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At least 1,099 records · Page 61

Hybrid SERS platform by adapting both chemical mechanism and electromagnetic mechanism enhancements: SERS of 4-ATP and CV by the mixture with GQDs on hybrid PdAg NPs

Surface-enhanced Raman spectroscopy (SERS) is a versatile analytical technique widely adapted for the identification of target analytes even at an extremely low concentration. Herein, a unique hybrid SERS platform is demonstrated by utilizing the graphene quantum dots (GQDs) and hybrid PdAg NPs for the detection of 4-amino-thiophenol (4-ATP) and crystal violet (CV). GQDs offer the rich charge transfer to the LUMO and HOMO of 4-ATP and CV by the CM enhancement. A significant EM enhancement is achieved by the strong localized surface plasmon resonance (LSPR) of uniquely designed hybrid core-shell PdAg NP, possessing the narrow nano-gaps with the highly dense small Ag NPs and Pd core Ag shell configuration. As a result, orders of enhancement of originally weak 4-ATP and CV Raman signal is witnessed by the combination of electromagnetic mechanism (EM) and chemical mechanism (CM) enhancements on a single SERS substrate. The hybrid GQD/HNP SERS substrate demonstrates significantly improved hot spots and strongly localized electromagnetic fields as confirmed by the finite-difference time-domain (FDTD) simulations. There for a proper mixture ratio of GQDs and probe molecules presents largely enhanced SERS signals by a strong adsorption of probe molecules through π - π interaction and the enhancement factors vary by the mixture ratio depending on the adsorption kinetics and Raman cross-section of molecules.

36 MATERIALS SCIENCE↗

Tailoring solid-electrolyte interphase and solvation structure for subzero temperature, fast-charging, and long-cycle-life sodium-ion batteries

The sluggish Na + reaction kinetics with carbon materials limits the fast-charging capability, Coulombic efficiency, and cycle life of sodium-ion batteries, especially at low temperatures. Herein, free-standing carbon nanofiber films, with controllable crystallinity and surface chemistry, are used as a platform to investigate the correlation between Na + reaction kinetics, storage mechanism, and electrolyte environment. The ion solvation effect and solid-electrolyte interphase (SEI) properties determine the kinetics and storage mechanism. A strong Na + -solvent interaction, such as Na + -diglyme, tends to form a "pseudo-SEI" layer dominated by anion decomposition, enabling fast Na + -solvent co-intercalation kinetics. Tuning the SEI chemistries by pre-cycling in the weakly solvated electrolyte (e.g., ester electrolyte), the intercalation capacity rapidly disappears due to the high energy barrier for Na + transport. Finally, such mechanistic insights allow us to develop the optimal combination of electrode materials and electrolyte chemistry to achieve high initial Coulombic efficiency, ultra-long cycle life under fast charging, and excellent low-temperature performance.

25 ENERGY STORAGE↗

“Antenna-like” Light-Harvesting in Partially Metalated Porphyrin Hydrogen-Bonded Organic Frameworks

Arrays of light harvesting molecules with long-range order hold promise as materials capable of efficient collection of photons as well as rapid transport of captured solar energy to chemical catalysts. Hydrogen-bonded organic frameworks (HOFs) could be promising artificial light-harvesting platforms, due to their crystalline nature and their comparative ease of synthesis. In this work, mixed-linkers of either zinc-metallated or free base tetrakis(4-carboxyphenyl)porphyrin HOFs were examined and found to demonstrate ‘antenna-like’ light harvesting behavior. Using time-resolved emission spectroscopy, Förster resonance energy transfer from zinc porphyrin to free-base porphyrin was assessed. Based on changes in the emission peak profile as the ratio of zinc porphyrin to free-base porphyrin is varied, we find that, in the limit of 100% zinc porphyrin, a photogenerated exciton can sample ~48 chromophores. These findings suggest that stacked linkers within HOFs can act as light harvesting ‘antennae’ and with encapsulation of suitable catalysts, may offer prospective application as photochemical energy conversion systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis and application of thermally responsive nanofiber coatings for overtemperature monitoring

This study presents a one-pot synthesis route to organometallic nanofibers based on copper thiolate, exhibiting distinctive chemical and physical characteristics. Electron microscopy analysis of morphology and composition revealed 2-10 μm-long, 50-90 nm-diameter hollow and non-hollow fibers composed of copper, sulfur, oxygen, hydrocarbon, and chlorine. Thermogravimetric analysis showed a pronounced mass loss within 120°C-135°C. To elucidate the thermal responsive pathways, the nanofibers were characterized before and after heating. X-ray photoelectron spectroscopy indicates that an initially mixed Cu(I)/Cu(II) oxidation states transition to predominantly Cu(I) upon heating. A layer of nanofiber was coated on battery pouch foil and evaluated as a candidate thermally sensitive coating. At elevated temperature (100-130°C), nanofiber coating released volatile organic compounds, sulfide and sulfur dioxide as detected using multiple gas sensors. This thermally responsive gas release/sensing approach provides a potential large-area temperature monitoring strategy, which is particularly relevant where direct temperature measurements of individual batteries is impractical. The results established proof of concept for nanofiber-coated battery pouch foil as overtemperature warning platform that can provide alerts when surface temperatures exceed a critical threshold. More broadly, the ability to form interconnected fiber networks positions copper thiolate nanofiber coatings as promising materials for advanced applications.

Ihala Gamaralalage, Chanaka [ORNL] (ORCID:00000002↗

High-Entropy Perovskite Fluorides: A New Platform for Oxygen Evolution Catalysis

High-entropy perovskite fluorides (HEPFs) have great potential in electrocatalysis that has not been realized because of the limitation of a high-temperature synthetic route and the limited understanding of high-entropy materials. The use of HEPFs in effective oxygen evolution catalysis and a feasible synthesis route for HEPFs in a boiled solution by combining a hydrothermal method with mechanochemistry are first reported here. These HEPFs consisting of cost-effective elements dramatically gave excellent catalytic activity for the oxygen evolution reaction in an alkaline media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recent efforts of vapour-phase strategies for EUV resist toward high- and hyper-NA extreme ultraviolet lithography

Extreme ultraviolet lithography (EUVL, λ = 13.5 nm) is critical for sub-1 nm technology nodes but remains constrained by inherent trade-offs among resolution, line-edge roughness (LER), and sensitivity. Stochastic effects originating from photon shot noise, low-energy secondary electron blur, and the random distribution of resist components further limit its advancement toward high numerical-aperture (NA, NA = 0.55) and hyper-NA (NA ≥0.75) EUVL. While the optimization of spin-on chemically amplified resists (CARs) continues, metal-oxide resists (MORs) have emerged as strong candidates for next-generation EUVL by incorporating metals with high EUV absorption coefficients, which enhances both resist sensitivity and etch resistance during pattern transfer. Besides spin-coating, recent advances in vapour-phase techniques, such as vapour-phase infiltration (VPI), chemical vapour deposition (CVD), and molecular atomic layer deposition (MALD), offer promising pathways to achieve new resist platforms, such as dry resists, that satisfy the stringent thickness and uniformity requirements of next-generation EUVL. These methods enable the direct incorporation of metal species into existing resist matrices or the formation of hybrid inorganic–organic resist platforms, thereby improving film uniformity, etch durability, and pattern fidelity while mitigating stochastic defects. This review highlights the latest advancements in vapour-phase-synthesized EUV resists, emphasizing material design, lithographic performance, and the underlying exposure mechanisms. Although still emerging, vapour-phase strategies are paving the way for an all-dry integration framework that could improve EUV patterning workflows and meet the demands of future technology nodes.

36 MATERIALS SCIENCE↗

Initial dynamic photoactive materials testing of an atmospheric chamber intended for radioactive and hazardous gases

Radioisotopes and hazardous gases can have undetermined environmental pathways. Researchers at Pacific Northwest National Laboratory constructed a chamber that complies with the requirements needed for an atmospheric reaction platform and the safety principles of interacting with hazardous dispersible sources to enable the environmental testing of these gases. Initial dynamic testing showed inter-chamber mixing completed from minutes to 1.5 hours. The photooxidation of butyl iodine showed the presence of signals from reaction products, and intermediaries for up to 50 hours. Current detection limits of the chamber and analytical collection and testing approach were shown to be in the single-digit parts per billion levels. In conclusion, the comparisons between the measured oxidation trends and literature show the utility of performing laboratory experiments to validate the results of modeling for larger-scale scenarios.

54 ENVIRONMENTAL SCIENCES↗

Stronger field-emission science via coupling novel nanoscale imaging techniques

We implemented a vacuum field emission electron microscope (FEM) using the electron optics of a low-energy /photoemission electron microscope (LEEM/PEEM). Historically, there have been other FEM hardware platforms, and the distinctive feature of our method is that it integrates with the LEEM/PEEM and associated techniques, enabling a powerful multi-capability toolset for studying fundamental materials properties underpinning field emission (FE) and vacuum arc initiation. Typically, LEEM is used to image surface structure, which influences both work function and electric field distribution near a surface, while PEEM is used to map photoelectric work function across a surface. Our FEM adds the capability for spatially-correlated coincident-site measurements of FE currents to go-along with structure and work function. LEEM, PEEM, and our FEM implementation achieve nanoscale spatial resolution relevant for materials studies in nanoscience/engineering. Our approach requires a straightforward calibration of the electron optics to enable focused FEM imaging under intentional electric field variation. We demonstrate the FEM approach by imaging field emitter arrays relevant for vacuum nanoelectronics. We demonstrate submicron spatial resolution and dynamic measurement of FE versus applied electric field. We anticipate this capability will enable fundamental structure-function studies of FE and arc initiation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Towards High-Repetition-Rate Fast Neutron Sources Using Novel Enabling Technologies

High-flux, high-repetition-rate neutron sources are of interest in studying neutron-induced damage processes in materials relevant to fusion, ultimately guiding designs for future fusion reactors. Existing and upcoming petawatt laser systems show great potential to fulfill this need. Here, we present a platform for producing laser-driven neutron beams based on a high-repetition-rate cryogenic liquid jet target and an adaptable stacked lithium and beryllium converter. Selected ion and neutron diagnostics enable monitoring of the key parameters of both beams. A first single-shot proof-of-principle experiment successfully implemented the presented platform at the Texas Petawatt Laser facility, achieving efficient generation of a forward-directed neutron beam. This work lays the foundation for future high-repetition-rate experiments towards pulsed, high-flux, fast neutron sources for radiation-induced effect studies relevant for fusion science and applications that require neutron beams with short pulse duration.

47 OTHER INSTRUMENTATION↗

Smart Building Technology Training Modules for Academic and Professional Education

Smart building technologies are a new suite of resources that improve building energy efficiency and resilience, reduce carbon emissions, and provide load flexibility to the grid. However, in both college curricula and building professionals’ continuing education, there is a lack of systematic instruction on smart building technologies–topics that include smart building concepts, key components, smart building controls, “Internet of Things” (IoT) devices, and how to integrate multiple energy systems including distributed energy resources (DER). This major gap in smart building education prevents stakeholders from understanding and adopting smart building technologies in building design and operations. Slipstream leads a DOE-funded project developing a semester-long smart building curriculum for college students and adapting the contents into 16 training videos for building professionals and the general public. The education and training cover the drivers and benefits of smart building technologies, key building energy systems, the latest sensor technologies and IoT devices, and focus on topics related to smart building controls (i.e., energy management information systems, smart building control platforms, cybersecurity, grid-interactive-efficient buildings (GEBs), smart building control methods, and occupant-centric control. This paper describes the project approach, provides outlines of the training materials, and identifies lessons learned in creating the content. We also suggest ways to scale the instruction of smart building concepts to empower the workforce to accelerate the adoption of smart building technologies in the real world.

99 GENERAL AND MISCELLANEOUS↗

An Open-Source Framework for Characterizing Urban Energy Models: Integrating Top-Down and Bottom-Up Methods to Predict Residential Buildings Characteristics: Preprint

Bottom-up urban energy models are crucial for understanding current energy use patterns and informing design strategies. However, accurately characterizing these models to represent different communities remains a challenge due to the extensive data needed for simulating existing energy use behavior. This data includes information related to human activities and building characteristics, all of which correlate with socioeconomic factors. To overcome this challenge, we developed an automated framework that utilizes both top-down and bottom-up data, to predict unknown building and occupant characteristics that are needed for more accurate and equitable modeling and analytics. Our framework, integrated into the URBANopt district energy modeling platform, uses statistical data models from ResStock. URBANopt models co-located buildings and neighborhoods. At this scale there are data gaps in building characteristic data, such as materials, insulation, occupancy, income, and energy usage of the buildings. To address this data gap, we use ResStock data, representative at the census tract scale, and develop machine-learning and deeplearning techniques to disaggregate it to individual buildings. By mapping unique occupant, building and economic properties to URBANopt energy models, we gain detailed insights into the variability of building energy use across different neighborhoods. This insight helps deploy technologies for co-located buildings and supports targeted upgrades for communities with unique economic and demographic characteristics, ensuring energy equity. Accurate characterization of energy models allows us to develop equitable strategies tailored to diverse neighborhoods, whether underserved or affluent. Our automated framework streamlines energy modeling and provides a reliable tool for building energy characterization.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

Long-Range Resonant Charge Transport through Open-Shell Donor–Acceptor Macromolecules

A grand challenge in molecular electronics is the development of molecular materials that can facilitate efficient longrange charge transport. Research spanning more than two decades has been fueled by the prospects of creating a new generation of miniaturized electronic technologies based on molecules whose synthetic tunability offers tailored electronic properties and functions unattainable with conventional electronic materials. However, current design paradigms produce molecules that exhibit off-resonant transport under low bias, which limits the conductance of molecular materials to unsatisfactorily low levels several orders of magnitude below the conductance quantum 1 G 0 and often results in an exponential decay in conductance with length. Here, we demonstrate a chemically robust, air-stable, and highly tunable molecular wire platform comprised of open-shell donor−acceptor macromolecules that exhibit remarkably high conductance close to 1 G 0 over a length surpassing 20 nm under low bias, with no discernible decay with length. Single-molecule transport measurements and ab initio calculations show that the ultralong-range resonant transport arises from extended π-conjugation, a narrow bandgap, and diradical character, which synergistically enables excellent alignment of frontier molecular orbitals with the electrode Fermi energy. The implementation of this long-sought-after transport regime within molecular materials offers new opportunities for the integration of manifold properties within emerging nanoelectronic technologies.

36 MATERIALS SCIENCE↗

Quantum Theory, Quantum Materials, Quantum Computing

The Sanibel Symposium series is renowned amongst materials theorists, quantum chemists, and condensed matter physicists as meetings driving progress on theory, mod eling, and simulation of materials and their molecular and nano-scale constituents. The Symposia are highly unusual (perhaps unique) in their priority emphasis on theory and computation, in having no parallel sessions, in cultivating well-attended Hot-Topic contributed oral sessions, and accessible poster sessions. These provide highly visible, influential platforms for cross-fertilization among specialist investigators, hence are strong contributors to the advance of quantum information sciences (QIS) research of strategic importance to the Office of Basic Energy Sciences (BES). As part of a five-year plan to highlight QIS challenges and opportunities and foster progress on them, each of the pre ceding three Sanibel Symposia had a thematic focus, Quantum Theory, Quantum Materi als, Quantum Computing, as a major program component. Emphasis was on quantum materials and their molecular constituents. The award for 2024 was for year four of that sustained thematic focus.

36 MATERIALS SCIENCE↗

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗

Visualizing electron localization of WS 2 /WSe 2 moiré superlattices in momentum space

The search for materials with flat electronic bands continues due to their potential to drive strong correlation and symmetry breaking orders. Electronic moirés formed in van der Waals heterostructures have proved to be an ideal platform. However, there is no holistic experimental picture for how superlattices modify electronic structure. By combining spatially resolved angle-resolved photoemission spectroscopy with optical spectroscopy, we report the first direct evidence of how strongly correlated phases evolve from a weakly interacting regime in a transition metal dichalcogenide superlattice. By comparing short and long wave vector moirés, we find that the electronic structure evolves into a highly localized regime with increasingly flat bands and renormalized effective mass. The flattening is accompanied by the opening of a large gap in the spectral function and splitting of the exciton peaks. These results advance our understanding of emerging phases in moiré superlattices and point to the importance of interlayer physics.

36 MATERIALS SCIENCE↗

Correlated nanoelectronics and the second quantum revolution

The growing field of correlated nanoelectronics exists at the intersection of two established fields: correlated oxide electronics and semiconductor nanoelectronics. The development of quantum technologies that exploit quantum coherence and entanglement for the purposes of computation, simulation, and sensing will require complex material properties to be controlled at nanoscale dimensions. Heterostructures and nanostructures formed at the interface between LaAlO 3 and SrTiO 3 exhibit striking behavior that arises from the ability to program the conductive behavior at extreme nanoscale dimensions. The active electronic layer, SrTiO 3 , exhibits a wide range of gate-tunable phenomena such as ferroelectricity, ferroelasticity, magnetism, superconductivity, and spin–orbit coupling, all of which can be controlled at the nanoscale using two reversible methods: conductive atomic force microscope lithography and ultra-low-voltage electron beam lithography. Mesoscopic devices such as single-electron transistors and quasi-one-dimensional electron waveguides can be “sketched” using these techniques, and the properties of these devices differ significantly from those created from traditional semiconductors, such as Si or GaAs. The strongly correlated nature of the SrTiO 3 system is evident from superconducting behavior as well as a state in which electrons are paired outside the superconducting state. A highly exotic phase was discovered in which a degenerate quantum liquid is formed from bound states of n = 2, 3, 4, … electrons. Further development of correlated nanoelectronics based on the LaAlO 3 /SrTiO 3 system can potentially lead to a general platform for quantum simulation as well as a pathway for the development of highly entangled states of multiple photons.

36 MATERIALS SCIENCE↗

Macrovoid resolved simulations of transport through HPRO relevant membrane geometries

Modeling the transport properties such as diffusivity and permeability of high pressure reverse osmosis (HPRO) membranes is critical for the selection and manufacture of membranes suitable for operation under high pressure. These properties can be significantly affected by the changes in heterogeneous pore structures due to compaction. Here, the modeling platform presented in this work resolves the two scale porosity in HPRO relevant membranes. A synthetic membrane geometry is constructed based on available experimental visualizations of pore structures. The simulations directly capture the flow channeling that results from a combination of material properties and geometric features of the macrovoids. A parametric study is presented to account for the transition of flow characteristics from a material governed regime to a macrovoid governed regime. Permeability of the membrane is evaluated using the simulation data and compared with an existing model that scales with the square of tortuosity over a range of material properties. The model is found to perform well under a narrow range of tortuosity while deviating from the calculated permeabilities at extreme conditions. The effective permeability of the membrane is found to vary by at least two orders of magnitude between the two flow regimes. It is also observed that tortuosity is a bounded property with its upper limit determined by the macrovoid geometry. Consequently, the tortuosity based correlations fail near a flow regime that is mainly governed by the macrovoids. The modeled permeability can be more than an order of magnitude smaller than the simulation result. A new model based on flux-weighted porosity of a membrane is introduced and its correlation with tortuosity is studied. The model agrees with the simulated data as, in addition to tortuosity, it also accounts for the flux partition within and outside the flow channels. Such correlations enable extending the existing understanding of flow characteristics to enhance predictability of porous media models.

42 ENGINEERING↗

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗