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At least 217 records · Page 12

Stable yet hydrophilic graphene oxide nanomembranes by zwitterionic reduction for dye desalination

Holey graphene oxide (HGO) nanosheets have emerged as a promising membrane platform for dye desalination, and they must be reduced to enhance hydrophobicity and stability for long-term underwater operation, which usually decreases water and salt permeance. Herein, we develop a facile method to stabilize HGO nanosheets while retaining their hydrophilicity by reducing them with sulfobetaine amine (SBAm, a superhydrophilic zwitterion), achieving high water and salt permeance and a high salt/dye separation factor. Specifically, HGO nanosheets react with SBAm via an amine-epoxide reaction, rendering reduced HGO nanosheets containing superhydrophilic zwitterions. The effects of in-plane pores, zwitterion content, and layer thickness on the membrane chemistry, structure, and salt/dye separation properties of the SBAm-reduced HGOs (SHGOs) are thoroughly examined. The membrane achieves a Na 2 SO 4 /Direct red separation factor of up to 850, surpassing the state-of-the-art GO membranes. Moreover, hollow fiber membrane modules based on SHGOs are fabricated and exhibit stable performance in multi-cycle tests over 100 h of operation with mixed dye-salt solutions, demonstrating the scalability of our approach and its potential for practical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidating Norrish type I reactive pathways by ultrafast X-ray absorption spectroscopy

Norrish type I reactions selectively cleave carbon–carbon bonds directly adjacent to carbonyl groups. Despite their broad use in combination with aromatic carbonyls for additive manufacturing and dental UV curing applications, the nature of the photochemically active state and its population mechanism remain insufficiently understood. Detailed mechanistic insight requires mapping of the photoexcited population flow involving internal conversion and intersystem crossing. We present a time-domain study of gas phase acetophenone as a prototypical aromatic carbonyl combining soft X-ray time-resolved near-edge X-ray absorption fine structure (TR-NEXAFS) spectroscopy at the oxygen K-edge with ab initio multiple spawning (AIMS) simulations. Exploiting the specific sensitivity of TR-NEXAFS spectroscopy to states with nπ* character, we observe population transfer from the initially excited 1 ππ* state to the 1 nπ* state with a time constant of (0.13 ± 0.02) ps after an initial induction period of (0.12 ± 0.02) ps without population transfer, in quantitative agreement with the AIMS simulations. The population in the 1 nπ* state subsequently decays via intersystem crossing, likely mediated by a 3 ππ* state, within (3.17 ± 0.66) ps to a long-lived 3 nπ* state, which is presumed to be active towards Norrish type I chemistry.

Graßl, Martin [SLAC National Accelerator Laborator↗

Iterative quantum optimization of spin glass problems with rapidly oscillating transverse fields

In this work, we introduce a new iterative quantum algorithm, called Iterative Symphonic Tunneling for Satisfiability problems (IST-SAT), which solves quantum spin glass optimization problems using high-frequency oscillating transverse fields. IST-SAT operates as a sequence of iterations, in which bitstrings returned from one iteration are used to set spin-dependent phases in oscillating transverse fields in the next iteration. Over several iterations, the novel mechanism of the algorithm steers the system toward the problem ground state. We benchmark IST-SAT on sets of hard MAX-3-XORSAT problem instances with exact state vector simulation, and report polynomial speedups over Trotterized adiabatic quantum computation and the best known semi-greedy classical algorithm. When IST-SAT is seeded with a sufficiently good initial approximation, the algorithm converges to exact solution(s) in a polynomial number of iterations. Our numerical results identify a critical Hamming radius, or quality of initial approximation, where the time-to-solution crosses from exponential to polynomial scaling in problem size. This work proposes IST-SAT a new quantum algorithm, which improves upon solutions obtained from initial classical or quantum optimization algorithms. The steering mechanism we introduce through IST-SAT presents a new path toward achieving quantum advantage in optimization.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Structure-Based Discovery and Development of Highly Potent Dihydroorotate Dehydrogenase Inhibitors for Malaria Chemoprevention

Malaria remains a serious global health challenge, yet treatment and control programs are threatened by drug resistance. Dihydroorotate dehydrogenase (DHODH) was clinically validated as a target for treatment and prevention of malaria through human studies with DSM265, but currently no drugs against this target are in clinical use. We used structure-based computational tools including free energy perturbation (FEP+) to discover highly ligand efficient, potent, and selective pyrazolebased Plasmodium DHODH inhibitors through a scaffold hop from a pyrrole-based series. Optimized pyrazole-based compounds were identified with low nM-to-pM Plasmodium falciparum cell potency and oral activity in a humanized SCID mouse malaria infection model. The lead compound DSM1465 is more potent and has improved absorption, distribution, metabolism and excretion/pharmacokinetic (ADME/PK) properties compared to DSM265 that support the potential for once-monthly chemoprevention at a low dose. This compound meets the objective of identifying compounds with potential to be used for monthly chemoprevention in Africa to support malaria elimination efforts.

60 APPLIED LIFE SCIENCES↗

Physical properties, internal structure, and the three‐dimensional petrography of CI chondrites

physical properties and the nature of their breccation, we investigated nine samples of the Ivuna and Orgueil CI chondrites ranging in size from 1 mm to 4 cm in approximate diameter. The combined mass of unique material investigated in this work is 113 g. For our investigations, we use ideal gas pycnometry, 3-D laser scanning, x-ray computed microtomography (μCT), and accompanying digital data extraction techniques. We found that the bulk density of the samples ranged from 1.61 to 2.10 g cm −3 . Larger samples tend to have a lower bulk density. Grain density (ranging from 2.44 to 2.55 g cm −3 ) is significantly less variable than the bulk density in our samples and the quantity of porosity (ranging from 14.6% to 33.8%) is the dominant factor in determining the bulk density of CI chondrite material. Our μCT results show that the visible porosity across all sizes of our CI chondrite samples is in the form of cracks, but these cracks can account for less than two-thirds of the porosity in the CI chondrites. Other porosity is not visible, even at μCT resolutions of 2.7 μm voxel edge −1 and we conclude that it is sub-micron in nature. It is not clear if the cracks seen in our samples are indigenous to the chondrites or are a result of terrestrial processes. We also find that the CI chondrites are excellent examples of the fractal-like nature of brecciation, where clasts can be observed at all scales we imaged. The breccias are composed of sub-equant-shaped and sub-rounded-textured clasts like melt-free impact breccias on other solar system bodies. From our μCT volume and digital data extraction, we determine that the Ivuna CI chondrite breccia is organized: the mostly sub-equant clasts within our ~2 cm chunk of Ivuna have a mean diameter of 1.33 mm and their aligned longest axes define a lineation structure. We speculate that the lineation was imparted after fragmentation of the clasts by slight shear on the parent asteroid which could be the result of seismic-related granular flow or mild non-axial impact-related compaction. These data will help to place returned asteroidal material from asteroids 162173 Ryugu and 101955 Bennu and the CI chondrites into a mutual geological context.

CI chondrite↗

Extending Orbital-Optimized Density Functional Theory to L-Edge XPS and Beyond: Spin–Orbit Coupling via Nonorthogonal Quasi-Degenerate Perturbation Theory

Quantum mechanical calculations of core electron binding energies (CEBEs) are relevant to interpreting X-ray photoelectron spectroscopy (XPS). Orbital-optimized density functional theory (OO-DFT) accurately predicts K-edge CEBEs but is challenged by the presence of significant spin–orbit coupling (SOC) at L- and higher edges involving inner-shell orbitals with nonzero angular momentum. Here, to extend OO-DFT to L-edges and higher, our method utilizes scalar-relativistic, spin-restricted open-shell OO-DFT to construct a minimal, quasi-degenerate basis of core-hole states corresponding to a chosen inner-shell (e.g., ionizing all six possible 2p spin orbitals). Nonorthogonal configuration interaction (NOCI) is then used to obtain the matrix elements of the full Hamiltonian including SOC in this quasi-degenerate model space of determinants. Using a screened 1-electron SOC operator parametrized with the Dirac-Coulomb-Breit (DCB) Hamiltonian results in doublet splitting (DS) values for third row elements that are nearly in quantitative agreement with experiment. The resulting NOCI eigenvalues are shifted by the average of the (scalar) OO-DFT CEBEs to yield CEBEs (split by SOC) corrected for dynamic correlation. Comparing calculations on gas phase molecules with experimental results establishes that NO-QDPT with the SCAN functional (NO-QDPT/SCAN), using the DCB screened 1-electron SOC operator is accurate to about 0.2 eV for L-edge CEBEs of molecules containing third row atoms. However, this NO-QDPT approach becomes less accurate for fourth-row elements starting in the middle of the 3d transition metal series, with errors increasing as atomic number increases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic Surface Restructuring in Cu(Au) Alloys Driven by Oxygen-Mediated Au Mobility

Alloying plays a crucial role in tuning the surface properties of metals, but the atomic-level mechanisms by which alloying elements influence surface structure dynamics under reactive conditions remain elusive. Using Cu(Au) in oxidizing environments as a model system, we reveal a dynamic oxygen-induced transformation of the topmost atomic layer into a periodically hill-and-valley morphology with reversible switching between undulated and flattened surface states. These interconversions are driven by the retreat of surface Au to the subsurface during oxygen adsorption and its resegregation to the surface upon oxygen desorption. This cyclical mobility establishes a feedback loop, allowing the surface to dynamically reconfigure in response to changes in the oxygen pressure. The results offer a broadly applicable framework for understanding atomic-scale surface restructuring in alloy systems, where differences in the chemical reactivity of alloying elements drive dynamic redistribution between surface and subsurface regions. As a result, this dynamic coupling has practical implications for designing corrosion-resistant coatings and metastable nanostructures with tunable catalytic properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Chemical Control of Symmetry and Bandgap in Tungsten Oxyhalide van der Waals Semiconductors

Tunability in solid-state materials is essential for testing theory, discovering quantum phases, and enabling functionality. Layered van der Waals (vdW) semiconductors offer a unique platform, providing new degrees of freedom at the two-dimensional (2D) limit through exfoliation and external controls. Here, in this study, we demonstrate tunability of symmetry and electronic structure via halogen substitution in a family of layered vdW tungsten oxyhalides. Substituting the halogens in WO 2 X 2 (X = I, Br, Cl) tunes the bandgap across a broad energy range and modifies the structural symmetry from centrosymmetric to noncentrosymmetric. By alloying WO 2 I 2– y Br y , we continuously tune the polar distortion and optical gap across the visible range. These insights into halogen substitution effects on symmetry and electronic structure lay the foundation for new tunable vdW semiconductors for optoelectronics and nonlinear optics.

36 MATERIALS SCIENCE↗

High Pressure Synthesis of Ultrasmall Nanodiamonds with Nitrogen Vacancy Centers

C–H terminated nanometer scale diamonds ( d = 1 to 15 nm) are synthesized from 1-fluoroadamantane at high pressure (6–8 GPa) and high temperature (500–1500 °C) in a multianvil press. High resolution transmission electron microscopy, X-ray diffraction, Raman, diffuse reflectance Fourier transform infrared, and X-ray absorption spectroscopies demonstrate the excellent crystallinity and atomically flat C–H terminated surfaces of nanodiamonds with (111) and (110) facets. The importance of hydrogen to the synthesis of nanodiamond and its faceting is discussed. Following vacancy generation, annealing and oxidation of the nanodiamonds, optically detected magnetic resonance and electron spin resonance coherence times ( T 2 = 0.9 and 2.1 μs) of nitrogen vacancy (NV) centers are measured. Finally, the obtained T 2 values are equivalent to the shallow NV centers (depth <10 nm) in bulk diamond crystals and larger nanocrystals prepared by mechanical milling.

36 MATERIALS SCIENCE↗

A tunable autonomous RNA-fueled micro-engine

Autonomous molecular machines capable of converting chemical energy into mechanical motion are foundational components for synthetic nanoscale systems. Inspired by biological motors, we report the construction of a tunable, RNA-fueled DNA origami engine that drives the cyclic movement of a 500 nm-diameter particle at the microscale. The engine operates via sequential RNA–DNA hybridization and enzymatic cleavage by RNase H, enabling reversible switching between folded and unfolded conformations without external intervention. By modulating RNA and enzyme concentrations and controlling temperature, we achieve tunable switching kinetics, with transition periods as short as ~10 s. Kinetic modeling reveals that the folding pathway is governed by both productive RNA binding and the enzymatic clearance of misfolded intermediates, while unfolding is primarily controlled by RNase H activity. Since the RNA fuel binds specifically to the DNA strands, each engine is addressable simply by changing the sequences. This work demonstrates a programmable, self-resetting molecular actuator and offers a blueprint for building more complex nanomechanical systems with forces and energies comparable to molecular motors.

DNA nanomachines↗

Frustrated electron hopping from the orbital configuration in a two-dimensional lattice

Electron hopping on spatially periodic lattices gives rise to intriguing electronic behaviour. For example, hopping on the geometrically frustrated two-dimensional kagome, dice and Lieb lattices yields electronic band structures with both massless Dirac-like and perfectly dispersion-less, flat bands. As materials featuring the dice and Lieb lattice structures are scarce, an alternative approach proposes to leverage atomic orbitals to realize the characteristic electron hopping of geometrically frustrated lattices. This strategy promises to expand the list of candidate materials with frustrated electron hopping, but is yet to be shown in experiments. Here, in this study, we demonstrate frustrated hopping in the van der Waals intermetallic Pd 5 AlI 2 , emerging from the arrangement of atomic orbitals in a primitive square lattice. Using angle-resolved photoemission spectroscopy and quantum oscillation measurements, we reveal that the band structure of Pd 5 AlI 2 includes linear Dirac-like bands intersected at their crossing point by a locally flat band—an essential characteristic of frustrated hopping in Lieb and dice lattices. Moreover, this compound shows exceptional chemical stability, with its unusual bulk band structure and metallicity persisting in ambient conditions down to the monolayer limit. Hence, our results showcase a way to realize electronic structures characteristic of geometrically frustrated lattices in non-frustrated systems.

36 MATERIALS SCIENCE↗

Synthesis and Evaluation of Cu@ZnO Core@Shell Nanowires for Use in the Carbon Dioxide Thermal Reduction Reaction

Copper-based core@shell nanomaterials are of interest for the catalytic hydrogenation of carbon dioxide toward value-added products. In this context, we have developed a facile, microwave-based procedure for the reliable and reproducible synthesis of Cu@ZnO core@shell nanowires. A systematic assessment of the effect of rationally varying various reaction conditions on this protocol was completed in order to better evaluate the growth process of these core–shell motifs. We determined that among different reaction parameters, it was the critical role of reaction time which enabled the quantitatively reliable growth of external shells with tunable thicknesses of up to 20 nm. As a demonstration of the material’s practical viability, catalytic testing was subsequently performed for the reverse water–gas shift reaction (CO 2 + H 2 → CO + H 2 O), with the evolution of the process followed with in situ X-ray diffraction and X-ray absorption spectroscopy in order to probe structural changes and gauge stability. These tests found the catalysts to be effective at converting CO 2 to CO, with notable stability detected in the shell layer and no observed alloying between copper and zinc. Furthermore, our studies support the idea that the Cu–ZnO and CuO x –ZnO interfaces are essential for the effective activation of CO 2 and H 2 .

36 MATERIALS SCIENCE↗

Coupling of electronic transition to ferroelectric order in a 2D semiconductor

A ferroelectric material often exhibits a soft transverse optical (TO) phonon mode which governs its phase transition. Charge coupling to this ferroelectric soft mode may further mediate emergent physical properties, including superconductivity and defect tolerance in semiconductors. However, direct experimental evidence for such coupling is scarce. Here we show that a photogenerated coherent phonon couples strongly to the electronic transition above the bandgap in the van der Waals (vdW) two-dimensional (2D) ferroelectric semiconductor NbOI 2 . Using terahertz time-domain spectroscopy and first-principles calculations, we identify this mode as the TO phonon responsible for ferroelectric order. This exclusive coupling occurs only with the above-gap electronic transition and is absent in the valence band as revealed by resonant inelastic X-ray scattering. Our findings suggest a new role of the soft TO phonon mode in electronic and optical properties of ferroelectric semiconductors.

36 MATERIALS SCIENCE↗

Opportunities for installed combined heat and power (CHP) to increase grid flexibility in the U.S.

Increasing use of renewable energy requires sufficient grid flexibility to address uncertainty and variability in electricity generation. Previous studies suggest that combined heat and power (CHP) systems may support grid flexibility but they do not consider operating hours. In this paper, we used CHP operating data and determined annual and monthly availability of the installed CHP capacity from various sectors (e.g., utility, independent power producer, commercial, and industrial) in all seven U.S. independent system operators (ISOs) and regional transmission organizations (RTOs). Also, we estimated hourly CHP availability installed in five facility types (i.e., hospitals, universities, hotels, offices, and manufacturing) in the state of New York. The results show that regardless of ISO/RTO, sector, or season, more than 40% of the installed CHP capacity (0.7–8.7 GW) was not fully utilized in 2019; the results are similar for 2018. This available CHP capacity accounted for up to 9% of the ISO/RTO's peak electric demand, which may yield cost savings up to $16 billion by avoiding installation costs of new natural gas combustion or combined-cycle turbines. To exploit the available CHP capacity to enhance grid flexibility, we recommend different policy implications including flexible contract lengths between CHP owners and grid operators, improved market designs, and simplified interconnection standards.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultrasonic Jet Bat Deterrent System Advancement

General Electric Renewable Energy (GE) and the Department of Energy (DOE) worked to develop a project with an objective to increase confidence in acoustic ultrasonic bat deterrent technologies in wind turbines, by mitigating stakeholder investment risks that currently hinder the adoption of deterrent technologies. Many wind turbine sites utilize a bat conservation plan that curtail wind turbines and stop energy production. Curtailment is a known bat impact mitigation solution that has an history of environmental regulatory acceptance. To help support a solution that allows for simultaneous bat conservation and energy production with regulatory acceptance of acoustic bat deterrents, GE proposed a study to compare four treatments: control (no curtailment or deterrent), deterrent only, deterrent plus curtailment, and curtailment only. The concept was to provide a direct comparison of bat deterrent and curtailment effectiveness within the same wind farm and bat migration season. This comparison was intended to advocate for the adoption of bat deterrents with a large-scale field study by addressing customer concerns on regulatory acceptance of deterrents. The study was to be hosted at a forested habitat site during a bat migration season, by Stony Creek Energy, LLC (SCE), the owner of the Orangeville Wind Farm (OWF) in the state of New York. Included was a behavioral study plan with two turbines to monitor bat flight paths with thermal imaging cameras.

17 WIND ENERGY↗

Context-Aware Learning for Inverse Design in Photovoltaics

This document describes progress in the ARPA-E DIFFERENTIATE project titled “Context-Aware Learning for Inverse Design in Photovoltaics” during the period of May 2019 to May 2022. This project is being performed at Iowa State University, New York University, Stanford University, and National Renewable Energy Laboratory. The project aims to develop a new machine learning (ML) framework to significantly accelerate the design of organic microstructures for improved organic photovoltaic performance. In this project, we had developed an inverse design framework using Deep Learning called InvNets for generating microstructures with desired physics-driven properties. As a preliminary product, in Milestone 3, we demonstrated how InvNets show 20% improvement in the performance of the microstructures and over 100X speedup in the performance compared to traditional processes for physics-driven inverse design. Later, in Milestone 6, we demonstrated that InvNets work for more complex physics properties, specifically, generating microstructures for organic photovoltaic cells with desired current-voltage characteristics. Further, in Milestone 4, we explored the idea of using physics-aware surrogates for obtaining solutions of partial differential equations(PDE) called as DiffNets(now called as NeuFENets to avoid ambiguity of names). The connection between both frameworks is that DiffNet surrogates form the physics-aware surrogate in the InvNet framework. Finally in Milestone 8, we extend our framework for other physics domains. Specifically, we explore building geometry-aware NeuFENets by developing physics surrogates that exploit ideas from traditional immersed boundary finite element methods. With these updates, we are able to achieve all the Milestones.

36 MATERIALS SCIENCE↗

Nuclear Plant Inspection

Engineers from the Power Authority of the State of New York use a Crack Growth Analysis Program supplied by COSMIC (Computer Software Management and Information Center) in one stage of nuclear plant inspection. Welds of the nuclear steam supply system are checked for cracks; radiographs, dye penetration and visual inspections are performed to locate cracks in the metal structure and welds. The software package includes three separate crack growth analysis models and enables necessary repairs to be planned before serious problems develop.

Source record↗

Detecting Unclassified Electromagnetic Signals for Secure Wireless Communication Using Open Set Recognition

We developed multiple machine learning methods for the detection and classification of new wireless communication waveforms, which is critical for targeted attacks in wireless networks and electronic warfare. Our machine learning models are capable of dynamically detecting security threats in near real time through our advanced open set recognition (OSR) approach. This model has demonstrated significant improvements in the detection of unknown waveforms, thereby enhancing the security and reliability of mission critical communications. Our approach to detecting uncertain security threats is novel; we advanced OSR techniques by incorporating domain knowledge of wireless signals. Specifically, we combined time and frequency domain model features to enhance the model’s performance. Utilizing an OSR approach eliminates the need for training data to be distributed similarly to the deployment environment and removes the requirement for the training set to contains all possible threat classes. This is crucial because it is often infeasible to determine and characterize all potential security threats in advance. Our model were trained on simulated data, generated in partnership with the University at Albany, State of New York. The data set contained a diverse array of wireless signals, including those with additive white Gaussian noise and multipath signals, with and without line of sight. This comprehensive training set allowed us to optimize our models to detect unknown waveforms under various challenging scenarios, such as low signal-to-noise ratios. By training on various waveforms, varying signal-to-noise ratio, and different sample sizes under normal conditions, our models were fine tuned to perform effectively in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗