, and demand, rather than from single bottlenecks. By clarifying how system stress propagates through the grid, this diagnostic perspective helps explain why shortages occur under specific conditions and can complement traditional planning and operational tools to support adaptive reliability strategies, targeted monitoring, and coordinated infrastructure investments.

power systems↗

Solid-State Hydroxide Ion Conductivity in Silver(I) Oxide, Ag 2 O

Silver (I) oxide, Ag 2 O, precipitated as microcrystals by combining aqueous silver(I) nitrate and KOH solutions, was found to be a solid-state hydroxide ion conductor with ionic conductivity on the order of 10 -3 S/cm. The proton chemical shifts at 4.87 and -7.35 ppm measured by solid-state 1H-NMR experiments are attributed to water molecules and in-lattice OH - coordinated to silver, respectively. The lack of spinning sidebands around the 4.87 ppm peak indicates rapid reorientation on the NMR timescale, suggesting that the water molecules are adsorbed to the surface of the Ag 2 O crystals. Pulsed field gradient measurements gave similar diffusion coefficients (2 x 10 -7 cm 2 /s at 298K) for all three proton environments indicating chemical exchange between sites on the millisecond timescale. The activation energy for OH - diffusion measured by NMR (0.18 eV) was comparable to that obtained by conductivity measurements and density functional theory (DFT) electronic structure calculations. Furthermore, the calculated Pourbaix diagram of Ag 2 O is consistent with the slightly lower sample density observed in He pycnometry and thermogravimetric measurements.

25 ENERGY STORAGE↗

Design and synthesis of aryl-functionalized carbazole-based porous coordination cages

A subset of coordination cages have garnered considerable recent attention for their potential permanent porosity in the solid state. Herein, we report a series of functionalized carbazole-based cages of the structure type M 12 (R-cdc) 12 (M = Cr, Cu, Mo) where the functional groups include a range of aromatic substituents. Single-crystal X-ray structure determinations reveal a variety of intercage interactions in these materials, largely governed by pi–pi stacking. Density functional theory for a subset of these cages was used to confirm that the nature of the increased stability of aryl-functionalized cages is a result of inter-cage ligand interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the nonadiabatic collisional quenching of OH(A) by H 2 : a four coupled quasi-diabatic state description

A four-state diabatic potential energy matrix (DPEM), H d , for the description of the nonadiabatic quenching of OH(A 2 Σ + ) by collisions with H 2 is reported. The DPEM is constructed as a fit to adiabatic energies, energy gradients, and derivative couplings obtained exclusively from multireference configuration interaction wave functions. A four-adiabatic-electronic-state representation is used in order to describe all energetically accessible regions of the nuclear coordinate space. Partial permutation-inversion symmetry is incorporated into the representation. Here, the fit is based on electronic structure data at 42 882 points, described by over 1.6 million least squares equations with a root mean square (mean unsigned) error of 178(83) cm –1 . Comparison of ab initio and H d determined minima, saddle points, and energy minimized points on C 2v , C s , C ∞v , and C 1 (noncoplanar) portions of two conical intersection seams are used to establish the accuracy of the H d .

74 ATOMIC AND MOLECULAR PHYSICS↗

Dicopper( i ) complexes of a binucleating, dianionic, naphthyridine bis(amide) ligand

The dinucleating ligand, 1,8-naphthyridine-2,7-bis(2,6-diisopropylphenyl)carboxamide (NBDA), was synthesized by palladium-catalyzed aminocarbonylation. This ligand was treated with two equivalents of mesitylcopper(I) in the presence of [nBu4N]X (X = Cl, N3) to give the anionic complexes [nBu4N][Cu2(NBDA)(μ-Cl)] and [nBu4N][Cu2(NBDA)(μ-N3)]. Treatment of H2NBDA with mesitylcopper(I) and two equivalents of xylyl isocyanide led to the formation of a charge-neutral dicopper(I) complex, [Cu2(NBDA)(CNXyl)2], displaying two isocyanide ligands, each terminally bound to one of the copper atoms. The complexes were characterized by NMR and IR spectroscopy, as well as by single-crystal X-ray diffraction analysis. Electrochemical characterization of the complexes using cyclic voltammetry revealed a reversible ligand-based reduction between -1.65 and -2.0 V vs. Fc/Fc+. DFT calculations suggest a more ionic bonding character and weaker Cu-Cu interactions in the NBDA complexes compared to those with other 1,8-naphthyridine-based ligands. This is congruent with intermetallic separations of over 3 Å induced by relatively strong coordination of the copper atoms to the amide nitrogen donor atoms observed in the solid state molecular structures.

Sévery, Laurent↗

Influence of Heat Treatments in H 2 and Ar on the E 1 center in β -Gs 2 O 3

In this report the influence of heat treating n-type bulk β-Ga 2 O 3 in hydrogen (H2) and argon (Ar) gases on the presence of the defect level commonly labeled as E 1 was studied. Fourier transform-infrared spectroscopy confirms that hydrogen (H) is incorporated into β-Ga 2 O 3 during H 2 annealing at 900 °C. Deep-level transient spectroscopy measurements reveal that the concentration of the E 1 level is promoted by the introduction of H, in contrast to what is observed in samples heat-treated in an Ar flow. We further find the E 1 level to be stable against heat treatments at 650 K, both with and without an applied reverse-bias voltage. Potential candidates for the defect origin of E 1 are investigated using hybrid-functional calculations, and three types of defect complexes involving H are found to exhibit charge-state transition levels compatible with E 1 , including substitutional H at one of the threefold coordinated O sites, Ga-substitutional shallow donor impurities passivated by H, and certain configurations of singly hydrogenated Ga–O divacancies. Among these types, only the latter exhibit H binding energies that are consistent with the observed thermal stability of E 1 .

36 MATERIALS SCIENCE↗