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New experimental results are presented on the dissociation dynamics of small neutral molecules in time-resolved photoexcitation-photoionization experiments by ultrashort vacuum- and extreme-ultraviolet laser pulses and charged particle momentum imaging.
Mobile ions at mineral surfaces can respond to an applied electric field, adopting a new distribution that effectively represents polarization of the electrical double layer. When the field is released, the ions relax to their equilibrium distribution. In both cases, the dynamics are characteristic of the interface. However, current models of electrokinetic phenomena are not sufficiently robust to accurately predict collective ion dynamics at structurally and chemically specific mineral–water interfaces. Here, in this study, we use electrostatic force microscopy (EFM) to investigate the dynamics of ion relaxation at hydrated calcite (104) surfaces at controlled relative humidity (RH). Electrically biased probes are used to polarize the distributions of calcium and carbonate ions that are intrinsic to this interface across a range of RH values. Polarization kinetics are tracked by monitoring the tip–sample force gradient during charging, and EFM imaging is used to characterize the spatial relaxation dynamics after the applied field is released. Electrostatic finite element modeling of the sample/probe system across length-scales from nanometers to millimeters reproduces the observed stretched exponential charging response. Together, these results allow us to estimate the ion diffusivities at the interface across a wide range of RH values. These diffusivities increase by roughly 5 orders of magnitude as the RH is increased from 5 to 90%, highlighting the critical role of adsorbed water for surface ion solvation that enables ion mobility.
Mesoporous films of the metal chalcogenide B-FeSe were grown on MgO substrates by KrF pulsed laser deposition (PLD) in an argon background. At 100 mTorr, gated intensified charge-coupled device imaging and ion probe measurements showed that the plasma plume responsible for crystal growth initially comprised three components, with distinct expansion velocities. Plume interactions with the substrate heater and ablation target gave rise to complex dynamics, including collisions between the charged leading edge—rebounding between the substrate and the target—and slower-moving species in the plume interior. Film growth was dominated by species with kinetic energies ≤0.5 eV/atom. X-ray reflectivity revealed that films grown in this environment—with a substrate temperature of 350 ° C, a laser fluence of 1.0 J cm −2 , and a 7.5 mm 2 spot area—formed a porous framework with 15% porosity. Atomic force microscopy showed surface features that suggest pore sizes below 100 nm. X-ray diffraction indicated that the porous films were epitaxial with respect to the substrate and likely grew by oriented-attachment of gas-phase molecular clusters or very small nanoparticles, in contrast to the conventional epitaxy of vacuum films from atomic constituents. The in-plane orientation of the mesoporous films was B-FeSe [100]||[110] MgO, attributed to the soft landing of pre-formed crystallites on the MgO substrates, where protruding Se rows of B-FeSe aligned with corrugations of the MgO surface. In conclusion, this work implies that growth of candidate electrocatalyst materials by PLD in inert gas background may allow mesoporous frameworks with a single crystallographic orientation that expose specific crystal facets for electrochemical reactions and active site engineering.
Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.
Characterizing ionization wave propagation in low temperature plasma jets is critical to predicting production of reactive species and plasma–surface interactions for biomedical applications and surface functionalization. In this work, results from optical emission and laser induced fluorescence measurements of the ionization wave in a He plasma jet operating in a controlled gas environment are discussed and used for comparison with numerical modeling. Additionally, the ionization wave was observed using ICCD (Intensified Charge Coupled Device) imaging and characterized by time and spatially resolved electron density measurements using laser-collision-induced fluorescence. The plasma jet was initially characterized using pure He (nominally at 200 Torr), while varying pressure and voltage. When operating in pure He, the ionization wave broadly expands exiting the plasma tube. Increasing the operating pressure reduces the speed and isotropic expansion of the ionization wave. Furthermore, the jet operated with a humid He shroud was also studied. The humid He shroud results in the electron density increasing and having an annular profile due to the lower ionization potential of H2O compared to He and localized photoionization in the mixing region. Numerical modeling highlighted the importance of resonance radiation emitted by excited states of He, photoelectron emission from the quartz tube, and the kinetic behavior of the electrons produced by photoionization ahead of the ionization front.
In this work, the temporal decay of electrons produced by an atmospheric pin-to-pin nanosecond discharge operating in the spark regime was measured via a combination of microwave Rayleigh scattering (MRS) and laser Rayleigh scattering (LRS). Due to the initial energy deposition of the nanosecond pulse, a variation in the local gas density occurs on the timescale of electron decay. Thus, the assumption of a constant collisional frequency is no longer applicable when electron number data are extracted from MRS measurements. Furthermore, to recalibrate MRS measurements throughout the electron decay period, temporally resolved LRS measurements of the local gas density were performed over the event duration. The local gas density was calculated to be 30% of the ambient level during the later stages of electron decay, and it recovers at about 1 ms after discharge. A shock front traveling approximately 500 m/s was additionally observed. Coupled with plasma volume calibration via temporally resolved intensified charge-coupled device imaging, the corrected decay curves of the electron number and electron number density are presented with a measured peak electron number density of 4.5 × 1015 cm -3 and a decay rate of ~(0.1–0.35) × 10 7 s -1 . A hybrid MRS and LRS diagnostic technique can be applied for a broad spectrum of atmospheric-pressure microplasmas where a variation in the gas number density is expected due to energy deposition in the discharge.
In this work we used molecular beam mass spectrometry to characterize ion fluxes produced by a modulated radiofrequency (RF)-driven atmospheric pressure plasma jet operating in a homogeneous gas environment (Ar + 1% O 2 ). The influence of the RF modulation frequency (100 Hz to 20 kHz) on the ion fluxes was investigated by time-resolved measurements, and the lifetimes of the dominant ions, O 2 + , NO + , O − , O 2 − and O 3 − , were found to be 28 ± 2, 117 ± 8, 7.3 ± 0.4, 17 ± 1 and 23 ± 2 μs, respectively. The absolute ion densities in the near afterglow region were found to be of the order of 1011 cm−3. Significant differences in the dynamics of the positive and negative ions were found; these are explained by the presence of electrons at similar densities in the afterglow produced by electron detachment reactions from negative ions due to the large concentrations of atomic oxygen and singlet delta oxygen. Transitions in ion flux dynamics for different modulation frequencies and at the startup of the plasma were analyzed together with intensified charge coupled device images recording the plasma propagation in order to assess the dynamics of plasma plume propagation and how it is impacted by ‘memory effects’. Quantitative measurements of the ion densities enabling these memory effects are reported. The results in this paper highlight the tremendous impact of memory effects on plasma propagation and the corresponding pre-ionization.
Injection of impurities in the form of sub-millimeter powder grains is performed for the first time in the Large Helical Device (LHD) plasma, employing the Impurity Powder Dropper (IPD) [A. Nagy et al., RSI 2018], developed and built by PPPL. Controlled amounts of boron (B) and boron nitride (BN) powder are injected into the helical plasma. Visible camera imaging, UV and charge exchange spectroscopy measurements show that the injected impurities effectively penetrate into the plasma in two different magnetic configurations.The prompt effects of the impurities on the plasma are characterized as the injection rate is scanned. The injected impurities provide a supplemental electron source, causing the plasma density to increase, together with the radiated power. Beneficial effects on the confined plasma temperature are observed at low plasma densities, due to an increased efficiency in NBI power absorption. For $n_{e,av}<10^{19}m^{-3}$ the powder grains penetrate deeper into the plasma, as they can be less effectively deflected by the plasma flow in the divertor leg, which they have to cross first as they are injected from the top of the machine.In this case, the created B ions are observed to move outwards from UV spectroscopy and charge exchange measurements, due to the outwards direction of the radial electric field. This makes low density plasmas a better candidate for powder boronization techniques.
The CALorimetric Electron Telescope (CALET) on the International Space Station consists of a high-energy cosmic-ray CALorimeter (CAL) and a lower-energy CALET Gamma-ray Burst Monitor (CGBM). CAL is sensitive to electrons up to 20 TeV, cosmic-ray nuclei from Z = 1 through Z ~ 40, and gamma rays over the range 1 GeV–10 TeV. CGBM observes gamma rays from 7 keV to 20 MeV. The combined CAL-CGBM instrument has conducted a search for gamma-ray bursts (GRBs) since 2015 October. We report here on the results of a search for X-ray/gamma-ray counterparts to gravitational-wave events reported during the LIGO/Virgo observing run O3. No events have been detected that pass all acceptance criteria. We describe the components, performance, and triggering algorithms of the CGBM—the two Hard X-ray Monitors consisting of LaBr 3 (Ce) scintillators sensitive to 7 keV–1 MeV gamma rays and a Soft Gamma-ray Monitor BGO scintillator sensitive to 40 keV–20 MeV—and the high-energy CAL consisting of a charge detection module, imaging calorimeter, and the fully active total absorption calorimeter. The analysis procedure is described and upper limits to the time-averaged fluxes are presented.
We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus ‘super-resolution’). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.
We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus $super$-$resolution$). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.
Integrating the optoelectronic properties of quantum dots (QDs) with biological enzymatic systems to form microbe-semiconductor biohybrids offers promising prospects for both solar-to-chemical conversion and light-modulated biochemical processes. Developing these nano–bio hybrid systems necessitates a deep understanding of charge-transfer dynamics at the nano–bio interface. Photoexcited carrier transfer from QDs to microbes is driven by complex interactions, with emerging insights into the relevant thermodynamic and kinetic factors. The heterogeneities of both microbes and QD ensembles pose significant challenges in mechanistic understanding, which is critical for designing advanced nano–bio hybrids. We used fluorescence lifetime imaging microscopy to analyze charge transfer between a CdSe QD film andShewanella oneidensismicrobes. We correlated the spatiotemporal fluorescence data with an analytical model. Our analysis revealed two distinct distributions of QD de-excitation pathways. The characteristics of these distributions: 1) a faster transfer rate ( k ¯ E T 1 = 1.5 10 9 s - 1 ), with a lower acceptor number ( N ¯ a 1 = 0.03 ) and 2) a slower transfer rate ( k ¯ E T 2 = 4.1 10 8 s - 1 ) with a higher acceptor number ( N ¯ a 2 = 0.18 ). We assign these distributions to the indirect and direct electron transfer mechanisms, respectively. Our findings demonstrate how spectroscopic imaging can uncover fundamental electron transfer mechanisms at complex interfaces, offering valuable design principles for future nano–bio hybrids.
Abstract Establishing connections between material impurities and charge transport properties in emerging electronic and quantum materials, such as wide‐bandgap semiconductors, demands new diagnostic methods tailored to these unique systems. Many such materials host optically‐active defect centers which offer a powerful in situ characterization system, but one that typically relies on the weak spin‐electric field coupling to measure electronic phenomena. In this work, charge‐state sensitive optical microscopy is combined with photoelectric detection of an array of nitrogen‐vacancy (NV) centers to directly image the flow of charge carriers inside a diamond optoelectronic device, in 3D and with temporal resolution. Optical control is used to change the charge state of background impurities inside the diamond on‐demand, resulting in drastically different current flow such as filamentary channels nucleating from specific, defective regions of the device. Conducting channels that control carrier flow, key steps toward optically reconfigurable, wide‐bandgap optoelectronics are then engineered using light. This work might be extended to probe other wide‐bandgap semiconductors (SiC, GaN) relevant to present and emerging electronic and quantum technologies.
Image sensors with nondestructive charge readout provide single-photon or single-electron sensitivity, but at the cost of long readout times. We present a smart readout technique to allow the use of these sensors in visible light and other applications that require faster readout times. The method optimizes the readout noise and time by changing the number of times pixels are read out either statically, by defining an arbitrary number of regions of interest in the array, or dynamically, depending on the charge or energy of interest in the pixel. This technique is tested in a Skipper CCD showing that it is possible to obtain deep subelectron noise, and therefore, high resolution of quantized charge, while dynamically changing the readout noise of the sensor. These faster, low noise readout techniques show that the skipper CCD is a competitive technology even where other technologies such as electron multiplier charge coupled devices, silicon photo multipliers, etc. are currently used. This technique could allow skipper CCDs to benefit new astronomical instruments, quantum imaging, exoplanet search and study, and quantum metrology.
The Single electron Sensitive Read Out (SiSeRO) is a novel on-chip charge detector output stage for charge-coupled device (CCD) image sensors. Developed at MIT Lincoln Laboratory, this technology uses a p-MOSFET transistor with a depleted internal gate beneath the transistor channel. The transistor source-drain current is modulated by the transfer of charge into the internal gate. At Stanford, we have developed a readout module based on the drain current of the on-chip transistor to characterize the device. In our earlier work, we characterized a number of first prototype SiSeROs with the MOSFET transistor channels at the surface layer. An equivalent noise charge (ENC) of around 15 electrons root mean square (RMS) was obtained. In this work, we examine the first buried-channel SiSeRO. Here we have achieved substantially improved noise performance of around 4.5 electrons root mean square (RMS) and a full width half maximum (FWHM) energy resolution of 132 eV at 5.9 keV, for a readout speed of 625 kpixel/s. We also discuss how digital filtering techniques can be used to further improve the SiSeRO noise performance. Additional measurements and device simulations will be essential to further mature the SiSeRO technology. This new device class presents an exciting new technology for the next-generation astronomical X-ray telescopes requiring fast, low-noise, radiation-hard megapixel imagers with moderate spectroscopic resolution.
The GammaTPC is an MeV-scale single-phase liquid argon time-projection-chamber gamma-ray telescope concept with a novel dual-scale pixel-based charge-readout system. It promises to enable a significant improvement in sensitivity to MeV-scale gamma rays over previous telescopes. The novel pixel-based charge readout allows for imaging of the tracks of electrons scattered by Compton interactions of incident gamma rays. The two primary contributors to the accuracy of a Compton telescope in reconstructing an incident gamma-ray’s original direction are its energy and position resolution. In this work, we focus on using deep learning to optimize the reconstruction of the initial position and direction of electrons scattered in Compton interactions, including using probabilistic models to estimate predictive uncertainty. We show that the deep-learning models are able to predict locations of Compton scatters of MeV-scale gamma rays from simulated 500 μm pixel-based data to better than 1 mm rms error and are sensitive to the initial direction of the scattered electron. We compare and contrast different deep-learning uncertainty estimation algorithms for reconstruction applications. Additionally, we show that event-by-event estimates of the uncertainty of the locations of the Compton scatters can be used to select those events that were reconstructed most accurately, leading to improvement in locating the origin of gamma-ray sources on the sky.
Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.
The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations.