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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 235 records · Page 13

Deactivating Emission in Azulene via Solvent-Induced (Anti)Aromaticity

Anti-Kasha emission is a coveted feature in optoelectronics, with promise in areas such as imaging, sensing, and the production of white-light LEDs via dual-photon emission. Despite being a rare feature in organic systems, anti-Kasha emission is readily observed in the deceptively simple molecule azulene, which possesses two bright singlet states in the UV–visible spectrum and readily emits from the S 2 state. With dominant anti-Kasha emission and decades of synthetic study, azulene is a perfect candidate for novel material fabrication; however, large gaps persist in understanding the photophysics of even the simple parent compound. These range from competing, experimentally unverified models of azulene reactivity and aromaticity to the unexplained deactivation of anti-Kasha emission in a host of azulene derivatives. Herein, we use fluorescence and transient absorption spectroscopies to explore the detailed solvent dependence of azulene photophysics. We discover a tunable reduction in the S 2 lifetime via weak complexation with aromatic solvents. Interestingly, our results are independent of polarity, highlighting the primacy of peripherally delocalized 10-π Hückel aromaticity over zwitterionic character. When the dipolar character is enhanced through chemical functionalization, we observe even greater sensitivity to solvent aromaticity and more rapid quenching, revealing the role of conical intersections in azulenes with zwitterionic excited states. Overall, this work provides essential mechanistic insight into the photophysics of azulene and reveals a simple new approach to control the excited-state aromaticity and anti-Kasha emission in this class of materials.

Absorption↗

Universal diamond edge Raman scale to 0.5 terapascal and implications for the metallization of hydrogen

The recent progress in generating static pressures up to terapascal values opens opportunities for studying novel materials with unusual properties, such as metallization of hydrogen and high-temperature superconductivity. However, an evaluation of pressure above ~0.3 terapascal is a challenge. We report a universal high-pressure scale up to ~0.5 terapascal, which is based on the shift of the Raman edge of stressed diamond anvils correlated with the equation of state of Au and does not require an additional pressure sensor. According to the new scale, the pressure values are substantially lower by 20% at ~0.5 terapascal compared to the extrapolation of the existing scales. We compare the available data of H 2 at the highest static pressures. We show that the onset of the proposed metallization of molecular hydrogen reported by different groups is consistent when corrected with the new scale and can be compared with various theoretical predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-pressure annealing driven nanocrystal formation in Zr 50 Cu 40 Al 10 metallic glass and strength increase

Pressure-induced structural changes in metallic glasses have been of great interest as they are expected to open new ways to synthesize novel materials with unexpected properties. Here, we investigated the effect of simultaneous high-pressure and high-temperature treatment on the structure and properties of a Zr 50 Cu 40 Al 10 metallic glass by in situ X-ray structure measurement and property analysis of the final material. We found the unusual formation of Cu-rich nanocrystals at high pressure and temperature, accompanied by significant strength and hardness enhancement. Based on reverse Monte Carlo modeling and molecular dynamics simulations, the structure of the metallic glass changed to a densely packed, chemically uniform configuration with high short-range and medium-range ordering at high pressure and temperature. These results show that high-pressure annealing processes provide a new way to improve and control properties without changing their composition.

36 MATERIALS SCIENCE↗

Correlating the Morphological Changes to Electrochemical Performance During Carbon Corrosion in Polymer Electrolyte Fuel Cells

A mechanistic understanding of carbon corrosion in polymer electrolyte fuel cells (PEFCs) is required to design durable catalyst layers. Uncontrolled startup and shutdown of PEFCs cause electrochemical oxidation of carbon, which leads to several degradation phenomena, such as loss in electrochemical surface area (ECSA), pore structure collapse or increase in mass transport resistance. In this study, the chronology of morphological changes in the cathode catalyst layer due to carbon corrosion was identified and correlated with electrochemical performance degradation. PEFCs were subjected to the Department of Energy carbon corrosion accelerated stress test (AST) protocol. The study revealed two phases: in the initial phase (~500 AST cycles), amorphous carbon in contact with Pt nanoparticles oxidized fast. Rapid carbon loss and catalyst layer thinning occurred, but pore structure did not change significantly. Pt nanoparticles detached from the support and ECSA decreased drastically. In the second phase (~1500 AST cycles), carbon corrosion slowed down, but severe pore structure collapse was observed. Porosity and pore connectivity within the cathode catalyst layer decreased considerably. Electrochemical diagnostics corroborated this finding by showing significantly higher O2 mass transport resistance. Lastly, no significant change was observed in the concentration of oxides on the carbon surface after AST. But overall water management in the cathode catalyst layer deteriorated as the pore structure collapsed. This study provides an in-depth understanding of morphological changes during PEFC carbon corrosion AST protocol and motivates novel material design strategies to enable durable PEFCs.

catalyst layers↗

Boosting the performance of reversible solid oxide electrochemical cells with a novel hybrid oxygen electrode, Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ

Solid oxide electrochemical cells (SOECs) stand out as a highly promising clean energy technology that offers several benefits, showing significant potential to play a pivotal role in the transition towards a sustainable and low-carbon energy future. SOECs can efficiently convert the chemical energy stored in fuels to electricity in fuel cell mode, and produce various chemicals from abundant feedstocks (e.g., CO 2 , H 2 O) and intermittent solar/wind-based renewable electricity. Despite extensive efforts that have been devoted to designing novel materials and optimizing SOEC manufacturing processes, aiming to achieve enhanced energy efficiency, the current SOECs still suffer from poor performance, which is mainly due to the sluggish oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) kinetics. To address this challenge, in this work, we have successfully designed an in situ formed hybrid oxygen electrode material (Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ ), which significantly improves the surface oxygen exchange coefficient and bulk oxygen-ion diffusion coefficient, enhancing the OER and ORR electrocatalytic activities. Further, the SOECs equipped with this newly developed oxygen electrode achieved exceptional performance for power generation using both hydrogen and propane as the fuels. At 750 °C, a peak power density of 2.4 W cm -2 was obtained with H 2 as the fuel. Additionally, the SOECs attain unprecedented performance in steam electrolysis mode. A current density of 4.4 A cm -2 was achieved at 1.3 V and 750 °C, which represents the highest performance among all yttria-stabilized zirconia (YSZ) electrolyte-based SOECs. The SOECs also deliver remarkable stability during the accelerated stability testing, highlighting the great potential of Pr 1.39 Ba 0.14 Sr 0.53 Co 1.48 Fe 0.76 O 6- δ -Ba 0.66 Sr 0.34 CoO 3- δ as a high-performance oxygen electrode for next generation SOECs.

08 HYDROGEN↗

Mean-field theory for the structure of strongly interacting active liquids

Active systems, which are driven out of equilibrium by local non-conservative forces, exhibit unique behaviors and structures with potential utility for the design of novel materials. An important and difficult challenge along the path toward this goal is to precisely predict how the structure of active systems is modified as their driving forces push them out of equilibrium. Here, we use tools from liquid-state theories to approach this challenge for a classic minimal active matter model. First, we construct a nonequilibrium mean-field framework that can predict the structure of systems of weakly interacting particles. Second, motivated by equilibrium solvation theories, we modify this theory to extend it with surprisingly high accuracy to systems of strongly interacting particles, distinguishing it from most existing similarly tractable approaches. Furthermore, our results provide insight into spatial organization in strongly interacting out-of-equilibrium systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Autonomous convergence of STM control parameters using Bayesian optimization

Scanning tunneling microscopy (STM) is a widely used tool for atomic imaging of novel materials and their surface energetics. However, the optimization of the imaging conditions is a tedious process due to the extremely sensitive tip–surface interaction, thus limiting the throughput efficiency. In this paper, we deploy a machine learning (ML)-based framework to achieve optimal atomically resolved imaging conditions in real time. The experimental workflow leverages the Bayesian optimization (BO) method to rapidly improve the image quality, defined by the peak intensity in the Fourier space. The outcome of the BO prediction is incorporated into the microscope controls, i.e., the current setpoint and the tip bias, to dynamically improve the STM scan conditions. We present strategies to either selectively explore or exploit across the parameter space. As a result, suitable policies are developed for autonomous convergence of the control parameters. The ML-based framework serves as a general workflow methodology across a wide range of materials.

97 MATHEMATICS AND COMPUTING↗

Compositionally complex carbide ceramics: A perspective on irradiation damage

Extensive experimental and computational studies have demonstrated outstanding physical and chemical properties of the novel materials of compositionally complex carbides (CCCs), enabling their promising applications in advanced fission and fusion energy systems. This perspective provides a comprehensive overview of radiation damage behavior reported in the literature to understand the fundamental mechanisms related to the impact of multi-principal metal components on phase stability, irradiation-induced defect clusters, irradiation hardening, and thermal conductivity of compositionally complex carbides. Several future research directions are recommended to critically evaluate the feasibility of designing and developing new ceramic materials for extreme environments using the transformative “multi-principal component” concept. Compared to the existing materials for nuclear applications including stainless steels, nickel alloys, ZrC, SiC, and potentially high-entropy alloys, as well as certain other compositionally complex ceramic families. CCCs appear to be more resistant to amorphization, growth of irradiation defect clusters, and void swelling.

36 MATERIALS SCIENCE↗

Perspectives of active Si photonics devices for data communication and optical sensing

Si photonics has made rapid progress in research and commercialization in the past two decades. While it started with electronic–photonic integration on Si to overcome the interconnect bottleneck in data communications, Si photonics has now greatly expanded into optical sensing, light detection and ranging (LiDAR), optical computing, and microwave/RF photonics applications. From an applied physics point of view, this perspective discusses novel materials and integration schemes of active Si photonics devices for a broad range of applications in data communications, spectrally extended complementary metal–oxide–semiconductor (CMOS) image sensing, as well as 3D imaging for LiDAR systems. We also present a brief outlook of future synergy between Si photonic integrated circuits and Si CMOS image sensors toward ultrahigh capacity optical I/O, ultrafast imaging systems, and ultrahigh sensitivity lab-on-chip molecular biosensing.

electronic band structure↗

Causal discovery from data assisted by large language models

Knowledge-driven discovery of novel materials necessitates the development of causal models for property emergence. While in the classical physical paradigm, the causal relationships are deduced based on physical principles or via experiment, the rapid accumulation of observational data necessitates learning causal relationships between dissimilar aspects of material structure and functionalities based on observations. For this, it is essential to integrate experimental data with prior domain knowledge. Here, we demonstrate this approach by combining high-resolution scanning transmission electron microscopy data with insights derived from large language models (LLMs). By applying ChatGPT to domain-specific literature, such as arXiv papers on ferroelectrics, and combining the obtained information with data-driven causal discovery, we construct adjacency matrices for directed acyclic graphs that map the causal relationships between structural, chemical, and polarization degrees of freedom in Sm-doped BiFeO 3 . This approach enables us to hypothesize how synthesis conditions influence material properties and guides experimental validation. Furthermore, the ultimate objective of this work is to develop a unified framework that integrates LLM-driven literature analysis with data-driven discovery, facilitating the precise engineering of ferroelectric materials by establishing clear connections between synthesis conditions and their resulting material properties.

Causal inference↗

Operando characterization of conductive filaments during resistive switching in Mott VO 2

Significance To perform hardware-based neuromorphic computing, novel materials exhibiting a wide variety of electronic properties are currently being explored. VO 2 is well known to exhibit an insulator-to-metal transition as well as volatile resistive switching. Many questions regarding the basic mechanism of the nonvolatile switching in this material are unanswered. In this work, the formation and relaxation of conductive filaments through nonvolatile resistive switching in VO 2 devices have been realized. The V 5 O 9 Magnéli phase conductive filament has been identified. Our results demonstrate that both resistive switching behaviors can be achieved in a single material, crucial for future technology like resistive switching memories or neuromorphic logic.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integral Nuclear Data and Benchmarking Needs for Fusion Energy Systems

Fusion energy systems are currently being designed and optimized using radiation transport codes. To deal with the unique environment inside a fusion-based system, many of these designs incorporate novel materials able to withstand the high radiation fields, ensure adequate cooling and thermal protection, and produce tritium. Validation plays a vital role in building trust in the predictive power of these models and computational methods. Validation of a code consists of modeling documented real-world experiments and comparing the code-predicted response to the measured response. Adequate validation requires measured responses from real-world experiments, also known as integral data, that mimic the system being designed, including materials, impinging radiation, and temperature, among other variables. The most trusted integral data are experimental responses that have been through a rigorous benchmarking process that develops a recommended computational model and evaluates all experimental uncertainties. Finally, there are a few research groups around the world that have been producing integral data for fusion applications, but a substantial investment is needed to address the unique validation needs of the fusion community.

Fusion↗

Bibliometric review and recent advances in total scattering pair distribution function analysis: 21 years in retrospect

Global research activities have been driven by the quest to develop and characterize novel materials for technological advancements. The total scattering pair distribution function (TSPDF) is a powerful and versatile characterization technique for examining the structural details of diverse complex materials including liquid, amorphous, disordered crystalline, and nanostructured materials. Thus, it is critical to keep track of research progress, identify research gaps, and future research directions of the application of the TSPDF technique in materials development and discovery. In this work, a bibliometric analysis of literature regarding the TSPDF technique between 2000 and 2021 was conducted using datasets retrieved from the Web of Science database. The research trends based on publication outputs, research subject distribution, co-authorships among institutions, countries/regions, co-citation of referenced sources, and keyword co-occurrence are evaluated and discussed herein. The impact of the TSPDF technique is projected to increase due to its importance in probing emerging functional materials, and the advances in specialized facilities and instrumentation among the scientific communities engaged with it. Finally, current and emerging research hotspots related to TSPDF technique such as catalysis, computer modeling and simulation, pharmaceutics, machine learning, hydrogen storage, battery materials, and layered structured materials are also identified and discussed.

36 MATERIALS SCIENCE↗

Roadmap for warm dense matter physics

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter (WDM) physics. Originating from strongly coupled plasma physics, high pressure physics and high energy density science, the WDM physics community has recently taken a giant leap forward. This is due to spectacular developments in laser technology, diagnostic capabilities, and computer simulation techniques. Only in the last decade has it become possible to perform accurate enough simulations & experiments to truly verify theoretical results as well as to reliably design experiments based on predictions. Consequently, this roadmap discusses recent developments of and contemporary challenges for theoretical methods and experimental techniques needed to describe, create and diagnose WDM. A large part of this roadmap is dedicated to specific WDM systems and applications in astrophysics, inertial confinement fusion and novel material synthesis.

dense astrophysical objects↗

Experimental observations of large changes in electron density distributions in β - Ge

We report the electron density distributions in β-Ge have been experimentally determined at in situ high-pressure conditions using synchrotron diffraction techniques in a diamond anvil cell. Upon decompression, the electron density along the $c$ axis in tetragonal β-Ge displays a sudden drop at 10–11 GPa close to that of the structural α-β transition, while the β-Ge samples remain as single crystals until transforming to metastable Ge phases around 6.7–8.5 GPa. In contrast to the covalently bonded α-Ge that displays only a weak participation of $d$ electrons in the valence band under compression above 7.7 GPa, our experimental results suggest that a large change in $d$-orbital participation can occur in the β-Ge lattice which has mixed covalent and metallic bonding. The β-Ge below 10 GPa may display large fluctuations in electronic properties, which sheds light for exploring novel materials with intriguing electronic and optical properties.

36 MATERIALS SCIENCE↗

Predicting band gaps and band-edge positions of oxide perovskites using density functional theory and machine learning

Density functional theory (DFT) within the local or semilocal density approximations, i.e., the local density approximation (LDA) or generalized gradient approximation (GGA), has become a workhorse in the electronic structure theory of solids, being extremely fast and reliable for energetics and structural properties, yet remaining highly inaccurate for predicting band gaps of semiconductors and insulators. The accurate prediction of band gaps using first-principles methods is time consuming, requiring hybrid functionals, quasiparticle GW, or quantum Monte Carlo methods. Efficiently correcting DFT-LDA/GGA band gaps and unveiling the main chemical and structural factors involved in this correction is desirable for discovering novel materials in high-throughput calculations. In this direction, we, in this study, use DFT and machine learning techniques to correct band gaps and band-edge positions of a representative subset of ABO 3 perovskite oxides. Relying on the results of HSE06 hybrid functional calculations as target values of band gaps, we find a systematic band-gap correction of ~1.5 eV for this class of materials, where ~1 eV comes from downward shifting the valence band and ~0.5 eV from uplifting the conduction band. The main chemical and structural factors determining the band-gap correction are determined through a feature selection procedure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Li interaction-induced phase transition from black to blue phosphorene

A comprehensive first-principle calculation has been carried out and revealed that at sufficiently high Li concentration and certain well-defined configurations a phase transition from black to blue phosphorene can take place. Blue phosphorene, a newly predicted allotrope of phosphorus, possesses unique crystalline and electronic structure and is a promising candidate, not only for fundamental research but also for electronic and optoelectronic applications. Methods to growth high quality blue phosphorene layers are highly desirable but challenging. Here, a novel kinetic pathway to grow blue phosphorene layers from black phosphorene layers via Li intercalation is proposed based on first principle study. This study pointed out that Li atoms intercalated in black phosphorene could act as ‘catalyst’ in the ‘reactive region’ of the lone pair of P atoms, leading to a P-P bond breaking and subsequently, a local structural transformation from orthorhombic lattice to an assembly of parallel narrow nanoribbons with rhombohedra-like symmetry. During Li deintercalation, these nanoribbons are self-mended and form blue phosphorene layers. The interlayer distance was found 4.60 Å for double layer with AA stacking and 4.13 Å for multilayer with ABC stacking, respectively, indicating a monolayer blue phosphorene can be mechanically exfoliated. Furthermore, this study also points out the possibility of new phases in other systems, where intercalation can lead to an unexpected structural phase transition and even a discovery of novel materials.

36 MATERIALS SCIENCE↗

Synthesis and characterization of the novel breathing pyrochlore compound Ba 3 ⁢Tm 2⁢ Zn 5⁢ O 11

In this study, a novel material from the rare-earth based breathing pyrochlore family, Ba 3 ⁢Tm 2 ⁢Zn 5 ⁢O 11 , was successfully synthesized. Powder x-ray diffraction and high-resolution powder neutron diffraction confirmed phase purity and the $F\bar4$3⁢𝑚 breathing pyrochlore crystal structure, while thermogravimetric analysis revealed incongruent melting behavior compared to its counterpart, Ba 3 ⁢Yb 2⁢ Zn 5⁢ O 11 . High-quality single crystals of Ba 3 ⁢Tm 2 ⁢Zn 5 ⁢O 11 were grown using the traveling solvent floating zone technique and assessed using Laue x-ray diffraction and single crystal x-ray diffraction. Further, thermodynamic characterization indicated paramagnetic behavior down to 0.05 K, and inelastic neutron scattering measurements identified distinct dispersionless crystal electric field energy bands, with the fitted crystal electric field model predicting a single-ion singlet ground state and an energy gap of ∼9 meV separating it from the first excited (singlet) state. Additional low-energy excitation studies on single crystals revealed dispersionless bands at 0.8 and 1 meV. Computed phonon dispersions from first-principles calculations ruled out phonons as the origin of these modes, further illustrating the puzzling and unique properties of Ba 3 ⁢Tm⁢ 2 Zn 5 ⁢O 11 .

36 MATERIALS SCIENCE↗