Simple Systems Research Articles

Analytical solution for one‐dimensional steady‐state VOCs diffusion in simplified capillary cover systems

AbstractThe analytical solution for a one‐dimensional and steady‐state model is proposed to investigate the diffusion of VOCs within landfill capillary cover systems under unsaturated water flow and stable conditions. Examples of coupled water flow and VOCs diffusion are evaluated by the proposed analytical solution to discuss the effects of the evaporation rate and clay thickness. The proficiency of the unsaturated cover system in minimising VOC emissions was also investigated. It was found that the non‐uniform distribution of water content can cause one order of magnitude reductions in the effective diffusion coefficient of VOCs, resulting in the attenuation of VOCs in the cover system. The concentration profile of VOCs is lower for the case with a larger evaporation rate. Ignoring the non‐uniform distribution of water content induced by water flow would underestimate the surface flux of VOCs by a factor of 1.8. The water content and VOC concentration in the cover system can be effectively diminished with the thickness of the clayey layer increasing. The surface flux of VOCs is considerably decreased with increasing thickness of clayey layer. Increasing the thickness of clayey layer from 0.2 to 1 m leads to a reduction in the surface flux of VOCs by a factor of 2.9. The sensitivity analysis provides further insights into the critical role of water flow in affecting VOC transport through the unsaturated cover system. The outcomes highlight that the impacts of unsaturated water flow within the covering system should be considered for assessment of VOC emissions.

Design of compact off-axis freeform imaging systems based on optical-digital joint optimization.

Using a freeform optical surface can effectively reduce the imaging system weight and volume while maintaining good performance and advanced system specifications. But it is still very difficult for traditional freeform surface design when ultra-small system volume or ultra-few elements are required. Considering the images generated by the system can be recovered by digital image processing, in this paper, we proposed a design method of compact and simplified off-axis freeform imaging systems using optical-digital joint design process, which fully integrates the design of a geometric freeform system and the image recovery neural network. This design method works for off-axis nonsymmetric system structure and multiple freeform surfaces with complicated surface expression. The overall design framework, ray tracing, image simulation and recovery, and loss function establishment are demonstrated. We use two design examples to show the feasibility and effect of the framework. One is a freeform three-mirror system with a much smaller volume than a traditional freeform three-mirror reference design. The other is a freeform two-mirror system whose element number is reduced compared with the three-mirror system. Ultra-compact and/or simplified freeform system structure as well as good output recovered images can be realized.

Spinal Cord Organoids to Study Motor Neuron Development and Disease.

Motor neuron diseases (MNDs) are a heterogeneous group of disorders that affect the cranial and/or spinal motor neurons (spMNs), spinal sensory neurons and the muscular system. Although they have been investigated for decades, we still lack a comprehensive understanding of the underlying molecular mechanisms; and therefore, efficacious therapies are scarce. Model organisms and relatively simple two-dimensional cell culture systems have been instrumental in our current knowledge of neuromuscular disease pathology; however, in the recent years, human 3D in vitro models have transformed the disease-modeling landscape. While cerebral organoids have been pursued the most, interest in spinal cord organoids (SCOs) is now also increasing. Pluripotent stem cell (PSC)-based protocols to generate SpC-like structures, sometimes including the adjacent mesoderm and derived skeletal muscle, are constantly being refined and applied to study early human neuromuscular development and disease. In this review, we outline the evolution of human PSC-derived models for generating spMN and recapitulating SpC development. We also discuss how these models have been applied to exploring the basis of human neurodevelopmental and neurodegenerative diseases. Finally, we provide an overview of the main challenges to overcome in order to generate more physiologically relevant human SpC models and propose some exciting new perspectives.

Proving “new physics” by measuring cosmic ray fluxes

Radiation on Earth’s surface has been measured for more than a century using different particle detectors. These detectors have evolved from electroscopes to sophisticated, thousands-ton LHC detectors. Recently, with the availability of cheap particle detectors and simple data acquisition systems, publications have attempted to link changes in detector count rate to various astrophysical phenomena. However, measurement errors, meteorological conditions, and disturbances of electrical and geomagnetic fields can significantly impact cosmic ray fluxes. Some authors overlook these factors and publish “unique” correlations between their detector count rates and events such as solar and lunar eclipses, lightning strokes, Venus’s transit over the Sun, and others.When searching for the causes of cosmic ray enhancements, carefully distinguishing the atmospheric, instrumental, and astrophysical effects is essential. This paper aims to demonstrate how analyzing different species of cosmic ray flux can provide valuable insights into the underlying physical processes. We will explain how to verify that measurements are not due to abrupt changes in atmospheric conditions or equipment malfunctions but rather evidence of a novel physical phenomenon. Our goal is to provide a clear path from measurement to physical inference.

Discovering Reaction Pathways, Slow Variables, and Committor Probabilities with Machine Learning.

A significant challenge faced by atomistic simulations is the difficulty, and often impossibility, to sample the transitions between metastable states of the free-energy landscape associated with slow molecular processes. Importance-sampling schemes represent an appealing option to accelerate the underlying dynamics by smoothing out the relevant free-energy barriers, but require the definition of suitable reaction-coordinate (RC) models expressed in terms of compact low-dimensional sets of collective variables (CVs). While most computational studies of slow molecular processes have traditionally relied on educated guesses based on human intuition to reduce the dimensionality of the problem at hand, a variety of machine-learning (ML) algorithms have recently emerged as powerful alternatives to discover meaningful CVs capable of capturing the dynamics of the slowest degrees of freedom. Considering a simple paradigmatic situation in which the long-time dynamics is dominated by the transition between two known metastable states, we compare two variational data-driven ML methods based on Siamese neural networks aimed at discovering a meaningful RC model─the slowest decorrelating CV of the molecular process, and the committor probability to first reach one of the two metastable states. One method is the state-free reversible variational approach for Markov processes networks (VAMPnets), or SRVs─the other, inspired by the transition path theory framework, is the variational committor-based neural networks, or VCNs. The relationship and the ability of these methodologies to discover the relevant descriptors of the slow molecular process of interest are illustrated with a series of simple model systems. We also show that both strategies are amenable to importance-sampling schemes through an appropriate reweighting algorithm that approximates the kinetic properties of the transition.

Natural Factorization of Linear Control Systems through Parallel Gathering of Simple Systems

Linear systems over vector spaces and feedback morphisms form an additive category taking into account the parallel gathering of linear systems. This additive category has a minimal exact structure and thus a notion of simple systems as those systems have no subsystems apart from zero and themselves. The so-called single-input systems are proven to be exactly the simple systems in the category of reachable systems over vector spaces. The category is also proven to be semisimple in objects because every reachable linear system is decomposed in a finite parallel gathering of simple systems. Hence, decomposition result is fulfilled for linear systems and feedback morphisms, but category of reachable linear systems is not abelian semisimple because it is not balanced and hence fails to be abelian. Finally, it is conjectured that the category of linear systems and feedback actions is in fact semiabelian; some threads to find the result and consequences are also given.

Self-hybridized exciton-polaritons in thin films of transition metal dichalcogenides for narrowband perfect absorption.

Monolayer direct-band gap transition metal dichalcogenides (TMDCs) have been extensively investigated in the context of light-matter interactions. To reach strong coupling, these studies make use of external optical cavities supporting well-defined resonant modes. However, use of an external cavity might limit the scope of possible applications of such systems. Here, we demonstrate that thin films of TMDCs can themselves serve as high-quality-factor cavities due to the guided optical modes they sustain in the visible and near-infrared ranges. Making use of the prism coupling, we achieve the strong coupling between excitons and guided-mode resonances lying below the light line, and show that the thickness of TMDC membranes can be used to tune and promote photon-exciton interactions within the strong-coupling regime. Additionally, we demonstrate narrowband perfect absorption in thin TMDC films through critical coupling with guided-mode resonances. Our work not only provides a simple and intuitive picture to tame interaction of light and matter in thin TMDC films, but also suggests that these simple systems are a promising platform for realizing polaritonic and optoelectronic devices.

Increasing Pump-Probe Signal toward Asymptotic Limits.

Optimization of pump-probe signal requires a complete understanding of how signal scales with experimental factors. In simple systems, signal scales quadratically with molar absorptivity, and linearly with fluence, concentration, and path length. In practice, scaling factors weaken beyond certain thresholds (e.g., OD > 0.1) due to asymptotic limits related to optical density, fluence and path length. While computational models can accurately account for subdued scaling, quantitative explanations often appear quite technical in the literature. This Perspective aims to present a simpler understanding of the subject with concise formulas for estimating absolute magnitudes of signal under both ordinary and asymptotic scaling conditions. This formulation may be more appealing for spectroscopists seeking rough estimates of signal or relative comparisons. We identify scaling dependencies of signal with respect to experimental parameters and discuss applications for improving signal under broad conditions. We also review other signal enhancement methods, such as local-oscillator attenuation and plasmonic enhancement, and discuss respective benefits and challenges regarding asymptotic limits that signal cannot exceed.

Characterizing the Interactions of Cell-Membrane-Disrupting Peptides with Lipid-Functionalized Single-Walled Carbon Nanotubes.

Lipid-functionalized single-walled carbon nanotubes (SWNTs) have garnered significant interest for their potential use in a wide range of biomedical applications. In this work, we used molecular dynamics simulations to study the equilibrium properties of SWNTs surrounded by the phosphatidylcholine (POPC) corona phase and their interactions with three cell membrane disruptor peptides: colistin, TAT peptide, and crotamine-derived peptide. Our results show that SWNTs favor asymmetrical positioning within the POPC corona, so that one side of the SWNT, covered by the thinnest part of the corona, comes in contact with charged and polar functional groups of POPC and water. We also observed that colistin and TAT insert deeply into the POPC corona, while crotamine-derived peptide only adsorbs to the corona surface. In separate simulations, we show that three examined peptides exhibit similar insertion and adsorption behaviors when interacting with POPC bilayers, confirming that peptide-induced perturbations to POPC in conjugates and bilayers are similar in nature and magnitude. Furthermore, we observed correlations between the peptide-induced structural perturbations and the near-infrared emission of the lipid-functionalized SWNTs, which suggest that the optical signal of the conjugates transduces the morphological changes in the lipid corona. Overall, our findings indicate that lipid-functionalized SWNTs could serve as simplified cell membrane model systems for prescreening of new antimicrobial compounds that disrupt cell membranes.

Vacuum decay and Euclidean lattice Monte Carlo

The decay rate of a metastable vacuum is usually calculated using a semiclassical approximation to the Euclidean path integral. The extension to a complete Euclidean lattice Monte Carlo computation, however, is hampered by analytic continuations that are ill-suited to numerical treatment, and the nonequilibrium nature of a metastable state. In this paper we develop a new methodology to compute vacuum decay rates from Monte Carlo simulations of Euclidean lattice theories. To test the new method, we consider simple quantum mechanical systems systems with metastable vacua. This work can be extended to Euclidean field theories, which we discuss in the Conclusions.

Perturbation theory with quantum signal processing

Perturbation theory is an important technique for reducing computational cost and providing physical insights in simulating quantum systems with classical computers. Here, we provide a quantum algorithm to obtain perturbative energies on quantum computers. The benefit of using quantum computers is that we can start the perturbation from a Hamiltonian that is classically hard to solve. The proposed algorithm uses quantum signal processing (QSP) to achieve this goal. Along with the perturbation theory, we construct a technique for ground state preparation with detailed computational cost analysis, which can be of independent interest. We also estimate a rough computational cost of the algorithm for simple chemical systems such as water clusters and polyacene molecules. To the best of our knowledge, this is the first of such estimates for practical applications of QSP. Unfortunately, we find that the proposed algorithm, at least in its current form, does not exhibit practical numbers despite of the efficiency of QSP compared to conventional quantum algorithms. However, perturbation theory itself is an attractive direction to explore because of its physical interpretability; it provides us insights about what interaction gives an important contribution to the properties of systems. This is in sharp contrast to the conventional approaches based on the quantum phase estimation algorithm, where we can only obtain values of energy. From this aspect, this work is a first step towards “explainable'' quantum simulation on fault-tolerant quantum computers.

Behaviour and the Origin of Organisms.

It is common in origins of life research to view the first stages of life as the passive result of particular environmental conditions. This paper considers the alternative possibility: that the antecedents of life were already actively regulating their environment to maintain the conditions necessary for their own persistence. In support of this proposal, we describe 'viability-based behaviour': a way that simple entities can adaptively regulate their environment in response to their health, and in so doing, increase the likelihood of their survival. Drawing on empirical investigations of simple self-preserving abiological systems, we argue that these viability-based behaviours are simple enough to precede neo-Darwinian evolution. We alsoexplain how their operation can reduce the demanding requirements that mainstream theories place upon the environment(s) in which life emerged.

Cyclic desorption based efficacy of polyvinyl alcohol-chitosan variant resins for multi heavy-metal removal

The simultaneous removal of Cu, Pb and Fe from water bodies has been targeted in this work with polyvinyl alcohol (PVA) and chitosan (low, medium, and high molecular weight) derivative and with cyclic desorption efficacy target. For a varied range of adsorbent loading (0.2–2 g L−1), initial concentration (187.7–563.1 mg L−1 for Cu, 5.2–15.6 mg L−1 for Pb, and 61.85–185.55 mg L−1 for Fe), and resin contact time (5 to 720 min), batch adsorption-desorption studies were conducted. After first adsorption-desorption cycle, the optimum absorption capacity was 6.85 mg g−1 for Pb, 243.90 mg g−1 for Cu, and 87.72 mg g−1 for Fe for the high molecular weight chitosan grafted polyvinyl alcohol resin (HCSPVA). The alternate kinetic and equilibrium models were analyzed along with the interaction mechanism between metal ions and functional groups. The cyclic desorption studies were carried out with simple eluent systems such as HCl, HNO3, H2SO4, KOH, and NaOH. The experiments revealed that the HCSPVA derivative has been an impressive, reusable, and effective sorbent for the mitigation of Pb, Fe, and Cu in complex wastewater systems. This is due to its easy synthesis, excellent adsorption capacity, quick sorption rate, and remarkable regeneration capabilities.

A novel observer design for friction estimation

In this paper, we propose a novel adaptive friction estimator for simple mechanical systems with Coulomb friction. We assume that the friction constant is unknown and we propose an adaptive observer for its estimation. We show that under certain conditions the observer structure is asymptotically stable. The proposed observer dynamics has two tuning parameters and essentially behaves as a second-order switching system. These parameters could be utilised to tune some time domain performance measures such as settling time, per cent overshoot. etc., under certain conditions. Lastly, simulations reveal that when the actual friction is not confined to Coulomb friction only, the proposed design improves the position tracking performance, especially when the position controller has low bandwidth.

Pair Interaction between Two Catalytically Active Colloids.

Due to the intrinsically complex non-equilibrium behavior of the constituents of active matter systems, a comprehensive understanding of their collective properties is a challenge that requires systematic bottom-up characterization of the individual components and their interactions. For self-propelled particles, intrinsic complexity stems from the fact that the polar nature of the colloids necessitates that the interactions depend on positions and orientations of the particles, leading to a 2d - 1 dimensional configuration space for each particle, in d dimensions. Moreover, the interactions between such non-equilibrium colloids are generically non-reciprocal, which makes the characterization even more complex. Therefore, derivation of generic rules that enable us to predict the outcomes of individual encounters as well as the ensuing collective behavior will be an important step forward. While significant advances have been made on the theoretical front, such systematic experimental characterizations using simple artificial systems with measurable parameters are scarce. Here, two different contrasting types of colloidal microswimmers are studied, which move in opposite directions and show distinctly different interactions. To facilitate the extraction of parameters, an experimental platform is introduced in which these parameters are confined on a 1D track. Furthermore, a theoretical model for interparticle interactions near a substrate is developed, including both phoretic and hydrodynamic effects, which reproduces their behavior. For subsequent validation, the degrees of freedom are increased to 2D motion and resulting trajectories are predicted, finding remarkable agreement. These results may prove useful in characterizing the overall alignment behavior of interacting self-propelling active swimmer and may find direct applications in guiding the design of active-matter systems involving phoretic and hydrodynamicinteractions.

Intrinsic Interface Adsorption Drives Selectivity in Atomically Smooth Nanofluidic Channels.

Specific molecular interactions underlie unexpected and useful phenomena in nanofluidic systems, but these require descriptions that go beyond traditional macroscopic hydrodynamics. In this letter, we demonstrate how equilibrium molecular dynamics simulations and linear response theory can be synthesized with hydrodynamics to provide a comprehensive characterization of nanofluidic transport. Specifically, we study the pressure driven flows of ionic solutions in nanochannels comprised of two-dimensional crystalline substrates made from graphite and hexagonal boron nitride. While simple hydrodynamic descriptions do not predict a streaming electrical current or salt selectivity in such simple systems, we observe that both arise due to the intrinsic molecular interactions that act to selectively adsorb ions to the interface in the absence of a net surface charge. Notably, this emergent selectivity indicates that these nanochannels can serve as desalination membranes.

Enzo Ferroni (1921-2007): the History of an Eclectic Chemist

Enzo Ferroni (Florence, 25 March 1921 – 9 April 2007) was an Italian chemist, full professor in physical chemistry at the University of Florence, where he served as Rector from 1976 to 1979, a renowned international scientist who initiated a new branch of chemistry, that applied to cultural heritage conservation. The history of his scientific and academic life offers a particular interest in a half-century cross-section of the history of chemistry in Italy and the entire world. In particular, Ferroni developed the colloids, surface, and interface chemistry in Italy immediately after the Second World War in a country where it was almost non-existent, sensing the extraordinary potential of this branch of chemistry in the fields of basic and applied research. This paper aims to reconstruct the history of this eclectic chemist starting from his pioneering studies in Italy on colloids, surfaces, and interfaces that, after the Second World War, came to be widely popular within the international scientific literature following three milestones represented by the studies of the Nobel laureates in chemistry, Richard A. Zsigmondy (1925), Theodor Svedberg (1926), and Irving Langmuir (1932). Enzo Ferroni’s far-sighted and visionary ideas concerning the investigation of these systems and others with biological implications by the nascent resonance spectroscopies and surface diffraction techniques were recognised and underlined as the revolutionary approach by ever more sophisticated instrumentations that were to characterise chemistry research to this day. The consecration of the extraordinary potential and peculiarities of colloids, surfaces, and interfaces would come to fruition in 1991 with the Nobel laureate in physics Pierre-Gilles de Gennes, who finally discovered that “the methods developed to study ordinary phenomena in simple systems can be generalised to more complex states of matter, especially liquid crystals, and polymers” (official motivation of the Prize), recognising soft matter as a peculiar form of matter in the condensed phase. These pioneering frontiers in the newly established soft matter field can be considered Ferroni’s last message in the bottle to young researchers facing the twenty-first century. The eclecticism of this chemist emerged from two other compelling aspects that are illustrated in this article: the chemistry for cultural heritage that Ferroni conceived, pushed by the dramatic damages suffered by the works of art after the Florence flood in 1966, and his strong vision about the equal dignity of basic and applied research, that led him to establish fruitful relationships with industries aimed to enhance technological fallouts, as the research by the Nobel laureates in chemistry (1963) Giulio Natta and Karl Ziegler had clearly shown.

Characterization of the planarian surface electroencephalogram

BackgroundDespite large morphological differences between the nervous systems of lower animals and humans, striking functional similarities have been reported. However, little is known about how these functional similarities translate to cognitive similarities. As a first step towards studying the cognitive abilities of simple nervous systems, we here characterize the ongoing electrophysiological activity of the planarian Schmidtea mediterranea. One previous report using invasive microelectrodes describes that the ongoing neural activity is characterized by a 1/fx power spectrum with the exponent ‘x’ of the power spectrum close to 1. To extend these findings, we aimed to establish a recording protocol to measure ongoing neural activity safely and securely from alive and healthy planarians under different lighting conditions using non-invasive surface electrodes.ResultsAs a replication and extension of the previous results, we show that the ongoing neural activity is characterized by a 1/fx power spectrum, that the exponent ‘x’ in living planarians is close to 1, and that changes in lighting induce changes in neural activity likely due to the planarian photophobia.ConclusionsWe confirm the existence of continuous EEG activity in planarians and show that it is possible to noninvasively record this activity with surface wire electrodes. This opens up broad possibilities for continuous recordings across longer intervals, and repeated recordings from the same animals to study cognitive processes.

Stability of Carbonates during Subduction: Influence of the Dehydration Regime of Chlorine-Bearing Metapelite

It was shown that, at a pressure of 3.0, 5.5, and 7.8 GPa and a temperature of 750–1030°C, a set of reactions occurred in carbonate and Cl-bearing pelite that is finally converted into an eclogite-like assemblage and formed a H2O–CO2 Cl-bearing fluid. The eclogite-like assemblage remains stable when the P–T conditions change concordantly with hot subduction geotherms, whereas carbonate is completely dissolved in the fluid already at ≥5.5 GPa. The CO2 content in the quenched fluid reaches 20–30 wt %. However, preliminary defluidization of pelite at 3.0 GPa and 750°С leads to chlorine removal and carbonate stabilization at 5.5 GPa and at 7.8 GPa in equilibrium with the next chlorine-free portions of the fluid. Comparison of the data available for simplified model systems and new data on carbonate and Cl-bearing pelite indicate that chlorine fluid essentially contributes to carbonate dissolution in the fluid. Thus, the stability of carbonates under P–T conditions typical of subduction zones is dependent on the behavior of chlorine during defluidization of marine sediments.

Phase‐Field Simulation of Texture Evolution in Magmatic Rocks

AbstractThe tool of phase‐field modeling for the prediction of chemical as well as microstructural evolution during crystallization from a melt in a mineralogical system has been developed in this work. We provide a compact theoretical background and introduce new aspects such as the treatment of anisotropic surface energies that are essential for modeling mineralogical systems. These are then applied to two simple model systems—the binary olivine‐melt and plagioclase‐melt systems ‐ to illustrate the application of the developed tools. In one case crystallization is modeled at a constant temperature and undercooling while in the other the process of crystallization is tracked for a constant cooling rate. These two examples serve to illustrate the capabilities of the modeling tool. The results are analyzed in terms of crystal size distributions (CSD) and with a view toward applications in diffusion chronometry; future possibilities are discussed. The modeling results demonstrate that growth at constant rates may be expected only for limited extents of crystallization, that breaks in slopes of CSD‐plots should be common, and that the lifetime of a given crystal of a phase is different from the lifetime of this phase in a magmatic system. The last aspect imposes an inherent limit to timescales that may be accessed by diffusion chronometry. Most significantly, this tool provides a bridge between CSD analysis and diffusion chronometry—two common tools that are used to study timescales of magmatic processes.