Massimiliano Chiappini
email: m.chiappini@uu.nl

Eric Grelet

Marjolein Dijkstra
email: m.dijkstra@uu.nl

Speeding up dynamics by tuning the non-commensurate size of rod-like particles in a smectic phase

Using simulations, we study the diffusion of rod-like guest particles in a smectic environment of rod-like host particles. We find that the dynamics of guest rods across smectic layers changes from a fast nematic-like diffusion to a slow hopping-type dynamics via an intermediate switching regime by varying the length of the guest rods with respect to the smectic layer spacing. We determine the optimal rod length that yields the fastest and the slowest diffusion in a lamellar environment. We show that this behavior can be rationalized by a complex 1D effective periodic potential exhibiting two energy barriers, resulting in a varying preferred mean position of the guest particle in the smectic layer. The interplay of these two barriers controls the dynamics of the guest particles yielding a slow, an intermediate and a fast diffusion regime depending on the particle length.

Understanding the dynamics of particles or objects in crowded environments is important in many fields ranging from traffic jams [1], evacuations of crowds, sheep herding, evasive tumor growth, to caging in colloidal glasses [2][3][4]. The motion of a guest particle in a disordered crowded environment is severely hampered by its surrounding constituents. As most disordered systems are characterized by only one relevant length scale (e.g. particle size), a simple picture emerges: the bigger the particle the slower its dynamics [5][6][7][8]. This phenomenon is invariant across scales as demonstrated by the abovementioned examples. However, this simple picture breaks down as the environment becomes inhomogeneous and ordered, yielding additional competing length scales and giving rise to remarkable exceptions to this general rule.

The motion of particles in ordered environments has been thoroughly studied in the field of liquid crystals, finding that crowded environments with different degrees of positional and/or orientational order lead to a wide variety of dynamic behaviors. For nematic liquid crystals, exhibiting long-range orientational order, the anisotropy of the environment is transferred to the motion of the particles. A fast longitudinal self-diffusion is observed in the direction parallel to the nematic director n (the average particle orientation), and a slow transverse selfdiffusion in the perpendicular direction [START_REF] Van Bruggen | [END_REF][12][13].

In the case of long-range positional order, the dynamics strongly depends on the dimensionality of the translational order and the corresponding effective energy landscape. In 3D colloidal crystals, particles are confined to their lattice positions, and the diffusion is largely determined by the motion of defects [14][15][16]. In columnar liquid crystals, showing 2D positional order, a liquid-like longitudinal diffusion is observed within the columns, accompanied by a transverse hopping-type dynamics between different columns [17,18]. Finally, in smectic liquid crystal phases characterized by a quasi long-range 1D translational order, a quantized hopping-type dynamics is found across smectic layers as the particles experience an effective one-dimensional periodic potential due to the lamellar organization [19][20][21]. Furthermore, computer simulations demonstrated cooperative motion of stringlike clusters of particles across the smectic layers [22].

In general, the presence of positional and/or orientational order introduces additional length scales to the system. In the presence of guest particles, their interplay with the various length scales associated with the structure increases the complexity of the dynamics. On the one hand, the diffusion of guest spherical particles in nematic phases of rod-like host liquid crystals has been widely addressed in literature [23][24][25][26][27][28][29], finding a faster diffusion in the direction longitudinal to the nematic director field. On the other hand, the diffusion of non-spherical particles in anisotropic liquid crystalline environments is still largely unexplored. Recently, Alvarez et al. [9] studied in experiments the diffusion of tracer amounts of non-commensurate guest viral rods in a smectic phase of shorter host fd filamentous viruses with a size ratio L guest /L host ≃ 1.3. Surprisingly they found that while the host particles experience the usual hopping-type dynamics across smectic layers, the noncommensurate guest particles undergo a fast and almost continuous nematic-like diffusion, yielding the exceptional case of larger guest particles diffusing faster than the smaller host ones. No significant differences between host and guest particles were found in the transverse in-layer diffusion. The typical slow hopping-type diffusion across smectic layers was recovered for dimeric and trimeric mutants of the host fd particles, namely for guest particles with length ratios of 2 and 3, respectively.

In this Letter, we study using computer simulations the dynamics of guest particles of varying lengths in a smectic environment of host particles in order to unravel the mechanism behind this highly counterintuitive fast diffusion of large non-commensurate guest particles. We show that by tuning the length of the guest rods with respect to the smectic layer spacing their longitudinal dynamics changes from a fast nematic-like diffusion to a slow hopping-type dynamics via an intermediate switching regime, thereby obtaining control over the speed and type of behavior of the longitudinal diffusion. More importantly, we determine the optimal rod size for either the fastest or slowest diffusion, and rationalize this behavior in terms of a complex 1D effective smectic periodic potential characterized by two energy barriers that each rod feels in the lamellar structure of the smectic phase. We show that the interplay and relative height of the two energy barriers control the dynamics of the guest particles, yielding a slow, an intermediate and a fast diffusion regime depending on the particle length.

We model the experimental mixture of long and short filamentous bacteriophage viruses as a binary mixture of rigid rods. Each guest and host rod is modeled by a hard spherocylinder, i.e. a cylinder of diameter d and length L g and L h , respectively, capped at both ends with hemispheres of diameter d, yielding an end-to-end length of L g,h + d (Fig. 1a). We introduce a tracer amount of N g = 6 guest particles in a system of N h = 3072 host particles with a length L h = 40d. The overall phase sequence of isotropic, nematic, smectic-A (Sm A ), and smectic-B/crystal phases of fd-viruses [30] is well captured by that of hard spherocylinders with L h = 40d [31], even though fd virus suspensions also display a columnar phase [32]. The aspect ratio of the host rods in the simulations is set such that it roughly matches the effective rod length over diameter ratio of the experimental system, thereby taking into account the electrostatic repulsion of the fd viruses [30].

We equilibrate the system in a low-density Sm A state using Monte Carlo (MC) simulations in an isothermalisobaric ensemble, i.e. the pressure, temperature, N g and N h are kept fixed. Note that the smectic layer spacing in simulations is λ ∼ 1.1L h , whereas λ ∼ 1.0L host in the experimental system of filamentous viruses [30]. After full equilibration we investigate using both standard and Dynamic MC (DMC) simulations [33,34] the longitudinal dynamics along the z-axis, parallel to the nematic director n, for various L g ∈ [0.2, 2.5]L h corresponding to various size ratios r = (L g + d)/λ. Within this range of lengths the probability of finding guest rods in a transverse inter-lamellar configuration is negligible [35,36].

We refer the reader to the Supplemental Material [START_REF]which includes details on the computational methods and on the conversion between computational and experimental time units, the caging time that a particle typically spend within a smectic layer[END_REF] for technical details on the simulations.

In Fig. 1b, we present typical longitudinal trajectories from both simulations and experiments, showing remarkably similar slow hopping-type dynamics of host particles (r ∼ 1) as well as fast diffusive behavior of noncommensurate guest particles (r ∼ 1.3). For each particle trajectory z(t) we measure the mean square displacement along the director n, MSD(t) = (z(t 0 + t) -z(t 0 )) 2 , and average the MSDs of all particles with equal length. In Fig. 1c we show the MSDs for a selected set of size ratios r. For particles with a length commensurate with the smectic layer spacing (r ∼ 1) we obtain the typical of particles in a lamellar phase [20] with a cagetrapping plateau between the short-and long-time diffusion regimes corresponding to the intra-and inter-layer dynamics, respectively (See Supplemental Material [START_REF]which includes details on the computational methods and on the conversion between computational and experimental time units, the caging time that a particle typically spend within a smectic layer[END_REF]). As the length of the guest particles increases, the time interval for the caging becomes shorter, and eventually disappears for r ∼ 1.25 when the dynamics becomes nematic-like with a diffusive behavior (Fig. 1c). Upon further increasing the particle length, the cage-trapping plateau reappears (r ∼ 1.45) and becomes more pronounced as the dynamics becomes hopping-type again for nearly commensurate dimers (r ∼ 1.90). Similarly, for guest rods shorter than the smectic layer spacing, the time interval of caging decreases (r ∼ 0.47) and eventually disappears for guest particles of low anisotropy (r ∼ 0.29). To quantify the long-term dynamic behavior, we determine the long-time diffusion coefficient D defined as half the slope of the MSD at long times, i.e. MSD(t) = 2D t γ (1), and we present D normalized by the particle diffusion coefficient at infinite dilution D (r) as a function of the size ratio r in Fig. 2. In the range 1 ≤ r < 2, a strong increase of the diffusion is observed with a maximum D (r)/D 0 (r) at r ∼ 1.25, corresponding to a fast nematic-like diffusion of particles whose length is not commensurate with the smectic layer spacing. This yields an optimal value for the fastest longitudinal diffusion remarkably close to the particle length ratio for which fast diffusion was observed in experiments [9]. For larger r the diffusion slows down as the hopping-like dynamics is retrieved. The slowest diffusion is not found for particles twice the length of the smectic layer spacing (r ∼ 2) but at slightly smaller lengths (r ∼ 1.75). We also observe in Fig. 2 that the values of D (r)/D 0 (r) are in good quantitative agreement with the experimental values marked by the purple symbols despite the simplicity of our model. For guest particles shorter than the host ones (r < 1), the fastest and the slowest dynamics are obtained by non-commensurate particles of size ratio r ∼ 0.25 and r ∼ 0.75 respectively, corresponding to the fast nematic-like diffusion for the former and slow hopping-like dynamics for the latter. Interestingly, the normalized values for r < 1 of the diffusion coefficients for the slowest and fastest dynamics are very similar to their corresponding values for r > 1, emphasizing again that the shortest particles do not necessarily diffuse the fastest. In the long rod limit, i.e. for r > 2, we find another maximum of D (r)/D 0 (r) at r ∼ 2.25.

The dependence of D (r)/D 0 (r) on the size ratio r in Fig. 2 suggests a periodic behavior of the longitudinal dynamics with a period set by the smectic layer spacing λ. For each size ratio interval r ∈ [n, n + 1] with n = 0, 1, 2, • • • , the dynamics first speeds up as r increases and the smectic caging becomes less severe, reaches a maximum value at r ≃ n + 0.25 corresponding to the fastest nematic-like diffusion, and then slows down and reaches a minimal value at r ≃ n+0.75. This periodic behavior can be explained by dividing the end-to-end guest rod length L g +d = rλ into a length ℓ⌊r⌋ that is commensurate with ⌊r⌋ smectic layers (where the floor function ⌊x⌋ denotes the largest integer that is less than x), and an "excess" length of ℓ(r -⌊r⌋). The longitudinal dynamics of guest particles is predominately determined by the excess part of the guest rod, which creates voids in the smectic layers and affects the caging of the lamellar phase. Here, the only effect of the "commensurate" part of the particle is a general slowing down of the dynamics with n (See the inset of Fig. 2).

To quantify the effect of the excess particle length, we measure the effective potential βU Sm (z) = -ln(ρ(z)) felt by a guest rod, where ρ(z) is the probability distribution of finding a rod-shaped particle in an infinitesimal interval of [z, z + δz] and β = 1/k B T . The effective potential is periodic due to the smectic host ordering, therefore ρ(z) is only measured in a single smectic layer 0 ≤ z < λ. In Fig. 3a-f, we report the smectic potential for varying length ratios 0 < r < 2. Surprisingly, we find that the smectic potentials exhibit two barriers, or equivalently two minima at z min 1 and z min 2 which merge into a single minimum when r ≃ n, namely when particles are commensurate with the layer spacing. We plot z min 1 and z min 2 for varying r in Fig. 4, allowing us to distinguish three different regimes as schematically illustrated in Fig. 3g.

In the first regime (I) corresponding to size ratios r ∈ [n, n + 0.3], the guest particles are on average located at the same position as their commensurate counterparts with r = n, i.e. in the middle of the smectic layers. However, as they are longer than nλ, they create holes in the adjacent smectic layers resulting in a release of the cage constraint thereby facilitating the inter-layer diffusion and speeding up the dynamics, with the fastest nematic-like diffusion found for r ∼ n+0.25. In the opposite limit, the third regime (III) having r ∈ [n+ 0.6, n+ 1] exhibits the slowest diffusion behavior and corresponds to guest particles which already have the same equilibrium position as the next commensurate multimer (r = n + 1). Because the guest rods are shorter than (n + 1)λ, they first have to diffuse within the smectic layer to reach one of its two boundaries, before they can jump to the adjacent layer, slowing down the longitudinal diffusion in comparison to the one associated with commensurate particles. We denote regime III as the slow diffusive correspond to the center-of-mass positions at which one of the ends of the guest particles touches one of the boundaries of the smectic layers (Fig. 3b ande). This was re-cently experimentally observed for short rods dispersed in colloidal monolayer of host rod-shaped particles with a length ratio r ∼ 0.5 [37]: the short rods were found to strongly anchor to the membrane interfaces, and only occasionally hop to the opposite interface. Our results confirm this anchoring behavior and extend it to particles even larger than the lamellar spacing. The preferential adsorption of non-commensurate guest rods at the interface of smectic layers can be explained by the fact that guest rods at the interface generates large voids that can be partially filled via small angular fluctuations of neighboring host particles, thereby hindering their diffusion. However, if the guest particle is at the center of a smectic layer (or in between two smectic layers), the resulting voids are smaller, making it harder for host particles to occupy the empty space. This would indeed require higher tilt angle of the host rods, hence generating a defect structure in the smectic organization. As a consequence, the guest particles escape from this central position and adhere to one of the two smectic layer interfaces. In this regime II, referred as the switching regime, the guest particles experience two potential barriers of varying height (Fig. 3b andd) for varying r, which results from a non-trivial interplay of the effective smectic potentials that are felt by single host rods (r ∼ 1, Fig. 3c) as well as by commensurate rods (r ∼ 2, Fig. 3f) and which are out-of-phase in terms of barrier locations (See Supplemental Material [START_REF]which includes details on the computational methods and on the conversion between computational and experimental time units, the caging time that a particle typically spend within a smectic layer[END_REF]).

In conclusion, we showed that the dynamics of guest rods can be controlled by tuning the ratio r of their size over the lamellar spacing. We observed that the longtime diffusion coefficient D is a periodic function of r, as the longitudinal dynamics is entirely determined by the excess length ℓ(r -⌊r⌋) of the guest particle. We show that this behavior can be rationalized by a 1D effective periodic potential exhibiting up to two energy barriers, yielding a slow, an intermediate and a fast diffusive regime, granting complete control over the type and speed of the dynamics of guest particles in a smectic environment.

FIG. 1 .

 1 FIG. 1. (a) Snapshot from simulations of a guest spherocylinder (cyan) with cylindrical length Lg and diameter d diffusing in a host smectic phase of layer spacing λ formed by hard spherocylinders (purple) with equal diameter d and length L h = 40d. (b) Example trajectories of guest particles with varying size ratio r = (Lg + d)/λ along the nematic director n of the host smectic phase in simulations (top) and experiments (bottom) [9] showing the fast nematic-like diffusion of non-commensurate guest rods with r ∼ 1.3 and discrete hopping-type diffusion of host particles (r ∼ 1). The conversion factor from the computational time unit τ to seconds s (τ ∼ 2 • 10 -6 s) is discussed in the Supplemental Material [10]. (c) Longitudinal mean square displacement (MSD) of simulated guest particles of varying size ratios r = (Lg + d)/λ, showing either a fast nematic-like diffusion for noncommensurate guest rods of r ∼ 1.3 and 0.3, or a sub-diffusive regime for the other guest and host particles. The diffusion exponents γ = 0.5 and 1 are indicated for comparison (See Eq. (1)).

FIG. 2 .

 2 FIG. 2. Long-time diffusion coefficient D (r) normalized by the infinite-dilution diffusion coefficient D0(r) [10] of guest particles as a function of the size ratio r. The experimental values of D (r) are shown in purple for r = 1, 1.3, and 2 [9]. The inset shows the raw diffusion coefficients. The background is colored according to the three diffusion regimes displayed in Fig. 3, and the dashed lines are guides to the eye.

FIG. 3 .

 3 FIG. 3. (a-f) Effective potential USm(z) experienced by guest particles for varying size ratios r = (Lg + d)/λ in a smectic phase with a layer spacing λ. The dashed vertical lines indicate the equilibrium positions of the rod particles, z min 1 and z min 2 , corresponding to the minima of the ordering potential USm(z). A video showing the variation of USm(z) with the size ratio r can be found in the SM [10]. (g) Sketches of the host (purple) and guest (cyan) particles at their equilibrium positions z min1

FIG. 4 .

 4 FIG. 4. Center-of-mass positions z min 1 and z min2of the guest rods corresponding to the minima of the effective smectic potential as a function of size ratio r. The background is colored according to the three diffusive regimes displayed in Fig.3.

2

 2

  M. C. and M. D. acknowledge financial support from the EU H2020-MSCA-ITN-2015 project MULTIMAT (Marie Sklodowska-Curie Innovative Training Networks) [project number: 676045].


Antoine Saverimoutou

Bertrand Mathieu

Sandrine Vaton

Web View: A Measurement Platform for Depicting Web Browsing Performance and Delivery



Abstract-Web browsing is the main Internet Service and every customer wants the minimum web page loading times. To satisfy this perpetual need, web browsers offer new processing engines and increased functionalities. Web developers make use of new programming languages and paradigms, new transport protocols have been introduced, network operators offer increased bandwidth and Content Delivery Networks (CDN) providers deploy web servers closest to end-users. To assess the efficiency of these evolutions, delivered performance is often evaluated into a standalone manner, without considering the whole chain of web browsing. We propose Web View, a measurement platform, which performs automated web browsing sessions on popular websites in a user-representative environment. Through different configurable parameters, Web View measures a wide set of information in order to evaluate the impact of the different parameters (transport protocols, web browsers, CDN, access networks, etc.). Based on those measurements, to ease the understanding of web browsing and the corresponding evolutions, Web View offers a public visualization website (https://webview.orange.com). For instance, with Web View, we were able to detect that the use of different CDNs at different times of the day can decrease loading times up to 400% and that the delivery of content through different transport protocols can decrease loading times up to 79%. This paper presents the Web View measurement platform as well as remarkable events we noticed during more than one year of measurements.

Index terms -Web, QoE, QoS, CDN, HTTP/2, QUIC I. INTRODUCTION The Web was originally meant to deliver static contents but has evolved considerably over the last years to deliver a wide range of contents through different service providers (analytics, advertising, social networking and CDNs). To cope with the increasing usage of dynamic contents embedded in today's web pages, web browser's engines are regularly improves and offer new functionalities. New Internet protocols are defined to improve content delivery such as HTTP/2 (Version 2 of the HyperText Protocol) [START_REF] Belshe | Hypertext Transfer Protocol Version 2 (HTTP/2)[END_REF] which runs over TCP and QUIC (Quick UDP Internet Connections) [START_REF] Iyengar | QUIC: A UDP-Based Multiplexed and Secure Transport[END_REF] running over UDP, to be standardized as HTTP/3. Network operators offer increased throughput for Manuscript received October 10, 2019 Antoine Saverimoutou and Bertrand Mathieu are with Orange Labs, Lannion, France. Sandrine Vaton is with IMT Altantique, Brest, France. their access networks and content service providers increase the availability of CDN infrastructures.

One important aspect for Web browsing is the web pages' loading times and recent studies show that high loading times (more than 5 seconds) may lead to web page abandonment. In order to measure web pages loading times, standardization bodies like the W3C (World Wide Web Consortium) provide different web metrics. Research work has been done to study web pages structures and the impact of Internet protocols on web browsing quality, but these solutions focus on a specific subject and do not analyze the whole chain of web browsing sessions (e.g., loading times, protocol distribution, types of services, location of web servers, etc.). Furthermore, those solutions make use of tools where JavaScript is sometimes disabled (whereas JavaScript is nowadays widely used in web pages), do not embark latest updated web browsers and are not connected to residential access networks when performing measurement campaigns leading to results qualifying web browsing quality which might be biased.

In this paper, we present Web View, a measurement platform which aims at overcoming such limitations by using probes connected to real residential access networks, launching real web browsers, and monitoring several parameters of the whole chain of Web browsing sessions. Since web pages' structures and used technologies regularly evolve, we make use of web browsers' network logs to obtain fine-grained information. Through our monitoring website, we visually represent the different loading times of a set of websites, the protocol distribution (assess their deployment rate), the number of downloaded resources and their web servers location, etc. In a second page, we show in detail the different web servers delivering content to end-users (origin or CDN servers together with their geographic location).

This paper is organized as follows: Section II describes the existing web metrics and related work meant to quantify web browsing, followed by Section III which illustrates our measurement platform. The section IV depicts our public visualization website and section V describes some remarkable events related to websites' evolutions and content delivery. We conclude in section VI.

II. RELATED WORK

There have been several contributions from the research community to understand the Web ecosystem better.

Web metrics. Aiming to bring uniform benchmarking indicators, standardization bodies such as the W3C together with large service companies and researchers have laid out a set of web metrics. The Page Load Time (PLT) is the time between navigation start until a web page is fully loaded. The Resource Timing provides some low-level information about the downloaded content (used transport protocol or type and size of objects). The Paint Timing exposes the First Paint (FP) which is the moment a first pixel appears in the web browser window. The Above-The-Fold (ATF) [START_REF] Brutlag | Above the Fold Time: Measuring Web Page Performance Visually[END_REF] exposes the time needed to load the visible part of a web page without scrolling by making use W3C web metrics. The Time for Full Visual Rendering (TFVR) [START_REF] Saverimoutou | Web Browsing Measurements: An Above-the-Fold Browser-Based Technique[END_REF] reflects the time to load the visible portion of a web page at first glance by making use of web browsers' networking logs. Web browsing quality. Research works have been studying the impact of the transport protocols, the web page structures and the used technologies on web page loading times [START_REF] Butkiewicz | Characterizing Web Page Complexity and Its Impact[END_REF] and on end-users experience [START_REF] Bocchi | Measuring the Quality of Experience of web users[END_REF]. Research work has also been performed on different networking architectures which can improve content delivery by identifying the different objects to be served with higher priority by CDNs [START_REF] Narayanan | Reducing latency through page-aware management of web objects by content delivery networks[END_REF], exposing the different caching policies of CDNs [START_REF] Flores | Caching the internet: A view from a global multi-tenant cdn[END_REF] and identify the optimal transit selection from a CDN perspective [START_REF] Ahmed | Optimizing Internet Transit Routing for Content Delivery Networks[END_REF]. Regarding web metrics, studies question their versatility and objectiveness and offer new techniques to improve their accuracy [START_REF] Kelton | Improving user perceived page times using gaze[END_REF], new tools to better understand how web pages being wrongly designed can impact loading times [START_REF] Varvello | EYEORG: A platform for crowdsourcing web quality of experience measurements[END_REF] and how measurements setups can make web metrics to be biased [START_REF] Enghardt | Web performance pitfalls[END_REF]. Actual web metrics are mainly meant to measure static contents (dynamic contents are nowadays the de-facto standard).

Measurement tools. Different measurement tools have been used by the research community in order to perform automated web browsing. Among all these tools, OpenWPM [START_REF] Englehardt | Online tracking: A 1-million-site measurement and analysis[END_REF] uses real web browsers to better quantify web privacy by supporting stateful and stateless measurements. Additional research work has also focused on web pages' structure and identified leading causes of degraded web browsing experience [START_REF] Wang | Demystifying page load performance with wprof[END_REF]. Eager to perform measurements on a larger geographic scope, web browser-plugins [START_REF] Da Hora | Narrowing the gap between QoS metrics and web QoE using above-thefold metrics[END_REF] have been proposed to measure in the wild the impacts of web page loadings.

This related work allows highlighting that each proposed solution is specific and that there is no complete user-representative tool investigating the whole Web browsing chain over long periods of time. These solutions do not embark various web browsers (and different versions) and are not attached to different home access networks (and different network operators). Our tool is regularly updated with new versions of web browsers and easily deployable on-the-fly everywhere. Compared to our platform, the other tools do not allow comparisons amongst multiple websites, neither aggregate different measurements nor allow an analysis into an historical way (e.g., comparing results from now versus values from 15 months ago).

Fig. 1: Web View infrastructure

Web View embarks all web metrics available to date which helps in getting many information and link them so as to better understand the whole chain of web browsing sessions and the impact of each parameter. Finally, regarding content servers, the impact of the delivery via CDN, geographic location and corresponding protocol distribution is not really investigated in the research literature. The second functionality of our tool performs an analysis of this delivery part.

III. WEB VIEW PROBE

Web View is a measurement platform (Fig. 1), composed of 3 main components: the probes, the database and a public visualization website showing the obtained measurement results for a set of websites.

The Web View probe is a user-oriented measurement tool whose main objective is to perform automated web browsing sessions, measuring representative information of web pages in order to better qualify and understand web browsing, both in terms of performance and delivery. The probes emulate end-users' web browsing within a real end-user environment: real web browsers, residential access network, etc. Actually, 17 probes are currently deployed at 5 different geographic locations: 10 in Lannion (France), 4 in Paris (France), 1 in Vannes (France), 1 in Curepipe (Mauritius) and 1 in Tokyo (Japan). Our aim is to deploy more probes, worldwide, at various locations, in order to get many measurements results, from many places. For instance, we will install other probes in countries where Orange is, but deployment in other entities is also possible (as examples, we recently installed probes on other French network operators). With more probes we will be able to collect more data and analysis from the research community will help web developers to improve web page designs.

For each measurement test, we have to specify different configuration parameters: the web browser we want to use (currently Chrome web browser v.63-68-71-73-75-76-77 and the Mozilla Firefox web browser v.63-64-66-68-69 are supported), the access network of the probe since one probe is connected to only one access network (can currently be Fiber, ADSL or home WiFi of different network operators), the transport protocol we want to evaluate to get the contents (HTTP/1.1, HTTP/2, QUIC), the window size of the screen we want to emulate, the use of an ad blocker or not and the list of websites to measure.

It can be a list of pre-defined websites or the Top N Alexa websites (most visited websites on a daily basis: https://www.alexa.com/siteinfo). As we are performing many measurements all over the day/week/month, we scripted the different measurements tests to do and it is automatically launched via the script.

Since content servers might not implement all transport protocols, we allow fallback to protocols used by content servers. Typically, when performing measurements and requesting HTTP/1.1, we deactivate the HTTP/2 and QUIC protocol; requesting HTTP/2 implies deactivating QUIC but fallback to HTTP/1.1 is allowed; when requesting QUIC, we allow fallback to HTTP/1.1 and HTTP/2 for non-QUIC web servers; when requesting the Repeat mode (HTTP/2 or QUIC), we favor 0-RTT UDP and 1-RTT TCP connections by firstly navigating to the website, close the web browser, clear the resources' cache but keep the DNS (Domain Name System) cache. We then navigate once more to the website where measurements are collected. For every measurement, the resources' cache is always emptied and a timeout of 18 seconds is set to limit the impact of possible downtimes of content servers (value derived from all our measurements).

For every visited website, Web View probes offer 84 parameters. For the computation and collection of these parameters, we rely on the HTTP Archive (HAR) file which is the web browser's exposed networking logs. The use of networking information is privileged to W3C calculations in order to be more accurate when calculating loading times of dynamic and progressive content (Progressive Web Applications). For some parameters, we take the values offered by the HAR file, as others tools do, but for others, further processing tasks are performed leading to a richer information, than just what the HAR provides (e.g., the protocol distribution through which responses are delivered to end-users, the location of web servers, the different content providers, etc.).

Amongst the measured and computed 84 parameters by the Web View probes, we can mention 4 different loading times, namely the First Paint (FP), the Page Load Time (PLT), the The probe also provides information about resources composing the web page, i.e., the number of resources, their provenance, type, size and transfer rate. Since content can be delivered using a different transport protocol than the one we requested, we compute the distribution of received protocols for the given web page.

Finally, information about the content server is deeply processed in order to identify if a resource was provided by a content server or a CDN provider. For this, we use a part of the HAR file which indicates if the resource is retrieved from a cache (HIT) or not (MISS). For example, in Fig. 2, the first server replies with a MISS (cache-miss), meaning that the resource is not in its cache and the second server replies with a HIT (cache-hit) meaning that the needed resource is present in its cache. The corresponding content is thus delivered by the second CDN. From the exposed IP address, we perform a WHOIS to query the registered assignees, which results into the CDN Fastly. Relying on the MaxMind GeoIP2 database (https://www.maxmind.com/), we then identify the geographic location of the web server (town, country and continent).

IV. WEB VIEW VISUALIZATION

The Web View visualization tool is a public website (https://webview.orange.com), based on Grafana, and allows a straightforward visual analysis of our collected measurements. Grafana is connected to an Elasticsearch database, which stores all measurement results performed and sent by our Web View probes. The website offers several tabs illustrating how our platform works and has 2 main pages: one showing different panels related to the analysis of the web page browsing (loading times, resources, the protocol distribution, etc. ) and the second one representing content servers (CDNs or origin servers) on a world map, with information about resources and protocols.

{"name": "X-Cache", "value": "MISS, HIT"}, {"name": "X-App-Cache", "value": "HIT"}, {"name": "X-Served-By", "value": "cache-iad2132-IAD, cache-cdg20761-CDG"}, "serverIPAddress": "151.101.120.175"

Fig. 4: Location of origin web servers and CDN servers delivering resources to end-users in France

For the web page offering websites' analysis, a menu allows a user to filter out several parameters: select a specific website, transport protocols, access networks, location of probes, web browser's window size, used web browser and use of an ad blocker or not. For the web page representing servers delivering contents, the menu offers an additional filter to select a specific CDN provider.

A. Web Pages Analysis

The first web page of our visualization tool depicts information to better understand the implications of the Web ecosystem during web browsing sessions. While some panels show the time needed to load a web page as a whole or through its progression by comparing different browsers (Chrome and Firefox), others compare the obtained timings when requesting specific transport protocols (HTTP/1.1, HTTP/2, QUIC). To better follow up with the deployment of the newest transport protocols, namely HTTP/2 and more recently QUIC, additional panels show the distribution of Internet protocols (how many resources are retrieved from web servers through HTTP/1.1, HTTP/2 or QUIC) as per a requested transport protocol. Additional information is also provided regarding the geographic location of web servers continent-wise. Following a set of filters selected by a user, all the panels are automatically updated.

For instance, Fig. 3 shows the protocol distribution when requesting QUIC and browsing the homepage of youtube.com. The web browser used is Google Chrome and we can see that even if Google promotes the QUIC protocol, on average 55% of contents are still distributed through HTTP/2 over TLS/TCP. When using an ad blocker, a mean number of 56 resources are downloaded from 8 different domains. These domains deliver all contents in a secured manner (HTTPS) and only 5 domains are QUIC-enabled.

B. Content Servers Analysis

The CDN web page allows to lay out figures on the delivery of contents, and mainly which web server provides a corresponding resource, the type of service delivered and their geographic location. An end-user located in Europe expects to firstly download objects from the same homepage domain and secondly from web servers located in Europe. Our visualization website allows to detect that at different times of the day, content might be fetched from different web servers at different geographic locations mainly due to Content Delivery Networks edge servers. Domains delivering contents and having an authoritative DNS name server different from the one of the homepage are entitled Non-Origin domains and conversely Same-Origin domains.

For instance, we can see through Fig. 4 that when an end-user is located in France and performs web browsing on the Top 50 Alexa websites, contents are mainly retrieved from France and Europe. Nevertheless, a non-negligible amount of content is also downloaded from North America and Asia. The different circles represent the distribution of content following the geographic location of web servers. Any user can hover the different circles and obtain fine-grained details about the web servers and the amount of content served. The Fig. 4 popup window illustrates the web servers delivering contents from a datacenter located in the Kansas County, United States. Additional panels represent the Internet protocol distribution (HTTP/1.1, HTTP/2 and QUIC) from servers located all around the globe when performing web browsing measurements. Content servers referenced as "No CDN" imply that they are regular content web servers. From all our measurements performed on a set of websites, the list of CDN providers is automatically updated.

V. REMARKABLE EVENTS

The Web View visualization website shows measurements performed since February 2018 where different web browsers have been used. Since web browsers are often updated (on average every month), the platform is also regularly updated. Measuring websites' loading times on large time-spans help in identifying the impact of actors of the Web ecosystem which can increase or decrease loading times. The Web View website being public, everyone can access it and analyze different behavior, but for people wanted to go into raw data, an open dataset can be found at: https://webview.orange.com/public/WebViewOpenDataset.z ip. As examples, we present in this section some remarkable events we noticed over the past year.

A. Web Browsers

Our tool makes use of two web browsers, Chrome and Firefox.

Number of resources. On average, 78% of our measured websites make use of Google services and when launching the Chrome browser, an average of 7 Google objects are downloaded and stored in the web browser's cache and used during further web navigation. When launching the Firefox web browser, no Google objects are downloaded which at the end of the day makes the Firefox web browser to download more objects in the PLT lapse of time.

PLT timing. Irrespective of the measured website, the Firefox web browser takes on average 1400 ms more time compared to Chrome to load an entire web page.

Over long time spans, we have been noticed that a higher loading time with Firefox web browser is mainly due to an increased processing time.

TFVR timing. When performing measurements with web browsers having a window size 1440 x 900, the Chrome version 75 loads the visible portion of a web page faster compared to Firefox version 64 since Chrome is embarked with a native ad blocker and downloads images in different formats of smaller sizes. The Firefox web browser TFVR timing is on average 750 ms more compared to Chrome. This points out that the different web browsers' engine policies can impact the perceived quality of an end-user.

Processing time. Chrome version 63 has been released in December 2017 and Chrome version 68 in July 2018. Chrome v.68 offers increased functionalities regarding the processing engine and security features. Firefox 63 has been released in June 2018. When comparing the different processing time of the above web browsers, Chrome 63 outperforms Firefox 63 on average by 900 ms, which plays a considerable role to the final exposed loading time (processing and network time). We have also identified that Chrome outperforms Firefox in terms of download and processing times since it downloads images in WebP format, being smaller in size, when Firefox downloads in JPG format (does not support WebP). It is important to measure processing time because, depending on the processing engine of the web browser, specific objects can be processed on a longer time and thus delay the download and processing of further downloaded resources.

B. Transport protocols

Measurements are performed by requesting a specific transport protocol where fallback to a subsequent protocol is allowed if a distant web server does not implement it.

Protocol distribution. From our measured websites, when requesting HTTP/1.1, all web servers reply in strict HTTP/1.1 (any web server is HTTP/1.1 enabled which is a standard). When requesting HTTP/2, we can see that the overall HTTP/2 delivery has increased from 77% one year ago to 85%. When requesting the QUIC protocol, no website replies fully in QUIC following two reasons. Firstly due to the protocol mechanism itself, first requests to web servers are sent into HTTP/2 in order to assess if the corresponding web server is UDP-enabled. Secondly the QUIC protocol is mainly deployed on Google web servers. The QUIC Repeat mode can increase the QUIC distribution by up to 94%. As example, when considering the website blogspot.com (a Google website), requesting QUIC triggers the delivery of content through QUIC at a rate of 83% and QUIC Repeat enables the delivery of contents fully (100 %) in QUIC.

Loading times following requested protocol. When requesting HTTP/1.1, the average PLT of all our measured websites are on average 3400 ms. Requesting HTTP/2 reduces PLT values on average by 200 ms (not all web servers are HTTP/2-enabled). As indicated previously, the QUIC protocol is mainly deployed on Google web servers and requesting it creates a considerable fallback to the HTTP/2 protocol (UDP throttling) for non UDP-enabled web servers which increases on average the PLT by 100 ms. Requesting QUIC Repeat decreases the average PLT up to 1200 ms (compared to requesting HTTP/2). As an example, since May 2018, the website amazon.com has increased content delivery in HTTP/2 (from 92% to 98%) which has resulted in a decrease of 79% of PLT timings.

C. Content servers

When browsing to a website, several domains from all over the world might serve contents to end-users. Fig. 5 shows the amount of objects downloaded from different continents between October 2018 and February 2019 when a European end-user browses the homepage csdn.net (tech blog). Until November 12 (Period 1), an average total number of 133 objects are downloaded when browsing to the website's homepage. On average 50 objects are retrieved from Asia, 2 from North America and 81 from Europe (CDN provider Level 3) through 63% HTTP/2 and 37% HTTP/1.1. Between November 13 and November 28 (Period 2), the homepage structure changes and a mean number of 123 objects are downloaded on average. These objects are served mainly from Asia (only 3 objects are downloaded from a CDN provider in Europe) which results in an increase of 3100 ms in the PLT. As from November 29 (Period 3), the CDN provider Level 3 delivers on average 70 resources from Europe. When moving from Period 2 to Period 3, the average PLT is decreased by 32% thanks to the re-introduction of a CDN provider. When comparing Period 1 versus Period 3 where objects are delivered by a CDN provider, the average PLT is decreased by 36% mainly due to the shift in Level 3 With the CDN page of our website, we have been able to detect that the CDN provider EdgeCast, can now deliver some contents using the QUIC protocol, e.g., for the website tumblr.com. In May 2019, the QUIC protocol started to be officially discussed at the IETF (Internet Engineering Task Force) for standardization and we could notice in June 2019 that major CDNs (Fastly, Akamai, Verizon, etc.) started to implement the protocol. It us to follow the deployment of the QUIC protocol also in CDN products.

Websites referenced as News can make usage of several CDNs to deliver their content. As illustrated in Table I, when browsing to the homepage of lefigaro.fr (French news website) from Mauritius in the Indian Ocean, on average 151 objects are downloaded. From our visualization website, we can identify that 96 objects were downloaded from CDN providers and 55 objects from regular content web servers ("No CDN"). Among the different CDN providers, Akamai delivers the greatest amount of objects with respectively 45 objects from South-Africa, 12 objects from North-America and 3 objects from Mauritius (As shown in Fig. 2, objects may be cached by different CDN providers at specific geographic locations and the first CDN provider having the content in its cache is selected).

VI. CONCLUSION AND FUTURE WORK

The Web browsing ecosystem is complex, involves several actors and resources are delivered by content servers located all around the world. In order to analyze it and identify which parameters play the most important role for web browsing, we proposed our Web View probe which makes use of real web browsers and residential access networks to measure finely web browsing sessions. The obtained measurements are visually represented, via our public Web View visualization website, so that any user can better understand the Web ecosystem.

The measurements performed by the probes for more than one year, allow us to better understand when, how and why the web browsing loading times might be increased or decreased: the used web browser, the transport protocol and the use of CDN impact them. Furthermore, having a history of measurements over more than one year, we have been able to see several evolutions of websites' content delivery. However, more probes deployed worldwide we can have, more measurements we can get and thus obtain more precise analysis and findings. In the next future, we aim at deploying probes in others countries where Orange operates network and opening the Web View platform to others entities could help to deploy probes in other locations and thus enrich the dataset of measured information.

In our technical future work, we will apply Deep Learning techniques such as Neural Networks Models (e.g., Random Forest) on the dataset to be able to predict loading times and non-parametric Bayesian Models (e.g., Hidden Markov Models) to capture patterns regarding resources delivery and loading times. This will allow to automatically detect changes in web browsing performance and delivery.

VII. ACKNOWLEDGEMENT

This work is partially funded by the French ANR BottleNet project, No ANR-15-CE25-0013-001.

Fig. 2 :

 2 Fig. 2: Part of HAR file related to CDN delivery

Fig. 3 :

 3 Fig. 3: Protocol distribution for homepage "youtube.com" Time for Full Visual Rendering (TFVR) and the processing time, all obtained from HAR files.The probe also provides information about resources composing the web page, i.e., the number of resources, their provenance, type, size and transfer rate. Since content can be delivered using a different transport protocol than the one we requested, we compute the distribution of received protocols for the given web page.Finally, information about the content server is deeply processed in order to identify if a resource was provided by a content server or a CDN provider. For this, we use a part of the HAR file which indicates if the resource is retrieved from a cache (HIT) or not (MISS). For example, in Fig.2, the first server replies with a MISS (cache-miss), meaning that the resource is not in its cache and the second server replies with a HIT (cache-hit) meaning that the needed resource is present in its cache. The corresponding content is thus delivered by the second CDN. From the exposed IP address, we perform a WHOIS to query the registered assignees, which results into the CDN Fastly. Relying on the MaxMind GeoIP2 database (https://www.maxmind.com/), we then identify the geographic location of the web server (town, country and continent).

Fig. 5 :

 5 Fig. 5: Location of servers for the website "csdn.net" CDN Provider Downloaded contents Akamai 60 No CDN 55 Fastly 25 Google 7 Amazon 2 Cdn77 1 KeyCdn 1

Table I :

 I Content delivery for the website "lefigaro.fr" for an end-user located in Curepipe(Mauritius, Africa)

	edge domain web servers delivering contents in HTTP/2
	(from 63% to 97%). Increasing the protocol distribution
	from HTTP/1.1 to HTTP/2 by 34% can reduce the PLT by
	36% and up to 33% for the TFVR.

BIOGRAPHIES

Antoine Saverimoutou is a Ph.D student with Orange labs and IMT Atlantique (Brest, France). He obtained his Bachelor degree in Applied Mathematics at the University of Cambridge, Bachelor degree in Computer Science at the University of Caen and M.Sc degree from Caen, France. His thesis research is about Web browsing, and more specifically the study of new Internet protocols impact on end-users QoE.

Dr Bertrand Mathieu received a Diploma of Engineering in Toulon, the MsC degree from the University of Marseille, the PhD degree from the University Pierre et Marie Curie in Paris, and the « Habilitation à Diriger des Recherches » from the University of Rennes. He is working on programmable networks, QoS and QoE and new network solutions. He contributed to 11 national and European projects. He published more than 70 papers in international conferences, journals or books. He is member of several conferences Technical Program Committee and an IEEE senior member.

Sandrine Vaton is a full professor at IMT Atlantique (Brest, France). She has received an engineering degree and a Ph.D degree in signal processing from Telecom Paris, and then accreditation to supervise research (HDR) in computer science from Unity of Rennes. Her research studies are statistical modelling of telecommunications network and traffic, performance evaluation, network monitoring and anomaly detection.


Paul Mosset

René Grée

Majed Kammoun
email: majed_kammoun@yahoo.fr

Awatef Selmi

Rihab Aydi

Archive for Organic Chemistry Arkivoc 2019, part

Keywords: Synthesis, oxaziridine, nitrone, sulfoxidation Arkivoc 2019, v

Synthesis and reactivity of new dihydroisoquinoline-derived oxaziridines

Introduction

Since their discovery by Emmons in 1956, 1 oxaziridines have gained increasing attention. 2 The oxaziridine function contains a three-membered ring with a carbon, an oxygen and a nitrogen atom. The literature indicates that these compounds have been extensively explored because of the inherently weak N-O bond due to the strained ring that makes the molecule unusually highly reactive. These heterocycles have attracted considerable attention due to various biological properties such as anti-tumor, 3,4 anti-malarial, 5 and antifungal 6 to analogues of penicillin. 7 Furthermore, they are widely used as reagents and intermediates in the preparation of biologically active molecules. 8,9 Recently, dihydroisoquinoline oxaziridines, including those with trichloromethyl in position 1, have been shown to have potent hypolipidemic effect in high-fat diet-fed rats. 10 The major routes to the synthesis of oxaziridines involve the photolysis of nitrones, 11 the electophilic amination of carbonyl compounds, 12 and the double 1,4-conjugate addition of hydroxamic acids to propiolates. 13 Oxaziridines can also be prepared by oxidation of imines with several oxidizing agents, such as cobalt-mediated molecular oxygen, 14 urea-hydrogen peroxide, 15 oxone, 16 hydrogen peroxide, 17 or a nitrilehydrogen peroxide system. 18 The oxidation of an imine with a peracid, usually meta-chloroperbenzoic acid (m-CPBA), is the most frequently employed method for oxaziridine preparation. 19 Since the first discovery of this function, 1 oxaziridines are well known as both aminating and oxygenating reagents in their reactions with a wide variety of nucleophiles and their structural electronic features. [20][21][22] The substituents on the nitrogen atom of oxaziridines play a significant role in atom transfer reactions. 23,24 The presence of an electron-withdrawing group on the nitrogen atom substantially increases the reactivity of oxaziridines as oxygen donors. 25 However, oxaziridines with small groups substituted on the nitrogen are electrophiles and they behave as amino group transfer agents to nucleophiles such as N-H, 21 N-alkyl, 21 and Nalkoxycarbonyloxaziridines. 21 The oxidation of sulfides to sulfoxides is an important synthetic transformation that has received much attention in recent years. 26 Moreover, sulfoxides are useful as synthons and chiral auxiliaries in asymmetric synthesis. 27 Some of the most successful techniques that are currently available for asymmetric sulfoxidation include the stoichiometric or catalytic 28 use of enantiomerically pure oxaziridine reagents and the use of oxaziridium salts, 29 which give the greatest enantioselectivities for the oxidation of sulfides.

The dihydroisoquinoline oxaziridines have previously been reported to be promising agents for the transfer of oxygen to organosulfides in the presence and absence of acid. [30][31][32][33] The substitution at position 1 onto the dihydroisoquinoline skeleton has a marked influence in the formation of sulfoxide or nitrone products from the oxidation reactions of the oxaziridines. 31,33 We have noted a significant variation in reaction times when we changed the structure of oxaziridine, most notably the substitution at position 1. Indeed, the unsubstituted dihydroisoquinoline oxaziridine can oxidize quickly the p-tolylmethyl sulfide to the sulfoxide, 32 whereas oxygen transfer is slowest in the presence of steric hindrance, in position 1, of the oxaziridine. 31 As part of our interest in the reactivity of oxaziridines and particularly in the design of a dihydroisoquinoline-derived family which is able to react in an oxygen transfer process, the present study aimed to synthesize new oxaziridines, namely 6-9. We also examine the effect of the introduction of a p-chlorophenyl group substituted in position 1 and of two nitro groups, one in the phenyl ring and one in the isoquinoline skeleton, on the reaction of oxygen transfer to sulfides forming sulfoxides in an acid promoted reaction.

Results and Discussion

The new oxaziridines presented in the current study were synthesized starting from the commercial tertiary alcohol 1 (Scheme 1). The imines 2-4 from the first step were obtained by condensation of the tertiary alcohol 1 in a Ritter-type procedure. The nitration of imine 3 under mild conditions 34,35 selectively led to the derived imine 5. Oxidation of imines 2-5 with m-CPBA 42 rapidly leads to oxaziridines 6-9 respectively, in good yields (Scheme 1).

Scheme 1. Synthesis of oxaziridines 6-9.

We have focused on the structural modification of the oxaziridines, most notably the substitution at position 1, that can lead to useful reagents for the electrophilic oxidation of wide variety of nucleophiles. 31 In an acidic medium and in the absence of nucleophiles, the oxaziridine can be subject to a competitive transformation which, through O-protonation, isomerize to a nitrone. In the presence of nucleophiles, the oxaziridine can be an oxygen transfer agent to organo-sulfides, as has previously been reported. 31,32 Herein, we study the isomerization reaction of new oxaziridines 6-9 with various amounts of methanesulfonic acid (MsOH) in dichloromethane as solvent at room temperature are reported in Table 1 below.

It can be noted from Table 1 that the isomerization of the oxaziridines 6-9 to nitrones 10-13 necessitates the optimization of the reaction conditions through adjusting the time for each one, which depends on the equivalents of methanesulfonic acid used [MsOH] and the different substrates employed, in particular those which are substituted at position 1.

Remarkably, we note an increase in the rate of conversion of oxaziridines into nitrones with increase in the number of equivalents of acid introduced in the reaction. Exceptional acceleration is noted for the isomerization on the addition of acid into the reaction. For example, when we change gradually the acid proportion to oxaziridine 9 we note that for 3 equivalents of acid (entry1, Table1) to transform 9 into the

N R OH N Cl O 2 N O 2 N H 2 SO 4 N O O 2 N O 2 N Cl N O R R-C 6 H 4 CN Hexane, 68°C 2h.30min KNO 3 , H 2 SO 4 rt, 2h; 60°C, 4h 1
2, R = H 3, R = Cl 4, R = NO 2 9 m-CPBA 3 m-CPBA 6, R = H 7, R = Cl 8, R = NO 2
nitrone 13 takes 5 days, and 2 days when 4 equivalents of acid are added (entry 2, Table1), but with 5 equivalents of acid (entry 3, Table1), 5 h are enough for the total isomerization of this oxaziridine into the corresponding nitrone in 82% yield.

Table 1. Oxaziridines 6-9 under the action of methanesulfonic acid in various concentrations

6 R = R' = R'' = H 10 7 R = Cl; R' = R'' = H 11 8 R = NO2; R' = R'' = H 12 9 R = Cl; R' = R'' = NO2 13
a Reaction time followed by TLC . b Isolated product. c Determined by 1 H NMR spectroscopy in CDCl3.

It is noteworthy that the reaction of oxaziridine 8, with a p-nitrophenyl group in position 1, during the introduction of 3 equivalents of methanesulfonic acid (MsOH) (entry 1, Table 1) forms the corresponding nitrone 12 after only 3 days. While we were pleased to find that, with the oxaziridine 7, the presence of pchlorophenyl group in position 1 accelerates the reaction. It was only after 5min that the starting material is totally converted and the reaction led to nitrone 11 (entry 1, Table 1).

The results reported in Table 1 indicated that the presence of the withdrawing group (nitro) of the dihydroisoquinoline decreased the basicity of the substrate and slowed the isomerization reaction. In fact, the isomerizations of the oxaziridines 8 and 9 to nitrones were slower than those of oxaziridines 6 and 7 (entries 1 and 3).

Table 2 summarizes the results of the oxidations of p-tolylmethyl sulfide with oxaziridines 6-9, first performed under the conditions previously described elsewhere 32 at room temperature in the presence of 3 equivalents of methanesulfonic acid (MsOH), in dichloromethane.

As shown in Table 2, the different substituents at positions 1 and 7 on the dihydroisoquinoline skeleton of the function are primarily responsible for the formation of sulfoxides or nitrones products from the oxidation reaction onto oxaziridines 6-9 (Table 2).

The oxidation of methyl p-tolyl sulfide to sulfoxides observed for 8 and 9 and give good sulfoxide conversion without any signs of overoxidation to the sulfones (Table 2, entries 3 and 4). When the oxidation of sulfide was performed using oxaziridines 6 and 7 under the same conditions, the reaction leads quantitatively and quickly to the corresponding nitrones 10 and 11 (Table 2, entries 1 and 2); no oxygen transfer reaction was observed. Considering both the reaction time and yield, the best results were obtained using oxaziridine 8 and 9 (Table 2, entries 3and 4); the reactions proceeded to completion within 15 min and 5 min respectively in high yields. The above data show that the introduction of a nitro group onto the dihydroisoquinoline skeleton could increase the electrophilicity of oxaziridines 8 and 9, thus making the reaction of the oxygen transfer onto sulfide easier.

N O R R'' R' MsOH CH 2 Cl 2 N R R'' R' O Time a Yield of nitrone b (%) (conversion
In our previous work, 33 the introduction of the two attractor groupings, trichloromethyl in position 1 and nitro group in position 7, onto the dihydroisoquinoline skeleton of the function was noted to being able to oxidize sulfide into sulfoxide with heating at reflux for 7 h. Herein, we show that with the introduction of a p-chlorophenyl group in position 1 and of two electron-withdrawing nitro groups in position 7 and in the phenyl group, it was possible to oxidize the sulfide to sulfoxide at room temperature.

The structure of the oxaziridine C-aryl group has an effect on the oxygen transfer (Table 2). Although, the results revealed that the introduction of p-chlorophenyl group in position 1 and of two electron withdrawing nitro groups onto the dihydroisoquinoline skeleton of the function led to a significant variation in terms of oxaziridine 9 reactivity and thus notably accelerated the transfer of the oxygen atom ( entry 4), the sulfoxide was observed. In fact, the resulting oxaziridine 9 being able to oxidize sulfide into sulfoxide in the best time compared with the previously reported result in the literature. 31,33 Next, In order to check the oxidizing properties of oxaziridine 9, the results of oxygen transfer of other sulfides into the corresponding sulfoxides was studied using a set of structurally diverse sulfides, in the presence of acid, in dichloromethane, at room temperature.

The results of oxygen transfer are shown in Table 3. It can be noted that the presence of sulfide leads to an oxygen transfer. The reaction yields and times were dependent on the nucleophilicity of the sulfides. The oxidation of sulfides by oxaziridine 9 is very efficient (Table 3). It leads to the complete conversion of sulfides to the corresponding sulfoxides in excellent yields; this conversion depends on the nucleophilicity of the different functional-group sulfides. Comparing the electron-withdrawing character of the groups on the phenyl ring, those with an electron-donating substituent showed good conversion of the sulfides (entry 1-5). The influence of steric effects could be observed. Yields of oxygen transfer reaction are slightly decreased (entries 6-9) when diphenyl, dibenzyl, benzyl phenyl, and aryl benzyl sulfides were used. Conversely, oxidation of dimethyl sulfide by oxaziridine 9 was fastest (entry 10).

Conclusions

The present study aimed to investigate the effect of introducing a p-chlorophenyl group in position 1 and two nitro groups on the dihydroisoquinoline skeleton. The results revealed that the oxaziridine became more electrophilic and that the reaction of oxygen transfer to sulfide became faster.

Considering the promising properties of these new products, the three oxaziridines and their corresponding nitrones, further studies are currently under way in our laboratories to investigate their biological activities.

Experimental Section

General. Chromatography: All reactions were monitored by TLC: Merck silica gel 60 (0.25mm). Visualization of the TLC was performed by UV light or stained with Dragendorff reagent. Solvents were purified by standard methods. High resolutions (HR) were obtained on a GC-HRMS Micromass Autospec (IE). 1 H and 13 C were recorded on a Bruker 400 and a Bruker AC 300, using CDCl3 as solvent. Data are reported as follows: chemical shifts, multiplicity (s = singlet, d = doublet, dd = doublet of doublets, t = triplet, dt = doublet triplet, m = multiplet), coupling constants (Hz), and integration. Melting points (mp) were determined under microscope with a Leitz Wetzlair device. All reagents and solvents were used as received. Imines, oxaziridines and nitrones were prepared according to the literature. Reference sulfoxide compounds were synthesized following procedures described in literature.

General procedure for preparation of imines 2-4. To cooled (0 °C) 95% sulfuric acid (10 ml) and under magnetic stirring, was added dropwise a benzonitrile (1.25eq). Then (500 mg, 3.33mmol) of tertiary alcohol 1,1-dimethyl-2-phenylethanol (1, commercial product) in cyclohexane (10 ml) was added to the solution. After return to room temperature, the resulting mixture was stirred under reflux for 2.5 hours. Then, the solution is cooled at room temperature and versed on ice-cold water under magnetic stirring. The solution is alkalized with ammonia. The organic layer was extracted with dichloromethane (100 ml), washed with a saturated aqueous NaCl solution, dried over sodium sulfate and filtered. The solvent was removed in vacuo and the crude material was then purified by chromatography (silicia gel) to afford the imine as pure compound. 3,3-Dimethyl-1-phenyl-3,4-dihydroisoquinoline (imine 2). Reaction of benzonitrile (429 mg, 1.25eq) according to the general procedure afforded 2 of (83%), isolated as a white solid, mp 69-71 °C; 1 H NMR (CDCl3, 400MHz): δ (ppm) 1.34 (s, 6H, 2-CH3), 2.86 (2H, CH2), 7.23-7.61 (m, 9H). 13 1-(4-Chlorophenyl)-3,3-dimethyl-3,4-dihydroisoquinoline (imine 3). Reaction of 4-chlorobenzonitrile (572mg, 4.16mmol) according to the general procedure afforded 3 (72%), isolated as a white solid, mp 112-115 °C; 1 H NMR (CDCl3, 300 MHz): δ (ppm) 1.27 (s, 6H, 2-CH3), 2.80 (2H, CH2), 7.16 (m, 1H), 7.39 (m, 2H), 7.39 (m, 2H), 2H). 13

8b-(4-Chloro-3-nitrophenyl)-3,3-dimethyl-7-nitro-4,8b-dihydro-3H-oxazirino[2,3-a]isoquinoline (oxaziridine 9).

Reaction of imine 5 (100 mg, 0.27 mmol) according to the general procedure afforded 9 (96%), isolated as a white solid, mp 221-223 °C; 1 General Procedure for preparation of nitrones 10-13 Methanesulfonic acid (50 mg, 0.52 mmol) was added to a solution of oxaziridine 6-9 in dichloromethane (6 ml) and the mixture was stirred at room temperature. A control of the reaction mixture by TLC (dichloromethane) indicated the disappearance of the oxaziridine. The solution was diluted with dichloromethane (25 ml) and washed with a solution of sodium bicarbonate. The organic phase was dried on sodium sulfate, filtered, and concentrated. 3,3-Dimethyl-1-phenyl-3,4-dihydroisoquinoline 2-oxide (nitrone 10). Reaction of oxaziridine 6 (50 mg, 0.19 mmol) according to the general procedure afforded 10 (62%), isolated as a yellow solid, mp 86-87 °C; 1

Oxygen transfer to sulfides with oxaziridine 9

A solution of the oxaziridine 9 (0.50 mmol) in methylene chloride (2 ml) was added to a solution of sulfide (0.50 mmol) and methanesulfonic acid (1.5 mmol) in methylene chloride (2 ml). The reaction mixture was stirred at room temperature until the disappearance of the active oxygen, as monitored by TLC (dichloromethane) and potassium iodide test, and then diluted with methylene chloride and washed with an aqueous sodium bicarbonate solution. © ARKAT USA, Inc

The organic phase was dried with Na2SO4 and concentrated in vacuo. The sulfoxides were purified by chromatography on silica gel using dichloromethane / methanol 95:5 as eluent. The sulfoxides obtained were compared and identified with with commercial samples. The various results obtained are presented in Table 3.

Characterisation data for sulfoxides

Methyl phenyl sulfoxide (entry 1) 36 : 1 H NMR (400 MHz, CDCl3) (ppm): 7.65-7.63 (m, 2H), 7.55-7.47 (m, 3H), 2.72 (s, 3H). 13 C NMR (100 MHz, CDCl3) (ppm): 145.8, 131.2, 129.5, 123.6, 44.1. p-Tolylmethyl sulfoxide (entry 2) 36 : 1 H NMR (400 MHz, CDCl3) (ppm): 7.54 (d, J= 8.0 Hz, 2H), 7.33 (d, J 8.0 Hz, 2H), 2.69 (s, 3H), 2.40 (s, 3H). 13 C NMR (100 MHz, CDCl3) 142.5, 141.6, 130.2, 130.1, 123.6, 44.1, 21.5. 4-Methoxyphenyl methyl sulfoxide (entry 3) 36 : 1 H NMR (400 MHz, CDCl3) (ppm): 7.57 (d, J 8.0 Hz, 2H), 7.01 (d, J 8.0 Hz, 2H), 3.82 (s, 3H), 2.67 (s, 3H). 13 C NMR (100 MHz, CDCl3) (ppm): 162.0, 136.6, 125.5, 114.9, 55.6, 44.0. p-Chlorophenyl methyl sulfoxide (entry 4) 36 : 1 H NMR (400 MHz, CDCl3) (ppm): 7.59 (d, J 8.0 Hz, 2H), 7.50 (d, J 8.0 Hz, 2H), 2.70 (s, 3H). 13 13 C NMR (75 MHz, CDCl3) δ (ppm): 130.85, 129.9, 128.5, 127.9, 57.0, 54.5, 27.0, 25.0, 24.9, 24.0. Dimethyl sulfoxide (entry 10) 41 : 1 H NMR (300 MHz, CDCl3) (ppm): 2.62 (s, 6H). 13 C NMR (75 MHz, CDCl3) (ppm): 40.8.

  :1 H NMR (300 MHz, CDCl3) (ppm): 3.89 (d, 4H), 7.21-7.40 (m, 10H).13 C NMR (100 MHz, CDCl3) (ppm): 130.1, 129.0, 128.0, 57.1. Benzyl phenyl sulfoxide (entry 8) 39 :1 H NMR (400 MHz, CDCl3) (ppm): 7.47-7.36 (m, 5H), 7.29-7.23 (m, 3H), 6.99 (d, J 8.0 Hz, 2H), 4.12 (d, J 16.0 Hz, 1H), 4.01 (d, J 12.0 Hz, 1H).13 C NMR (100 MHz, CDCl3) (ppm): 131.2, 130.4, 129.1, 128.9, 128.5, 128.3, 124.5. Benzyl cyclohexyl sulfoxide (entry 9) 40 : 1 H NMR (300 MHz, CDCl3) δ (ppm): 1.29 (m, 3H), 1.51 (m, 2H), 1.69 (m, 1H), 1.88 (m, 3H), 2.09 (m, 1H), 2.48 (m, 1H), 3.90 (m, 2H) 7.34 (m, 5 H).

Table 2 .

 2 Oxidation of methyl p-tolyl sulfide with oxaziridines 6-9 in the presence of methanesulfonic acid a

	Entry	MsOH	Oxaziridine	Time b	Yield of sulfoxide (%)(conversion) d
	1	3 eq	6	2 min	0
	2	3 eq	7	5 min	0
	3	3 eq	8	15 min	75 c (100)
	4	3 eq	9	5 min	80 c (100)

a Reaction performed at room temperature in CH2Cl2. b Reaction time followed by TLC. c Isolated product. d Determined by

1

H NMR spectroscopy in CDCl3

Table 3 .

 3 Oxidation of sulfides with oxaziridine 9 in the presence of methanesulfonicacid a .

	Entry	Sulfide	Time b	Yield of sulfoxide(%) (conversion) d
	1		5 min	93 c (100)
	2		5 min	91 c (100)
	3		10 min	90 c (100)
	4		10 min	80 c (100)
	5		10 min	83 c (100)
	6		20 min	72 c (100)
	7		20min	75 c (100)
	8		20 min	76 c (100)
	9		20 min	78 c (100)
	10		2 min	(100)

a Reaction performed at room temperature in CH2Cl2. b Determined by TLC. c Isolated product. d Determined by

1

H NMR spectroscopy in CDCl3.

  C NMR (CDCl3, 75MHz): δ27.64 (2C), 38.8, 54.5, 126.4, 127.9, 128.0, 128.1, 128.2, 128.8, 128.95, 130.7, 137.5, 139.3, 164.5. HRMS (ESI) [M + H] + calc. For C17H18N 236.1433; found 236.1424.

  C NMR (CDCl3, 100 MHz): δ 22.8, 28.5, 37.0, 57.0, 81.0, 123.35, 126.6, 128.5, 129.0 (2C), 129.3, 130.3, 135.4, 144.2, 148.0. HRMS (ESI) [M + H] + calc. For C17H17N2O3: 297.1233; found 297.1224.

  H NMR (CDCl3, 400 MHz): δ (ppm) 1.13 (s, 3H, CH3), 1.58 (s, 3H, CH3), 2.72 (d, J 16.0 Hz, 1H), 2.96 (d, J 16.0 Hz, 1H), 7.43 (d, J 8.3 Hz, 1H), 7.63 (dd, J 8.3, 2.2 Hz, 1H), 7.72 (d, J=8.3 Hz, 1H), 7.90 (d, J 2.2 Hz, 1H), 8.01 (d, J 2.2 Hz, 1H), 8.27 (dd, J 8.3, 2.2 Hz, 1H). 13 C NMR (CDCl3, 100 MHz): δ 22.75, 28.4, 37.2, 57.2, 79.55, 124.5, 124.9, 125.0, 128.3, 130.2, 130.95, 131.8, 132.4, 136.15, 142.9, 146.8, 147.9. HRMS (ESI) [M + H] + calc. For C17H15ClN3O5 376.0694; found 376.0678.

-(4-Chlorophenyl)-3,3-dimethyl-3,4-dihydroisoquinoline 2-oxide (nitrone 11).

  H NMR (CDCl3, 400 MHz): δ (ppm) 1.56 (s, 6H, 2-CH3), 3.22 (s, 2H, CH2), 6.86 (d, J 7.2 Hz, 1H), 7.22 (m, 2H), 7.31 (m, 1H), 7.50 (m, 5H). 13 C NMR (CDCl3, 100 MHz): δ 24.7, 41.8, 67.2, 126.7, 127.0, 127.65, 128.36, 128.9, 129.05, 130.08, 131.14, 131.9, 143.0. HRMS (ESI) [M + H] + calc. For C17H18NO 252.1382; found 252.1373 1Reaction of oxaziridine 7 (50 mg, 0.17 mmol) according to the general procedure afforded 11 (76%), isolated as a white solid, mp 125-127

	°C; 1 H NMR (CDCl3, 400 MHz): δ (ppm) 1.52 (s, 6H, 2-CH3), 3.18 (s, 2H, CH2), 6.83 (d, J 7.8 Hz, 1H), 7.18 (m, 1H),
	7.29 (m, 2H), 7.48 (m, 4H). 13 C NMR (CDCl3, 100 MHz): δ 24.6, 41.6, 67.2, 126.1, 127.1, 127.8, 128.5, 128.7,
	130.1, 130.4, 131.0, 131.7, 134.8, 140.2. HRMS (ESI) [M + Na] + calc. For C17H16ClNO Na 308.0812; found
	308.0796.
	3,3

-Dimethyl-1-(4-nitrophenyl)-3,4-dihydroisoquinoline 2-oxide (nitrone 12). Reaction

	of oxaziridine 8 (50
	mg, 0.16mmol) according to the general procedure afforded 12 (80%), isolated as a white solid, mp 156-158
	°C; 1 H NMR (CDCl3, 400 MHz): δ (ppm) 1.55 (s, 6H, 2-CH3), 3.22 (s, 2H, CH2), 6.76 (d, J 7.8 Hz, 1H), 7.21 (m, 1H),
	7.31 (m, 2H), 7.76 (d, J 8.2 Hz, 2H), 8.35 (d, J 8.2 Hz, 2H). 13 C NMR (CDCl3, 100 MHz): δ24.6, 41.6, 67.8, 123.45,
	125.7, 127.3, 128.0, 129.2, 130.2, 131.0, 131.6, 138.8, 139.6, 147.7. HRMS (ESI) [M + H] + calc. For C17H17N2O3
	297.1233; found 297.1224.
	1-(

4-Chloro-3-nitrophenyl)-3,3-dimethyl-7-nitro-3,4-dihydroisoquinoline 2-oxide (nitrone 13).

	Reaction of
	oxaziridine 9 (50 mg, 0.13mmol) according to the general procedure afforded 13 (59%), isolated as a yellow
	solid, mp 201-203 °C; 1 H NMR (CDCl3, 400 MHz): δ (ppm) 1.53 (s, 6H, 2-CH3), 3.32 (s, 2H, CH2), 7.50 (d, J 8.2 Hz,
	1H), 7.66 (d, J 2.2 Hz, 1H), 7.69-7.72 (m, 2H), 8.16 (dd, J 8.2, 2.2 Hz, 1H), 8.21 (d, J 2.2 Hz, 1H). 13 C NMR (CDCl3,
	100 MHz): δ 24.6, 41.3, 68.3, 119.6, 123.4, 127.9, 128.2, 129.2, 130.7, 132.2, 134.95, 136.4, 137.5, 147.5,
	147.9. HRMS (ESI) [M + Na] + calc. For C17H14ClN3O5 Na 398.0514; found 398.0509.

  C NMR (100 MHz, CDCl3) (ppm): 144.3, 137.3, 129.8, 125.1, 125.0, 44.1. p-Nitrophenyl methyl sulfoxide (entry 5) 37 : 1 H NMR (300 MHz, CDCl3, 278K, TMS) (ppm): 2.56 (s, 3H, Me), 7.84 (d, 2H) 8.34 (d, 2H). 13 C NMR (75 MHz, CDCl3, 278K, TMS) (ppm):47.7, 124.5, 149.3, 153.1. Diphenyl sulfoxide (entry 6) 36 : 1 H NMR (400 MHz, CDCl3) (ppm): 7.65-7.63 (m, 4H), 7.47-7.43 (m, 6H). 13 C NMR (100 MHz, CDCl3) (ppm): 145.7, 131.2, 129.4, 124.9. Dibenzyl sulfoxide (entry 7) 38

© ARKAT USA, Inc

Acknowledgements

This research was supported by the Ministry of High Education and Scientific Research, Tunisia.

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Supplementary Material

The Supplementary Material, copies of 1 H NMR and 13 C NMR spectra for compounds 2-6, 6a, 7, 7a, 8, 8a, 9, and 9a, associated with this article, can all be found in the online version of the text.