Archive for the ‘Subject Areas’ Category

Upgrading Methanol Using Zinc-Indium-Sulfide and Solar Light

Based on the chemical formulae, can you figure out how to convert methanol (CH3OH) into ethylene glycol (HOCH2CH2OH)? If you have constantly practiced your organic chemistry, you might have already found the answer: combining two methanol molecules and eliminating one hydrogen molecule (H2). Indeed, this methanol-coupling reaction is a promising, low-cost chemical route to upgrade methanol to chemicals with more carbon atoms. The feasibility of this route, however, is low under mild conditions without catalysts to drive the reaction.

A group of scientists led by Shunji Xie and Ye Wang, both at Xiamen University, China, has developed an environmentally friendly catalyst, Zn2In2S5, for room-temperature methanol coupling to produce ethylene glycol using solar light. This work has been published in Chemical Communications (DOI: 10.1039/c9cc09205f).

The synthesized Zn2In2S5 catalyst is comprised of 1-3 layers of nanosheets. Through a hydrothermal reaction, the researchers first synthesized multi-layer Zn2In2S5 stacks in an aqueous solution (Fig. 1a). Subsequent ultrasonication exfoliated the stacks into few-layer Zn2In2S5­ nanosheets that were confirmed by transmission electron microscopy (Fig. 1b). Zn2In2S5 is a semiconductor and its valence band (VB) resides below the redox potential of ethylene glycol/methanol (Fig. 1c). The band alignment enables Zn2In2S5 to catalyze the oxidation of methanol to ethylene glycol.

Figure 1. (a) A scheme of the synthesis procedures of few-layer ZnmIn2Sm+3 (m=1-3) nanosheets. (b) Transmission electron microscopy images of few-layer Zn2In2S5 nanosheets. (c) Positions of the valence bands (VBs) and conduction bands (CBs) of different metal-sulfide semiconductors.

Zn2In2S5 and its composite exhibited high catalytic activity. Upon irradiation with visible light and solar light (AM 1.5), photo-induced electrons and holes generated in Zn2In2S5 (Fig. 2a). The electrons reduced protons in electrolytes and liberated hydrogen gas, while the holes moved to the Zn2In2S5 surface and split the C—H bond of methanol, forming ·CH2OH radicals. These radicals then dimerized into ethylene glycol. Through depositing a hydrogen evolution co-catalyst, cobalt monophosphide (CoP), and illuminating using AM 1.5 solar light, the authors observed that the CoP/Zn2In2S5 catalyst achieved a rapid formation rate (18.9 mmol gcat-1 h-1) and high selectivity (~90%) of ethylene glycol (Fig. 2b). The yield of ethylene glycol after 12 h of reaction was 4.5%.

Figure 2. (a) A scheme of the formation mechanisms of ethylene (from methanol) and 2,3-butanediol (from ethanol) on Zn2In2S5. EG: ethylene glycol. 2,3-BD: 2,3-butanediol. (b) Formation rates and ethylene glycol selectivity of Zn2In2S5 and CoP/Zn2In2S5 under two illumination conditions. AM 1.5: air mass 1.5 solar irradiance. HCHO is a byproduct.

Zn2In2S5 was demonstrated to effectively catalyze C—H cleavages and C—C couplings of different alcohols, e.g., from ethanol to 2,3-butanediol.

 

To find out more, please read:

C–H Activations of Methanol and Ethanol and C–C Couplings into Diols by Zinc–Indium–Sulfide Under Visible Light

Haikun Zhang, Shunji Xie, Jinyuan Hu, Xuejiao Wu, Qinghong Zhang, Jun Cheng, and Ye Wang

Chem. Commun., 2020, DOI: 10.1039/c9cc09205f

 

The blogger acknowledges Zac Croft at Virginia Tech, U.S., for his careful proofreading of this post.

 

About the blogger:

Tianyu Liu obtained his Ph.D. (2017) in Chemistry from the University of California, Santa Cruz, in the United States. He is passionate about the communication of scientific endeavors to both the general public and other scientists with diverse research expertise to introduce cutting-edge research to broad audiences. He is a blog writer for Chem. Comm. and Chem. Sci. More information about him can be found at http://liutianyuresearch.weebly.com/.

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What Does the New Carbon Allotrope Look Like, Theoretically?

A long-lasting dispute regarding the most stable structure of cyclo[18]carbon, a new carbon allotrope, has been settled. Cyclo[18]carbon is an all-carbon ring comprised of eighteen interconnected carbon atoms. It is proposed to have two possible structures: the cumulenic structure with only carbon-carbon double bonds (Figure 1a), and the polyynic structure having alternating carbon-carbon triple and single bonds (Figure 1b). Recent experiments have confirmed that the polyynic structure is the stable form, but theorists were still puzzled: Why can’t the various computational methods reach an agreement on the molecular structure of cyclo[18]carbon?

Figure 1. The (a) cumulenic and (b) polyynic structures of cyclo[18]carbon.

Anton J. Stasyuk and coworkers from the University of Girona, Spain, offered an answer in ChemComm (DOI: 10.1039/C9CC08399E). They found that the simulated structure strongly depended on the type of functionals used in density functional theory (DFT), which is a computational tool to derive energy-minimum molecular structures. The functionals used for DFT calculations are mathematical terms that can tune the simulation accuracy.

The authors discovered that the weight of the exact exchange term (HF% exchange) in the DFT functionals determined the most stable simulated structure of cyclo[18]carbon. The researchers compared 13 functionals with various percentages of HF% exchanges. They found that functionals with the HF% exchange higher than 50% predicted the appreciably different lengths of the neighboring bonds (quantified as the bond length alternation, the vertical axis of Figure 2), corresponding to the polyynic structure (Figure 2, red zone). This structure was recently observed experimentally. Functionals with lower HF% exchange either obtained the cumulenic structure (Figure 2, green zone) or the mixed cumulenic-polyynic structure (Figure 2, gray zone).

Figure 2. Variation in the HF% exchange of the B3LYP functional changed the predicted molecular structure of cyclo[18]carbon. BLA: Bond length alternation.

With the correct functionals identified, the authors revealed the electronic properties of cyclo[18]carbon. Calculations showed that cyclo[18]carbon was a strong electron acceptor, making it the smallest all-carbon electron acceptor reported so far.

 

To find out more, please read:

Cyclo[18]Carbon: Smallest All-Carbon Electron Acceptor

Anton J. Stasyuk, Olga A. Stasyuk, Miquel Solà, and Alexander Voityuk

Chem. Commun., 2019, DOI: 10.1039/C9CC08399E

Tianyu Liu acknowledges Zac Croft at Virginia Tech, U.S., for his careful proofreading of this post.

 

About the blogger:

Tianyu Liu obtained his Ph.D. (2017) in Chemistry from the University of California, Santa Cruz, in the United States. He is passionate about the communication of scientific endeavors to both the general public and other scientists with diverse research expertise to introduce cutting-edge research to broad audiences. He is a blog writer for Chem. Comm. and Chem. Sci. More information about him can be found at http://liutianyuresearch.weebly.com/.

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Tuning Zeolite Catalysis with Organic Molecules

Zeolites, a class of porous alumina-silicate materials, are industrially critical adsorbents and catalysts. Their highly robust nature and wide range of structural types (over 200!) make them suited to a range of applications. In particular, the general zeolite topology and pore size are selected to match and stabilize the intermediates of a chemical reaction. However, the tunability of zeolites is limited when compared to molecular catalysts, making them more like a solvent than, say, an enzyme. An active field of research is bridging the gap between the robust, scalable zeolites and highly controllable homogenous catalysts. Recent work identified organic residues maintained with the zeolite pores as key in the transformation of methanol to hydrocarbons. Previous fundamental studies demonstrated that a wide range of carbonyl and carbonyl derivative compounds promote the dehydration of methanol to dimethyl ether (DME).

Researchers at BP used methyl mono- and di-carboxylate esters to dehydrate methanol to DME at low temperatures. The mild reaction conditions allowed for high selectivity for DME while eliminating convoluting side reactions. They added either methyl formate or methyl n-hexanoate to a series of zeolite with pores ranging from narrow to wide. At a 5 mol% concentration relative to methanol they saw significant increases in DME production, particularly for the medium and wide pores. Systematic testing of carboxylate chain length found that increasing chain length increased turnovers occurred until methyl n-hexanoate, after which no further benefits were observed as the n-methyl hexanoate had already saturated the catalyst (Figure 1). All proved highly selective for converting methanol to DME with no observed hydrocarbon formation.

Figure 1. Production of DME on a medium-pore zeolite with methyl carboxylate esters of varying chain lengths.

The experimental results were coupled with theoretical work modeling the energetics of the adsorption of the ester onto the zeolite. The calculations showed an increase in adsorption energy with increased chain length, attributed to van der Waals interactions.

Figure 2. Transition state predicted by molecular modeling with methanol attacking the organic promoter adsorbed on the zeolite catalyst.

They also gave even higher energies to molecules with two carboxylate esters, like dimethyl adipate. In fact, the strongly binding molecules produced increased catalysis at loadings as low as 0.001% with respect to methanol. The promoters can be easily switched by changing the input, demonstrating the reversibility of binding at the active site. Additional molecular modeling was used to study possible transition states to develop a catalytic cycle. A proposed transition state involves a direct reaction between the methanol and the organic promotor, however specific evidence has yet to be seen. Additional work examining the role of the water present as a co-adsorbate and its impacts on transition states has yet to be done. Overall, the use of various organic molecules as promotors for the dehydration of methanol to DME on various zeolite catalysts was explored. This represents exciting fundamental study of industrially-relevant chemistry with significant room for future work.

To find out more, please read:

Getting zeolite catalysts to play your tune: methyl carboxylate esters as switchable promoters for methanol dehydration to DME

Benjamin J. Dennis-Smither, Zhiqiang Yang, Corneliu Buda, Xuebin Liu, Neil Sainty, Xingzhi Tan and Glenn J. Sunley

Chem. Commun., 2019, 55, 13804-13807.

About the blogger:

Beth Mundy is a PhD candidate in chemistry in the Cossairt lab at the University of Washington in Seattle, Washington. Her research focuses on developing new and better ways to synthesize nanomaterials for energy applications. She is often spotted knitting in seminars or with her nose in a good book. You can find her on Twitter at @BethMundySci.

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How does LiNO3 Make Lithium–Sulfur Batteries Long-Lasting?

Lithium–sulfur (Li–S) batteries are rechargeable batteries with elemental sulfur and metallic lithium as the cathode and anode, respectively. These batteries are promising electrochemical energy storage devices because their energy densities are three to five times higher than those of Li-ion batteries. Unfortunately, the practicality of Li–S batteries is hindered by their short lifetimes due to two processes that occur on the Li anode surface: the growth of Li dendrites and the irreversible polysulfide reduction. Adding LiNO3 into battery electrolytes has proven to be useful to prolong battery lifetimes, but the underlying mechanism is uncertain.

In Chemical Communications (doi: 10.1039/c9cc06504k), Sawangphruk and coworkers from Vidyasirimedhi Institute of Science and Technology, Thailand have offered valuable insights to settle the dispute over the effects of LiNO3. The researchers performed theoretical reactive molecular dynamics simulations and elucidated two roles of LiNO3 in Li–S batteries.

The first discovery was that LiNO3 promoted the formation of smooth, double-layered solid electrolyte interfaces (SEIs) on the Li surface. SEIs are thin layers composed of electrolyte-decomposition products, including Li-containing organic compounds and inorganic salts. By simulating the charge distribution near a Li metal surface, the authors mapped the Li-Li radial pair distribution profiles in three phases (Fig. 1a). The similarity between the profiles of the dense phase (the Li metal) and the nest phase evidenced the presence of an amorphous, Li-containing layer atop the Li metal surface. Beyond this amorphous layer was a liquid-like film with Li element distributed homogenously. This double-layered SEI altered the kinetics of Li deposition onto the Li surface upon charging, resulting in smooth and dense SEIs (Figs. 1b and c) that avoided Li dendrite formation.

Figure 1. (a) Li-Li radial pair distribution functions of the dense phase (Li metal), nest phase (the layer atop Li), and disperse phase (the outermost layer). (b and c) Top-view scanning electron microscopy images of the Li metal surface in (b) LiNO3-free and (c) LiNO3-containing electrolytes. Both electrolytes had lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) as a solute, and 1,3-dioxolane (DOL) and 1,2-dimethoxyethane (DME) as solvents.

Another effect of LiNO3 was to capture polysulfide compounds. Through their simulations, the authors deduced the reaction pathways involving the electrolyte molecules, LiNO3 or LiClO4 additives, and lithium polysulfide compounds (Fig. 2a). The concentration of LixNOy, the reduction products of LiNO3 when contacted Li metal, in the LiNO3-containing electrolyte was much higher than those in the additive-free and LiClO4-containing electrolytes. First-principle calculations proved that the highly electro-negative N and O atoms in LixNOy could capture lithium polysulfides via dipole-dipole interactions. This process reduced the likelihood of polysulfide reduction on Li that passivated anodes.

Figure 2. (a) A scheme of the reaction pathways involving the electrolyte, additive, and polysulfide molecules. (b) Product distributions in electrolytes without additives and with LiNO3 or LiClO4.

LiNO3 elongates the lifetimes of Li–S batteries by forming smooth SEIs to impede Li dendrite formation, while maintaining the reactivity of Li anodes by capturing lithium polysulfides.

 

To find out more, please read:

Insight into the Effect of Additives Widely Used in Lithium–Sulfur Batteries

Salatan Duangdangchote, Atiweena Krittayavathananon, Nutthaphon Phattharasupakun, Nattanon Joraleechanchai, and Montree Sawangphruk

Chem. Commun., 2019, 55, 13951-13954

Tianyu Liu acknowledges John Elliott of Virginia Tech, the U.S., for his careful proofreading of this post.

About the blogger:

Tianyu Liu obtained his Ph.D. (2017) in Chemistry from the University of California, Santa Cruz, in the United States. He is passionate about the communication of scientific endeavors to both the general public and other scientists with diverse research expertise to introduce cutting-edge research to broad audiences. He is a blog writer for Chem. Commun. and Chem. Sci. More information about him can be found at http://liutianyuresearch.weebly.com/.

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Designing Syntheses with Machine Learning

I don’t know if you’ve looked at the structure of pharmaceuticals recently, but most novel drugs are rather complicated. Identifying promising new targets is just the start for synthetic chemists; they then need to figure out how to use a series of reactions to take simple (and commercially available) molecules and transform them into a new drug. They also must predict all possible side reactions and products given a set of reaction conditions, particularly when a range of functional groups are involved. Historic approaches involved manual curation of reaction rules, limited by personal experience and the state of the accessed chemical literature. Newer approaches seek to create templates directly from data but are defined by available data sets and cannot reliably extrapolate. The emergence of machine learning offers the opportunity to move beyond traditional templating and atom mapping of reactants to products. It also offers to take full advantage of novel technologies and address problems with dataset bias and ineffective modeling systems.

In a collaboration between academics in the UK and industrial scientists in the US, researchers used Molecular Transformer, an attention-based machine translation model, to perform both reaction prediction and retrosynthesis analysis after training on a publicly available dataset. Instead of atom mapping, which moves atoms from the reactants to the products, Molecular Transformer (MT) relies on SMILES text strings, which represent structures in a line format. A unique aspect of this work is the validation and training performed using proprietary data of drug targets from Pfizer. They used three datasets: the first a literature standard from the US Patent and Trade Office (USPTO), the second from internal medicinal chemistry projects in Pfizer, and the final a diverse range of 50,000 reactions from US patents (USPTO-R). Building on previous research from the authors, they trained the MT on both the Pfizer data and the initial USPTO data sets. They found that the Pfizer data provided the most accurate product predictions and that the MT could also return a confidence rating to determine the probability the prediction is correct.

Figure 1. Sample syntheses predicted by Molecular Transformer for various bioactive molecules of interest.

While synthesis predictions can easily be checked, it’s harder to confirm accuracy with retrosynthesis since there is not a single correct answer. The researchers used the broad USPTO-R to train MT, which consistently outperformed both a benchmark template-based program and another literature machine learning method also trained on USPTO-R. When tested on the Pfizer dataset, the MT performed best with 31.5% accuracy despite the datasets coming from different regions of chemical space (which increased to 91% when MT was trained on Pfizer data). Figure 1 shows several predicted routes for the synthesis of bioactive molecules as predicted by MT, which generally agree with established syntheses. These data suggest the highly generalizable nature of MT as a tool for developing novel pharmaceutically interesting molecules.

To find out more, please read:

Molecular Transformer unifies reaction prediction and retrosynthesis across pharma chemical space

Alpha A. Lee, Qingyi Yang, Vishnu Sresht, Peter Bolgar, Xinjun Hou, Jacquelyn L. Klug-McLeod and Christopher R. Butler

Chem. Commun., 2019, 55, 12152-12155.

About the blogger:

Beth Mundy is a PhD candidate in chemistry in the Cossairt lab at the University of Washington in Seattle, Washington. Her research focuses on developing new and better ways to synthesize nanomaterials for energy applications. She is often spotted knitting in seminars or with her nose in a good book. You can find her on Twitter at @BethMundySci.

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Strengthening Li+-Coordination Decelerates Li-Dendrite Growth in Li-Metal Batteries

Lithium-metal batteries are a family of rechargeable batteries with higher charge-storage capacities than those of lithium-ion batteries. The boosted charge-storage performance of lithium-metal batteries is rooted in its anode material – Li metal, as it possesses an ultrahigh theoretical capacity (3860 mAh/g). However, the growth of dendrites on Li surfaces during charging could short-circuit batteries, cause combustion, and trigger explosions.

A research group led by Feng Li at the Institute of Metal Research, Chinese Academy of Sciences, recently devised a strategy to suppress the notorious Li dendrite growth in lithium-metal batteries. By tuning the composition of the electrolytes, the authors strengthened the coordination between Li+ and electrolyte solvents, which slowed the growth of Li dendrites. This work has been published in Chemical Communications (doi: 10.1039/C9CC07092C).

The researchers introduced an electrolyte additive, tetraethylene glycol dimethyl ether (TEGDME), as a coordination ligand to Li+. Compared to other components in the electrolyte, i.e., 1,2-dimethoxyethane (DME) and 1,3-dioxolane (DOL), TEGDME contains more oxygen atoms that can form multiple, robust coordination bonds with Li+. Specifically, density functional theory calculations showed that the binding energy between Li+ and electrolyte molecules increased by 0.31 eV after introducing TEGDME, reaching an absolute value of 4.93 eV. The enhanced binding force made the separation of Li+ from TEGDME (a prerequisite for Li-dendrite growth) energetically consuming and kinetically sluggish (Figure 1). These characteristics could decelerate Li-dendrite formation and elongate battery lifetimes.

Figure 1. Lithium-dendrite growth in different electrolytes: (a) weak coordination with Li+ promotes fast dendrite growth while (b) strong coordination with Li+ decelerates dendrite formation.

To confirm the above idea, the authors assembled lithium batteries with TEGDME+DME+DOL or DME+DOL electrolytes. Cycling stability tests demonstrated that the battery with the TEGDME-added electrolyte survived 60 charge-discharge cycles at a current density of 1C, whereas the capacity of the battery without TEGDME rapidly decayed beyond 30 cycles under identical testing conditions (Figure 2a). Scanning electron microscopy images revealed that the number of rod-shaped Li dendrites on the anode in the TEGDME-added electrolyte (Figure 2c) was less than that in the TEGDME-free electrolyte (Figure 2b), further confirming that the enhanced cycling stability resulted from the Li-dendrite suppressing effect of TEGDME.

Figure 2. (a) Cycling stability performance of lithium-metal batteries with two different electrolytes. The cathode material in both batteries was lithium iron phosphate (LFP). (b and c) SEM images of the Li anode surface after charging in (b) DME+DOL and (c) DME+DOL+TEGDME electrolytes.

This work highlights the importance of tailoring the electrolyte composition for preserving the stability and safety of lithium-metal batteries.

 

To find out more, please read:

Suppressing Lithium Dendrite Formation by Slowing Its Desolvation Kinetics

Huicong Yang, Lichang Yin, Huifa Shi, Kuang He, Hui-Ming Cheng, and Feng Li

Chem. Commun., 2019, doi: 10.1039/C9CC07092C

Tianyu Liu acknowledges Xiaozhou Yang of Virginia Tech, the U.S., for his careful proofreading of this post.

About the blogger:

Tianyu Liu obtained his Ph.D. (2017) in Chemistry from the University of California, Santa Cruz, in the United States. He is passionate about the communication of scientific endeavors to both the general public and other scientists with diverse research expertise as a way to introduce cutting-edge research to broad audiences. He is a blog writer for Chem. Commun. and Chem. Sci. More information about him can be found at http://liutianyuresearch.weebly.com/.

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MOF-Derived Solid-State Lithium-Oxygen Batteries

Just in case you weren’t aware, it turns out that lithium-based batteries are kind of a big deal. While the Nobel-winning batteries have already revolutionized consumer electronics, further development requires batteries with even higher energy densities. Enter: lithium-oxygen batteries (LOBs) with theoretical energy densities of 3500 W h/kg. LOBs come in non-aqueous, aqueous, hybrid, and solid-state varieties based on their electrolytes. Given the previous safety issues for lithium-based batteries with liquid electrolytes (remember the exploding phones?), solid-state electrolytes have attracted substantial research attention. Specifically, Li1+xAlxGe2x(PO4)3, or LAGP, shows promise given its high Li+ transport number and electrochemical stability over a wide window. These solid-state electrolytes need to be combined with new catalytically active high surface area cathode materials that will not react with the lithium and degrade, a persistent issue with MOFs.

Figure 1. Schematic of an assembled all solid-state lithium-oxygen battery.

Researchers in China and Japan have combined LAGP electrolyte with NiCo2O4 (NCO) nanoflakes as the catalytically active cathode material. They then assembled full solid-state batteries, the structure of which is shown in Figure 1, for electrochemical and stability testing. The LAGP was prepared using previously established methods and found to exhibit the expected high stability and lithium mobility. To prepare the nanoflakes, the researchers annealed cobalt-based MOFs on a sacrificial carbon substrate then dipped them in a Ni(NO3)2 solution for nickel doping and annealed once more. This leaves the final nanostructured metal oxide, with the elemental composition confirmed by TEM elemental mapping. As a conveniently freestanding electrode material, the nanoflakes were then loaded in as the cathode.

Once assembled, the researchers tested the full all solid-state LOBs for stability and performance. They demonstrated high discharge capacity and electron transfer efficiency with charge and discharge potentials well within the electrochemical window of the LAGP electrolyte. These are attributable to the high lithium ion mobility and the porous bimetallic nature of the cathode. To confirm that the incorporation of nickel impacted the overall device performance, the pure cobalt nanoflakes were used as the cathode.

Figure 2. Cycling performance of cobalt (left) and cobalt-nickel cathodes (right) at a current density of 100 mA/g.

As seen in Figure 2, the cobalt-only batteries exhibit significant capacity loss in only 35 cycles whereas the NCO cathodes showed no degradation after 90 cycles. While cycling the NCO electrodes, the reversible formation of Li2O2, a common discharge product, occurred in the open pores of the cathode. These pores allow the 500 nm Li2O2 particles to form and dissolve without disrupting the structure of the cathode and give a more stable battery. This research brings completely solid-state lithium-oxygen batteries one step closer to reality.

To find out more, please read:

All solid-state lithium–oxygen batteries with MOF-derived nickel cobaltate nanoflake arrays as high-performance oxygen cathodes

Hao Gong, Hairong Xue, Xueyi Lu, Bin Gao, Tao Wang, Jianping He and Renzhi Ma

Chem. Commun., 2019, 55, 10689-10692.

About the blogger:

Beth Mundy is a PhD candidate in chemistry in the Cossairt lab at the University of Washington in Seattle, Washington. Her research focuses on developing new and better ways to synthesize nanomaterials for energy applications. She is often spotted knitting in seminars or with her nose in a good book. You can find her on Twitter at @BethMundySci.

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Synthesizing Polymers Using CO2

Ring-opening polymerizations produce commercial polymeric materials including epoxy resins, but they usually liberate small molecules such as the greenhouse gas, CO2. In the context of climate change, it is urgent to reduce CO2 emissions. Recently, a group of UK researchers led by Prof. Charlotte K. Williams at the University of Oxford developed a step-growth polymerization method that self-consumed CO2. The work has been published in a recent issue of Chemical Communications.

The synthesis involved two catalytic cycles (Figure 1). The first cycle polymerized L-lactide-O-carboxyanhydride into poly(L-lactide acid) (PLLA) via a ring-opening polymerization and released one CO2 molecule per polymer repeat unit. In the second cycle, epoxide molecules (cyclohexeneoxide) combined with the CO2 generated in the first step and grew into poly(cyclohexene carbonate) (PCHC) from the terminal ends of the PLLA chains. A di-zinc-alkoxide compound catalyzed both cycles and coupled the two processes together. The product is PLLA-b-PCHC block copolymers, which are composed of PLLA and PCHC covalently tethered together.

Figure 1. The two catalytic cycles are joined by a zinc-based catalyst, [LZn2(OAc)2]. The CO2 gas produced in the first step serves as a reactant in the second step. OCA: O-carboxyanhydride; ROP: ring-opening polymerization; CHO: cyclohexeneoxide; ROCOP: ring-opening copolymerization.

The two reactions resulted in block copolymers with few byproducts. In-situ 1H NMR revealed that the reactants in the first step (LLAOCA) were rapidly consumed during the first four hours (Step I, Figure 2a), and the concentration of PLLA increased notably. The concentration of PCHC only markedly increased after the concentration of PLLA saturated (Step II, Figure 2a). The byproduct of the second step, trans-cyclohexene carbonate, exhibited consistently low concentrations. The pronounced single peak in each size-exclusion chromatogram of the corresponding product confirmed the presence of block copolymers, instead of polymer mixtures (Figure 2b). Although the authors did not fully elucidate the origin of the excellent selectivity towards the block copolymer, they speculated that the change in CO2 partial pressure played a role. Significantly, nearly all CO2 molecules were consumed in the second step, with 91% incorporated into the block copolymer, and 9% converted to the byproduct.

Figure 2. (a) The evolution of the concentrations of PLLA, PCHC, and trans-CHC (the byproduct of the second step) with reaction time. (b) Size-exclusion chromatograms of the products at different reaction times. Mn: number-average molecular weight; Đ: polydispersity.

The authors are investigating the detailed polymerization mechanism, as well as identifying new catalysts to expand the polymerization scheme to other polymers.

 

To find out more, please read:

Waste Not, Want Not: CO2 (Re)cycling into Block Copolymers

Sumesh K. Raman, Robert Raja, Polly L. Arnold, Matthew G. Davidson, and Charlotte K. Williams

Chem. Commun., 2019, 55, 7315-7318

 

About the blogger:

Tianyu Liu obtained his Ph.D. (2017) in Chemistry from University of California, Santa Cruz in the United States. He is passionate about scientific communication to introduce cutting-edge research to both the general public and scientists with diverse research expertise. He is a blog writer for Chem. Commun. and Chem. Sci. More information about him can be found at http://liutianyuresearch.weebly.com/.

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Guiding Light with Molecular Crystals

We’re all used to communications and computing happening at high, and seemingly ever-increasing speeds. Continuing on this trajectory requires the development of materials capable of acting as micro/nanoscale waveguides that don’t experience interference effects from strong external electromagnetic fields. Molecular crystals represent an exciting but relatively under-explored materials class due to their inherently limited emission and absorption properties. However, an international group of researchers recently combined two different crystalline materials with complementary optical properties in a filled-hollow crystal architecture, involving no binding materials or polymer matrices.

Figure 1. Spectra and structure of DCA (left) and PDI (right).

The group used 9,10-dicyanoanthracine (DCA) as the hollow outer crystal, with a perylene diimide derivative (PDI) as the interior compound (Figure 1). When combined, these two compounds exhibit fluorescence that covers the visible and near-IR portions of the electromagnetic spectrum. The researchers grew hollow crystals of DCA with diameters ranging from 50-400 μm in diameter with pores of 10-200 μm and filled them with 1-50 μm PDI crystal fibrils manually by hand(!) (Figure 2) (I honestly can’t imagine how many crystals ended up broken during that experimental learning curve!). The assembled structure for study had a single hollow DCA crystal filled with 18 individual PDI fibrils to create the waveguide.

Figure 2. Schematic of hollow crystal architecture (top) with demonstration of construction (bottom).

When the researchers excited the full structure with a 365 nm continuous wavelength LED, both crystal components emitted light that was guided down to the opposite end. The specific makeup of the spectrum depends on the point of illumination; only the excited compounds emit. This supports the active waveguiding capabilities of the materials. The emissive properties can also be controlled by changing the excitation wavelengths to exclude the absorbance of one of the molecular crystals. PDI can be selectively excited using light above 550 nm and both PDI and DCA act simply as passive waveguides for light in the infrared region of the spectrum, of particular importance for wireless communication. This study represents an exciting next step for organic molecular materials as optical waveguides with a new architecture for devices.

To find out more please read:

A filled organic crystal as a hybrid large-bandwidth optical waveguide

Luca Catalano, Patrick Commins, Stefan Schramm, Durga Prasad Karothu, Rachid Rezgui, Kawther Hadef and Panče Naumov

Chem. Commun, 2019, 55, 4921-4924.

About the blogger:

Beth Mundy is a PhD candidate in chemistry in the Cossairt lab at the University of Washington in Seattle, Washington. Her research focuses on developing new and better ways to synthesize nanomaterials for energy applications. She is often spotted knitting in seminars or with her nose in a good book. You can find her on Twitter at @BethMundySci.

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ChemComm: Our Vision

Vision statement

“ChemComm is the Royal Society of Chemistry’s most cited journal, and has a long history of publishing exciting new findings of exceptional significance, across the breadth of chemistry.

With its Communication format, we recognise the importance of rapid disclosure of your work, and we are proud that our times to publication remain among the fastest in the field.

Our vision for ChemComm is to maintain our longstanding tradition of quality, trust and fairness, and we encourage you to join our community by publishing your most exciting research with us.”

Véronique Gouverneur, Editorial Board Chair

Scope

ChemComm is committed to publishing findings on new avenues of research, drawn from all major areas of chemical research, from across the world. Main research areas include (but are not limited to):

  • Analytical chemistry
  • Biomaterials chemistry
  • Bioorganic/medicinal chemistry
  • Catalysis
  • Chemical Biology
  • Coordination Chemistry
  • Crystal Engineering
  • Energy
  • Sustainable chemistry
  • Green chemistry
  • Inorganic chemistry
  • Inorganic materials
  • Main group chemistry
  • Nanoscience
  • Organic chemistry
  • Organic materials
  • Organometallics
  • Physical chemistry
  • Supramolecular chemistry
  • Synthetic methodology
  • Theoretical and computational chemistry

Learn more about ChemComm online! Submit your latest high impact research here!

Keep up-to-date with our latest journal news on Twitter @ChemCommun or via our blog!

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