Charged Multiplicity Research Articles

Multiplication of the orbital angular momentum of phonon polaritons via sublinear dispersion

Optical vortices (OVs) promise to greatly enhance optical information capacity via orbital angular momentum multiplexing. The need for the on-chip integration of orbital angular momentum technologies has prompted research into subwavelength-confined polaritonic OVs. However, the topological order imprinted by the structure used for transduction from free-space beams to surface polaritons is inherently fixed after fabrication. Here we overcome this limitation via dispersion-driven topological charge multiplication. We switch the OV topological charge within a small frequency range (~3%) by leveraging the strong sublinear dispersion of low-loss surface phonon polaritons on silicon carbide membranes. Applying the Huygens principle, we quantitatively evaluate the topological order of experimental OVs detected by near-field imaging. We further explore the deuterogenic effect, which predicts the coexistence of multiple topological charges in higher-order polaritonic OVs. Our work demonstrates a viable method to manipulate the topological charge of polaritonic OVs, paving the way for the exploration of novel orbital-angular-momentum-enabled light–matter interactions at mid-infrared frequencies.

Possible charge ordering and anomalous transport in graphene/graphene quantum dot heterostructure

Observations of superconductivity and charge density waves (CDW) in graphene have been elusive thus far due to weak electron–phonon coupling (EPC) interactions. Here, we report a unique observation of anomalous transport and multiple charge ordering phases at high temperatures ( T1∼213K , T2∼325K ) in a 0D−2D van der Waals (vdW) heterostructure comprising of single layer graphene (SLG) and functionalized (amine) graphene quantum dots (GQD). The presence of functionalized GQD contributed to charge transfer with shifting of the Dirac point ∼ 0.05 eV above the Fermi level (ab initio simulations) and carrier density n∼−0.3×1012 cm−2 confirming p-doping in SLG and two-fold increase in EPC interaction was achieved. Moreover, we elucidate the interplay between electron–electron and electron–phonon interactions to substantiate high temperature EPC driven charge ordering in the heterostructure through analyses of magnetotransport and weak anti-localization (WAL) framework. Our results provide impetus to investigate strongly correlated phenomena such as CDW and superconducting phase transitions in novel graphene based heterostructures.

EV Charging Scheduling Under Demand Charge: A Block Model Predictive Control Approach

This paper studies the online scheduling of electric vehicle charging by a service provider subject to a demand charge in a distribution system. Demand charge imposes a penalty on the peak power consumption over each billing period, representing a substantial cost for the service provider with a large number of clients. Because the demand charge is calculated at the end of the billing period, it poses challenges in real-time scheduling when energy demand forecasts are inaccurate, resulting in either overly conservative power consumption or substantial demand charge. We propose a block model predictive control approach that decomposes the demand charge into a sequence of stage costs. Optimality conditions on demand patterns are also presented and analyzed. Numerical simulations demonstrate the efficacy of the proposed approach. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper addresses a significant practical problem of minimizing the demand charge on the real-time scheduling of deferrable demands. In particular, we consider a setting where a commercial electric vehicle (EV) charging service provider has to manage the online scheduling of a large number of arriving EVs at a charging facility subject to a maximum charging power constraint and a tariff with the demand charge. A major practical challenge is to balance the tradeoff between maximizing profit in scheduling as much EV charging as possible and the need to minimize penalty on the peak charging power. We propose a model predictive control strategy that decomposes the overall demand charge into a sequence of terminal costs. Also addressed is the practical constraint arising from the mismatched EV charging decision period and the power measurement period used to compute the demand charge. Using real data collected at the Adaptive Charging Network (ACN) testbed in simulations, the proposed approach yields 8-12% improvement in operational profit over existing benchmarks, while it has yet been tested in actual charging systems. In the future research, we will address the charging scheduling under demand charge over multiple charging stations.

Multiple charge carrier species as a possible cause for triboelectric cycles.

The tendency of materials to order in triboelectric series has prompted suggestions that contact electrification might have a single, unified underlying description. However, the possibility of "triboelectric cycles," i.e., series that loop back onto themselves, is seemingly at odds with such a coherent description. In this work, we propose that if multiple charge carrying species are at play, both triboelectric series and cycles are possible. We show how series arise naturally if only a single charge carrier species is involved and if the driving mechanism is approach toward thermodynamic equilibrium, and simultaneously, that cycles are forbidden under such conditions. Suspecting multiple carriers might relax the situation, we affirm this is the case by explicit construction of a cycle involving two carriers, and then extend this to show how more complex cycles emerge. Our work highlights the importance of series and cycles towards determining the underlying mechanism(s) and carrier(s) in contact electrification.

Comparative study of the impact of interpad nominal length on the onset of the charge multiplication in standard segmented LGAD with 2 p-stops and bias ring as isolated structures

We present an investigation of the interpad region (IP) in the Ultra-Fast Silicon Detector (UFSD) Type 10, utilizing a femtosecond laser and the transient current technique (TCT). We elucidate the isolation structure and measure the IP distance between pads, comparing it to the nominal value provided by the vendor. A comparison of sensors with identical layouts but different nominal IP distances (49 μm vs. 61 μm) and different processing parameters revealed their significant different charge collection properties in the IP.

Self-assembly of N,S-MXene/3DPC heterostructure with multiple charge transfer channels for high-performance supercapacitors and sodium-ion batteries

Individual MXene (Ti3C3Tx) films tend to re-accumulate, seriously reducing the electrochemical properties. Herein, a viable hydrothermal method is being adopted to achieve the self-assembly of N and S co-doped three-dimensional porous carbon (3DPC) with conductive networks and MXene. For SCs, the N,S-MXene/3DPC electrode displays 412.7 F g−1 at 1 A g−1. When all-solid-state asymmetric SCs (ASCs) are manufactured with active carbon, the N,S-MXene/3DPC//AC ASCs present 210.5 F g−1 at 1 A g−1 and retain 97.5% of initial cycle through 5000 rotations. The energy density reaches its maximum of 94.7 Wh kg−1 at 900 W kg−1. In addition, the N,S-MXene/3DPC anode of SIBs demonstrates a reversible capability of 465.5 mAh g−1 at 0.2 A g−1. It also sustains a remarkable 72.9% preservation of capacity over 1000 rotations at 2.0 A g−1. The excellent electrochemical performance is attributed to following points: 3DPC with conductive networks can provide multiple transfer paths for ions and charges and support MXene. The co-doping of N and S for 3DPC can provide numerous active sites for electrochemical reactions, while the addition of MXene improves conductivity and mechanical stability. The N,S-MXene/3DPC material and its preparation method exhibit great potential for application in the field of electrochemical energy storage.

Symmetry Breaking and Ascending in the Magnetic Kagome Metal FeGe

Spontaneous symmetry breaking—the phenomenon in which an infinitesimal perturbation can cause the system to break the underlying symmetry—is a cornerstone concept in the understanding of interacting solid-state systems. In a typical series of temperature-driven phase transitions, higher-temperature phases are more symmetric due to the stabilizing effect of entropy that becomes dominant as the temperature is increased. However, the opposite is rare but possible when there are multiple degrees of freedom in the system. Here, we present such an example of a symmetry-ascending phenomenon upon cooling in a magnetic kagome metal FeGe by utilizing neutron Larmor diffraction and Raman spectroscopy. FeGe has a kagome lattice structure with simple A-type antiferromagnetic order below Néel temperature TN≈400 K and a charge density wave (CDW) transition at TCDW≈110 K, followed by a spin-canting transition at around 60 K. In the paramagnetic state at 460 K, we confirm that the crystal structure is indeed a hexagonal kagome lattice. On cooling to around TN, the crystal structure changes from hexagonal to monoclinic with in-plane lattice distortions on the order of 10−4 and the associated splitting of the double-degenerate phonon mode of the pristine kagome lattice. Upon further cooling to TCDW, the kagome lattice shows a small negative thermal expansion, and the crystal structure gradually becomes more symmetric upon further cooling. A tendency of increasing the crystalline symmetry upon cooling is unusual; it originates from an extremely weak structural instability that coexists and competes with the CDW and magnetic orders. These observations are against the expectations for a simple model with a single order parameter and hence can only be explained by a Landau free energy expansion that takes into account multiple lattice, charge, and spin degrees of freedom. Thus, the determination of the crystalline lattice symmetry as well as the unusual spin-lattice coupling is a first step towards understanding the rich electronic and magnetic properties of the system, and it sheds new light on intertwined orders where the lattice degree of freedom is no longer dominant. Published by the American Physical Society 2024

Spatially Extended Charge Density Wave Switching by Nanoscale Local Manipulation in a VTe2 Monolayer.

Monolayer transition metal dichalcogenide VTe2 exhibits multiple charge density wave (CDW) phases, mainly (4 × 4) and (4 × 1). Here we report facile dynamic and tens-of-nanometer scale switching between these CDW phases with gentle bias pulses in scanning tunneling microscopy. Bias pulses purposely stimulate a reversible random CDW symmetry change between the isotropic (4 × 4) and anisotropic (4 × 1) CDWs, as well as CDW phase slips and rotation. The switching threshold of ∼1.0 V is independent of bias polarity, and the switching rate varies linearly with the tunneling current. Density functional theory calculations indicate that a coherent CDW phase switching incurs an energy barrier of ∼2.0-3.0 eV per (4 × 4) unit cell. While there is a challenge in understanding the observed large-area CDW random fluttering, we provide some possible explanations. The ability to manipulate electronic CDW phases sheds new light on tailoring CDW properties on demand.

Incorporating long-range electrostatics in neural network potentials via variational charge equilibration from shortsighted ingredients

We present a new approach to construct machine-learned interatomic potentials including long-range electrostatic interactions based on a charge equilibration scheme. This new approach can accurately describe the potential energy surface of systems with ionic and covalent interactions as well as systems with multiple charge states. Moreover, it can either be regressed against known atomic charge decompositions or trained without charge targets, without compromising the accuracy of energy and forces. We benchmark our approach against other state-of-the-art models and prove it to have equivalent performances on a set of simple reference systems while being less computationally expensive. Finally, we demonstrate the accuracy of our approach on complex systems: solid and liquid state sodium chloride. We attain accuracy in energy and forces better than the model based on local descriptors and show that our electrostatic approach can capture the density functional theory tail of the potential energy surface of the isolated Na-Cl dimer, which the local descriptor-based model fails to describe.

Trap properties of novel UV-A persistent phosphor Sr3MgSi2O8:Ce3+

For the last few decades, there has been extensive research on the materials that persist to emit optical radiation long after any type of charging has stopped. Most of the established persistent luminescence (PersL) materials emit light in the visible part of the spectrum; however, in recent years, there has been a growing interest in UV-emitting persistent phosphors in recent years. These materials have been tested for various applications, such as photocatalysis, sterilization, and anti-counterfeiting, among others. Here, we report on the X-ray and UV-activated UV-A long PersL of Ce3+-doped Sr3MgSi2O8 material. We prepared samples with varied Ce3+ concentrations using solid–state reaction synthesis in an ambient atmosphere and conducted a thorough investigation using photoluminescence (PL), electron paramagnetic resonance (EPR), and thermally stimulated luminescence (TSL) spectroscopy methods. Our experiments show that the PersL signal of Ce3+ in the 300–450 nm range can be detected for at least 16 h when samples are irradiated with X-rays or UV. The TSL analysis reveals multiple discrete charge traps in the material with activation energies between 0.5 and 1.7 eV. Further EPR measurements confirm the presence of four paramagnetic centers. The thermal stability of these centers was analyzed, and it is established that one of these centers (g1 = 2.0056, g2 = 1.9981, and g3 = 1.9926) gradually decays at room temperature, which is correlated with the PersL processes.

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

One-Time Prediction of Battery Capacity Fade Curve under Multiple Fast Charging Strategies

Using different fast charging strategies for lithium-ion batteries can affect the degradation rate of the batteries. In this case, predicting the capacity fade curve can facilitate the application of new batteries. Considering the impact of fast charging strategies on battery aging, a battery capacity degradation trajectory prediction method based on the TM-Seq2Seq (Trend Matching—Sequence-to-Sequence) model is proposed. This method uses data from the first 100 cycles to predict the future capacity fade curve and EOL (end of life) in one-time. First, features are extracted from the discharge voltage-capacity curve. Secondly, a sequence-to-sequence model based on CNN, SE-net, and GRU is designed. Finally, a trend matching loss function is designed based on the common characteristics of capacity fade curves to constrain the encoding features of the sequence-to-sequence model, facilitating the learning of the underlying relationship between inputs and outputs. TM-Seq2Seq model is verified on a public dataset with 132 battery cells and multiple fast charging strategies. The experimental results indicate that, compared to other popular models, the TM-Seq2Seq model has lower prediction errors.

An A-D-A'-D-A-Type Narrow Bandgap Electron Acceptor Based on Selenophene-Flanked Diketopyrrolopyrrole for Sensitive Near-Infrared Photodetection.

Near-infrared organic photodetectors possess great application potential in night vision, optical communication, and image sensing, but their development is limited by the lack of narrow bandgap organic semiconductors. A-D-A'-D-A-type molecules, featuring multiple intramolecular charge transfer effects, offer a robust framework for achieving near-infrared light absorption. Herein, we report a novel A-D-A'-D-A-type narrow bandgap electron acceptor named DPPSe-4Cl, which incorporates a selenophene-flanked diketopyrrolopyrrole (Se-DPP) unit as its central A' component. This molecule demonstrates exceptional near-infrared absorption properties with an absorption onset reaching 1120 nm and a low optical bandgap of 1.11 eV, owing to the strong electron-withdrawing ability and quinoidal resonance effect induced by the Se-DPP unit. By implementing a doping compensation strategy assisted by Y6 to reduce the trap density in the photoactive layer, the optimized organic photodetector based on DPPSe-4Cl exhibited efficient spectral response and remarkable sensitivity in the range of 300-1100 nm. Particularly, a specific detectivity surpassing 1012 Jones in the wavelength range of 410-1030 nm is achieved. This work offers a promising approach for developing highly sensitive visible to near-infrared broadband photodetection technology using organic semiconductors.

Multiple Ion Charge Extraction (MICE) for High-Throughput Charge Detection Mass Spectrometry

Multiple Ion Charge Extraction (MICE) for High-Throughput Charge Detection Mass Spectrometry

Predicted multiple charge density wave phases in monolayer 1T-NbO2

Layered transition-metal dichalcogenides, such as NbSe2, have been extensively studied for almost half a century due to their intriguing properties, such as charge density wave (CDW) and superconductivity. Can the layered transition-metal dioxide, such as NbO2, be stable and exhibit CDW, given that it has the same crystal structure and electronic configuration as NbSe2? Here, we use first-principles calculations to predict that 1T-NbO2 is possibly stable at high temperatures, but it would undergo two CDW transitions with 12×12 and 13×13 periodicities at low temperatures. Both CDW transitions are accompanied by a metal-semiconductor transition. Notably, the 13×13 CDW phase of NbO2 possesses localized magnetic moments and hosts a Mott insulating state. This work offers a fresh outlook on studying CDW and Mott transition in low-dimensional oxide materials.

Tracking Sodium Cluster Dynamics in Hard Carbon with a Low Specific Surface Area for Sodium‐Ion Batteries

AbstractHere, the sodium storage mechanism in commercial grade hard carbon with a low surface area is comprehensively investigated using electrochemical impedance spectroscopy (EIS), the galvanostatic intermittent titration technique, and in situ Raman spectroscopy for fresh and cycled electrodes. The reversible shift of the carbon G‐band peak on Raman spectra and substantial change of the charge‐transfer resistance in the sloping region of the voltage profile indicates the intercalation of sodium ions into hard carbon, whereas the low‐voltage plateau is associated with the pore‐filling process. In situ Raman analysis at low frequencies reveals that the pore filling is progressed via formation of small sodium clusters in closed pores. Prolonged cycling demonstrates that intercalation is stable and consistent throughout multiple charge–discharge cycles. The transition from intercalation to pore filling strongly affects the diffusion behavior, leading to considerably slower diffusivity at low voltage. The EIS effectively differentiates the contribution of adsorption to charge storage. The gradual growth of the solid‐electrolyte interphase layer affects the rise of the interfacial resistance as cycling progresses. In combination with the slower diffusivity, the low‐voltage plateau region strictly impedes fast de/sodiation and eventually causes capacity fade.

Ultrafast and selective capture of 99TcO4-/ReO4- from wastewater by hyper-branched quaternary ammonium group-functionalized resin

99Tc primarily exists high mobility in the natural aqueous environment due to its extremely high solubility and non-complexing features, which can easily cause radioactive pollution. We herein report a general strategy for constructing a novel resin (SiPAN-PEI) with multiple positive charges nitrogen, exhibiting ultrafast adsorption kinetics (< 3 min), superior adsorption capacities (463.96 mg g−1), and excellent selectivity in the presence of excess competitive anions, which exceed those of most commercial resins. Moreover, based on impressive structure stability in extreme conditions, SiPAN-PEI can still maintain superior adsorption abilities after suffering irradiation, calcination, and immersion in strong acid. In addition, the separation performance kept excellently after five loading-washing-eluting cycles and the total adsorption ratio can still reach 97 %. Outstandingly, SiPAN-PEI can remove most of ReO4- from simulated nuclear wastewater through a sequential injection automatic separation system and can reduce the concentration of ReO4- to the maximum concentration standard set by the World Health Organization (WHO) in a short time. Leveraging density functional theory calculations and other characteristics clearly elucidated adsorption mechanism of anion-exchange between Cl- and TcO4-/ReO4-. In terms of superior adsorption property, SiPAN-PEI is demonstrated to be a pretty candidate for 99Tc elimination from wastewater.

Transient‐Current Technique Characterization of Diamond Detector and Proposal of a Diamond Detector with Charge Amplification

Diamond holds promise as a potential candidate for future particle detectors owing to its remarkable electronic, mechanical, and thermal properties. However, a notable limitation is the need for a comprehensive model characterizing intrinsic diamond detectors. To address this, a specialized model integrated into the technology computer‐aided design simulation program is developed. The model's validation is accomplished through its application to the evaluation of an intrinsic diamond detector. Our investigation emphasizes three key attributes: charge carrier mobility, charge carrier lifetime, and the effective charge density within the bulk material. These attributes are carefully assessed using the transient current technique. Furthermore, our model serves as a valuable tool in the analysis of the quality of an high‐pressure high‐temperature diamond crystal and in the optimization of a diamond detector's design, exploiting the charge multiplication effect. This comprehensive methodology advances our grasp of diamond detector behavior and facilitates the development of even more sophisticated devices.

Multiplatform High-Definition Ion Mobility Separations of the Largest Epimeric Peptides.

Ion mobility spectrometry (IMS) coupled to mass spectrometry (MS) has become a versatile tool to fractionate complex mixtures, distinguish structural isomers, and elucidate molecular geometries. Along with the whole MS field, IMS/MS advances to ever larger species. A topical proteomic problem is the discovery and characterization of d-amino acid-containing peptides (DAACPs) that are critical to neurotransmission and toxicology. Both linear IMS and FAIMS previously disentangled d/l epimers with up to ∼30 residues. In the first study using all three most powerful IMS methodologies─trapped IMS, cyclic IMS, and FAIMS─we demonstrate baseline resolution of the largest known d/l peptides (CHH from Homarus americanus with 72 residues) with a dynamic range up to 100. This expands FAIMS analyses of isomeric modified peptides, especially using hydrogen-rich buffers, to the ∼50-100 residue range of small proteins. The spectra for d and l are unprecedentedly strikingly similar except for a uniform shift of the separation parameter, indicating the conserved epimer-specific structural elements across multiple charge states and conformers. As the interepimer resolution tracks the average for smaller DAACPs, the IMS approaches could help search for yet larger DAACPs. The a priori method to calibrate cyclic (including multipass) IMS developed here may be broadly useful.

χc1(4274) multiplicity in heavy-ion collisions

In a previous work we computed the thermally averaged cross sections for the production and absorption reactions of the χc1(4274) state in the hot hadron gas formed in heavy-ion collisions. In the present work we estimate the final yield of the χc1(4274) state in these collisions. We use the coalescence model to fix the initial multiplicity of the χc1(4274), which is treated as a P-wave bound state of DsD¯s0 and also as a compact tetraquark. The Bjorken picture is used to model the hydrodynamic expansion and cooling. We also consider the Hubble cooling, which is faster and mimics the effect of the transverse expansion. Then, the kinetic equation is solved to evaluate the time evolution of the χc1(4274) yield during the hot hadron gas phase. Since the χc1(4274) decay width is large it might decay inside the hadron gas. Therefore, we also include the χc1(4274) decay and regeneration terms by means of an effective coupling, estimated from the available data. The combined effects of hadronic interactions and the χc1(4274) decay have a strong impact on the final yield. Also, predictions of the χc1(4274) multiplicity as a function of centrality and of the charged hadron multiplicity measured at midrapidity [dNch/dη(η&lt;0.5)] are presented. Finally, we calculate the yield of a proposed P-wave molecular state of DsD¯s0, Y′(4274), characterized by a smaller width and smaller coupling constant obtained from the Weinberg compositeness condition. Published by the American Physical Society 2024