Zachary Arani

Drake Chapman

Chenxiao Wang
email: chenxiao@ou.edu

Le Gruenwald
email: ggruenwald@ou.edu

Laurent D'orazio
email: laurent.dorazio@univ-rennes1.fr

Taras Basiuk
email: taras.basiuk@ou.edu

A Scored Semantic Cache Replacement Strategy for Mobile Cloud Database Systems

Keywords: Big Data, Cloud Computing, Caching

Current mobile cloud database systems are widespread and require special considerations for mobile devices. Although many systems rely on numerous metrics for use and optimization, few systems leverage metrics for decisional cache replacement on the mobile device. In this paper we introduce the Lowest Scored Replacement (LSR) policy-a novel cache replacement policy based on a predefined score which leverages contextual mobile data and user preferences for decisional replacement. We show an implementation of the policy using our previously proposed MOCCAD-Cache as our decisional semantic cache and our Normalized Weighted Sum Algorithm (NWSA) as a score basis. Our score normalization is based on the factors of query response time, energy spent on mobile device, and monetary cost to be paid to a cloud provider. We then demonstrate a relevant scenario for LSR, where it excels in comparison to the Least Recently Used (LRU) and Least Frequently Used (LFU) cache replacement policies.

Introduction

Since a cache has limited space, it is important to use replacement policies which keep relevant data on a mobile device. In a mobile cloud database system, querying the cloud can often be an expensive operation in regards to time, money paid to a cloud provider, and mobile device energy. For this reason, leveraging a cache grants large boosts in efficiency. The rudimentary Least Recently Used (LRU) policy-which discards the least recently accessed entry when filled-is often implemented in caches. The similar Least Frequently Used (LFU) policy-which replaces the least frequently used entry when full-is also commonly implemented; however, LRU and LFU are not always the most efficient policies within the context of a relational database system [START_REF] Chou | An evaluation of buffer management strategies for relational database systems[END_REF][START_REF] Li | Ccf-lru: a new buffer replacement algorithm for flash memory[END_REF][START_REF] Sacco | Buffer management in relational database systems[END_REF][START_REF] Stonebraker | Operating system support for database management[END_REF]. Instead, many Database Management Systems (DBMS) implement specific replacement policies that cater to the system's needs. This paper seeks to describe a cache replacement policy for mobile cloud database systems that utilizes decisional semantic caching. We propose the Lowest Scored Replacement policy (LSR), which takes cache relevancy and mobile constraints into account while maintaining a LRU-like overhead. LSR partitions cache events into point scoring categories and utilizes a predefined score based on decisional semantic caching and the Normalized Weighted Sum Algorithm. LSR defines semantic relevancy within the cache while also taking into account user preferences on saving time, energy on mobile device, and cost paid to cloud providers. We then show an implementation of LSR using our existing decisional semantic cache system and demonstrate a relevant scenario for the algorithm. We find from our experiment that there exist scenarios where LSR significantly outperforms the common LRU and LFU cache replacement policies in the mobile cloud database environment.

Related Work

Device status and metadata is imperative in mobile cloud database decision making. Metrics such as current battery life, location, and connectivity quality may be leveraged to contextualize computational tasks. Mobile devices are, by their very nature, constrained through their short-term battery life and variable connection to wireless networks. Several replacement policies have been developed to address these issues [START_REF] Barbará | Sleepers and workaholics: Caching strategies in mobile environments (extended version)[END_REF]. These policies make use of metrics such as location, battery life, and on-device data size [START_REF] Chand | Cooperative caching strategy in mobile ad hoc networks based on clusters[END_REF][START_REF] Li | Energy-efficient cache replacement policies for cooperative caching in mobile ad hoc network[END_REF][START_REF] Yin | Supporting cooperative caching in ad hoc networks[END_REF]. Other caching systems, such as semantic caching [START_REF] Ren | Semantic caching and query processing[END_REF], have also been used to address constraints in a mobile cloud database environment. In our previous work we developed the decisional semantic MOCCAD-Cache [START_REF] Perrin | Time-, energy-, and monetary cost-aware cache design for a mobile-cloud database system[END_REF] as well as the Normalized Weighted Sum Algorithm (NWSA) [START_REF] Helff | Weighted sum model for multi-objective query optimization for mobile-cloud database environments[END_REF] to better meet constraints on a mobile device. However, our previous work did not propose any solution for a cache replacement policy.

One cache replacement approach that bears some similarities to ours is frequency-based. This method considers each cache entry's access frequency when performing decisional replacement. Examples are found in [START_REF] Leong | On adaptive caching in mobile databases[END_REF] where three different methods are proposed-each with its own contextual merits. These policies-The mean scheme, The window scheme, and The exponentially weighted moving average scheme-bear some resemblance to ours since they take into account how recently a cache entry was accessed; however, these cache replacement strategies do not take into account semantic information or mobile constraints such as the device's battery life.

There exist other policies which take data size and cloud retrieval cost into account. One example is the SAIU (Stretch Access-rate Inverse Update-frequency) replacement policy proposed in [START_REF] Xu | Saiu: An efficient cache replacement policy for wireless on-demand broadcasts[END_REF], as well as a modified version in [START_REF] Xu | Performance evaluation of an optimal cache replacement policy for wireless data dissemination[END_REF]. The SAIU defines a gain function based on access rate, update frequency, data size, data retrieval time, and (in the latter paper) consistency. The policy then uses this weight to determine replacement. A version proposed in [START_REF] Yin | A generalized target-driven cache replacement policy for mobile environments[END_REF] uses a more generalized cost function. By taking the various costs of each query into account, these methods for cache replacement share some similarity with ours; however, these methods do not factor the benefits of semantic caching into their replacement process. In our mobile cloud database environment, a user sends queries and constraints (in the form of a weight profile) from the mobile device for execution. User constraints are defined by their interest in conserving time, mobile device energy, or monetary cost paid to their cloud provider. Our system decides how to best execute queries with respect to user constraints: either through the cloud or from a local cache if possible. The user's query and weight profile is sent through some form of infrastructure (the data owner) to cloud services for query execution estimations. The data owner then uses these estimations to decisionally optimize query execution on some combination of the mobile device and the cloud.

MOCCAD-Cache

Our previously proposed MOCCAD-Cache introduces the concept of decisional semantic caching [START_REF] Perrin | Time-, energy-, and monetary cost-aware cache design for a mobile-cloud database system[END_REF] to solve issues with semantic caching in mobile contexts.

In a semantic caching system, both data and the semantic description of that data are provided to the cache [START_REF] Ren | Semantic caching and query processing[END_REF]. For instance, the result of a query will be stored along with what relations, attributes, and predicates the query consisted of. This means new queries can be compared against semantic descriptions of stored queries before execution.

Many systems only detect a cache hit event if both the input query and the cache query match exactly. Semantic caching instead allows recognition of overlaps in semantic descriptions. If an input query has overlap in the relations, attributes, and predicates of a cached query, it will be recognized as either a partial hit (some data in the cache) or an extended hit (all data in cache). If the query semantics match exactly or do not match at all, a cache hit or miss is detected. If the parser detects some semantic overlaps, a query trimmer is used to create two new queries for execution. For example, if only part of the input query is stored in the cache-a partial hit event-the query trimmer will transform the input query into a mobile device query (probe query) and a cloud query (remainder query) for execution. If the input query's semantic description is fully overlapped with cached semantics, it is recognized as an extended hit event; the query is then executed on the mobile device using cached data. Semantic caching is useful in many cases, especially on a device with limitations such as a mobile phone. However, there are some instances where local query trimming and execution is considerably worse than a simple cloud execution. After trimming the query, the MOCCAD-Cache runs estimations to decide whether to execute the query on the cloud or mobile device-if possible. Despite needing to go through an entirely new estimation phase, this system can improve query processing time (albeit with the general caveat of increased monetary cost).

Normalized Weighted Sum Algorithm

MOCCAD-Cache may outperform semantic caching in terms of time, but there are many scenarios where time is not the only imperative metric. Our later proposed Normalized Weighted Sum Algorithm (NWSA) addresses this issue by taking into account arbitrary metrics and normalizing them to calculate a score [START_REF] Helff | Weighted sum model for multi-objective query optimization for mobile-cloud database environments[END_REF]. The NWSA calculates a score based in part on the user's interest in saving time, energy, or monetary cost3 . These constraints are evaluated against query execution plans (QEPs) to decide a QEP that best respects the user's desires.

QEP1 : {M = $0.080; T = 0.5s; E = 0.012mA} QEP2 : {M = $0.050; T = 3.0s; E = 0.300mA} QEP3 : {M = $0.055; T = 0.6s; E = 0.013mA} The MOCCAD-Cache estimates the efficiency of executing a query on the cloud versus the mobile device. If the query is performed on the cloud, there are several QEPs that can be executed-each with its own costs. Some example QEPs for a given query are shown in Figure 2. The NWSA takes each QEP and scores how it respects user constraints. The lowest scoring QEP signifies the most efficient execution respecting user constraints. For instance, a user giving priority to time and monetary cost would result in QEP 3 from Figure 2 being executed, as it respects those two constraints the most.

The methodology of QEP scoring is shown in Figure 3. The NWSA looks at each QEP and scores it based on three factors. a ij is the i th QEP's estimated cost for the j th constraint (money, time, energy). m j is the maximum accepted value for the jth constraint. Any QEP with a constraint value higher than m j is not considered for best score. Figure 4 describes w j , a composite normalized weight factor derived from the user constraints (uw) as well as a device's environmental factors such as battery life or network connectivity (ew).

In summary, the MOCCAD-Cache with the NWSA dictates the structure of cache entries and how to handle new cache events, but it does not detail any methods of cache replacement and may assume an infinite cache size. In section 4 we propose a novel replacement policy leveraging data calculated by the MOCCAD-Cache using NWSA to efficiently replace entries while respecting constraints.

The Lowest Scored Replacement (LSR) Policy

This section explores our proposed cache replacement policy and its implementation. The Lowest Scored Replacement Policy (LSR) utilizes the QEP score calculated by the NWSA as well as cache events defined by the MOCCAD-Cache. A modified QEP score along with MOCCAD-Cache cache events score each cache entry for decisional replacement.

LSR Score

The initial LSR score of a cache entry is based on the QEP score for each query. Higher QEP scores indicate that a given query is more difficult to retrieve from the cloud, and therefore may be more valuable to keep in the cache. For the sake of precision and arithmetic simplicity, we keep baseline LSR scores close to the magnitude of 1. This requires the given QEP score to be multiplied by a scaling factor before being considered as the LSR score.

LSR Score = QEP Score * ScaleF actor

Scoring System

After being initialized, an entry's score is updated by cache events. The most desirable cache event-a cache hit-is rewarded a FULL-POINT whereas the least desirable outcome is given a ZERO-POINT score. Scores for cache events involving query trimming fall between these two extremes. The extended hit cache event (all relevant data in cache) is rewarded a HALF-POINT, as this event generally does not involve accessing the cloud. The partial hit cache event (some relevant data in cache) is rewarded a QUARTER-POINT, since some local data is often more desirable than a cache miss.

Since LSR rewards cache entries based on accessed data, it is worth noting its similarity to LFU. Unlike LFU, LSR takes into account the constraints of the mobile device (the QEP score) along with the query's semantic utility in the cache (MOCCAD-Cache events). This functionality is crucial for mobile cloud computing, where devices are constrained by limited resources and user requirements. In short, LSR inherently respects the constraints of mobile computing, unlike LFU.

Cache Implementation

The cache is implemented as a minimum priority queue. Entries are initialized with a given score and are updated as cache events occur; the cache entry score dictates the priority within the queue. When an entry needs to be removed, the lowest scoring entry is replaced.

Experimentation and Results

In this section we discuss our experiments-and the methodology behind themas well as their results. We have conducted an experiment to compare the performance of our proposed algorithm, LSR, against the ubiquitous LRU and LFU policies. We compare these replacement policies in terms of the monetary cost, query response time, and energy consumption.

Experimentation Hardware and Software

In order to simulate a cloud environment, a single node was set up using the Hadoop framework and data warehouse infrastructure. Apache Hive was used as the database system along with MySql for storing metadata. The node ran the Arch Linux operating system and featured an Intel Core i7-8750H CPU running at 2.20GHz as well as 16GB of RAM and a 512 GB Samsung 970 EVO NVMe PCIe M.2-2280 SSD. A RESTful java web servlet running on Apache Tomcat 8.5 was used to access the cloud infrastructure from mobile devices. This servlet is able to retrieve tuples, query cost estimations, and relational metadata from the hive server. 4 The mobile device ran a development branch of the Java based MOCCAD-Cache Android prototype that features an LSR implementation and other small improvements. 5The mobile device used for testing was a LG V10 Android device 6 , which featured a hexa-core Qualcomm MSM8992 Snapdragon 808, 2 GB of RAM, and a battery capacity of 3000 mAh. Table 1 summarizes the experiment parameters.

Example Scenario

In this section, we outline a relevant scenario for LSR. We envision a business worker using a mobile device to access company information while away from the office-where productivity may be affected by mobile constraints. The worker spends time focusing on one business context before switching to another. They may execute several queries all related to one product, customer, or region before suddenly switching to a different one. This means that variations of a complex query will be executed several times in sequence before completely unrelated queries are executed. The worker may then return to the original context they were working in later.

In this scenario, there is a full cache with an entry that is semantically useful but is difficult to retrieve from the cloud. If the entry has not been used for a short period (a context switch), LRU and LFU will remove it. These policies remove the useful entry because they do not respect semantic utility or mobile constraints but instead only respect recent accesses. If a query from the original context is then executed, it will be very expensive in terms of time, money, and energy for the LRU and LFU users. Unlike LRU or LFU, LSR will respect the constraints of the mobile cloud database environment and retain the entry for continued use.

Experimentation Methodology

In order to simulate the database environment of a business worker, we generated a 2GB database based on the TPC-H model, which is structured to simulate business data. 7 Before running the experiment, a series of ten warmup queries were executed to fill the cache with data prior to the experiment. These queries simulate previous contexts unrelated to the experimental ones in order to encourage cache replacement. We then ran twenty queries for this experiment, starting with a costly query:

SELECT DISTINCT l shipdate FROM lineitem WHERE l linestatus = 'O';

After this, we ran several semantic hits (extended and partial) in the same context before switching to unrelated queries of a different context. After several queries are run in this context, the original query and semantic hits were then run again near the end of the workload. The experiment measured total execution time, energy spent on mobile device, and estimated cost paid to the cloud provider. The experiment was run three times, with the results being averaged. The MOCCAD-Cache prototype's user preference weights for money, energy, and time were all set to an equal one-third amount.

Results

Figures 5,6, and 7 detail the results of our experimentation. As we expected, LSR significantly outperformed LRU and LFU in the business scenario. LSR performed over twice as fast, cheap, and energy efficient when compared to LRU. LFU managed to be somewhat competitive in cost, but still was eclipsed by LSR in speed and energy efficiency. In terms of all three metrics, LSR was clearly cheaper, faster, and more efficient in the mobile cloud database environment. Our policy used valuable metrics to recognize the utility of data as well as respect the constraints of the mobile device. Even though LFU and LRU may have only needed to run a handful of additional queries on the cloud-the re-execution of large or costly queries will not respect the constraints of a mobile device. These costs may be greatly exacerbated depending on the device's particular context. LSR, by comparison, leveraged user constraints and decisional semantic cache events to intelligently retain valuable data locally.

Conclusions

Mobile cloud database systems have become ubiquitous in recent memory. Several advancements have been made in the field, such as our previously proposed decisional semantic MOCCAD-Cache as well as the Normalized Weighted Sum Algorithm. LSR attempts to improve on existing cache replacement strategies in mobile cloud database systems by accounting for mobile device constraints and semantic utility. When combined with the MOCCAD-Cache and the Normalized Weighted Sum Algorithm, there exist scenarios where LSR significantly outperforms LFU and LRU in a mobile cloud database environment.

Although LSR's initial experiments are promising, future work is needed to better determine its use and applicability in the mobile cloud database setting. Experiments could be run to see how LSR compares against other common non-LRU based cache replacement policies. Experiments that vary the size of the cache would prove insightful on how useful LSR would be in other caching environments. On top of this, varying user preference weights for time, money, and energy for NWSA scoring may provide interesting results. Additional workloads and scenarios must be analyzed to investigate where LSR is most applicable to real world applications. Finally, implementing the LSR policy in non-mobile cloud database systems may also yield promising results in testing the policy's utility in other areas.

Fig. 1 .

 1 Fig. 1. Our Mobile Cloud Database Environment

Figure 1

 1 Figure 1 details our system architecture and illustrates the possible workflows for query execution. In our mobile cloud database environment, a user sends queries and constraints (in the form of a weight profile) from the mobile device for execution. User constraints are defined by their interest in conserving time, mobile device energy, or monetary cost paid to their cloud provider. Our system decides how to best execute queries with respect to user constraints: either through the cloud or from a local cache if possible. The user's query and weight profile is sent through some form of infrastructure (the data owner) to cloud services for query execution estimations. The data owner then uses these estimations to decisionally optimize query execution on some combination of the mobile device and the cloud.

Fig. 2 .Fig. 3 .Fig. 4 .

 234 Fig. 2. Example Query Execution Plans (QEPs) for a Sample Query

7Fig. 5 .

 5 Fig. 5. Scenario Monetary Cost Performance

Table 1 .

 1 Summary of Static Experiment Parameters

	Static Parameters	Value	Reference
	LG V10 Memory	2GB	Kernel
	LG V10 SoC CPU Active Mode	1.728 GHz	Kernel
	Frequency
	LG V10 SoC CPU Active Mode	157.44 mA	Power profile
	Current
	LG V10 SoC CPU Idle Mode Fre-	0	Kernel
	quency
	LG V10 SoC CPU Idle Mode Cur-	16.4	Power profile
	rent
	LG V10 SoC Wi-FI Network Low	0.1 mA	Power profile
	Current
	LG V10 SoC Wi-FI Network High	60 mA	Power profile
	Current
	LG V10 Battery Capacity	3000 mAh	Power profile
	LG V10 Average Bandwidth Up	8.47 Mbps	Google
			Speedtest
	LG V10 Average Bandwidth Down 12.9 Mbps	Google
			Speedtest
	Cloud Node Memory	16 GB	Kernel
	Cloud CPU	Intel i7-8750H @ 2.20	Kernel
		GHz
	Cloud Node Disk	512 GB Samsung 970	Kernel
		EVO NVMe PCIe M.2-
		2280 SSD
	Cloud Node Average Bandwidth	3.28 Mbps	Google
	Up		Speedtest
	Cloud Node Average Bandwidth	28.0 Mbps	Google
	Down		Speedtest
	Query Cache Maximum Size	100 MB
	Query Cache Maximum Entries	10
	Query Set Size	20 queries
	Dataset	TPC-H Benchmark	TPC
	Number of Relations	8	TPC
	Database Size	2 GB
	ScaleF actor	10 12	QEP Score
			Magnitude

Each parameter is given on a scale from 0 to 1, where the sum of all parameters must total 1

The source code for the cloud web service can be found at https://github.com/ZachArani/CloudWebService

The source code of MOCCAD-Cache and the NWSA can be found at http://cs.ou.edu/ database/MOCCAD/index.php. this experiment was conducted on the 'dev' branch.

Acknowledgments

This work is partially supported by the National Science Foundation Award No. 1349285.


Ruqaya Buhaibeh

Carine Duhayon

Dmitry A Valyaev

Jean-Baptiste Sortais

Yves Canac

Cationic PCP and PCN NHC Core Pincer-Type Mn(I) Complexes: From Synthesis to Catalysis

The coordination chemistry of NHC core pincer-type PCP and PCN ligands with Mn(I) center was systematically investigated. The reaction of [Mn(CO)5Br] with free carbenes, conveniently prepared from the corresponding imidazolium salts and a strong base, lead to the initial formation of bidentate fac-[MnBr(CO)3(κ 2 P,C,L)] complexes bearing a pending phosphine or pyridine donor extremity (L), which upon bromide abstraction, afford cationic [Mn(CO)3(κ 3 P,C,L)](OTf) derivatives exhibiting a meridional or a facial coordinating geometry of tridentate NHC core ligand depending on its relative flexibility. All bi-and tridentate Mn(I) complexes were characterized by X-ray diffraction analysis. The impact of the tridentate ligand structure on catalytic performance was illustrated in the Mn-catalyzed hydrogenation of acetophenone revealing fac-[Mn(CO)3(κ 3 P,C,N)](OTf) based on a 5,6-membered metallacyclic architecture to be the most active, thus evidencing the role of the pyridine arm lability in the catalytic cycle.

INTRODUCTION

Following the early generation of phosphines, N-heterocyclic carbenes (NHCs) have attracted much attention, leading to remarkable advances in different areas, such as organometallic chemistry, functional materials, and homogeneous catalysis. 1 For catalytic purposes, it is today generally accepted that NHCs are not just phosphine mimics, but also surpass their phosphine congeners in terms of activity and application scope. 2 Based on this knowledge, considerable efforts have been provided to introduce structural diversity, and a large variety of polydentate NHC ligands 3 bearing coordinating atoms of different nature (N, P, O, C) have been prepared improving the efficiency and selectivity of metal complexation. In particular, NHC-based ligands exhibiting L-type coordinating extremities such as pyridine 4 and phosphine 5 donors, or X-type such as phenolate, 6 and phosphonium ylide 7 donors were notably devised in the bi-and in the tridentate series extending naturally the scope of accessible metal fragments.

For catalytic applications, 8 especially in the field of hydrogenation, 9 Mn-based complexes have recently been the subject of intensive research, and many platforms have been developed over last five years. Pincer-type Mn(I) complexes based on a PNP, 10 PNN, 11 NNN, 12 or CNP 13 skeleton were reported as valuable catalysts for hydrogenation-type reactions. However, less sophisticated complexes featuring bidentate PN, 14 PP, 15 NN, 16 CN, 17 or CP 18 scaffolds were also found to efficiently catalyze such transformations. In this competitive area of catalysis, NHC-based ligands have also demonstrated their high potential as illustrated very recently in the tridentate series for the cationic [(CNP)Mn(CO)3] + complex exhibiting a NHC-aminephosphine ligand, 13 and in the bidentate series for the neutral [(CN)Mn(CO)3Br] and [(CP)Mn(CO)3Br] complexes based on NHC-amine 17 and NHC-phosphine 18 ligands, respectively.

Based on the general structure of the bidentate NHCphosphine ligand A recently described in our group, we wondered about the possible impact on catalytic activity of changing the 'spectator' N-mesityl substituent by a donor group capable of interacting with the metal center. In this contribution, we turned out attention to the preparation, the coordinating properties and the catalytic activity of the novel NHC core tridentate ligands of type B bearing phosphine and pyridine donor arms (Scheme 1). In a larger context, this comparative study also aimed to assess whether the improvement in catalytic performance necessarily involved the design of more complex architectures, as are pincer systems with respect to their bidentate versions. 18 and related tridentate NHCcore systems B targeted in this study.

Scheme 1. Representation of recently reported bidentate NHC-phosphine ligand A,

RESULTS AND DISCUSSION

Synthesis and NMR characterization of NHC-based preligands. The first representative ligand B-1 of the family was prepared from the N-phosphine oxide substituted imidazole 2 isolated in 70% yield by treating 1H-imidazole 1 with 1.0 equiv. of Ph2P(O)CH2OTs in the presence of K2CO3 in DMSO at 90 °C (Scheme 2, left). The second phosphine oxide arm was then introduced by the alkylation of imidazole 2 with the same tosylate precursor in toluene at 130 °C, allowing the bis(N-phosphine oxide)imidazolium salt [3](OTs) to be isolated in 87% yield. The reduction of the latter under classic conditions (excess of HSiCl3 in chlorobenzene at 80°C) 5b,18 led to the target bis(N-Scheme 2. Preparation of tridentate PCP and PCN pre-ligands [4](OTs), [7](OTs) and [10](OTs). phosphino)imidazolium salt [4](OTs) in ca. 80% yield. The formation yield of this product can be improved to 89% by organocatalytic reduction approach 19 by heating [3](OTs) in toluene at 110 °C with an excess of PhSiH3 in the presence of bis(4nitrophenyl)phosphate.

The PCN ligands B-2 (Scheme 2, middle) and B-3 (Scheme 2, right) were prepared from readily available N-pyridyl-5 20 and N-pyridylmethyl 8 21 substituted imidazoles following the same two-step strategy. In the first step, the imidazolium salts [6](OTs) and [9](OTs) featuring phosphine oxide arms were prepared in 90 and 87% yield, respectively upon solvent-free quaternization of the corresponding imidazoles with Ph2P(O)CH2OTs. In both cases, the transformation of phosphine oxide moieties into phosphines using strongly reducing agent HSiCl3 was found to be non-selective, resulting in partial reduction of the pyridine nucleus. Gratifyingly, the application of the alternative organocatalytic protocol 19 enabled the formation of the target pre-ligands [7](OTs) and [10](OTs) isolated in 89 and 86% yield, respectively.

The identity of all pre-ligands was mainly established on the basis of their characteristic 31 P, 1 H and 13 C NMR resonances (Table 1). For imidazolium salts [3](OTs), [6](OTs), and [9](OTs) exhibiting a phosphine oxide moiety, the 31 P NMR spectrum displayed a single signal at P 26.5-27.2 ppm in the typical range for such P(V)-based derivatives. As expected, the 31 P NMR singlet of N-(phosphino)imidazolium salts [4](OTs), [7](OTs), and [10](OTs) appeared at higher field at P -11.1 to -12.4 ppm in agreement with the presence of P(III) donor extremities of alkyl(diphenyl)phosphine nature. The cationic character of these salts was confirmed by 1 H and 13 C NMR spectroscopy by the characteristic low field signals of the CH imidazolium fragment at ppm. 138.6 138.1 135.6 136.0 138.5 137.5

Synthesis and spectroscopic characterization of NHCbased Mn(I) complexes. The complexation of pre-ligands [4](OTs), [7](OTs), and [10](OTs) was envisioned following a strategy developed recently in the case of the N-mesityl substituted NHC-phosphine A (Scheme 1). 18 Indeed, complexes 11, 13-14, and 16 were thus readily obtained from the corresponding precursors through the sequential addition of equimolar quantities of KHMDS and [Mn(CO)5Br] in 71, 80, and 60% isolated yield, respectively (Scheme 3). Scheme 3. Syntheses of cationic NHC-core tridentate Mn(I) complexes [12](OTf), [15](OTf), and [17](OTf) from the corresponding PCP [4](OTs) and PCN ligand precursors [7](OTs) and [10](OTs).

While only bidentate coordination was observed in all formed neutral Mn(I) complexes, a notable difference in the coordination mode was observed between the two ligands B-2 and B-3 bearing a pyridine extremity. From [7](OTs), in which the pyridine is directly connected to the imidazole core, two isomeric complexes 13 and 14 in a ca. 1:3 ratio were evidenced due to the possible formation of two thermodynamically favored five-membered metallacycles upon coordination of the phosphine or the pyridine arms. By contrast in the case of [10](OTs), only the bidentate complex 16 resulting from the concomitant coordination of NHC and PPh2 donor units was observed, the coordination of pyridine would indeed have led to a less stable six-membered metallacycle.

With the aim of synthetizing new NHC core tridentate Mn(I) systems, the access to both neutral [(L3)Mn(CO)2Br] and cationic [(L3)Mn(CO)3] + Br -complexes was then considered. Facing the non-selective formation of [(L3)Mn(CO)2Br] complexes upon CO dissociation under photochemical and thermal activation of stable bidentate [(κ 2 P,C,L)Mn(CO)3Br] species, the latter were treated by a stoichiometric amount of AgOTf in CH2Cl2 to induce the bromide abstraction and thus force the coordination of a pendant donor arm. Under these conditions, airstable cationic tridentate complexes [12](OTf), [15](OTf), and [17](OTf) were easily obtained as single isomers in 88, 76, and 96% yield, respectively. These compounds belong to rare examples of NHC-containing manganese pincer-type complexes 13,22,23 and constitute the first prototypes based on NHC core L3-type ligand scaffolds.

The most pertinent spectroscopic data for the Mn(I) NHC complexes are presented in Table 2. The formation of Mn(I) NHC complexes was clearly indicated by 1 H and 13 C NMR spectroscopy showing the disappearance of the C-H imidazolium signals of pre-ligands [4](OTs), [7](OTs), and [10](OTs). Regardless of their coordination mode, in the 13 C NMR spectra, the N2C-Mn carbon atoms of NHC core complexes (N 2 C 195.6-206.5 ppm) were typically found to be strongly deshielded with proper multiplicity with respect to the N2CH carbon atoms of corresponding precursors . The coordination of the N-substituted NHC-phosphine moiety was also apparent from the downfield shift of the 31 P NMR resonances, ranging from δP -(11.1-12.4) ppm in the preligands to P 71.0-71.8 ppm in the bidentate complexes and P 89.6-97.4 ppm in their tridentate analogues. Solution IR spectra of all bidentate NHC Mn(I) complexes exhibited three strong CO bands consistent with the presence of three CO ligands in a facial arrangement. The small differences observed between these frequency values seem to indicate that the three ligands of interest have similar electronic properties. In the tridentate series, complexes [12](OTf), [15](OTf) and [17](OTf) featured three CO bands with different relative intensity (Table 2) suggesting two distinct CO ligand arrangements.

In complement to these IR frequency values, 13 C NMR data revealed for complexes [12](OTf) and [15] ) for [17](OTf), indicating for the latter a lower molecular symmetry than for the two former complexes and suggesting that the NHC core backbone is a priori coordinated to the metal center in a meridional fashion within complexes [12](OTf) and [15](OTf), and adopts rather a tripodal coordination mode in [17](OTf).

X-ray diffraction structural studies of bidentate and tridentate NHC-based Mn(I) complexes. Single-crystal X-ray diffraction studies allowed us to establish the solid-state structures of the imidazolium salt [4](OTs) (Figure S1 in the Supporting Information), neutral bidentate Mn(I) complexes 13, 14 and 16 (Figure 1, upper line), and their cationic tridentate congeners [12](OTf), [15](OTf) and [17](OTf) (Figure 1, lower line). The most important metrical data are presented in Table 3. In all complexes, the hexacoordinate Mn(I) atom resides in a distorted octahedral environment. As anticipated by NMR and IR spectroscopy, three carbonyl co-ligands adopt a facial arrangement in all bidentate representatives. In the tridentate series, complexes [12](OTf) and [15](OTf) can be regarded as real pincers exhibiting the meridional coordination of the NHC core ligand with two CO co-ligands positioned in trans with respect to each other, while in [17](OTf) the PCN backbone acts as a tripodal ligand with the three CO co-ligands located cis to each other. Though such fac-arrangement is less common for [Mn(CO)3(L3)] + complexes, several examples based on pincertype PNP, 24 CNP, 13 NNN, 12,25 NNS 26 and NSN 27 ligands have been recently reported.

In the pincer systems, the two coordinating heteroatoms are positioned in pseudo-trans position with respect to the metal center ( [12](OTf): P1-Mn1-P2 = 160.148( 14); [15](OTf): P1-Mn1-N3 = 153.76(4)°) as opposed to the tripodal complex [17](OTf) where the related coordination angle is much more acute (P1-Mn1-N3 = 91.92(3)°). As generally observed in mer-Mn(I) complexes, the C-O distances in the mutually trans CO ligands are shorter ( [12](OTf): 1.1407 (17), 1.1383(17) Å;

[15](OTf): 1.139(2), 1.138(2) Å) than in the CO trans to the ligand, in this case the NHC core ( [12](OTf): 1.1423(16) Å;

[15](OTf): 1.151(2) Å). 28 The PCP and PCN pincer structures [12](OTf) and [15](OTf) are defined by the presence of two fused 5-membered metallacycles with the PCP backbone in the former symmetrically linked to Mn through two quasi-equal P-Mn bonds (2.2627(3) [17](OTf), lower line) Mn(I) NHC complexes with thermal ellipsoids drawn at the 30% probability level. The hydrogen atoms are omitted for clarity.

Table 3. Selected bond lengths (Å) and bond angles (°) for bidentate and tridentate Mn(I) NHC complexes.

observed in [17](OTf) can be rationalized by the presence of a longer lateral chain which offers more flexibility accommodating the formation of a six-membered metallacycle upon pyridine coordination. 29 As general trend, the Mn-NHC bond distances are significantly shortened in the tridentate systems compared to their bidentate precursors, a difference that may be attributed to the more constrained geometries and the cationic nature of the pincer-type complexes. It is noteworthy, that the Mncarbene bond in pincer complex [15](OTf) (1.9360(16) Å) is significantly shorter than that observed in binuclear [Mn2(CO)7(PCN)] complex bearing structurally close tridentate PCN ligand in the bridging μ-κ 2 C,N-M;κ 1 P-M-coordination mode (1.9700(17) Å) 30 and indeed represents one of the shortest distance known to date for manganese imidazol-2-ylidene complexes. 31 Since a similar trend was previously observed for re-lated Ni(II) complex, 4d it may be assumed that the rigid character of such PCN ligands forming two five-membered metallacycles is particularly favorable to strengthen metal-NHC bonding.

Catalytic investigations. Based on the recent observation that a Mn(I) complex of the bidentate NHC-phosphine ligand A behaves as one of the most efficient Mn-based catalytic system for the hydrogenation of ketones, 18 this transformation was naturally selected to evaluate the influence of an additional coordinating arm. For such comparative study, three pincer-type complexes [12](OTf), [15](OTf), and [17](OTf) differing only by the nature of one donor end were considered. The catalytic tests were performed under H2 pressure (50 bar) in t-AmOH at 60 or 100 °C, and in the presence of 10 mol% of t-BuOK (Table 4). Gratifyingly at 100 °C, in the presence of 1.0 mol% of [17](OTf), acetophenone was fully reduced to 1-phenylethanol (entry 9). The catalytic charge could be decreased to 0. at the same temperature keeping a good conversion of 80% (entry 10). At 60 °C, the alcohol was produced in lower yields with a conversion of 30 and 20% by using 1.0 and 0.5 mol% of [17](OTf), respectively (entries 11-12). Noteworthy, no reaction took place in the absence of base. The two other selected complexes were found to be significantly less active in this process. For instance, at 100 °C, with a catalytic charge of 1.0 mol% of pre-catalysts [12](OTf) and [15](OTf), the acetophenone was only converted into the corresponding alcohol in 27 and 39% yields, respectively (entries 1 and 5). The superiority of fac-complex [17](OTf) was tentatively attributed to the presence of a six-membered metallacycle resulting in greater lability of the pyridine arm and thus allowing the release of a vacant site during the catalytic cycle. 13 The lability of a donor extremity was also supported in other systems by the catalytic activities of the bidentate complexes 11, 14 and 16 which were found to be very close to those obtained with their corresponding tridentate forms [12](OTf), [15](OTf), and [17](OTf) (entries [13][START_REF] Van Putten | Non-pincer-type manganese complexes as efficient catalysts for the hydrogenation of esters[END_REF][15]. These results suggest that the same type of catalytic active species is certainly involved in both series. Noteworthy, the performance of complex [17](OTf) remains lower than that of the parent complex based on the bidentate NHC-phosphine ligand A, 18 showing that the development of more elaborate structures is not always a prerequisite to reach higher activities in the field of catalysis. a -Procedure: an autoclave was charged with a pre-catalyst, acetophenone (1.0 mmol), t-BuOK (10 mol%) in t-AmOH (2 mL) under H2 (50 bar) at 60 or 100 °C. b -Conversions determined by GC and 1 H NMR, isolated yield in parenthesis.

CONCLUSION

A family of cationic NHC-phosphine Mn(I) pincer-type complexes [Mn(CO)3(κ 3 P,C,L])(OTf) with a variable third donor extremity were efficiently prepared from the readily available imidazolium salts by a sequence of free NHCs coordination to [Mn(CO)5Br] and bromide abstraction in the resulting bidentate complexes fac-[MnBr(CO)3(κ 2 P,C,L)]. The complete series of bi-and tridentate Mn(I) species have been fully characterized and systematically studied by X-ray diffraction analysis revealing in particular two different coordination modes for the nonsymmetrical PCN ligands in complexes mer-[Mn(CO)3(κ 3 P,C,N)](OTf) ([15](OTf)) and fac-[Mn(CO)3(κ 3 P,C,N)](OTf) ([17](OTf)) rationalized by the higher flexibility of ligand with CH2Py extremity in the latter case. The evaluation of these compounds in catalytic hydrogenation of acetophenone revealed the fac-[Mn(CO)3(κ 3 P,C,N)(OTf) pre-catalyst to be the most active system, the efficiency of which was attributed to the presence of a 5,6-fused membered architecture promoting the dissociation of the pyridine arm and thereby releasing a vacant site beneficial to the catalytic process. Future studies will aim to engage these Mn(I) complexes in other catalytic processes, but also to implant this new class of NHC-core pincer-type ligands on different transition metal centers.

EXPERIMENTAL SECTION

General Remarks. All manipulations were performed under an inert atmosphere of dry nitrogen by using standard vacuum line and Schlenk tube techniques. Glassware was dried at 120 °C in an oven for at least three hours. Dry and oxygen-free organic solvents (THF, Et2O, CH2Cl2, toluene, pentane) were obtained using a LabSolv (Innovative Technology) solvent purification system. Acetonitrile was dried and distilled over P2O5 under argon. Chromatographic purification was carried out on silica gel (SiO2, 63-200 μm) and activated basic alumina (Brockmann I). 1 H, 31 P, and 13 C NMR spectra were obtained on Bruker AV300, AV400 or NEO600 spectrometers. NMR chemical shifts δ are in ppm, with positive values to high frequency relative to the tetramethylsilane reference for 1 H and 13 C and to 85% H3PO4 for 31 P. If necessary, additional information on the carbon signal attribution was obtained using 13 C{ 1 H, 31 P}, J-modulated spin-echo (JMOD) 13 C{ 1 H}, 1 H- 13 C HMQC, and/or HMBC experiments. Solution IR spectra were recorded in 0.1 mm CaF2 cells using a Perkin Elmer Frontier FT-IR spectrometer and given in cm -1 with relative intensity in parentheses. GC analyses were performed with GC-2014 (Shimadzu) 2010 equipped with a capillary column (Supelco, SPBTM-20, fused silica capillary column, 30 m × 0.25 mm × 0.25 mm film thickness). Highresolution mass spectra (ESI positive mode) were obtained using a Xevo G2 QTof (Waters) spectrometer. Elemental analyses were carried out at the LCC-CNRS (Toulouse) using a Perkin Elmer 2400 series II analyzer. Non-stirred 'Autoclave Maxitech' autoclaves (50 mL) were used for the hydrogenation. Ph2P(O)CH2OTs, 18 2-(1H-imidazol-1yl)pyridine 5, 20 and 2-(1H-imidazol-1-yl-methyl)pyridine 8, 21 were prepared according to known methods. All other reagent grade chemicals purchased from commercial sources were used as received.

Synthesis of [Ph2P(O)CH2Im] (2).

A Schlenk tube was charged with Ph2P(O)CH2OTs (4.0 g, 10.4 mmol), 1H-imidazole (0.71 g, 10.4 mmol) and K2CO3 (9.67 g, 70.0 mmol) under an air atmosphere. After addition of DMSO (40 mL), the suspension was vigorously stirred at 90 °C for 24 h. The reaction mixture was cooled to 50 °C and DMSO was removed under reduced pressure. The solid residue was dissolved in CHCl3 (20 mL), the solution was washed several times with H2O, dried over MgSO4 and evaporated under reduced pressure. The resulting solid was washed with Et2O (20 mL) and dried under vacuum to afford 2 as a white powder (1.98 g, 70%). 1 H NMR (400 MHz, CDCl3, 25 °C): δ 7.70-7.65 (m, 4H, CHPh), 7.61-7.57 (m, 2H, CHPh), 7.52-7.47 (m, 4H, CHPh), 7.30 (brs, 1H, CHIm-2), 6.96 (brs, 1H, CHIm-4,5), 6.91 (brs, 1H, CHIm-4,5), 4.77 (d, JPH = 4.5 Hz, 2H, CH2); 31 P{ 1 H} NMR (162 MHz, CDCl3, 25 °C): δ 25.7 (s); 13 C{ 1 H} NMR (101 MHz, CDCl3, 25 °C): δ 137.9 (brs, CHIm-2), 132.9 (d,JPC = 2.5 Hz,CHPh),131.2 (d,JPC = 9.5 Hz,CHPh),129.7 (s,5),129.1 (d,JPC = 103.7 Hz,Cipso Ph), 129.0 (d,JPC = 18.0 Hz,CHPh),120.3 (s,5),47.8 (d,JPC = 73.9 Hz,CH2);Anal. Found: C,65.58;H,5.63;N,9.

Synthesis of [(Ph2P(O)CH2)2Im]OTs [3](OTs).

A mixture of 2 (1.26 g, 4.5 mmol) andPh2P(O)CH2OTs (1.70 g, 4.5 mmol) was heated under stirring in toluene (5 mL) at 130 °C for 16 h. After cooling to RT, the light-brown solid formed was dissolved in CH2Cl2 (5 mL) and then Et2O (50 mL) was added. The resulting precipitate was triturated with Et2O (20 mL) until the formation of a white powder (ca. 30 min). The supernatant was then removed by decantation and the precipitate was washed with Et2O (10 mL) and dried under vacuum to afford [3](OTs) as a white powder (2.6 g, 87%). 1 H NMR (400 MHz, CDCl3, 25 °C): δ 9.85 (s, 1H, CHIm-2), 10H,CHAr),6H,CHAr),8H,CHAr)

Synthesis of [(Ph2PCH2)2Im]OTs [4](OTs).

A Schlenk tube was charged with bis(4-nitrophenyl)phosphate (408 mg, 1.2 mmol) and [3](OTs) (4.0 g, 6.0 mmol) under N2 flow. Dry toluene (40 mL), PhSiH3 (6 mL, 48 mmol) were added and the mixture was stirred at 110 °C for 16 h. After cooling to RT, the volatiles were removed under vacuum. The resulting solid was dissolved in degassed CH2Cl2 (10 mL) and then degassed Et2O was added (100 mL). The resulting precipitate was washed with degassed Et2O (30 mL) and dried under vacuum to afford [4](OTs) as a beige powder (3.4 g, 89%). Single crystals suitable for XRD were obtained by slow evaporation of a concentrated CH2Cl2 solution at RT. 1 H NMR (400 MHz, CDCl3, 25 °C): δ 9.62 (s, 1H, CHIm-2), 7.79 (d,JHH = 8.1 Hz,2H,CHTs),20H,CHPh),7.10 (d,JHH = 7.9 Hz,2H,CHTs),6.88 (brs,2H,5)

Synthesis of [Ph2P(O)CH2ImPy]OTs [6](OTs).

A mixture of 5 (0.68 g, 4.7 mmol) and Ph2P(O)CH2OTs (1.5 g, 3.9 mmol) was heated under stirring at 150 °C for 16 h. After cooling to RT, the resulting brown solid was dissolved in CH2Cl2 (5 mL) and then Et2O (100 mL) was added. The resulting precipitate was triturated with Et2O (30 mL) until the formation of a white powder (ca. 30 min). The supernatant was removed by decantation and the precipitate was washed with Et2O (10 mL) and dried under vacuum to afford [6](OTs) as a very hygroscopic white powder (1.8 g, 90%). 1 H NMR (400 MHz, CDCl3, 25 °C): δ 10.44 (s, 1H, CHIm-2), 8.34 (d,JHH = 4.6 Hz,1H,CHAr),8.08 (s,1H,CHAr),5H,CHAr),7.86 (s,1H,CHAr),3H,CHAr),6H,CHAr),1H,CHAr),7.08 (d,JHH = 7.8 Hz,2H,CHTs),5.75 (d,JPH = 6.3 Hz,2H, P(O)CH2), 2.27 (s, 3H, CH3Ts); 31 P{ 1 H} NMR (162 MHz, CDCl3, 25 °C): δ 27.1 (s); 13 C{ 1 H} NMR (101 MHz, CDCl3, 25 °C): δ 148.8 (s, CHPy), 145.7 (s, CPy), 143.3 (s, CTs), 140.5 (s, CHPy), 139.5 (s, CTs), 135.6 (d, JPC = 2.6 Hz, CHIm-2), 133.0 (d, JPC = 2.6 Hz, CHPh), 131.3 (d, JPC = 9.9 Hz, CHPh), 129.2 (d, JPC = 12.5 Hz, CHPh), 128.7 (s, CHTs), 127.9 (d, JPC = 103.6 Hz, Cipso Ph), 125.9 (s,CHTs),125.0 (s,CHPy),124.3 (s,CHPy),118.6 (s,5), 114.4 (s,5), 49.2 (d, JPC = 66.5 Hz, P(O)CH2), 21.3 (s,CH3Ts);Anal. Found: C,61.26;H,4.87;N,7.76. Calcd. (%) for C28H26N3O4PS. 0.25 (CH2Cl2): C,61.38;H,4.83;N,7.60; MS (ES + ): m/z: 360.1 [M] + ; HRMS (ES + ): calcd. for C21H19N3OP + 360.1266; found, 360.1266 (εr = 0.0 ppm).

Synthesis of [Ph2PCH2ImPy]OTs [7](OTs). A dried Schlenk tube containing a stirring bar was charged with bis(4-nitrophenyl) phosphate (128 mg, 0.38 mmol) and [6](OTs) (2.0 g, 3.8 mmol) under argon flow. Dry toluene (40 mL) and PhSiH3 (1.9 mL, 15 mmol) were added and the mixture was stirred at 140 °C for 16 h, cooled to RT and the volatiles were removed under vacuum. The resulting solid was dissolved in degassed CH2Cl2 (5 mL) and then degassed Et2O (50 mL) was added. The resulting precipitate was washed with degassed Et2O (20 mL) and dried under vacuum to afford [7](OTs) as a beige powder (1.7 g, 89%). 1 H NMR (600 MHz, CDCl3, 25 °C): δ 10.59 (s, 1H, CHIm-2), 8.40 (d,J = 4.5 Hz,1H,CHAr),8.26 (d,J = 8.2 Hz,1H,CHAr),8.08 (s,1H,CHAr),1H,CHAr),7.79 (d,JHH = 7.8 Hz,2H,CHTs),4H,CHAr),7H,CHAr),7.22 (s,1H,CHAr),7.09 (d,JHH = 7.8 Hz,2H,CHTs),5.34 (d,JPH = 5.3 Hz,2H, P(O)CH2), 2.30 (s, 3H, CH3Ts); 31 P{ 1 H} NMR (162 MHz CDCl3, 25 °C): δ -11.1 (s); 13 C{ 1 H} NMR (151 MHz, CDCl3, 25 °C): δ 148.9 (s, CHPy), 146.0 (s, CPy), 143.6 (s,CTs),140.8 (s,CHPy),139.5 (s,CTs),136.0 (s,133.4 (d,JPC = 19.8 Hz,CHPh),132.9 (d,JPC = 12.0 Hz,Cipso Ph), 130.3 (s,CHPh),129.3 (d,JPC = 7.3 Hz,CHPh),128.8 (s,CHTs),126.1 (s,CHTs),125.0 (s,CHPy),122.7 (s,CHPy),118.7 (s,5),115.0 (s,5), 49.7 (d, JPC = 21.9 Hz, PCH2), 21.4 (s,CH3Ts);Anal. Found: C,61.43;H,4.91;N,7.31. Calcd. (%)

Synthesis of [Ph2P(O)CH2ImCH2Py]OTs [9](OTs).

A mixture of 8 (1.98 g, 12.4 mmol) and Ph2P(O)CH2OTs (4.00 g, 10.4 mmol) was heated under stirring at 140 °C for 16 h. After cooling to RT, the brown solid formed was dissolved in CH2Cl2 (5 mL) and then Et2O (100 mL) was added. The resulting precipitate was triturated with Et2O (30 mL) until the formation of a white/brown powder (ca. 30 min). The supernatant was removed by decantation and the precipitate was washed with Et2O (10 mL) and dried under vacuum to afford [9](OTs) (4.8 g, 87%) as very hygroscopic brown crystals. 1 H NMR (400 MHz, CDCl3, 25 °C): δ 9.95 (s, 1H, CHIm-2), 8.43 (d,J = 4.8 Hz,1H,CHAr),4H,CHAr),7.79 (d,JHH = 7.7 Hz,2H,CHTs),7.65 (s,1H,CHAr),1H,CHAr),2H,CHAr),4H,CHAr),2H,CHAr),1H,CHAr),7.12 (d,JHH = 7.8 Hz,2H,CHTs)

Synthesis of [Ph2PCH2ImCH2Py]OTs [10](OTs).

A Schlenk tube was charged with bis(4-nitrophenyl) phosphate (180 mg, 0.53 mmol) and [9](OTs) (2.8 g, 5.3 mmol) under argon flow. Dry toluene (30 mL) and PhSiH3 (2.6 mL, 21 mmol) were added and the mixture was stirred at 110 °C for 16 h. After cooling to RT, the volatiles were removed under vacuum. The solid residue was dissolved in degassed CH2Cl2 (5 mL) and then degassed Et2O was added (50 mL). The precipitate formed was washed with degassed Et2O (20 mL) and dried under vacuum to afford [10](OTs) (2.4 g, 86%) as very hygroscopic brown crystals. 1 H NMR (400 MHz, CDCl3, 25 °C): δ 9.56 (s, 1H, CHIm-2), 8.37 (d,J = 4.8 Hz,1H,CHAr),7.74 (d,JHH = 7.7 Hz,2H,CHTs),1H,CHAr),7.44 (s,1H,CHAr),5H,CHAr),6H,CHAr),2H,CHAr),7.04 (d,JHH = 7.7 Hz,2H,CHTs),5.36 (s,2H,PyCH2),4.95 (d,JPH = 5.4 Hz,2H,PCH2), 2.26 (s, 3H, CH3Ts); 31 P{ 1 H} NMR (162 MHz, CDCl3, 25 °C): δ -12.2 (s); 13 C{ 1 H} NMR (101 MHz, CDCl3, 25 °C): δ 152.6 (s, CPy), 149.5 (s, CHPy), 143.9 (s, CTs), 139.0 (s, CTs), 137.5 (s, CHIm-2), 137.3 (s, CHPy), 133.0 (d,JPC = 19.4 Hz,CHPh),132.9 (d,JPC = 11.4 Hz, Cipso Ph), 129.9 (s, CHPh), 128.9 (d,JPC = 7.4 Hz,CHPh),128.5 (s,CHTs),125.9 (s,CHTs),123.5 (s,CHPy),123.4 (s,CHPy),122.7 (s,5),121.9 (s,5),53.7 (s,PyCH2),48.7 (d,JPC = 22.1 Hz,PCH2),21.2 (s,CH3Ts);Anal. Found: C,63.25;H,5.06;N,8.15. Calcd. (%) for C29H28N3O3PS. 0.3CH2Cl2: C,63.40;H,5.19;N,7.57; MS (ES + ): m/z: 358.1 [M] + ; HRMS (ES + ): calcd. for C22H21N3P + 358.1473; found, 358.1482 (εr = 2.5 ppm).

Synthesis of PCP Bidentate Complex 11. To a stirred suspension of [4](OTs) (0.40 g, 0.63 mmol) in toluene (30 mL), a solution of KHMDS (0.5 M in toluene, 1.3 mL, 0.66 mmol) was added at RT and then the resulting yellow suspension was sonicated during 5 min and stirred for additional 15 min. Solid [Mn(CO)5Br] (0.17 g, 0.63 mmol) was added in one portion inducing a vigorous CO evolution. The resulting orange solution was then stirred for 2 h at 60 °C. After cooling the reaction mixture to RT, filtration through Celite and evaporation of the solvent under vacuum, the crude product was crystallized in a THF/pentane mixture to afford 11 as a yellow powder (0.32 g, 71%). der an argon atmosphere, a Schlenk tube was charged with selected complex and acetophenone (1 mmol, 117 µL) in 2 mL of t-AmOH, the solution was placed in a steel autoclave. Then t-BuOK (10 mol%) was added and the autoclave was immediately pressurized with H2 (50 bar) and kept under stirring in an oil bath at 60 or 100 °C for 24 hours. After cooling the reactor to room temperature and release of H2, the reaction mixture was diluted with ethyl acetate (2.0 mL) and filtered through a small pad of Celite (2 cm in a Pasteur pipette) and the solution was analyzed by GC and 1 H NMR spectroscopy. To isolate the product, the crude residue was purified by column chromatography on silica using petroleum ether/ethyl acetate mixtures as eluent.

Single-crystal X-ray diffraction analyses. Single crystals suitable for X-ray diffraction were coated with paratone oil and mounted onto the goniometer. The X-ray crystallographic data were obtained at low temperature from a Bruker Apex2 diffractometer (MoKα radiation source) equipped with an Oxford Cryosystem. The structures have been solved with Superflip 32 and refined by means of least-square procedures on F or F 2 using the PC version of the program CRYSTALS. 33 The scattering factors for all the atoms were used as listed in the International Tables for X-ray Crystallography. Absorption correction was performed using a multi-scan procedure. All non-hydrogen atoms were refined anisotropically. The H atoms were located in a difference map, but those attached to carbon atoms were repositioned geometrically. The H atoms were initially refined with soft restraints on the bond lengths and angles to regularise their geometry and U[iso](H) (in the range 1.2-1.5 times U[eq] of the parent atom), after which the positions were refined with riding constraints. Detailed crystallographic data and structural refinement parameters are given in Table S1 of the Supporting Information.

  (OTf) the presence of two CO resonances ([12](OTf): C 220.7 (brt, JPC = 10.5 Hz), 213.6 (brt, JPC = 19.0 Hz); [15](OTf): C 218.4 (d, JPC = 9.7 Hz), 212.7 (d, JPC = 17.7 Hz)), and of three resonances (C 219.6 (brd, JPC = 25.5 Hz), 218.7 (d, JPC = 18.5 Hz)), 216.9 (d, JPC = 23.5 Hz)

  48. Calcd. (%) for C16H15N2OP. 0.25 (DMSO): C, 65.66; H, 5.51; N, 9.28; MS (ES + ): m/z: 283.1 [M + H] + ; HRMS (ES + ): calcd. for C16H16N2OP + 283.1000; found, 283.1006 (εr = 2.1 ppm).

  , 7.08(d, JHH = 7.8 Hz, 2H, CHTs), 5.28(d, JPH = 6.3 Hz, 4H, CH2), 2.30 (s, 3H, CH3Ts); 31 P{ 1 H} NMR (162 MHz, CDCl3, 25 °C): δ 26.5 (s); 13 C{ 1 H} NMR (101 MHz, CDCl3, 25 °C): δ 143.6 (s, CTs), 139.6 (s, CTs), 138.6 (s, CHIm-2), 133.0 (d, JPC = 2.0 Hz, CHPh), 131.3 (d, JPC = 9.9 Hz, CHPh), 129.2 (d, JPC = 12.5 Hz, CHPh), 128.8 (s, CHTs), 127.9 (d, JPC = 103.8 Hz, Cipso Ph), 126.0 (s, CHTs), 123.2 (s, CHIm-4,5), 48.6 (d, JPC = 66.0 Hz, CH2), 21.4 (s, CH3Ts); Anal. Found: C, 59.71; H, 4.97; N, 3.84. Calcd. (%) for C36H34N2O5P2S. 0.85 (CH2Cl2): C, 59.74; H, 4.86; N, 3.78; MS (ES + ): m/z: 497.1 [M] + ; HRMS (ES + ): calcd. for C29H27N2O2P2 + 497.1548; found, 497.1534 (εr = 2.8 ppm).

  , 4.92 (d, JPH = 5.5 Hz, 4H, CH2), 2.31 (s, 3H, CH3Ts); 31 P{ 1 H} NMR (162 MHz, CDCl3, 25 °C): δ -12.4 (s); 13 C{ 1 H} NMR (101 MHz, CDCl3, 25 °C): δ 143.9 (s, CTs), 139.3 (s, CTs), 138.1 (s, CHIm-2), 133.1 (d, JPC = 19.8 Hz, CHPh), 133.0 (d, JPC = 13.1 Hz, Cipso Ph), 130.2 (s, CHPh), 129.3 (d, JPC = 7.0 Hz, CHPh), 128.7 (s, CHTs), 126.2 (s, CHTs), 121.9 (d, JPC = 4.2 Hz, CH Im-4,5), 48.9 (d, JPC = 21.1 Hz, CH2), 21.4 (s, CH3Ts); Anal. Found: C, 65.83; H, 5.19; N, 4.25. Calcd. (%) for C36H34N2O3P2S. 0.30 (CH2Cl2): C, 65.84; H, 5.27; N, 4.23; MS (ES + ): m/z: 465.1 [M] + ; HRMS (ES + ): calcd. for C29H27N2P2 + 465.1649; found, 465.1648 (εr = 0.2 ppm).

Table 1 . Selected 31 P, 1 H and 13 C NMR chemical shifts in CDCl3 (ppm) for imidazolium salts [3](OTs), [4](OTs), [6](OTs), [7](OTs), [9](OTs) and [10](OTs).

 1

		[3] +	[4] +	[6] +	[7] +	[9] +	[10] +
	P	26.5	-12.4	27.1	-11.1	27.2	-12.2
	CH	9.85	9.62	10.44	10.59	9.95	9.56
	CH

Table 2 . Selected 31 P and 13 C NMR chemical shifts in CD2Cl2 (ppm) with signal multiplicity and JCP coupling constants (Hz) in parenthesis, and IR CO frequencies in THF solution (cm -1 ) with relative intensity in parenthesis for NHC-based Mn(I) complexes of bidentate (11, 13, 14, 16) and tridentate ([12](OTf), [15](OTf), [17](OTf)) nature.

 2

	a -IR CO frequencies were measured in a toluene solution; b -NMR data was recorded in CDCl3.

  and 2.2661(3) Å). The facial geometry

		11 a	[12](OTf)	13	14	[15](OTf) b	16	[17](OTf)
	P	71.0 (s) -17.0 (s)	89.6 (s)	71.8 (s)	-15.9 (s)	97.4 (s)	71.2 (s)	93.3 (s)
	N 2 C 197.1 (d, 16.5)

Figure 1. Perspective views of bidentate (13, 14, 16, upper line), and tridentate ([12](OTf), [15](OTf),

Table 4 . Catalytic hydrogenation of acetophenone with NHC core Mn(I) complexes [12](OTf), [15](OTf), and [17](OTf). a

 4

	Entry	Complex	Cat. (mol %)	Temp. (°C)	Conv. % b
	1	[12](OTf)	1.0	100	27
	2	[12](OTf)	0.5	100	19
	3	[12](OTf)	1.0	60	6
	4	[12](OTf)	0.5	60	3
	5	[15](OTf)	1.0	100	39
	6	[15](OTf)	0.5	100	21
	7	[15](OTf)	1.0	60	22
	8	[15](OTf)	0.5	60	11
	9	[17](OTf)	1.0	100	100 (95)
	10	[17](OTf)	0.5	100	80
	11	[17](OTf)	1.0	60	30
	12	[17](OTf)	0.5	60	20
	13	11	1.0	100	42
	14	14	1.0	100	33

  for C28H26N3O3PS. 0.50 (CH2Cl2): C, 61.34; H, 4.88; N, 7.53; MS (ES + ): m/z: 344.1 [M] + ; HRMS (ES + ): calcd. for C21H19N3P + 344.1317; found, 344.1317 (εr = 0.0 ppm).

  CHPy), 143.5 (s, CTs), 139.6 (s, CTs), 138.5 (d, JPC = 2.3 Hz, CHIm-2), 137.7 (s, CHPy), 133.1 (d, JPC = 2.3 Hz, CHPh), 131.4 (d, JPC = 10.0 Hz, CHPh), 129.3 (d, JPC = 12.5 Hz, CHPh), 128.8 (s, CHTs), 127.9 (d, JPC = 103.3 Hz, Cipso Ph), 126.0 (s, CHTs), 124.0 (s, CHPy), 123.5 (s,

	, 5.46 (d, JPH = 6.2 Hz, 2H, P(O)CH2), 5.33 (s, 2H,
	PyCH2), 2.32 (s, 3H, CH3Ts); 31 P{ 1 H} NMR (162 MHz, CDCl3, 25 °C):
	δ 27.2 (s); 13 C{ 1 H} NMR (101 MHz, CDCl3, 25 °C): δ 152.3 (s, CPy),
	149.9 (s, CHPy), 123.4 (s, CHIm-4,5), 122.3 (s, CHIm-4,5), 54.3 (s, PyCH2), 48.9 (d,
	JPC = 66.0 Hz, P(O)CH2), 21.4 (s, CH3Ts); Anal. Found: C, 61.20; H,
	5.02; N, 7.64. Calcd. (%) for C29H28N3O4PS. 0.35 (CH2Cl2): C, 61.27;
	H, 5.03; N, 7.30; MS (ES + ): m/z: 374.1 [M] + ; HRMS (ES + ): calcd. for
	C22H21N3OP + 374.1422; found, 374.1431 (εr = 2.4 ppm).

ACKNOWLEDGMENT

The authors thank the Centre National de la Recherche Scientifique (CNRS), the Université Toulouse III, Paul Sabatier, and the Institut Universitaire de France (IUF) for general support of this project. R.B. is grateful to the Embassy of Yemen in Paris, and the program Pause for financial support.

ASSOCIATED CONTENT Supporting Information

The Supporting Information is available free of charge on the ACS Publications website.

Copies of 1 H, 31 P and 13 C NMR spectra, representation of X-ray structure of [4](OTs), crystallographic data and structural refinement parameters for all studied compounds (PDF).

Accession Codes

CCDC 2042375 [4](OTs), CCDC 2042377 13, CCDC 2042380 14, CCDC 2042376 16, CCDC 2042403 [12](OTf), CCDC 2042379 [15](OTf), and CCDC 2042378 [17](OTf) contain the supplementary crystallographic data for this paper. These data can be obtained free of charge via www.ccdc.cam.ac.uk/data_request/cif, or by emailing data_request@ccdc.cam.ac.uk, or by contacting The Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, UK; fax: +44 1223 336033.

AUTHOR INFORMATION Corresponding Authors

* E-mails: yves.canac@lcc-toulouse.fr, jean-baptiste.sortais@lcctoulouse.fr, dmitry.valyaev@lcc-toulouse.fr Yves Canac: 0000-0002-3747-554X Jean-Baptiste Sortais: 0000-0003-1178-8588 Dmitry A. Valyaev: 0000-0002-1772-844X

Notes

The authors declare no competing financial interests.