Intermediate Scale Research Articles

Indicators of Cultural Ecosystem Services for Peri-Urban Agricultural and Natural Areas at an Intermediate Scale: A Case Study of Arequipa, Peru

The evaluation of management in peri-urban agricultural and natural areas (PANAs) constitutes a complex topic, particularly when considering its scale in cities where landscape planning is a priority. Therefore, indicators are required to assess the non-material well-being, biodiversity, and quality of life of society, which are criteria of cultural ecosystem services (CESs). This research develops identification and subclassification CESs and tangible and intangible indicators that facilitate the management of the PANA landscape, using the city of Arequipa as a case study—a dynamic cultural city with a declared cultural heritage, in turn located in an artificial oasis in the Atacama Desert. Therefore, the results will enable the selection of indicators that are practically applicable to planning instruments, serving as support systems for decision-making regarding interventions in PANAs. The methodology began with a systematic and meta-analytic (PRISMA) review, identifying 25 articles containing 230 indicators across 19 subclassifications. Using the Multiscale Indicators Framework (MSIF), the literature was integrated with a participatory workshop to validate these findings. The level of impact was assessed for 115 indicators across 13 subclassifications, applying criteria such as diversity, sustainable management, quality of life, and scalability—factors necessary to comply with urban sustainability policies.

Using eDNA to Supplement Population Genetic Analyses for Cryptic Marine Species: Identifying Population Boundaries for Alaska Harbour Porpoises.

Isolation by distance and biogeographical boundaries define patterns of population genetic structure for harbour porpoise along the Pacific coast from California to British Columbia. Until recently, inadequate sample sizes in many regions constrained efforts to characterise population genetic structure throughout the coastal waters of Alaska. Here, tissue samples from beachcast strandings and fisheries bycatch were supplemented with targeted environmental DNA (eDNA) samples in key regions of Alaska coastal and inland waters. Using a geographically explicit, hierarchical approach, we examined the genetic structure of Alaska harbour porpoises, using both mitochondrial DNA (mtDNA) sequence data and multilocus SNP genotypes. Despite a lack of evidence of genetic differentiation from nuclear SNP loci, patterns of relatedness and genetic differentiation from mtDNA suggest natal philopatry at multiple geographic scales, with limited gene flow among sites possibly mediated by male dispersal. A priori clustering of sampled areas at an intermediate scale (eastern and western Bering Sea, Gulf of Alaska and Southeast Alaska) best explained the genetic variance (12.37%) among regions. In addition, mtDNA differentiation between the Gulf of Alaska and eastern Bering Sea, and among regions within the Gulf of Alaska, indicated significant genetic structuring of harbour porpoise populations in Southeast Alaska. The targeted collection of eDNA samples from strata within Southeast Alaska was key for elevating the statistical power of our mtDNA dataset, and findings indicate limited dispersal between neighbouring strata within coastal and inland waters. These results provide evidence supporting a population boundary within the currently recognised Southeast Alaska Stock. Together, these findings will prove useful for ongoing management efforts to reduce fisheries conflict and conserve genetic diversity in this iconic coastal species.

Changing Your Martini Can Still Give You a Hangover.

The Martini 3.0 coarse-grained force field, which was parametrized to better capture transferability in top-down coarse-grained models, is analyzed to assess its accuracy in representing thermodynamic and structural properties with respect to the underlying atomistic representation of the system. These results are compared to those obtained following the principles of statistical mechanics that start from the same underlying atomistic system. To this end, the potentials of mean force for lateral association in Martini 3.0 binary lipid bilayers are decomposed into their entropic and enthalpic components and compared to those of corresponding atomistic bilayers that have been projected onto equivalent coarse-grained mappings but evolved under the fully atomistic forces. This is accomplished by applying the reversible work theorem to lateral pair correlation functions between coarse-grained lipid beads taken at a range of different temperatures. The entropy-enthalpy decompositions provide a metric by which the underlying statistical mechanical properties of Martini can be investigated. Overall, Martini 3.0 is found to fail to properly partition entropy and enthalpy for the PMFs compared to the mapped all-atom results, despite changes made to the force field from the Martini 2.0 version. This outcome points to the fact that the development of more accurate top-down coarse-grained models such as Martini will likely necessitate temperature-dependent terms in the corresponding CG force-field; although necessary, this may not be sufficient to improve Martini. In addition to the entropy-enthalpy decompositions, Martini 3.0 produces an incorrect undulation spectrum, in particular at intermediate length scales of biophysical pertinence.

Scale dependence of local shearing motion in decaying turbulence generated by multiple-jet interaction

Scale dependence of local shearing motion is investigated experimentally in decaying homogeneous isotropic turbulence generated through multiple-jet interaction. The turbulent Reynolds number, based on the Taylor microscale, is between approximately 900 and 400. Velocity fields, measured using particle image velocimetry, are analysed through the triple decomposition of a low-pass filtered velocity gradient tensor, which quantifies the intensities of shear and rigid-body rotation at a given scale. These motions manifest predominantly as layer and tubular vortical structures, respectively. The scale dependence of the moments of velocity increments, associated with shear and rigid-body rotation, exhibits power-law behaviours. The scaling exponents for shear are in quantitative alignment with the anomalous scaling of the velocity structure functions, suggesting that velocity increments are influenced predominantly by shearing motion. In contrast, the exponents for rigid-body rotation are markedly smaller than those predicted by Kolmogorov scaling, reflecting the high intermittency of rigid-body rotation. The mean flow structure associated with shear at intermediate scales is investigated with conditional averages around locally intense shear regions in the filtered velocity field. The averaged flow field exhibits a shear layer structure with aspect ratio approximately 4.5, surrounded by rotating motion. The analysis at different scales reveals the existence of self-similar structures of shearing motion across various scales. The mean velocity jump across the shear layer increases with the layer thickness. This relationship is well predicted by Kolmogorov's second similarity hypothesis, which is useful in predicting the mean characteristics of shear layers across a wide range of scales.

1-arcsecond imaging of the ELAIS-N1 field at 144MHz using the LoTSS survey with the international LOFAR telescope

We present the first wide area ($2.5 deg ^2$) LOFAR high band antenna image at a resolution of $1.2 with a median noise of $ Jy beam $. It was made from an 8-hour International LOFAR Telescope (ILT) observation of the ELAIS-N1 field at frequencies ranging from 120 to 168\,MHz with the most up-to-date ILT imaging methods. This intermediate resolution falls between the highest possible resolution (0.3 achievable by using all ILT baselines and the standard 6-arcsecond resolution in the LOFAR Two-meter Sky Survey (LoTSS) image products utilising the LOFAR Dutch baselines only. This is the first demonstration of the feasibility of imaging using the ILT at a resolution of sim 1 which provides unique information on source morphology at scales that fall below the surface brightness limits at higher resolutions. The total calibration and imaging computational time is approximately 52,000 core hours, which is nearly five times more than required to produce a $6 resolution image. We also present a radio source catalogue containing 2263 sources detected over the $2.5 deg ^2$ image of the ELAIS-N1 field, with a peak intensity threshold of $5.5 The catalogue has been cross-matched with the LoTSS deep ELAIS-N1 field radio catalogue, and its flux density and positional accuracy have been investigated and corrected accordingly. We find that sim 80<!PCT!> of sources that we expect to be detectable based on their peak brightness in the LoTSS $6 resolution image are detected in this image, which is approximately a factor of two higher than for $0.3 resolution imaging in the Lockman Hole, implying there is a wealth of information on these intermediate scales.

Flow patterns and energy spectra in forced quasi-two-dimensional turbulence: effect of system size and damping rate

An experimental investigation is conducted to study the flow patterns, spectral properties and energy fluxes in thin-layer turbulence with varying system sizes and damping rates. It is found that although a system-size vortex (an indicator of spectral condensation) occurs for small system sizes and does not for large ones, the spectra for different system sizes consistently exhibit a scaling close to $k^{-3}$ in inverse cascade (another indicator of spectral condensation). On the other hand, under a fixed system size larger than the friction-dominated length scale, the energy spectrum in the inverse cascade range changes from $k^{-3}$ to $k^{-5/3}$ as the damping rate increases, suggesting that the friction-dominated length scale may not be a suitable parameter for predicting spectral transition. At lower damping rates and large system sizes, turbulent structures grow larger via inverse cascade, manifesting as long streamers, and the small-scale vortices are suppressed. This suppression leads to a reduction of energy flux at intermediate scales and a change in the spectral shape. The dimensionless Taylor microscale is found to exhibit a monotonic dependence on the damping rate. With the reduction in the damping rate, the Taylor microscale increases to become comparable with the forcing scale, and the spectrum in inverse cascade transits to a steeper scaling, $k^{-3}$ , indicating that the dimensionless Taylor microscale may be used as a diagnostic parameter for spectral transition.

Rugged magneto-hydrodynamic invariants in weakly collisional plasma turbulence: Two-dimensional hybrid simulation results

Aims. We investigated plasma turbulence in the context of solar wind. We concentrated on properties of ideal second-order magneto-hydrodynamic (MHD) and Hall MHD invariants. Methods. We studied the results of a two-dimensional hybrid simulation of decaying plasma turbulence with an initial large cross helicity and a negligible magnetic helicity. We investigated the evolution of the combined energy and the cross, kinetic, mixed, and magnetic helicities. For the combined (kinetic plus magnetic) energy and the cross, kinetic, and mixed helicities, we analysed the corresponding Kármán-Howarth-Monin (KHM) equation in the hybrid (kinetic proton and fluid electron) approximation. Results. The KHM analysis shows that the combined energy decays at large scales. At intermediate scales, this energy cascades (from large to small scales) via the MHD non-linearity and this cascade partly continues via Hall coupling to sub-ion scales. The cascading combined energy is transferred (dissipated) to the internal energy at small scales via the resistive dissipation and the pressure-strain effect. The Hall term couples the cross helicity with the kinetic one, suggesting that the coupled invariant, referred to here as the mixed helicity, is a relevant turbulence quantity. However, when analysed using the KHM equations, the kinetic and mixed helicities exhibit very dissimilar behaviours to that of the combined energy. On the other hand, the cross helicity, in analogy to the energy, decays at large scales, cascades from large to small scales via the MHD+Hall non-linearity, and is dissipated at small scales via the resistive dissipation and the cross-helicity equivalent of the pressure-strain effect. In contrast to the combined energy, the Hall term is important for the cross helicity over a wide range of scales (even well above ion scales). In contrast, the magnetic helicity is scantily generated through the resistive term and does not exhibit any cascade.

Probing the physics of star formation (ProPStar)

Context. Turbulence is a key component of molecular cloud structure. It is usually described by a cascade of energy down to the dissipation scale. The power spectrum for subsonic incompressible turbulence is ∝k−5/3, while for supersonic turbulence it is ∝k−2. Aims. We determine the power spectrum in an actively star-forming molecular cloud, from parsec scales down to the expected magnetohydrodynamic (MHD) wave cutoff (dissipation scale). Methods. We analyzed observations of the nearby NGC 1333 star-forming region in three different tracers to cover the different scales from ∼10 pc down to 20 mpc. The largest scales are covered with the low-density gas tracer 13CO (1–0) obtained with a single dish, the intermediate scales are covered with single-dish observations of the C18O (3–2) line, while the smallest scales are covered in H13CO+ (1–0) and HNC (1–0) with a combination of NOEMA interferometer and IRAM 30m single-dish observations. The complementarity of these observations enables us to generate a combined power spectrum covering more than two orders of magnitude in spatial scale. Results. We derive the power spectrum in an active star-forming region spanning more than 2 decades of spatial scales. The power spectrum of the intensity maps shows a single power-law behavior, with an exponent of 2.9 ± 0.1 and no evidence of dissipation. Moreover, there is evidence that the power spectrum of the ions to have more power at smaller scales than the neutrals, which is opposite to the theoretical expectations. Conclusions. We show new possibilities for studying the dissipation of energy at small scales in star-forming regions provided by interferometric observations.

The universal multiplicity function: counting haloes and voids

We present a novel combination of the excursion-set approach with the peak theory formalism in Lagrangian space and provide accurate predictions for halo and void statistics over a wide range of scales. The set-up is based on an effective moving barrier. Besides deriving the corresponding numerical multiplicity function, we introduce a new analytical formula reaching the percent level agreement with the exact numerical solution obtained via Monte Carlo realisations down to small scales, ∼ 1012 h -1M⊙. In the void case, we derive the dependence of the effective moving barrier on the void formation threshold, δ v, by comparison against the Lagrangian void size function measured in the DEMNUni simulations. We discuss the mapping from Lagrangian to Eulerian space for both haloes and voids; adopting the spherical symmetry approximation, we obtain a strong agreement at intermediate and large scales. Finally, using the effective moving barrier, we derive Lagrangian void density profiles accurately matching measurements from cosmological simulations, a major achievement towards using void profiles for precision cosmology with the next generation of galaxy surveys.

The epidemiological footprint of contact structures in models with two levels of mixing.

Models with several levels of mixing (households, workplaces), as well as various corresponding formulations for , have been proposed in the literature. However, little attention has been paid to the impact of the distribution of the population size within social structures, effect that can help plan effective interventions. We focus on the influence on the model outcomes of teleworking strategies, consisting in reshaping the distribution of workplace sizes. We consider a stochastic SIR model with two levels of mixing, accounting for a uniformly mixing general population, each individual belonging also to a household and a workplace. The variance of the workplace size distribution appears to be a good proxy for the impact of this distribution on key outcomes of the epidemic, such as epidemic size and peak. In particular, our findings suggest that strategies where the proportion of individuals teleworking depends sublinearly on the size of the workplace outperform the strategy with linear dependence. Besides, one drawback of the model with multiple levels of mixing is its complexity, raising interest in a reduced model. We propose a homogeneously mixing SIR ODE-based model, whose infection rate is chosen as to observe the growth rate of the initial model. This reduced model yields a generally satisfying approximation of the epidemic. These results, robust to various changes in model structure, are very promising from the perspective of implementing effective strategies based on social distancing of specific contacts. Furthermore, they contribute to the effort of building relevant approximations of individual based models at intermediate scales.

Emergent time scales of epistasis in protein evolution

We introduce a data-driven epistatic model of protein evolution, capable of generating evolutionary trajectories spanning very different time scales reaching from individual mutations to diverged homologs. Our in silico evolution encompasses random nucleotide mutations, insertions and deletions, and models selection using a fitness landscape, which is inferred via a generative probabilistic model for protein families. We show that the proposed framework accurately reproduces the sequence statistics of both short-time (experimental) and long-time (natural) protein evolution, suggesting applicability also to relatively data-poor intermediate evolutionary time scales, which are currently inaccessible to evolution experiments. Our model uncovers a highly collective nature of epistasis, gradually changing the fitness effect of mutations in a diverging sequence context, rather than acting via strong interactions between individual mutations. This collective nature triggers the emergence of a long evolutionary time scale, separating fast mutational processes inside a given sequence context, from the slow evolution of the context itself. The model quantitatively reproduces epistatic phenomena such as contingency and entrenchment, as well as the loss of predictability in protein evolution observed in deep mutational scanning experiments of distant homologs. It thereby deepens our understanding of the interplay between mutation and selection in shaping protein diversity and functions, allows one to statistically forecast evolution, and challenges the prevailing independent-site models of protein evolution, which are unable to capture the fundamental importance of epistasis.

Continuous Space-Time Video Super-Resolution with Multi-Stage Motion Information Reorganization

Space-time video super-resolution (ST-VSR) aims to simultaneously expand a given source video to a higher frame rate and resolution. However, most existing schemes either consider fixed intermediate time and scale or fail to exploit long-range temporal information due to model design or inefficient motion estimation and compensation. To address these problems, we propose a continuous ST-VSR method to convert the given video to any frame rate and spatial resolution with Multi- s tage M otion information r eorganization (MsMr). To achieve time-arbitrary interpolation, we propose a forward warping guided frame synthesis module and an optical flow-guided context consistency loss to better approximate extreme motion and preserve similar structures among input and prediction frames. To realize continuous spatial upsampling, we design a memory-friendly cascading depth-to-space module. Meanwhile, with the sophisticated reorganization of optical flow, MsMr realizes more efficient motion estimation and motion compensation, making it possible to propagate information from long-range neighboring frames and achieve better reconstruction quality. Extensive experiments show that the proposed algorithm is flexible and performs better on various datasets than the state-of-the-art methods. The code will be available at https://github.com/hahazh/LD-STVSR .

Quantum Tunneling: From Theory to Error‐Mitigated Quantum Simulation

AbstractEver since the discussions about a possible quantum computer arised, quantum simulations have been at the forefront of possible utilities, with the task of quantum simulations being one that promises quantum advantage. Recently, advancements have made it feasible to simulate complex molecules using Variational Quantum Eigensolvers or study the dynamics of many‐body spin Hamiltonians. These simulations have the potential to yield valuable outcomes through the application of error mitigation techniques. Simulating smaller models carries a great amount of importance as well and currently, in the Noisy Intermediate Scale Quantum era, is more feasible since it is less prone to errors. The objective of this work is to examine the theoretical background and the circuit implementation of a quantum tunneling simulation, with an emphasis on hardware considerations. This study presents the theoretical background required for such implementation and highlights the main stages of its development. By building on classic approaches of quantum tunneling simulations, this study aims at improving the result of such simulations by employing error mitigation techniques, Zero Noise Extrapolation, and Readout Error Mitigation and uses them in conjunction with multiprogramming of the quantum chip, a technique used for solving the hardware under‐utilization problem that arises in such contexts.

Elastic Modulus Measurement at High Temperatures for Miniature Ceramic Samples Using Laser Micro-Machining and Thermal Mechanical Analyzer.

In this paper, we demonstrate a method of measuring the flexural elastic modulus of ceramics at an intermediate (~millimeter) scale at high temperatures. We used a picosecond laser to precisely cut microbeams from the location of interest in a bulk ceramic. They had a cross-section of approximately 100 μm × 300 μm and a length of ~1 cm. They were then tested in a thermal mechanical analyzer at room temperature, 500 °C, 800 °C, and 1100 °C using the four-point flexural testing method. We compared the elastic moduli of high-purity Al2O3 and AlN measured by our method with the reported values in the literature and found that the difference was less than 5% for both materials. This paper provides a new and accurate method of characterizing the high-temperature elastic modulus of miniature samples extracted from representative/selected areas of bulk materials.

Encoding spatiotemporal asymmetry in artificial cilia with a ctenophore-inspired soft-robotic platform

A remarkable variety of organisms use metachronal coordination (i.e., numerous neighboring appendages beating sequentially with a fixed phase lag) to swim or pump fluid. This coordination strategy is used by microorganisms to break symmetry at small scales where viscous effects dominate and flow is time-reversible. Some larger organisms use this swimming strategy at intermediate scales, where viscosity and inertia both play important roles. However, the role of individual propulsor kinematics-especially across hydrodynamic scales-is not well-understood, though the details of propulsor motion can be crucial for the efficient generation of flow. To investigate this behavior, we developed a new soft robotic platform using magnetoactive silicone elastomers to mimic the metachronally coordinated propulsors found in swimming organisms. Furthermore, we present a method to passively encode spatially asymmetric beating patterns in our artificial propulsors. We investigated the kinematics and hydrodynamics of three propulsor types, with varying degrees of asymmetry, using Particle Image Velocimetry and high-speed videography. We find that asymmetric beating patterns can move considerably more fluid relative to symmetric beating at the same frequency and phase lag, and that asymmetry can be passively encoded into propulsors via the interplay between elastic and magnetic torques. Our results demonstrate that nuanced differences in propulsor kinematics can substantially impact fluid pumping performance. Our soft robotic platform also provides an avenue to explore metachronal coordination at the meso-scale, which in turn can inform the design of future bioinspired pumping devices and swimming robots.

Apparent Parity Violation in the Observed Galaxy Trispectrum.

Recent measurements of the four-point correlation function in large-scale galaxy surveys have found apparent evidence of parity violation in the distribution of galaxies. This cannot happen via dynamical gravitational effects in general relativity. If such a violation arose from physics in the early Universe it could indicate important new physics beyond the standard model, and would be at odds with most models of inflation. It is therefore now timely to consider the galaxy trispectrum in more detail. While the intrinsic four-point correlation function, or equivalently the trispectrum, its Fourier counterpart, is parity invariant, the observed trispectrum must take redshift-space distortions into account. Although the standard Newtonian correction also respects parity invariance, we show that subleading relativistic corrections do not. We demonstrate that these can be significant at intermediate linear scales and are dominant over the Newtonian parity-invariant part around the equality scale and above. Therefore when observing the galaxy four-point correlation function, we should expect to detect parity violation on large scales.

Neuromodulation in Small Animal fMRI.

The integration of functional magnetic resonance imaging (fMRI) with advanced neuroscience technologies in experimental small animal models offers a unique path to interrogate the causal relationships between regional brain activity and brain-wide network measures-a goal challenging to accomplish in human subjects. This review traces the historical development of the neuromodulation techniques commonly used in rodents, such as electrical deep brain stimulation, optogenetics, and chemogenetics, and focuses on their application with fMRI. We discuss their advantageousness roles in uncovering the signaling architecture within the brain and the methodological considerations necessary when conducting these experiments. By presenting several rodent-based case studies, we aim to demonstrate the potential of the multimodal neuromodulation approach in shedding light on neurovascular coupling, the neural basis of brain network functions, and their connections to behaviors. Key findings highlight the cell-type and circuit-specific modulation of brain-wide activity patterns and their behavioral correlates. We also discuss several future directions and feature the use of mediation and moderation analytical models beyond the intuitive evoked response mapping, to better leverage the rich information available in fMRI data with neuromodulation. Using fMRI alongside neuromodulation techniques provide insights into the mesoscopic (relating to the intermediate scale between single neurons and large-scale brain networks) and macroscopic fMRI measures that correlate with specific neuronal events. This integration bridges the gap between different scales of neuroscience research, facilitating the exploration and testing of novel therapeutic strategies aimed at altering network-mediated behaviors. In conclusion, the combination of fMRI with neuromodulation techniques provides crucial insights into mesoscopic and macroscopic brain dynamics, advancing our understanding of brain function in health and disease. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Impact of Synthesis Method on the Structure and Function of High Entropy Oxides.

The term sample dependence describes the troublesome tendency of nominally equivalent samples to exhibit different physical properties. High entropy oxides (HEOs) are a class of materials where sample dependence has the potential to be particularly profound due to their inherent chemical complexity. In this work, we prepare a spinel HEO of identical nominal composition by five distinct methods, spanning a range of thermodynamic and kinetic conditions: solid state, high pressure, hydrothermal, molten salt, and combustion syntheses. By structurally characterizing these five samples across all length scales with a variety of X-ray methods, we find that while the average structure is unaltered, the samples vary significantly in their local structures and their microstructures. The most profound differences are observed at intermediate length scales, both in terms of crystallite morphology and cation homogeneity. As revealed by X-ray fluorescence microscopy ideal cation homogeneity is achieved only in the case of combustion synthesis. These structural differences in turn significantly alter the observed functional properties, which we demonstrate via characterization of their magnetic response. While ferrimagnetic order is retained across all five samples, the sharpness of the transition, the size of the saturated moment, and the coercivity all show marked variations with synthesis method. We conclude that the chemical flexibility inherent to HEOs is complemented by strong synthesis method dependence, providing another axis along which to optimize these materials for a wide range of applications.

Multiple states of two-dimensional turbulence above topography

The recent work of Siegelman & Young (Proc. Natl Acad. Sci. USA, vol. 120, issue 44, 2023, e2308018120) revealed two extreme states reached by the evolution of unforced and weakly damped two-dimensional turbulence above random rough topography, separated by a critical kinetic energy $E_\#$ . The low- and high-energy solutions correspond to topographically locked and roaming vortices, surrounded by non-uniform and homogeneous background potential vorticity (PV), respectively. However, we found that these phenomena are restricted to the particular intermediate length scale where the energy was initially injected into the system. Through simulations initialized by injecting the energy at larger and smaller length scales, we found that the long-term state of topographic turbulence is also dependent on the initial length scale and thus the initial enstrophy. If the initial length scale is comparable to the domain size, the long-term flow field resembles the minimum-enstrophy state proposed by Bretherton & Haidvogel (J. Fluid Mech., vol. 78, issue 1, 1976, pp. 129–154), with very few topographically locked vortices; the long-term enstrophy is quite close to the minimum value, especially when the energy is no larger than $E_\#$ . As the initial length scale becomes smaller, more vortices nucleate and become more mobile; the long-term enstrophy increasingly deviates from the minimum value. Simultaneously, the background PV tends to homogenization, even if the energy is below $E_\#$ . These results complement the phenomenology of topographic turbulence documented by Siegelman & Young, by showing that the minimum-enstrophy and background PV homogenization states can be adequately approached by large- and small-scale initial fields, respectively, with relatively arbitrary energy.

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs2LiYCl6:Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6Li(n,α) and 35Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252Cf source, an array of EJ-309 organic liquid scintillators, and a 6Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.