Neutron spin echo monitoring of segmental-like diffusion of water confined in the cores of carbon nanotubes.

Following the stream of increasing scientific interest in condensed-matter systems under ultra-hydrophobic confinement, the present work reports the first incoherent neutron spin echo assessment of the dynamics of water axially confined inside single-wall carbon nanotubes of diameter d∼ 1.4 nm. At the time scale of nanoseconds, two water populations are retrieved, whose relative proportion matches the one expected for a concentric shell + chain arrangement with cylindrical symmetry. The time dependence of the mean square displacement related to the external component is found to be subdiffusive, with peculiar resemblance to segmental diffusion typical of entangled polymeric systems.

Organization Science improves management effectiveness of Marine Protected Areas.

The ecological management effectiveness (EME) of Marine Protected Areas (MPAs) is the degree to which MPAs reach their ecological goals. The significant variability of EME among MPAs has been partly explained by MPA design, management and implementation features (e.g. surface area, enforcement, age of protection). We investigated EME variability by employing, for the first time, Organization Science. Eight Mediterranean MPAs were taken into account as case studies to explore the relationships between EME and MPA features, such as: 1) organizational size (i.e. the ratio between the number of full-time employees and the total MPA surface area), 2) management performance (i.e. the level of effort exerted to enhance and sustain the MPA management, including enforcement), 3) total surface area, and 4) MPA age. The log-response ratios of fish biomass and density in protected vs unprotected (control) areas were used as a proxy of EME. Management performance, organizational size and, to a lesser extent, MPA age were positively correlated with the log-response ratio of fish biomass, whereas total surface area did not display a significant role. None of the four features considered was significantly correlated with the log-response ratio of fish density. Based on our findings, we argue that the employment of Organization Science in the management effectiveness assessment can assist MPA managers to reach MPAs goals more effectively, with a more efficient use of available resources.

A spatial regression analysis of Colombia's narcodeforestation with factor decomposition of multiple predictors.

In the current accelerated process of global warming, forest conservation is becoming more difficult to address in developing countries, where woodlands are often fueling the illegal economy. In Colombia, the issue of narcodeforestation is of great concern, because of the ramification of narcoactivities that are affecting forests, such as agribusinesses and cattle ranching for money laundering. In this study, we use spatially explicit regressions incorporating a factor decomposition of predictors through principal component analysis to understand the impact of coca plantations on global and local-scale deforestation in Colombia. At national level we find a positive and statistically significant relationship between coca crops and deforestation. At the regional level, in two out of four regions, it appears that coca is causing deforestation, especially in the Department of Northern Santander and on the Pacific coast. The spatial models used reveal not only a direct effect but also positive and significant spillover effects, in line with the conjecture that narcodeforestation is not only due to the quest for new areas to expand coca-cultivation, which would determine a loss of forest only in the municipality where coca cultivation increases, but also to the need to launder illegal profits, or create clandestine routes and airplane strips, which can affect forests also in nearby municipalities.

The Effect of Embedded Nanoparticles on the Phonon Spectrum of Ice: An Inelastic X-ray Scattering Study.

As a contribution to the ongoing effort toward high-frequency sound manipulation in composite materials, we use Inelastic X-ray Scattering to probe the phonon spectrum of ice, either in a pure form or with a sparse amount of nanoparticles embedded in it. The study aims at elucidating the ability of nanocolloids to condition the collective atomic vibrations of the surrounding environment. We observe that a nanoparticle concentration of about 1 % in volume is sufficient to visibly affect the phonon spectrum of the icy substrate, mainly canceling its optical modes and adding nanoparticle phonon excitations to it. We highlight this phenomenon thanks to the lineshape modeling based on a Bayesian inference, which enables us to capture the finest detail of the scattering signal. The results of this study can empower new routes toward the shaping of sound propagation in materials through the control of their structural heterogeneity.

Altering Terahertz Sound Propagation in a Liquid upon Nanoparticle Immersion.

One of the grand challenges of new generation Condensed Matter physicists is the development of novel devices enabling the control of sound propagation at terahertz frequency. Indeed, phonon excitations in this frequency window are the leading conveyor of heat transfer in insulators. Their manipulation is thus critical to implementing heat management based on the structural design. To explore the possibility of controlling the damping of sound waves, we used high spectral contrast Inelastic X-ray Scattering (IXS) to comparatively study terahertz acoustic damping in a dilute suspension of 50 nm nanospheres in glycerol and on pure glycerol. Bayesian inference-based modeling of measured spectra indicates that, at sufficiently large distances, the spectral contribution of collective modes in the glycerol suspension becomes barely detectable due to the enhanced damping, the weakening, and the slight softening of the dominant acoustic mode.

Searching for a second excitation in the inelastic neutron scattering spectrum of a liquid metal: a Bayesian analysis.

When probed at nanometer and picosecond scales, the properties of a liquid present striking analogies with the ones of the corresponding solid, one of the most surprising is the ability of supporting shear wave propagation, as a rigid medium. Although this evidence is being reported by a growing number of terahertz scattering measurements, it remains an open question whether it is universal or rather typical of some liquids only. Furthermore, given its elusive signatures in the scattering signal, the detection of this effect appears as a typical case where an unintentional "bias of confirmation" can mislead experimentalists. We thus decided to use a Bayesian inference approach to achieve a probabilistically grounded and evidence-based lineshape modeling of the inelastic neutron scattering spectra from liquid silver, whose simulated density autocorrelations bear evidence of a shear mode propagation over very short distances. The result of our analysis indicates that the observation of any additional, non-longitudinal, acoustic modes in this simple system goes beyond the accuracy of the used scattering method.

The damping of terahertz acoustic modes in aqueous nanoparticle suspensions.

In this work, we investigate the possibility of controlling the acoustic damping in a liquid when nanoparticles are suspended in it. To shed light on this topic, we performed Inelastic X-Ray Scattering (IXS) measurements of the terahertz collective dynamics of aqueous suspensions of nanospheres of various materials, size, and relative concentration, either charged or neutral. A Bayesian analysis of measured spectra indicates that the damping of the two acoustic modes of water increases upon nanoparticle immersion. This effect seems particularly pronounced for the longitudinal acoustic mode, which, whenever visible at all, rapidly damps off when increasing the exchanged wavevector. Results also indicate that the observed effect strongly depends on the material the immersed nanoparticles are made of.

The Terahertz Dynamics of an Aqueous Nanoparticle Suspension: An Inelastic X-ray Scattering Study.

We used the high-resolution Inelastic X-ray Scattering beamline of the Advanced Photon Source at Argonne National Laboratory to measure the terahertz spectrum of pure water and a dilute aqueous suspension of 15 nm diameter spherical Au nanoparticles (Au-NPs). We observe that, despite their sparse volume concentration of about 0.5%, the immersed NPs strongly influence the collective molecular dynamics of the hosting liquid. We investigate this effect through a Bayesian inference analysis of the spectral lineshape, which elucidates how terahertz transport properties of water change upon Au-NP immersion. In particular, we observe a nearly complete disappearance of the longitudinal acoustic mode and a mildly decreased ability to support shear wave propagation.

Onset of interfacial waves in the terahertz spectrum of a nanoparticle suspension.

We used inelastic x-ray scattering to gain insight into the complex terahertz dynamics of a diluted Au-nanoparticle suspension in glycerol. We observe that, albeit sparse, Au nanoparticles leave clear signatures on the dynamic response of the system, the main one being an additional mode propagating at the nanoparticle-glycerol interface. A Bayesian inferential analysis of the line shape reveals that such a mode, at variance with conventional acoustic modes, keeps a hydrodynamiclike behavior well beyond the continuous limit and down to subnanometer distances.

Model-free description of polymer-coated gold nanoparticle dynamics in aqueous solutions obtained by Bayesian analysis of neutron spin echo data.

We present a neutron spin echo study of the nanosecond dynamics of polyethylene glycol (PEG) functionalized nanosized gold particles dissolved in D_{2}O at two temperatures and two different PEG molecular weights (400D and 2000D). The analysis of the neutron spin echo data was performed by applying a Bayesian approach to the description of time correlation function decays in terms of exponential terms, recently proved to be theoretically rigorous. This approach, which addresses in a direct way the fundamental issue of model choice in any dynamical analysis, provides here a guide to the most statistically supported way to follow the decay of the intermediate scattering functions I(Q,t) by basing on statistical grounds the choice of the number of terms required for the description of the nanosecond dynamics of the studied systems. Then, the presented analysis avoids from the start resorting to a preselected framework and can be considered as model free. By comparing the results of PEG-coated nanoparticles with those obtained in PEG2000 solutions, we were able to disentangle the translational diffusion of the nanoparticles from the internal dynamics of the polymer grafted to them, and to show that the polymer corona relaxation follows a pure exponential decay in agreement with the behavior predicted by coarse grained molecular dynamics simulations and theoretical models. This methodology has one further advantage: in the presence of a complex dynamical scenario, I(Q,t) is often described in terms of the Kohlrausch-Williams-Watts function that can implicitly represent a distribution of relaxation times. By choosing to describe the I(Q,t) as a sum of exponential functions and with the support of the Bayesian approach, we can explicitly determine when a finer-structure analysis of the dynamical complexity of the system exists according to the available data without the risk of overparametrization. The approach presented here is an effective tool that can be used in general to provide an unbiased interpretation of neutron spin echo data or whenever spectroscopy techniques yield time relaxation data curves.

Interpreting the Terahertz Spectrum of Complex Materials: The Unique Contribution of the Bayesian Analysis.

In the last few decades, experimental studies of the terahertz spectrum of density fluctuations have considerably improved our knowledge of the mesoscopic dynamics of disordered materials, which also have imposed new demands on the data modelling and interpretation. Indeed, lineshape analyses are no longer limited to the phenomenological observation of inelastic features, as in the pioneering stage of Neutron or X-ray spectroscopy, rather aiming at the extraction from their shape of physically relevant quantities, as sound velocity and damping, relaxation times, or other transport coefficients. In this effort, researchers need to face both inherent and practical obstacles, respectively stemming from the highly damped nature of terahertz modes and the limited energy resolution, accessible kinematic region and statistical accuracy of the typical experimental outcome. To properly address these challenges, a global reconsideration of the lineshape modelling and the enforcement of evidence-based probabilistic inference is becoming crucial. Particularly compelling is the possibility of implementing Bayesian inference methods, which we illustrated here through an in-depth discussion of some results recently obtained in the analysis of Neutron and X-ray scattering results.

Damping Off Terahertz Sound Modes of a Liquid upon Immersion of Nanoparticles.

The control of phonon propagation in nanoparticle arrays is one of the frontiers of nanotechnology, potentially enabling the discovery of materials with unknown functionalities for potential innovative applications. The exploration of the terahertz window appears quite promising as phonons in this range are the leading carriers of heat transport in insulators and their control is the key to implement devices for heat flow management. Unfortunately, this scientific field is still in its infancy, and even a basic topic such as the influence of floating nanoparticles on the terahertz phonon propagation of a colloidal suspension still eludes a firm answer. Shedding some light on this topic is the main motivation of the present work, which focuses an inelastic X-ray scattering (IXS) measurements on a dilute suspension of Au nanospheres in water. Measured spectra showed a nontrivial shape displaying multiple inelastic features that, based on a Bayesian inference analysis, we assign to phonon modes propagating throughout the nanoparticle interior. Surprisingly, the spectra bear no evidence of propagating modes, which are known to dominate the spectrum of pure water, owing to the scattering that these modes suffer from the sparse nanoparticles in suspension. In perspective, this finding may inspire simple routes to manipulate high-frequency acoustic propagation in hybrid-liquid and solid-materials.

A Nonparametric Multidimensional Latent Class IRT Model in a Bayesian Framework.

We propose a nonparametric item response theory model for dichotomously-scored items in a Bayesian framework. The model is based on a latent class (LC) formulation, and it is multidimensional, with dimensions corresponding to a partition of the items in homogenous groups that are specified on the basis of inequality constraints among the conditional success probabilities given the latent class. Moreover, an innovative system of prior distributions is proposed following the encompassing approach, in which the largest model is the unconstrained LC model. A reversible-jump type algorithm is described for sampling from the joint posterior distribution of the model parameters of the encompassing model. By suitably post-processing its output, we then make inference on the number of dimensions (i.e., number of groups of items measuring the same latent trait) and we cluster items according to the dimensions when unidimensionality is violated. The approach is illustrated by two examples on simulated data and two applications based on educational and quality-of-life data.