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At least 1,801 records · Page 100

Kinetic processes of phase separation and aggregation behaviors in slot-die processed high efficiency Y6-based organic solar cells

Morphological optimization has proved to be one crucial factor contributing to the 19% efficiency of Y6-based organic solar cells (OSCs). Although the relationship between component miscibility and film morphology has been established, it has not been clarified how the film formation processes proceed, especially for methods compatible with large-area fabrication, i.e. slot-die coating, which restricts the further optimization of the morphology. Herein, we comprehensively investigate the effect of miscibility and the film-formation kinetic process on film morphology during processing with different solvents. A highest power conversion efficiency (PCE) of 17.38% can be obtained in a D18:Y6 device processed with slot-die coating in an open-air environment. However, due to their relatively poor miscibility, incorporating a trace amount of chlorobenzene (CB) into CF can sufficiently promote Y6 aggregation, leading to increased phase separation and thus the average PCE drops to 15.16%. In contrast, a PM6:Y6 blend shows insensitive changes in the kinetic process as well as the final morphology, and thus in the comparable PCEs when cast with different solvents, which is ascribed to their relatively good miscibility. As a result, this work provides scientific guidelines for device optimization by combining the intermediate gap from miscibility to kinetic process and their impact on final morphology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-efficiency purification of CH 4 and H 2 energy sources enabled by a phosphotungstic acid-supported Os single-atom catalyst

Methane (CH 4 ) and hydrogen (H 2 ) show promise as low-carbon energy sources, but their impurities, including H 2 and CO, pose challenges for storage and use. To address these challenges, a robust purification protocol for CH 4 and/or H 2 , combined with the catalytic conversion of impurities into CO 2 and H 2 O, is a compelling solution. Here, in this work, we investigated 11 phosphotungstic acid (PTA)-supported single-atom catalysts (SACs) by density functional theory (DFT) computations. Os 1 /PTA SACs exhibited superior catalytic activity, and the ease of oxidation follows the CO > H 2 > CH 4 order. It facilitated efficient purification of CH 4 in solvents such as water, MeOH, and various others. For H 2 purification, Os 1 /PTA SACs demonstrated excellent performance in gas, water, and MeOH. Notably, in water and MeOH, it selectively removed CO without consuming H 2 with low free energy barriers. The strong Os-PTA interactions and charge transfer mechanism contributed to its exceptional catalytic activity. Our findings shed light on SAC behavior and their potential for efficient CH 4 and H 2 purification. By addressing impurity challenges and improving clean energy utilization, these findings contribute to the development of sustainable energy technologies.

30 DIRECT ENERGY CONVERSION↗

Tungsten single-atom catalysts for the efficient conversion of isobutene into highly branched liquid hydrocarbons

The catalytic transformation of isobutene into branched liquid hydrocarbons is crucial for the production of reformulated gasoline and fuel additives. Conventional supported catalysts often lack high activity and selectivity toward the desired highly branched dimers and trimers in isobutene oligomerization. Here, by developing a tungsten single-atom catalyst (W SAC ) atomically dispersed on a silica-doped alumina (SDA) support, we report that the W SAC /SDA catalyst enables efficient and selective conversion of isobutene into highly branched C 8 and C 12 liquid olefins while suppressing the formation of heavier hydrocarbons. The atomically dispersed W 1 –O 3 moieties incorporated within the SDA support were synthesized via a high-temperature pyrolysis of a templating zinc metal–organic framework (Zn-MOF) under argon, followed by annealing in static air. The W SAC /SDA catalysts with 1.6–3.7 wt% W loading exhibited single-atom dispersion (∼0.2 nm) and outstanding performance, achieving up to 60% and 95% selectivity to branched C8 olefins at 150 °C and 250 °C, respectively, under ambient pressure. With the demonstrated high activity, selectivity, and stability, the W SAC /SDA catalyst system presents a promising platform for next-generation heterogeneous catalysts for the efficient and selective upgrading of isobutene into high-performance fuel additives.

Branched Olefins↗

Rigid cationic ligands enable high-efficiency NIR-II photoluminescence in copper( i ) iodide hybrid semiconductors

Near-infrared (NIR) luminescent materials are pivotal for advanced optoelectronic and biomedical applications, yet attaining efficient emission in the NIR-II region (950-1400 nm) remains challenging. Here, we introduce a ligand cationization strategy for designing copper(i) iodide-organic hybrid materials that emit in the NIR-II region (920-1120 nm) with PLQYs up to 8.58%. By incorporating rigid cationic ligands with CuI modules, we synergistically achieve bandgap narrowing (to 1.51 eV) and structural rigidification via ionic-dative bonding, effectively suppressing non-radiative decay while extending emission beyond 1100 nm. Coupled with solution processability-enabled by the successful synthesis of nanometer-sized nanoparticles in various shapes-and excellent thermal stability (≥210 °C), this work establishes ligand cationization as a universal approach for designing efficient NIR-II emitters.

Chen, Jingwen↗

High-efficiency frost and ice control via sensing-assisted nanovibrational slippery surfaces

Frost and ice accretions on surfaces pose persistent challenges across numerous industrial, residential and transportation systems. While various removal strategies exist, they often suffer from limited effectiveness or high energy consumption, such as frosting delay, ice crack generation, and Joule heating. Here, in this work, we report a novel integrated approach combining vibrational quasi-liquid surface (QLS) and capacitive sensing for efficient condensate, frost, and ice management. Compared to Joule heating, our approach does not rely on complete melting and evaporation for removal, resulting in 68% and 95% energy savings for frost and ice removal, respectively. Our QLS coating significantly reduces surface retention forces, achieving 91% and 87% less residual mass compared to hydrophilic surfaces for frost and ice removal through surface nanovibration, respectively. The integrated capacitive sensor provides real-time detection of different phase states, enabling on-demand removal in precise timeframes. This sensor-assisted approach showed 3.8 times lower energy consumption compared to conventional Joule heating for defrosting. This synergistic integration of surface engineering, nanovibration, and intelligent sensing represents a significant advancement in phase change processes, offering an energy-efficient solution for frost and ice mitigation in energy-intensive systems.

Shen, Yuchen [Univ. of Texas at Dallas, Richardson↗

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN↗

A road map to cosmological parameter analysis with third-order shear statistics: III. Efficient estimation of third-order shear correlation functions and an application to the KiDS-1000 data

Context. Third-order lensing statistics contain a wealth of cosmological information that is not captured by second-order statistics. However, the computational effort it takes to estimate such statistics in forthcoming stage IV surveys is prohibitively expensive. Aims. We derive and validate an efficient estimation procedure for the three-point correlation function (3PCF) of polar fields such as weak lensing shear. We then use our approach to measure the shear 3PCF and the third-order aperture mass statistics on the KiDS-1000 survey. Methods We constructed an efficient estimator for third-order shear statistics that builds on the multipole decomposition of the 3PCF. We then validated our estimator on mock ellipticity catalogs obtained from N -body simulations. Finally, we applied our estimator to the KiDS-1000 data and presented a measurement of the third-order aperture statistics in a tomographic setup. Results. Our estimator provides a speedup of a factor of ∼100–1000 compared to the state-of-the-art estimation procedures. It is also able to provide accurate measurements for squeezed and folded triangle configurations without additional computational effort. We report a significant detection of tomographic third-order aperture mass statistics in the KiDS-1000 data (S/N = 6.69). Conclusions. Our estimator will make it computationally feasible to measure third-order shear statistics in forthcoming stage IV surveys. Furthermore, it can be used to construct empirical covariance matrices for such statistics.

Astronomy & Astrophysics↗

DAQExpert the service to increase CMS data-taking efficiency

The Data Acquisition (DAQ) system of the Compact Muon Solenoid (CMS) experiment at the LHC is a complex system responsible for the data readout, event building and recording of accepted events. Its proper functioning plays a critical role in the data-taking efficiency of the CMS experiment. In order to ensure high availability and recover promptly in the event of hardware or software failure of the subsystems, an expert system, the DAQ Expert, has been developed. It aims at improving the data taking efficiency, reducing the human error in the operations and minimising the on-call expert demand. Introduced in the beginning of 2017, it assists the shift crew and the system experts in recovering from operational faults, streamlining the post mortem analysis and, at the end of Run 2, triggering fully automatic recovery without human intervention. DAQ Expert analyses the real-time monitoring data originating from the DAQ components and the high-level trigger updated every few seconds. It pinpoints data flow problems, and recovers them automatically or after given operator approval. We analyse the CMS downtime in the 2018 run focusing on what was improved with the introduction of automated recovery; present challenges and design of encoding the expert knowledge into automated recovery jobs. Furthermore, we demonstrate the web-based, ReactJS interfaces that ensure an effective cooperation between the human operators in the control room and the automated recovery system. We report on the operational experience with automated recovery.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improving the efficiency of G 0 W 0 calculations with approximate spectral decompositions of dielectric matrices

Recently, it was shown that the calculation of quasiparticle energies using the G 0 W 0 approximation can be performed without computing explicitly any virtual electronic states, by expanding the Green function and screened Coulomb interaction in terms of the eigenstates of the static dielectric matrix. Avoiding the evaluation of virtual electronic states leads to improved efficiency and ease of convergence of G 0 W 0 calculations. Here, we propose a further improvement of the efficiency of these calculations, based on an approximation of density-density response functions of molecules and solids. The approximation relies on the calculation of a subset of eigenvectors of the dielectric matrix using the kinetic operator instead of the full Hamiltonian, and it does not lead to any substantial loss of accuracy for the quasiparticle energies. The computational savings introduced by this approximation depend on the system, and they become more substantial as the number of electrons increases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Compact and efficient elastocaloric heat pumps—Is there a path forward?

Elastocaloric cooling holds promise for energy-efficient heat pumping near room temperature with low environmental impact. Its adoption is, however, impeded by disproportionally large sizes of actuators compared with the active material volume. Taking magnetocaloric cooling as the baseline, the value of no more than 10:1 actuator volume to active material volume should lead to both size- and cost-effective solutions that may potentially be competitive with vapor-compression devices. With the goal to establish performance metrics that can lead to informed actuator selection for specific regenerator requirements, we analyze a wide range of elastocaloric materials and actuator technologies to find the best matches. We find that actuation with magnetic shape memory alloys meets all requirements; however, this technology is currently in early developmental stages and such actuators are not widely commercially available. Another promising and easily accessible option is standard rotary electric motors in combination with rotary-to-linear transduction mechanisms. A theoretical analysis of two case studies of elastocaloric systems using rotary electric motors with a Scotch yoke mechanism demonstrates the usefulness of our approach. Actuator requirements are based on two different regenerator configurations: one starting from zero strain without any mechanical energy recovery and another with 2% pre-strain and mechanical energy recovery to reduce the power and torque required from the motor. Our results indicate that the 10:1 target actuator to active material volume ratio can be met and feasibly lowered further, demonstrating that the proposed method for selecting actuators makes compact and efficient elastocaloric systems possible.

42 ENGINEERING↗

Hole–hole Tamm–Dancoff-approximated density functional theory: A highly efficient electronic structure method incorporating dynamic and static correlation

The study of photochemical reaction dynamics requires accurate as well as computationally efficient electronic structure methods for the ground and excited states. While time-dependent density functional theory (TDDFT) is not able to capture static correlation, complete active space self-consistent field methods neglect much of the dynamic correlation. Hence, inexpensive methods that encompass both static and dynamic electron correlation effects are of high interest. Here, we revisit hole–hole Tamm–Dancoff approximated (hh-TDA) density functional theory for this purpose. The hh-TDA method is the hole–hole counterpart to the more established particle–particle TDA (pp-TDA) method, both of which are derived from the particle–particle random phase approximation (pp-RPA). In hh-TDA, the N-electron electronic states are obtained through double annihilations starting from a doubly anionic (N+2 electron) reference state. In this way, hh-TDA treats ground and excited states on equal footing, thus allowing for conical intersections to be correctly described. Furthermore, the treatment of dynamic correlation is introduced through the use of commonly employed density functional approximations to the exchange-correlation potential. Additionally, we show that hh-TDA is a promising candidate to efficiently treat the photochemistry of organic and biochemical systems that involve several low-lying excited states—particularly those with both low-lying ππ* and nπ* states where inclusion of dynamic correlation is essential to describe the relative energetics. In contrast to the existing literature on pp-TDA and pp-RPA, we employ a functional-dependent choice for the response kernel in pp- and hh-TDA, which closely resembles the response kernels occurring in linear response and collinear spin-flip TDDFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing unit (GPU) support. These scaling and memory reductions greatly increase the number of orbitals that can practically be included in AFQMC calculations, increasing the accuracy. Advances in real space methods include techniques for accurate computation of bandgaps and for systematically improving the nodal surface of ground state wavefunctions. Results of these calculations can be used to validate application of more approximate electronic structure methods, including GW and density functional based techniques. To provide an improved foundation for these calculations, we utilize a new set of correlation-consistent effective core potentials (pseudopotentials) that are more accurate than previous sets; these can also be applied in quantum-chemical and other many-body applications, not only QMC. These advances increase the efficiency, accuracy, and range of properties that can be studied in both molecules and materials with QMC and QMCPACK.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Numerical simulation of high-efficiency, scalable, all-back-contact Cd(Se,Te) solar cells

In this work, all-back-contact thin film photovoltaic devices in lattice back contact (LBC) configuration are studied by device simulation to set the requirements for achieving efficiency > 20% with lateral contact spacing > 50 µm. The numerical device model is first validated against published data for an LBC perovskite device and extended to predict the performance of Cd(Se,Te)-based polycrystalline devices. Recent advances in the electronic properties of Cd(Se,Te) films have made high efficiency LBC devices feasible with industrially-scalable contact dimensions. Constraints on bulk, interface, and contact properties are quantified and discussed

14 SOLAR ENERGY↗

Linear embedding of nonlinear dynamical systems and prospects for efficient quantum algorithms

The simulation of large nonlinear dynamical systems, including systems generated by discretization of hyperbolic partial differential equations, can be computationally demanding. Such systems are important in both fluid and kinetic computational plasma physics. This motivates exploring whether a future error-corrected quantum computer could perform these simulations more efficiently than any classical computer. In this work, we describe a method for mapping any finite nonlinear dynamical system to an infinite linear dynamical system (embedding) and detail three specific cases of this method that correspond to previously studied mappings. Then we explore an approach for approximating the resulting infinite linear system with finite linear systems (truncation). Using a number of qubits only logarithmic in the number of variables of the nonlinear system, a quantum computer could simulate truncated systems to approximate output quantities if the nonlinearity is sufficiently weak. Other aspects of the computational efficiency of the three detailed embedding strategies are also discussed.

97 MATHEMATICS AND COMPUTING↗

Huzinaga projection embedding for efficient and accurate energies of systems with localized spin-densities

We demonstrate the accuracy and efficiency of the restricted open-shell and unrestricted formulation of the absolutely localized Huzinaga projection operator embedding method. Restricted open-shell and unrestricted Huzinaga projection embedding in the full system basis is formally exact to restricted open-shell and unrestricted Kohn–Sham density functional theory, respectively. By utilizing the absolutely localized basis, we significantly improve the efficiency of the method while maintaining high accuracy. Furthermore, the absolutely localized basis allows for high accuracy open-shell wave function methods to be embedded into a closed-shell density functional theory environment. The open-shell embedding method is shown to calculate electronic energies of a variety of systems to within 1 kcal/mol accuracy of the full system wave function result. For certain highly localized reactions, such as spin transition energies on transition metals, we find that very few atoms are necessary to include in the wave function region in order to achieve the desired accuracy. This extension further broadens the applicability of our absolutely localized Huzinaga level-shift projection operator method to include open-shell species. Here, we apply our method to several representative examples, such as spin splitting energies, catalysis on transition metals, and radical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum materials for energy-efficient neuromorphic computing: Opportunities and challenges

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short- and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This Perspective discusses select examples of these approaches and provides an outlook on the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.

36 MATERIALS SCIENCE↗

Quantum efficiency enhancement in simulated nanostructured negative electron affinity GaAs photocathodes

We report nanostructured negative electron affinity GaAs photocathodes for a polarized electron source are studied using finite difference time domain optical simulation. The structures studied are nanosquare columns, truncated nanocones, and truncated nanopyramids. Mie-type resonances in the 700–800 nm waveband, suitable for generation of polarized electrons, are identified. At resonance wavelengths, the nanostructures can absorb up to 99% of the incident light. For nanosquare columns and truncated nanocones, the maximum quantum efficiency (QE) at 780 nm obtained from simulation is 27%, whereas for simulated nanopyramids, the QE is ~21%. The high photocathode quantum efficiency is due to the shift of Mie resonance toward the longer wavelength, leading to increased light absorption. The field profile distribution shows the excitation of dipole and quadrupole modes within the nanostructures at resonant frequencies. This leads to enhanced photoabsorption and photoelectron generation closer to emission surfaces than for a flat photocathode. The enhanced photoabsorption and reduced electron transport distance for the nanostructured photocathode enhance its QE compared to that for the flat surface wafer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Energy localization efficiency in 1,3,5-trinitro-2,4,6-triaminobenzene pore collapse mechanisms

Atomistic and continuum scale modeling efforts have shown that the shock-induced collapse of porosity can occur via a wide range of mechanisms dependent on pore morphology, the shockwave pressure, and material properties. The mechanisms that occur under weaker shocks tend to be more efficient at localizing thermal energy but do not result in high, absolute temperatures or spatially large localizations compared to mechanisms found under strong shock conditions. However, the energetic material 1,3,5-trinitro-2,4,6-triaminobenzene (TATB) undergoes a wide range of collapse mechanisms that are not typical of similar materials, leaving the collapse mechanisms and the resultant energy localization from the collapse, i.e., hotspots, relatively uncharacterized. Therefore, we present the pore collapse simulations of cylindrical pores in TATB for a wide range of pore sizes and shock strengths that trigger viscoplastic collapses that occur almost entirely perpendicular to the shock direction for weak shocks and hydrodynamic-like collapses for strong shocks that do not break the strong hydrogen bonds of the TATB basal planes. The resulting hotspot temperature fields from these mechanisms follow trends that differ considerably from other energetic materials; hence, we compare them under normalized temperature values to assess the relative efficiency of each mechanism to localize energy. The local intra-molecular strain energy of the hotspots is also assessed to better understand the physical mechanisms behind the phenomena that lead to a latent potential energy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

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