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Periodic Narrowband Radio Wave Emissions and Inward Plasma Transport at Saturn's Magnetosphere
The abrupt brightening of an Energetic Neutral Atom (ENA) blob or cloud has been interpreted as plasma injection in the Kronian magnetosphere (termed ENA injection herein). Morphologically, there appears to be two types of abrupt ENA cloud brightening: (1) the brightening of a large cloud usually seen at distances >10–12 R {sub s} (R {sub s} ∼ 60,268 km) in the midnight or postmidnight region; (2) the brightening of a smaller cloud usually seen at distances <10–12 R {sub s} around 21–03 magnetic local time. Among many radio waves observed at Saturn, type 2 ENA injections correlate best with the 5 kHz narrowband (NB) waves. Using Cassini Ion and Neutral Camera (INCA) and Radio and Plasma Wave Science (RPWS) data, we examine the periodicities of the type 2 ENA injections and the 5 kHz NB emissions as well as their cross-correlations, which have been previously used to measure the lag times or phase differences. Because correlational analysis can only establish linear relationships, we also use mutual information to establish linear and nonlinear relationships. On average, the peak of the 5 kHz NB emission lags those of the type 2 ENA injection by about a few minutes to 2 hr. The injection of hot plasma to the inner magnetosphere can lead to temperature anisotropy, which can generate electrostatic upper hybrid waves, which upon encountering the high-density gradient at the outer edge of the Enceladus density torus, can mode convert to Z mode and then to O mode. The 5 kHz NB waves commonly propagate in the O mode.
High Thermoelectric Performance in the New Cubic Semiconductor AgSnSbSe 3 by High-Entropy Engineering
We investigate the structural and physical properties of the AgSn m SbSe m+2 system with m = 1-20 (i.e., SnSe matrix and ~5-50% AgSbSe 2 ) from atomic, nano, and macro length scales. We find the 50:50 composition, with m = 1 (i.e., AgSnSbSe 3 ), forms a stable cation-disordered cubic rock-salt p-type semiconductor with a special multi-peak electronic valence band structure. AgSnSbSe 3 has an intrinsically low lattice thermal conductivity of ~0.47 W m -1 K -1 at 673 K owing to the synergy of cation disorder, phonon anharmonicity, low phonon velocity, and low-frequency optical modes. Furthermore, Te alloying on Se sites creates a quinary high-entropy NaCl-type solid solution AgSnSbSe 3-x Te x with randomly disordered cations and anions. The extra point defects and lattice dislocations lead to glass-like lattice thermal conductivities of ~0.32 W m -1 K -1 at 723 K and higher hole carrier concentration than AgSnSbSe 3 . Concurrently, the Te alloying promotes greater convergence of the multiple valence band maxima in AgSnSbSe 1.5 Te 1.5 , the composition with the highest configurational entropy. Facilitated by these favorable modifications, we achieve a high average power factor of ~9.54 μW cm -1 K -2 (400-773 K), a peak thermoelectric figure of merit ZT of 1.14 at 723 K, and a high average ZT of ~1.0 over a wide temperature range of 400-773 K in AgSnSbSe 1.5 Te 1.5 .
Deep learning assisted jet tomography for the study of Mach cones in QGP
Abstract Mach cones are expected to form in the expanding quark-gluon plasma (QGP) when energetic quarks and gluons traverse the hot medium at a velocity faster than the speed of sound in high-energy heavy-ion collisions. The shape of the Mach cone and the associated diffusion wake are sensitive to the initial jet production location and the propagation direction of the parton shower relative to the radial flow because of the distortion caused by the collective expansion of the QGP and the large density gradient. The shape of jet-induced Mach cones and their distortions in heavy-ion collisions provide a unique and direct probe of the dynamical evolution and the equation of state of QGP. However, it is difficult to identify the Mach cone and the diffusion wake in current experimental measurements of final hadron distributions because they are averaged over all possible initial jet production locations and parton-shower propagation directions. To overcome this difficulty, we develop a deep learning assisted jet tomography which uses the full information of the final hadrons from jets to localize the initial jet production positions. This method can help to constrain the initial regions of jet production in heavy-ion collisions and enable a differential study of Mach-cones with different path lengths and orientations relative to the radial flow of the QGP in heavy-ion collisions.
A machine learning photon detection algorithm for coherent x-ray ultrafast fluctuation analysis
X-ray free electron laser experiments have brought unique capabilities and opened new directions in research, such as creating new states of matter or directly measuring atomic motion. One such area is the ability to use finely spaced sets of coherent x-ray pulses to be compared after scattering from a dynamic system at different times. This enables the study of fluctuations in many-body quantum systems at the level of the ultrafast pulse durations, but this method has been limited to a select number of examples and required complex and advanced analytical tools. By applying a new methodology to this problem, we have made qualitative advances in three separate areas that will likely also find application to new fields. As compared to the “droplet-type” models, which typically are used to estimate the photon distributions on pixelated detectors to obtain the coherent x-ray speckle patterns, our algorithm achieves an order of magnitude speedup on CPU hardware and two orders of magnitude improvement on GPU hardware. We also find that it retains accuracy in low-contrast conditions, which is the typical regime for many experiments in structural dynamics. Finally, it can predict photon distributions in high average-intensity applications, a regime which up until now has not been accessible. Our artificial intelligence-assisted algorithm will enable a wider adoption of x-ray coherence spectroscopies, by both automating previously challenging analyses and enabling new experiments that were not otherwise feasible without the developments described in this work.
Understanding the effect of minor alloying elements on helium bubble formation in ferritic-martensitic steels
Ferritic-martensitic steels are promising structural materials for advanced nuclear reactors. To minimize long-term radioactivity, reduced-activation ferritic-martensitic steels have been developed by substituting high-activation elements like Ni and Mo with low-activation elements such as W. However, the impact of these alloying modifications on helium bubble formation, which plays a key role in material swelling, remains unclear. Here, in this study, we compared helium bubble formation in ferritic-martensitic steel T91 and reduced-activation ferritic-martensitic steel F82H. Both materials were irradiated with sequential 100 keV, 150 keV, and 200 keV helium ions to a dose of 0.5 dpa and a helium concentration of 9,000 appm at 500°C. The helium bubbles in F82H exhibited a larger average size and a lower density than those in T91, suggesting differences in minor alloying elements may influence the bubble growth. Here, to investigate the effects of these alloying elements, we characterized radiation-induced segregation near bubbles and grain boundaries. Prominent Ni-Mn-Si enriched clusters were found near bubbles in T91, while only Mn-Si enriched clusters were found near bubbles in F82H. In addition, the obvious Cr enrichment near grain boundaries was absent around bubbles in both steels. The different segregation trends among elements revealed the variations in element diffusion mechanisms and the different sink biases between bubbles and grain boundaries. Cr enrichment near grain boundaries is mostly driven by interstitial-mediated diffusion. However, since bubble growth relies on net vacancy flux, vacancy-mediated diffusion plays a dominant role in controlling element segregation near bubbles. Therefore, Cr enrichment was not found near bubbles. Because of preferential vacancy-drag diffusion for Ni, Si and Mn, these elements were enriched near bubbles. Due to the strong binding energies of vacancies with these solute atoms, the vacancy diffusivity can be reduced near these solutes. Therefore, the more prominent Ni-Si-Mn clustered near helium bubbles in T91 lead to stronger suppression of helium bubble growth compared to F82H.
Deconvoluting the Magnetic Structure of the Commensurately Modulated Quinary Zintl Phase Eu 11– x Sr x Zn 4 Sn 2 As 12
The structure, magnetic properties, and 151 Eu and 119 Sn Mössbauer spectra of the solid-solution Eu 11– x Sr x Zn 4 Sn 2 As 12 are presented. A new commensurately modulated structure is described for Eu 11 Zn 4 Sn 2 As 12 ( R 3 m space group, average structure) that closely resembles the original structural description in the monoclinic C 2/ c space group with layers of Eu, puckered hexagonal Zn 2 As 3 sheets, and Zn 2 As 6 ethane-like isolated pillars. The solid-solution Eu 11– x Sr x Zn 4 Sn 2 As 12 (0 < x < 10) is found to crystallize in the commensurately modulated R 3 space group, related to the parent phase but lacking the mirror symmetry. Eu 11 Zn 4 Sn 2 As 12 orders with a saturation plateau at 1 T for 7 of the 11 Eu 2+ cations ferromagnetically coupled (5 K) and shows colossal magnetoresistance at 15 K. The magnetic properties of Eu 11 Zn 4 Sn 2 As 12 are investigated at higher fields, and the ferromagnetic saturation of all 11 Eu 2+ cations occurs at ~8 T. The temperature-dependent magnetic properties of the solid solution were investigated, and a nontrivial structure–magnetization correlation is revealed. The temperature-dependent 151 Eu and 119 Sn Mössbauer spectra confirm that the europium atoms in the structure are all Eu 2+ and that the tin is consistent with an oxidation state of less than four in the intermetallic region. The spectral areas of both Eu(II) and Sn increase at the magnetic transition, indicating a magnetoelastic effect upon magnetic ordering.
Role of Chemical Disorder in High Temperature Dislocation Glide in Refractory Multi-principal Element Alloys
Refractory multi-principal element alloys (RMPEAs) combine a chemically disordered lattice with a structurally ordered, single‐phase body‐centered cubic (bcc) crystal structure. Chemical fluctuations in these alloys give rise to significant energy barriers that impede dislocation motion. In this study, we use phase field dislocation dynamics to examine how spatial temperature fluctuations compete with randomness in energy barriers to affect the motion of long screw dislocations in three equi-atomic MoNbTa‐based RMPEAs: MoNbTa, MoNbTaW, and MoNbTaVW. Over a wide range of homologous temperatures (T h ≈ 0–0.6), we determined a screw dislocation ‘flow stress’ as the minimum applied stress to sustain continuous motion over a long excursion distance within a fixed timeframe. All three RMPEAs exhibit temperature dependent flow stress with three characteristic glide regimes: at low homologous temperatures, flow stress drops sharply, and screw glide remains planar and rectilinear; at intermediate homologous temperatures, the flow stress levels off as glide becomes planar but wavy; and at high homologous temperatures, flow stress plateaus as screws exhibit nonplanar, three‐dimensional motion. Glide kinetics and transition temperatures are controlled by the chemically induced fluctuations in the energy landscape. The rectilinear to wavy transition temperature is controlled by statistically weakest local barriers in the glide plane, whereas the wavy to 3D transition temperature is governed by statistically strongest local barriers. At low and intermediate homologous temperatures, the relative spread in energy barriers governs glide behavior by controlling the local kinetics of kink pair formation and kink pinning. At high homologous temperatures, the average barrier height governs the glide behavior by controlling the number of out-of-plane excursions during 3D glide. These findings reveal how random chemical fluctuations determine screw‐driven plasticity in RMPEAs, providing critical insight for the design of high temperature structural alloys.
Multiport High-pressure Fluid Cell (MHPFC) for Photon and Electron Beams
A multiport high-pressure fluid cell was developed based on an engineered thin film membrane solution with a reinforced frame of boron-doped silicon, optimized to withstand better pressure with an increase of 17.6% in average burst pressure over similar membranes without frame. The novel cells (patent pending) have 8 microfluidic ports, two intra-cavity electrodes and two pressure sensors on a 8 mm x 8 mm Si chip. The prototypes resisted up to 60 bar with 50-nm-thick silicon nitride membranes of size 70 nm x 70 nm. The cells can be used for testing reactions in fluids in medium-high pressure (up to 300 bar) using X-rays (primary application), electron beams, IR or visible light. Improvements in the pressure sensing setup and customization for applications are supposed to follow.
Laboratory-Scale Coal-Derived Graphene Process (Final Report)
The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.
Thermodynamics of Metal Carbonates and Bicarbonates and Their Hydrates for Mg, Ca, Fe, and Cd Relevant to Mineral Energetics
The heats of formation of carbonate, bicarbonate and bicarbonate/hydroxide metal complexes and hydrated versions these complexes of Mg 2+ , Ca 2+ , Fe 2+ , and Cd 2+ are predicted from atomization energies using correlated molecular orbital theory at the CCSD(T) level extrapolated to the complete basis set limit following the Feller-Peterson-Dixon (FPD) approach. Using the calculated gas phase values and the available experimental solid state values, the cohesive energies of selected minerals were calculated. The gas phase decomposition energies into MO, CO 2 and H 2 O follow the order Mg ~ Ca > Cd ~ Fe, and correlate with the hardness of the metal +2 ions. Gas phase hydration energies show that the order is Mg > Fe > Ca ~ Cd. There are a number of bulk hydrated Mg and Ca complexes that occur as minerals but there are few if any for Fe and Cd, suggesting that a number of factors are important in determining the stability of the bulk mineral hydrates. The FPD heats of formation were used to benchmark a range of density functional theory exchange-correlation functionals, including those commonly used in solid state mineral calculations. None of the functionals provided chemical accuracy agreement (± 1 kcal/mol) with the FPD results The best functionals are ωB97X and ωB97X-D with mean average unsigned errors of 10 kcal/mol.
Efficient perturbation-tracking method for directly probing the spectral phonon properties from molecular dynamics simulations
Existing methods for directly extracting the spectral phonon properties from molecular dynamics (MD) simulations, like the normal mode analysis (NMA) and spectral energy density analysis, all require a very long simulation time to produce reliable results with good convergence. So far, these methods are mainly applied in studies using small systems and with empirical potentials, as the heavy computational load has greatly hindered their further applications. Here we propose a perturbation-tracking (PT) method for directly probing the mode-wise phonon anharmonic frequencies and lifetimes. We show that results obtained from our method are in excellent agreement with those from the conventional NMA approach, using Si as the model material system. Comparing with the NMA approach, the PT method offers a greater accuracy and significant improvement of efficiency. It takes an average of two orders of magnitude and up to three orders of magnitude less simulation time to obtain the same lifetime result of a phonon mode with intermediate to high accuracy. Meanwhile, our method preserves all the dynamics of probed phonon mode from a particular state, which means it is capable of studying the transient thermal transport processes in a nonequilibrium system. Besides the exceptional efficiency, our method also comes with freedom to choose to probe only those modes of interest. This makes it ideal for use with large systems and in computationally demanding applications, such as ab initio MD simulations. Moreover, the PT method we propose here is very straightforward and easy to implement.
Real-time tracking of protein unfolding with time-resolved x-ray solution scattering
The correct folding of proteins is of paramount importance for their function, and protein misfolding is believed to be the primary cause of a wide range of diseases. Protein folding has been investigated with time-averaged methods and time-resolved spectroscopy, but observing the structural dynamics of the unfolding process in real-time is challenging. Here, we demonstrate an approach to directly reveal the structural changes in the unfolding reaction. We use nano- to millisecond time-resolved x-ray solution scattering to probe the unfolding of apomyoglobin. The unfolding reaction was triggered using a temperature jump, which was induced by a nanosecond laser pulse. We demonstrate a new strategy to interpret time-resolved x-ray solution scattering data, which evaluates ensembles of structures obtained from molecular dynamics simulations. We find that apomyoglobin passes three states when unfolding, which we characterize as native, molten globule, and unfolded. The molten globule dominates the population under the conditions investigated herein, whereas native and unfolded structures primarily contribute before the laser jump and 30 μs after it, respectively. The molten globule retains much of the native structure but shows a dynamic pattern of inter-residue contacts. Our study demonstrates a new strategy to directly observe structural changes over the cause of the unfolding reaction, providing time- and spatially resolved atomic details of the folding mechanism of globular proteins.
Effects of stereoisomeric structure and bond location on the ignition and reaction pathways of hexenes
The current work presents new experimental autoignition and speciation data on the two cis-hexene isomers: cis-2-hexene and cis-3-hexene. The new data provide insights on the effects of carbon-carbon double bond location and stereoisomeric structures on ignition delay times and reaction pathways for linear hexene isomers. Experiments were performed using the University of Michigan rapid compression facility to determine ignition delay times from pressure-time histories. Stoichiometric (Φ = 1.0) mixtures at dilution levels of inert gas to O 2 = 7.5:1 (mole basis) were investigated at an average pressure of 11 atm and temperatures from 809 to 1052 K. Speciation experiments were conducted at T = 900 K for the two cis-hexene isomers, where fast-gas sampling and gas chromatography were used to identify and quantify the two cis-hexene isomers and stable intermediate species. The ignition delay time data showed negligible sensitivity to the location of the carbon-carbon double bond and the stereoisomeric structure (cis-trans), and the species data showed no correlation with the stereoisomeric structure, but there was a strong correlation of some of the measured species with the location of the double bond in the hexene isomer. In particular, 2-hexene showed strong selectivity to propene, acetaldehyde, and 1,3-butadiene, and 3-hexene showed selectivity to propanal. Model predictions of ignition delay times were in excellent agreement with the experimental data. Furthermore, there was generally good agreement for the model predictions of the species data for 2-hexene; however, the mechanism overpredicted some of the small aldehyde (C 2 -C 4 ) species for 3-hexene. Reaction pathway analysis indicates the hexenes are almost exclusively consumed by H-atom abstraction reactions at the conditions studied (P = 11 atm, T > 900 K), and not by C 3 -C 4 scission as observed in high-temperature (>1300 K) hexene ignition studies. Improved estimates for 3-hexene + OH reactions may improve model predictions for the species measured in this work.
Simple and General Unitarity Conserving Numerical Real-Time Propagators of the Time-Dependent Schrödinger Equation Based on Magnus Expansion
Magnus expansion (ME) provides a general way to expand the real-time propagator of a time-dependent Hamiltonian within the exponential such that the unitarity is satisfied at any order. Here, we use this property and explicit integration of Lagrange interpolation formulas for the time-dependent Hamiltonian within each time interval and derive approximations that preserve unitarity for the differential time evolution operators of general time-dependent Hamiltonians. The resulting second-order approximation is the same as using the average of Hamiltonians for two end points of time. We identify three fourth-order approximations involving commutators of Hamiltonians at different times and also derive a sixth-order expression. A test of these approximations along with other available expressions for a two-state time-dependent Hamiltonian with sinusoidal time dependences provides information on the relative performance of these approximations and suggests that the derived expressions can serve as useful numerical tools for time evolution in time-resolved spectroscopy, quantum control, quantum sensing, real-time ab initio quantum dynamics, and open system quantum dynamics.
Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces
Heterogeneous catalysis is at the heart of chemical industry. Being able to tune and design efficient catalysts for processes of interest is of an utmost importance, and for this, the molecular-level understanding of heterogeneous catalysts is the first step, and indeed a prime focus of the modern catalysis research. For a long time, a single most thermodynamically stable structure of the catalytic interface attained in reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures, pressures, and binding and changing reagents. Among particularly dynamic interfaces are such widely-used catalysts as crystalline and amorphous surfaced supporting (sub-)nano metallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states in catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many (not one) structures. As such, every member in the ensemble contributes to the properties of the catalyst differently, and in proportion to its probability to be populated. This new notion flips the established paradigm and calls for new theory, modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported sub-nano cluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, CuPd clusters, catalytic toward oxidative and non-oxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous “every atom counts” phenomenon. The support and adsorbates affect catalyst structures, and state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time-scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations, and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima, and pathways sampling, as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and predicting of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.
The sPHENIX Micromegas Outer Tracker
The sPHENIX Time Projection Chamber Outer Tracker (TPOT) is a Micromegas based detector. It is a part of the sPHENIX experiment that aims to facilitate the calibration of the Time Projection Chamber, in particular the correction of the time-averaged and beam-induced distortions of the electron drift. Here, this paper describes the detector mission, setup, construction, installation, commissioning and performance during the first year of sPHENIX data taking.
Third-body stabilization of supercritical CO 2 in CO oxidation: development and application of a ReaxFF force field for the CO/O/CO 2 system
Supercritical CO 2 (scCO 2 ) plays a crucial role as a solvent in separation processes, advanced power cycles, and materials processing. Nonetheless, the atomistic comprehension of how the dense scCO 2 matrix influences the fundamental reaction of carbon monoxide (CO) is still insufficiently explored. Experimental studies and molecular dynamics (MD) simulations frequently fail to detect the highly reactive, transient intermediates, such as atomic oxygen (O), that drive these reactions. Here, to address this issue, we have developed a novel ReaxFF reactive force field for the CO 2 /CO/O system. The force field parameters were calibrated using density functional theory and second-order Møller-Plesset calculations to model CO 2 crystal properties, intermolecular interactions, bond dissociation curves, and reaction energy barriers. The force field reproduces the cohesive energy of the CO 2 crystal, the pressure characteristics of bulk scCO 2 , the equation-of-state behavior over a wide pressure–density range, the pressure dependence of the C–O bond length under compression, and the structural properties of liquid and scCO 2 , as documented by experiments, ab-initio MD, and prominent non-reactive models. The force field was subsequently applied to study the CO + O → CO 2 reaction. In a dilute environment, the reaction is inefficient as the newly formed CO 2 rapidly dissociates due to excess kinetic and potential energy acquired from the exothermic reaction. Conversely, in a dense scCO 2 environment, the surrounding matrix acts as an efficient third body, stabilizing the emerging CO2 product via molecular collisions. Statistical analysis confirms an average excess energy dissipation of 133.9 ± 3.6 kcal/mol over 112.4 ± 17.9 ps. Kinetic energy decomposition reveals that ∼ 92% of the excess kinetic energy is stored in internal (rotational and vibrational) degrees of freedom. This ReaxFF force field establishes a mechanistic foundation for third-body stabilization in dense reactive environments.