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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 973 records · Page 54

Pathways for decarbonization of the buildings sector in Ukraine

The paper focuses on Ukraine’s intention to achieve a two-thirds reduction in buildings’ energy consumption for heating and cooling by 2050, concurrently aiming for net zero greenhouse gas emissions and heightened energy security. Here, the study examines the outcomes of retrofitting existing residential, commercial, and public buildings with highly efficient materials, improving construction standards, and transitioning to advanced heating systems. However, Russia’s invasion in 2022 inflicted substantial damage, prompting a shift from retrofit and decarbonization to reconstruction. The Ukrainian government’s Reconstruction Plan emphasizes clean, sustainable, and resilient energy systems. The study employs energy system and integrated assessment models (TIMES-Ukraine and GCAM-Ukraine) to explore scenarios taking into consideration the war, reconstruction, and a net zero CO 2 pathway. Using two models allowed the inter-model comparison. The analysis addresses vital questions on energy resiliency measures and the compounding effects of decarbonization. Findings indicate that Ukraine’s energy goals can be met through strategic retrofitting and economy-wide decarbonization, emphasizing the importance of low-carbon alternatives like district heating with renewable sources. Electrification with renewables and fuel-switching emerges as crucial for achieving building decarbonization. The study offers valuable insights into navigating energy challenges amidst the war and outlines a pathway for Ukraine’s sustainable energy future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Understanding Advanced Vehicle Technology Adoption Potential in Commercial Fleets Across Major Trucking Sectors

Adopting advanced vehicle technologies, such as battery-electric, hybrid, and hydrogen fuel cell vehicles, can be an effective strategy for reducing fleet owners' operating costs. However, different trucking sectors, such as private and for-hire carriers and short- or long-haul operations, may face unique challenges in adopting those vehicle technologies due to their own operational needs and budget constraints. Current studies on fleet-wide vehicle technology projections frequently overlook such sectoral differences and fail to capture variation in adoption potential across sectors. This study addresses this gap by analyzing the disparities in the total cost of ownership (TCO) and payback period (PBP) among a large and heterogeneous sample of fleet owners. It aims to understand the sectoral differences in the long-term potential for adopting advanced vehicle technologies. Utilizing the 2021 US Vehicle Inventory and Use Survey (US VIUS), which offers data on various commercial vehicle sectors, their operational patterns, and current vehicle assets, this research estimates the TCO and PBP for individual trucks over multiple future years. The results reveal variation in the cost-effectiveness of different vehicle technologies across trucking sectors, as well as the potential technology landscape in both the short and long term. The findings from this study can inform policymakers and practitioners on how to prioritize sectors with lower barriers for advanced vehicle technology adoption and support industries that face challenges in switching to advanced vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Efficient formulation of multitime generalized quantum master equations: Taming the cost of simulating 2D spectra

Modern 4-wave mixing spectroscopies are expensive to obtain experimentally and computationally. In certain cases, the unfavorable scaling of quantum dynamics problems can be improved using a generalized quantum master equation (GQME) approach. However, the inclusion of multiple (light–matter) interactions complicates the equation of motion and leads to seemingly unavoidable cubic scaling in time. In this paper, we present a formulation that greatly simplifies and reduces the computational cost of previous work that extended the GQME framework to treat arbitrary numbers of quantum measurements. Specifically, we remove the time derivatives of quantum correlation functions from the modified Mori–Nakajima–Zwanzig framework by switching to a discrete-convolution implementation inspired by the transfer tensor approach. We then demonstrate the method’s capabilities by simulating 2D electronic spectra for the excitation-energy-transfer dimer model. In our method, the resolution of data can be arbitrarily coarsened, especially along the t2 axis, which mirrors how the data are obtained experimentally. Even in a modest case, this demands O(103) fewer data points. We are further able to decompose the spectra into one-, two-, and three-time correlations, showing how and when the system enters a Markovian regime where further measurements are unnecessary to predict future spectra and the scaling becomes quadratic. This offers the ability to generate long-time spectra using only short-time data, enabling access to timescales previously beyond the reach of standard methodologies.

Chemistry↗

Generic Multi-Frequency Modelling of Converter-Connected Renewable Energy Generators Considering Frequency and Sequence Couplings

Frequency and sequence couplings can compromise the trustworthiness of multi-frequency models for converter-based systems. There have been effective attempts to address the couplings mainly by linearized averaged models. Only a few studies have been conducted on practical optimization of such models with enormous matrices and experimental results. This paper provides a generic theory for coupling patterns and proposes a multi-frequency modelling method to detect and address only the main couplings in the sequence domain for converter-connected renewable energy generators. The proposed generic model is based on empirical tests using small-signal perturbations and adopting Fourier transform on the switching converter response. The proposed theory and modelling methodology are verified using a 7MVA grid emulator for voltage perturbation tests on a 2MVA photo-voltaic converter. Accordingly, the couplings can exist in more generic forms, including multiples of perturbation and fundamental frequencies. To the best of our knowledge, the patterns with the multiples of the perturbation frequency have been overlooked in the literature. Furthermore, the mirror frequency concept is valid for all coupling patterns and is included in the proposed model. Besides, the proposed patterns and the environment noise levels have been practical criteria for selecting the main couplings.

frequency and sequence couplings↗

Heterosynaptic plasticity in biomembrane memristors controlled by pH

Abstract In biology, heterosynaptic plasticity maintains homeostasis in synaptic inputs during associative learning and memory, and initiates long-term changes in synaptic strengths that nonspecifically modulate different synapse types. In bioinspired neuromorphic circuits, heterosynaptic plasticity may be used to extend the functionality of two-terminal, biomimetic memristors. In this article, we explore how changes in the pH of droplet interface bilayer aqueous solutions modulate the memristive responses of a lipid bilayer membrane in the pH range 4.97–7.40. Surprisingly, we did not find conclusive evidence for pH-dependent shifts in the voltage thresholds ( V* ) needed for alamethicin ion channel formation in the membrane. However, we did observe a clear modulation in the dynamics of pore formation with pH in time-dependent, pulsed voltage experiments. Moreover, at the same voltage, lowering the pH resulted in higher steady-state currents because of increased numbers of conductive peptide ion channels in the membrane. This was due to increased partitioning of alamethicin monomers into the membrane at pH 4.97, which is below the pKa (~5.3–5.7) of carboxylate groups on the glutamate residues of the peptide, making the monomers more hydrophobic. Neutralization of the negative charges on these residues, under acidic conditions, increased the concentration of peptide monomers in the membrane, shifting the equilibrium concentrations of peptide aggregate assemblies in the membrane to favor greater numbers of larger, increasingly more conductive pores. It also increased the relaxation time constants for pore formation and decay, and enhanced short-term facilitation and depression of the switching characteristics of the device. Modulating these thresholds globally and independently of alamethicin concentration and applied voltage will enable the assembly of neuromorphic computational circuitry with enhanced functionality. Impact statement We describe how to use pH as a modulatory “interneuron” that changes the voltage-dependent memristance of alamethicin ion channels in lipid bilayers by changing the structure and dynamical properties of the bilayer. Having the ability to independently control the threshold levels for pore conduction from voltage or ion channel concentration enables additional levels of programmability in a neuromorphic system. In this article, we note that barriers to conduction from membrane-bound ion channels can be lowered by reducing solution pH, resulting in higher currents, and enhanced short-term learning behavior in the form of paired-pulse facilitation. Tuning threshold values with environmental variables, such as pH, provide additional training and learning algorithms that can be used to elicit complex functionality within spiking neural networks. Graphical abstract

36 MATERIALS SCIENCE↗

An Optimized H5 Hysteresis Current Control with Clamped Diodes in Transformer-Less Grid-PV Inverter

With the rise of renewable energy penetration in the grid, photovoltaic (PV) panels are connected to the grid via inverters to supply solar energy. Transformer-less grid-tied PV inverters are gaining popularity because of their improved efficiency, reduced size, and lower costs. However, they can induce a path for leakage currents between the PV and the grid due to the absence of galvanic isolation. This leads to serious electromagnetic interference, loss in efficiency, and safety concerns. The leakage current is primarily influenced by the nature of the common mode voltage (CMV), which is determined by the switching techniques of the inverter. In this paper, a novel inverter topology of Hysteresis Controlled H5 with Two Clamping Diodes (HCH5-D2) is derived. The HCH5-D2 topology helps decouple the AC part (Grid) and DC part (PV) during the freewheeling period to make the CMV constant, thereby reducing the leakage current. Additionally, the extra diodes help reduce voltage spikes generated during the freewheeling period and maintain the CMV at a constant value. Finally, a 2.2 kW grid-connected single-phase HCH5-D2 PV inverter system’s MATLAB simulation is presented, showing better results compared to a traditional H4 inverter.

42 ENGINEERING↗

Magnetic Proximity Effects in Iron Germanium Telluride/Platinum Heterostructures

Van der Waals (vdW) magnetic materials have attracted considerable attention for use in spintronic devices such as those controlled by spin–orbit torque (SOT). Such SOT-driven devices are typically fabricated by bringing a vdW magnet in proximity to a spin–charge conversion layer to achieve current-driven magnetization switching. Here, we show that such structures fabricated with iron germanium telluride (FGT) and platinum can exhibit emergent magnetic properties, which we attribute to magnetic proximity effects at the FGT/Pt interface. These changes manifest as increased perpendicular magnetic anisotropy and the emergence of additional magnetization reversal steps as probed by magneto-transport, with the most significant changes appearing in thinner flakes. The behavior was found to be robust and consistently appeared in samples made with crystals from different vendors. In conclusion, our results demonstrate the potential for engineering vdW spintronic systems through magnetic proximity effects.

2D magnet↗

Fast climate responses to emission reductions in aerosol and ozone precursors in China during 2013-2017

China has been implementing a sequence of policies for clean air since the year 2013, and the aerosol pollution has been substantially improved, but ozone (O 3 )-related issues arose. Here, fast climate responses to emission reductions in aerosol and O 3 precursors over China during 2013–2017 are investigated using the Community Earth System Model version 2 (CESM2). The overall decreases in aerosols produced an anomalous warming of 0.09 ± 0.10°C in eastern China (22–40° N, 110–122.5° E), which is further intensified by the increase in O 3 in the lower troposphere, resulting in an enhanced warming of 0.16 ± 0.15° C in eastern China. Reductions in industrial emissions contributed the most to the aerosol-induced warming, while emission reductions from residential sector induced a cooling effect due to a substantial decrease in light-absorbing black carbon aerosols. This implies that switching the residential sector to cleaner energy is more effective to achieve climate and health benefits in China.

54 ENVIRONMENTAL SCIENCES↗

Yu-Shiba-Rusinov states and ordering of magnetic impurities near the boundary of a superconducting nanowire

We theoretically study the spectrum induced by one and two magnetic impurities near the boundary of a one-dimensional nanowire in proximity to a conventional s-wave superconductor and extract the ground-state magnetic configuration. We show that the energies of the subgap states, supported by the magnetic impurities, are strongly affected by the boundary for distances less than the superconducting coherence length. In particular, when the impurity is moved towards the boundary, multiple quantum phase transitions periodically occur in which the parity of the superconducting condensate oscillates between even and odd. We find that the magnetic ground-state configuration of two magnetic impurities depends not only on the distance between them, but also explicitly on their distance away from the boundary of the nanowire. As a consequence, the magnetic ground state can switch from ferromagnetic to antiferromagnetic while keeping the interimpurity distance unaltered by simultaneously moving both impurities away from the boundary. The ground-state magnetic configuration of two impurities is found analytically in the weak coupling regime and exactly for an arbitrary impurity coupling strength using numerical tight-binding simulations.

1-dimensional systems↗

Stimulated Nucleation of Skyrmions in a Centrosymmetric Magnet

Understanding the dynamics of skyrmion nucleation and manipulation is important for applications in spintronic devices. In this contribution, the spin textures at magnetic domain-boundaries stimulated by application of in-plane magnetic fields in a centrosymmetric kagome ferromagnet, Fe 3 Sn 2 , with thickness gradient are investigated using Lorentz transmission electron microscopy. Switching of the in-plane magnetic field is shown to induce a reversible transformation from magnetic stripes to skyrmions, or vice versa, at the interface between differently oriented domains. Micromagnetic simulations combined with experiments reveal that the rotatable anisotropy and thickness dependence of the response to the external in-plane field are the critical factors for the skyrmion formation. In addition, it is shown that the helicity of skyrmions can also be controlled using this dynamic process. Finally, the results suggest that magnetic materials with rotatable anisotropy are potential skyrmionic systems and provides a different approach for nucleation and manipulation of skyrmions in spintronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Air Handling Unit Shutdowns During Scheduled Unoccupied Hours: US Commercial Building Stock Prevalence and Energy Impact

Commercial buildings account for 18% of U.S. energy consumption, with 44% used for heating, ventilation, and air conditioning (HVAC). American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) 90.1 requires HVAC systems to shutdown fans and outdoor air ventilation during unoccupied times, only allowing fans to cycle on, without outdoor air, to maintain thermostat setpoints. However, it is minimally understood how often existing building operations align with energy code requirements and the energy implications of not doing so. This study used building automation system data from 843 buildings containing 5706 air handling units (AHUs) to determine three unoccupied AHU shutdown control schemes ranging in efficiency and then estimated their prevalence in the U.S. commercial building stock, segmented by building type. ComStock was then used to analyze the energy savings potential of implementing the most energy efficient unoccupied shutdown control scheme in non-participating buildings across the U.S commercial building stock. Results show that only 23% of AHUs align completely with the ASHRAE 90.1 requirement. ComStock modeling results show 4% annual stock energy savings by switching all non-participating buildings to the most efficient scheme, with 19% annual energy savings demonstrated for the median building switching from the least efficient scheme to the most efficient. Findings also show 114.5 TBtu electricity and 75.8 TBtu natural gas fuel savings when converting to the most efficient scheme. Furthermore, these findings help stakeholders understand the high prevalence of buildings not aligning with the ASHRAE-90.1 requirements for unoccupied AHU shutdowns and the energy savings potential of utilizing the most efficient unoccupied AHU shutdown scheme.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dielectric-Engineered Monolayer MoS 2 Memtransistors for Brain-Inspired Computing with High Recognition Accuracy

Two-dimensional transition metal dichalcogenides (2D-TMDs)-based memtransistors have emerged as promising candidates for neuromorphic hardware due to their exceptional ability to emulate synaptic behavior. However, many existing 2D-TMDs memtransistors rely on polycrystalline channels with grain boundaries or defects introduced through postgrowth treatments, raising concerns about material integrity and the preservation of intrinsic properties. Here, in this work, we demonstrate a monocrystalline monolayer MoS 2 memtransistor fabricated on a silicon nitride (SiN X ) substrate, achieving a large resistive switching ratio of 10 4 , a dynamic range exceeding 90, along with highly linear and symmetric weight updates, minimal cycle-to-cycle variability, and low device-to-device variability. These attributes are critical for enabling high-performance neuromorphic hardware. Based on experimental data, we further show that these artificial synapses enable a recognition accuracy of more than 97% on the MNIST handwritten digits data set. Our findings present a straightforward approach to realizing 2D-TMDs memtransistors through dielectric engineering, offering a promising platform for next-generation neuromorphic computing systems.

2D TMDs↗

Octahedral to tetrahedral bonding transitions in the local structure of phase change optical media Ge 2 Sb 2 Se 5 x Te 5-5 x with Se doping

Random access memories utilize fast, reversible switching between ordered and disordered states of matter in phase change materials (PCMs) such as Ge2Sb2Te5-5x. The short-range structure in the disordered phase has been described either as (i) a network of Ge tetrahedra or (ii) Peierls distorted Ge/Sb octahedra. The PCM transition was investigated in bulk Ge2Sb2Se5xTe5-5x (GSST), in which amorphization sets in with Se doping (x ≈ 0.85) upon quenching. GSST has a hexagonal crystalline ground state with Ge/Sb octahedral coordination, but the phase change transition to the amorphous state that is only observed when the system is quenched brings a short-range structure with sharp, tetrahedrally coordinated Ge/Sb correlations and shortened bonds that are distinctly different from the expected octahedral pairing.

97 MATHEMATICS AND COMPUTING↗

Intrinsically stretchable neuromorphic devices for on-body processing of health data with artificial intelligence

For leveraging wearable technologies to advance precision medicine, personalized and learning-based analysis of continuously acquired health data is indispensable, for which neuromorphic computing could provide the most efficient implementation of artificial intelligence (AI) data processing. For realizing on-body neuromorphic computing, skin-like stretchability is required, but yet to be combined with the suite of desired neuromorphic metrics, including linear, symmetric weight update, and sufficient state retention, for achieving high computing efficiency. Here, we report an intrinsically stretchable neuromorphic device based on an electrochemical transistor, which provides a large number (>800) of states, linear/symmetric weight update, excellent switching endurance (>100 million), good state retention (>10 4 s), together with high stretchability of 100% strain. Further integration into a prototype array successfully realized the implementation of vector-matrix multiplication even at 100% strain. Finally, we demonstrate the feasibility of implementing AI-based classification of health signals (as exemplified by electrocardiograms) with a high accuracy that is minimally influenced by the stretched state of the neuromorphic hardware. Finally, this work breaks the ground for combining AI data analysis into skin-like wearable electronics for achieving human-integrated/mimetic intelligent systems.

60 APPLIED LIFE SCIENCES↗

A custom high-stability pulse generator for the test of a novel in-situ magnetic sensor developed to detect radiation damage in undulators

High-performance analog-to-digital converters (ADC) have been widely applied in many areas of science. For instance, magnetic field measurements based on the Faraday’s induction law require high-precision voltmeters to measure induced voltages. In this study in the context of free-electron lasers technology, the Magnetic Measurements Team at SLAC National Accelerator Laboratory proposed a novel in-situ radiation damage detection system (RDDS) for detecting small field variations in undulators. The system measures the flux change in a flexible printed-circuit coil attached to the magnet array during the undulator gap movement. The gap movement changes the magnetic field, which induces a voltage signal in the coil that is measured and integrated with an ADC. Although the system is capable of detecting relative flux changes better than 100 ppm, drift in the ADC’s gain or offset can cause apparent changes in the relative flux. This paper describes the first attempt to developed a high-precision verification circuit to perform ADC testing in the framework of the novel RDDS. The circuit generates a reference voltage pulse with a voltage–time integral relative precision better than 50 ppm for a few hundreds of mVs — the typical order of magnitude measured with the RDDS. The circuit’s design combines a fast and precise switch with a low-noise voltage reference. Long-term measurements allowed statistical analysis and showed that averaging the voltage–time integral of ten pulses gives the required 50 ppm stability. Moreover, reproducibility tests confirmed that the circuit’s output is invariable under small power supply instabilities and equipment shutdown. Instruments and applications designed to quantify the magnetic field by integrating voltage signals may use the pulse generator proposed in this paper for verification purposes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

N -Arylimide Molecular Balances: A Comprehensive Platform for Studying Aromatic Interactions in Solution

Noncovalent interactions of aromatic surfaces play a key role in many biological processes and in determining the properties and utility of synthetic materials, sensors, and catalysts. However, the study of aromatic interactions has been challenging because these interactions are usually very weak and their trends are modulated by many factors such as structural, electronic, steric, and solvent effects. Recently, N-arylimide molecular balances have emerged as highly versatile and effective platforms for studying aromatic interactions in solution. These molecular balances can accurately measure weak noncovalent interactions in solution via their influence on the folded–unfolded conformational equilibrium. The structure (i.e., size, shape, π-conjugation, and substitution) and nature (i.e., element, charge, and polarity) of the π-surfaces and interacting groups can be readily varied, enabling the study of a wide range of aromatic interactions. These include aromatic stacking, heterocyclic aromatic stacking, and alkyl–π, chalcogen–π, silver–π, halogen–π, substituent–π, and solvent–π interactions. The ability to measure a diverse array of aromatic interactions within a single model system provides a unique perspective and insights as the interaction energies, stability trends, and solvent effects for different types of interactions can be directly compared. Some broad conclusions that have emerged from this comprehensive analysis include: (1) The strongest aromatic interactions involve groups with positive charges such as pyridinium and metal ions which interact with the electrostatically negative π-face of the aromatic surface via cation–π or metal–π interactions. Attractive electrostatic interactions can also form between aromatic surfaces and groups with partial positive charges. (2) Electrostatic interactions involving aromatic surfaces can be switched from repulsive to attractive using electron-withdrawing substituents or heterocycles. These electrostatic trends appear to span many types of aromatic interactions involving a polar group interacting with a π-surface such as halogen–π, chalcogen–π, and carbonyl–π. (3) Nonpolar groups form weak but measurable stabilizing interactions with aromatic surfaces in organic solvents due to favorable dispersion and/or solvophobic effects. Furthermore, a good predictor of the interaction strength is provided by the change in solvent-accessible surface area. (4) Solvent effects modulate the aromatic interactions in the forms of solvophobic effects and competitive solvation, which can be modeled using solvent cohesion density and specific solvent–solute interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum Networks for Resilient Power Grids: Theory and Simulated Evaluation

Quantum networks are considered the future of secure communication in the coming quantum era. Yet there lack significant efforts on developing practical quantum networks for power grids. Here, in this paper, we establish a quantum network-based power grid (QNetGrid) framework and develops a real-time, reliable, flexible, programmable, and cost-effective QNetGrid software testbed containing repeater-based quantum communication, quantum routing, real software-defined networking (SDN) switches, and real-time networked microgrids (NMs) operations. It makes the following contributions: 1) a repeater and routing based quantum network simulator (QNSim) is developed, 2) repeaters with and without quantum memories are respectively simulated in QNSim, 3) different routing scenarios in QNetGrid are investigated, 4) a real-time QNetGrid software testbed is built in RTDS incorporating QNSim and real SDN switches, and 5) various test cases are designed, and experimental results produced with the QNetGrid testbed provide valuable insights for building quantum networks in power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗