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Chemical Structure| 937-41-7

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Lin, Yi-hung ; Clinch, McKenna F ; Beckingham, Bryan S ;

Abstract: CO2 reduction cells are innovative devices that convert CO2 into valuable chemicals, such as formate (OFm-) and acetate (OAc-), at the cathode. One of the key challenges in these devices is the development of ion exchange membranes that enable the transport of charge carriers between electrodes while minimizing the transfer of CO2 reduction products. This study focuses on the preparation and characterization of crosslinked anion exchange membranes (AEMs) made of phenyl acrylate (PA) and (3-acrylamidopropyl) trimethylammonium chloride (APTA), crosslinked with either poly(ethylene glycol) diacrylate (PEGDA) or N,N’-methylenebisacrylamide (MBAA). The membranes are characterized to understand their physiochemical properties and corresponding transport behavior through characterization of water volume fraction, mechanical properties, ionic conductivity, ion exchange capacity, water contact angle, glass transition temperature as well as their permeability and solubility to formate and acetate. MBAA crosslinked membranes exhibit higher Young’s modulus and lower strain at break compared to PEGDA-crosslinked membranes, which is attributed to their shorter chain length. Within a series of membranes of varied comonomer content, for either PEGDA or MBAA as crosslinker, permeabilities generally follow free volume theory (increasing permeability with increasing water content where water content increases with decreasing crosslinker content). Interestingly, for membranes with different crosslinkers but analogous water volume fraction significant differences (∼2 orders of magnitude) in permeability are observed which we attribute to differences in chain mobility as characterized through the glass transition temperature.

Purchased from AmBeed:

Adam L. Bachmann ; Brock Hunter ; Bryan S. Beckingham ;

Abstract: Ammonia is a promising carbon-free fuel, but current methods to produce ammonia are energy intensive. New methods are thereby needed, with one promising method being electrochemical nitrogen reduction cells. Efficient cell operation requires robust catalysts but also efficient membrane separators that permit the selective transport of ions while minimizing the transport of the products across the cell. Commercial membranes have an unknown morphology which makes designing improved cells challenging. To address this problem, we synthesized a series of membranes with controlled crosslinking density and chemical composition to understand their impact on ammonium transport. Higher crosslinking density led to lower ammonium permeability. At the highest crosslinking density, similar ammonium permeability was observed independent of the water volume fraction and hydrophobicity of the monomers. These results suggest new directions to develop membranes with reduced ammonium crossover to improve the efficiency of these electrochemical cells.

Keywords: cation exchange membrane ; sulfonic acid ; nitrogen reduction

Purchased from AmBeed:

Lin, Yi-hung ; Kim, Jung Min ; Beckingham, Bryan S. ;

Abstract: Produced water is a byproduct of industrial operations, such as hydraulic fracturing for increased oil recovery, that causes environmental issues since it includes different metal ions (e.g., Li+, K+, Ni2+, Mg2+, etc.) that need to be extracted or collected before disposal. To remove these substances using either selective transport behavior or absorption-swing processes employing membrane-bound ligands, membrane separation procedures are promising unit operations. This study investigates the transport of a series of salts in crosslinked polymer membranes synthesized using a hydrophobic monomer (Ph acrylate, PA), a zwitterionic hydrophilic monomer (sulfobetaine methacrylate, SBMA), and a crosslinker (methylenebisacrylamide, MBAA). Membranes are characterized according to their thermomech. properties, where an increased SBMA content leads to decreased water uptake due to structural differences within the films and to more ionic interactions between the ammonium and sulfonate moieties, resulting in a decreased water volume fraction, and Young′s modulus increases with increasing MBAA or PA content. Permeabilities, solubilities, and diffusivities of membranes to LiCl, NaCl, KCl, CaCl2, MgCl2, and NiCl2 are determined by diffusion cell experiments, sorption-desorption experiments, and the solution-diffusion relationship, resp. Permeability to these metal ions generally decreases with an increasing SBMA content or MBAA content due to the corresponding decreasing water volume fraction, and the permeabilities are in the order of K+ > Na+ > Li+ > Ni2+ > Ca2+ > Mg2+ presumably due to the differences in the hydration diameter

Keywords: zwitterionic membranes ; salt transport ; phenyl acrylate ; crosslinked

Purchased from AmBeed:

Kim, Jung Min ; Lin, Yi-hung ; Bannon, Sean M. ; Geise, Geoffrey M. ; Beckingham, Bryan S. ;

Abstract: Understanding the mixed solute transport behavior of CO2 reduction products (methanol and formate) in ion exchange membranes (IEMs) is of interest for CO2 reduction cells (CO2RCs). The role of an IEM in a typical CO2RC is to suppress the crossover of all CO2 reduction products while allowing the transport of electrolytes. Tuning the polymer rigidity of the membrane is a key contributor to such highly controlled transport of organic solutes in a dense hydrated membrane. Here, we study the mixed solute transport behavior of methanol and formate in a series of tough Ph acrylate-based cross-linked IEMs. We then study the effects of a structural modification on mixed solute transport behavior by introducing quaternary carbons within the membrane. We measured the relative permittivity properties of swollen films to determine if the water hydrogen bonding environment within the IEMs, which is related to maintaining selective ion transport within the membrane (electrolytes over CO2 reduction products), was impacted by various organic solutes. We observed films with methacrylate backbone linkages have effectively constant relative permittivities when exposed to solutions containing methanol, formate, and a mix thereof. These findings may assist in designing membranes for applications, including CO2 reduction cells and water-organic separation

Purchased from AmBeed:

Membrane science ; Polymer chemistry ; Ion exchange membranes ; Multi-solute transport ; Charge screening ; Crosslinked membranes

Abstract: As global climate change is a major concern which is accelerated by CO2 emissions, we need to reduce CO2 emissions from the environment. In order to do that, researchers conceptualized CO2 reduction cells which electrochemically convert CO2 to other chemicals such as CO or methanol. A major problem faced by such devices is the crossover of the CO2 reduction products (i.e. methanol (MeOH), formate (OFm-), and acetate (OAc-)) through ion exchange membranes (IEM) which reduces the efficiency of the cell. Therefore, it is critical to design IEMs that suppress the transport of CO2 reduction products. Towards this goal, our group has been investigating the transport behavior of these products in crosslinked PEGDA-based IEMs, where we observed the diffusivities of cation exchange membranes to OFm- and OAc- increased in co-diffusion with MeOH, which is a concerning behavior. Here, we prepared analogous films with a series of phenyl- containing comonomers of different chain lengths [i.e. phenyl acrylate (PA, n = 0), phenyl ether acrylate (PEA, n = 1), and poly(ethylene glycol) phenyl ether acrylate (PEGPEA, n = 3)]. We then measured the permeabilities of these films toto OFm- and OAc-, where we observed the permeabilities of films with the shorter chain length [PEGDA-PA (n = 0)] to be lower than films with longer comonomer chain lengths. This work lays the foundation for further understanding of transport in these films, where in the future we will measure permeabilities to MeOH, cotransport MeOH-OFm-, and MeOH-OAc- as well as the solubilities of these species within the films.

Purchased from AmBeed:

Jung Min Kim ; Yuyang Wang ; Yi-hung Lin ; Jaesik Yoon ; Tina Huang ; Dong-Joo Kim , et al.

Abstract: Ion exchange membranes (IEMs) are crucial for direct fuel cells, including direct methanol and direct urea fuel cells (DUFCs). While commercially available IEMs (e.g., FAA-3-50) show decent power density in direct fuel cells, they experience considerable methanol or urea crossover, reducing device performance and motivating design of IEMs that suppress fuel crossover. Here, we prepare cross-linked IEMs with high mechanical toughness utilizing a cross-linker (methylenebis(acrylamide)), hydrophobic monomer (phenyl acrylate (PA) or phenyl methacrylate (PMA)), and charged monomer (2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS) for cation exchange or methacroylcholine chloride (MACC) for anion exchange). To validate these membranes in a fuel cell application, we perform DUFC experiments utilizing a PA/MACC AEM and observe good power density compared to FAA-3-50. To understand the role of urea crossover in DUFC performance, permeabilities of both membranes to urea are measured by diffusion cells with in situ ATR-FTIR spectroscopy, where our PA/MACC exhibited lower urea permeability than FAA-3-50.

Purchased from AmBeed:

Kim, Jung Min ;

Abstract: The ion exchange membrane (IEM) is a crucial part of various applications from water purification (i.e. electrodialysis) to energy conversion (i.e. photoelectrochemical CO2 reduction cells (PEC-CRC) and direct urea fuel cells (DUFC)). Theoretically, these approaches are more profitable and eco-friendly than their alternatives, such as distillation and fossil fuels. However, a major drawback of these applications is the selectivity of existing IEMs not being adequate (i.e. crossover of undesired solutes). Moreover, each application requires a different membrane specification. For instance, membranes for PEC-CRCs should be minimizing the crossover of CO2 reduction products (i.e. methanol (MeOH), ethanol (EtOH), formate (OFm-), acetate (OAc-)), while allowing the permeation of electrolytes (i.e. bicarbonate (HCO3-)). In the case of DUFC, membranes should minimize the crossover of urea to avoid catalyst sweeping effect. To design target-specific membranes, we took three series of investigations, which are (1) understanding alcohol-carboxylate co-transport behavior in IEMs, (2) analyzing the impact of charge-neutral comonomers in cation exchange membranes (CEM), and (3) introducing a new class of IEMs. From the first series, we conjectured a charge screening behavior based on the carboxylate diffusivity of CEMs being increased and that of anion exchange membranes (AEM) being decreased in co-diffusion with an alcohol. From the second series, we conjectured the interaction between different two dissimilar pendant groups on polymer network can offset the charge screening behavior in CEMs, where the carboxylate diffusivity in CEMs with sulfopropyl groups and poly(ethylene glycol) phenyl ether (PEGPE) groups being consistent in co-diffusion with alcohol. From the third series, we introduced a new class of crosslinked IEMs with phenyl acrylate (hydrophobic monomer). More findings from each series of investigations will be discussed in corresponding sections.

Keywords: Membrane science ; Polymer chemistry ; Ion exchange membranes ; Multi-solute transport ; Charge screening ; Crosslinked membranes

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Alternative Products

Product Details of [ 937-41-7 ]

CAS No. :937-41-7
Formula : C9H8O2
M.W : 148.16
SMILES Code : C=CC(OC1=CC=CC=C1)=O
MDL No. :MFCD00048145
InChI Key :WRAQQYDMVSCOTE-UHFFFAOYSA-N
Pubchem ID :61242

Safety of [ 937-41-7 ]

GHS Pictogram:
Signal Word:Danger
Hazard Statements:H302-H319-H372-H410
Precautionary Statements:P501-P273-P260-P270-P264-P280-P391-P314-P337+P313-P305+P351+P338-P301+P312+P330
Class:9
UN#:3082
Packing Group:

Computational Chemistry of [ 937-41-7 ] Show Less

Physicochemical Properties

Num. heavy atoms 11
Num. arom. heavy atoms 6
Fraction Csp3 0.0
Num. rotatable bonds 3
Num. H-bond acceptors 2.0
Num. H-bond donors 0.0
Molar Refractivity 42.27
TPSA ?

Topological Polar Surface Area: Calculated from
Ertl P. et al. 2000 J. Med. Chem.

26.3 Ų

Lipophilicity

Log Po/w (iLOGP)?

iLOGP: in-house physics-based method implemented from
Daina A et al. 2014 J. Chem. Inf. Model.

2.04
Log Po/w (XLOGP3)?

XLOGP3: Atomistic and knowledge-based method calculated by
XLOGP program, version 3.2.2, courtesy of CCBG, Shanghai Institute of Organic Chemistry

2.08
Log Po/w (WLOGP)?

WLOGP: Atomistic method implemented from
Wildman SA and Crippen GM. 1999 J. Chem. Inf. Model.

1.78
Log Po/w (MLOGP)?

MLOGP: Topological method implemented from
Moriguchi I. et al. 1992 Chem. Pharm. Bull.
Moriguchi I. et al. 1994 Chem. Pharm. Bull.
Lipinski PA. et al. 2001 Adv. Drug. Deliv. Rev.

2.16
Log Po/w (SILICOS-IT)?

SILICOS-IT: Hybrid fragmental/topological method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

2.02
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

2.02

Water Solubility

Log S (ESOL):?

ESOL: Topological method implemented from
Delaney JS. 2004 J. Chem. Inf. Model.

-2.27
Solubility 0.787 mg/ml ; 0.00531 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Soluble
Log S (Ali)?

Ali: Topological method implemented from
Ali J. et al. 2012 J. Chem. Inf. Model.

-2.26
Solubility 0.811 mg/ml ; 0.00547 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Soluble
Log S (SILICOS-IT)?

SILICOS-IT: Fragmental method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

-2.51
Solubility 0.456 mg/ml ; 0.00308 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Soluble

Pharmacokinetics

GI absorption?

Gatrointestinal absorption: according to the white of the BOILED-Egg

High
BBB permeant?

BBB permeation: according to the yolk of the BOILED-Egg

Yes
P-gp substrate?

P-glycoprotein substrate: SVM model built on 1033 molecules (training set)
and tested on 415 molecules (test set)
10-fold CV: ACC=0.72 / AUC=0.77
External: ACC=0.88 / AUC=0.94

No
CYP1A2 inhibitor?

Cytochrome P450 1A2 inhibitor: SVM model built on 9145 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.83 / AUC=0.90
External: ACC=0.84 / AUC=0.91

No
CYP2C19 inhibitor?

Cytochrome P450 2C19 inhibitor: SVM model built on 9272 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.80 / AUC=0.86
External: ACC=0.80 / AUC=0.87

No
CYP2C9 inhibitor?

Cytochrome P450 2C9 inhibitor: SVM model built on 5940 molecules (training set)
and tested on 2075 molecules (test set)
10-fold CV: ACC=0.78 / AUC=0.85
External: ACC=0.71 / AUC=0.81

No
CYP2D6 inhibitor?

Cytochrome P450 2D6 inhibitor: SVM model built on 3664 molecules (training set)
and tested on 1068 molecules (test set)
10-fold CV: ACC=0.79 / AUC=0.85
External: ACC=0.81 / AUC=0.87

No
CYP3A4 inhibitor?

Cytochrome P450 3A4 inhibitor: SVM model built on 7518 molecules (training set)
and tested on 2579 molecules (test set)
10-fold CV: ACC=0.77 / AUC=0.85
External: ACC=0.78 / AUC=0.86

No
Log Kp (skin permeation)?

Skin permeation: QSPR model implemented from
Potts RO and Guy RH. 1992 Pharm. Res.

-5.73 cm/s

Druglikeness

Lipinski?

Lipinski (Pfizer) filter: implemented from
Lipinski CA. et al. 2001 Adv. Drug Deliv. Rev.
MW ≤ 500
MLOGP ≤ 4.15
N or O ≤ 10
NH or OH ≤ 5

0.0
Ghose?

Ghose filter: implemented from
Ghose AK. et al. 1999 J. Comb. Chem.
160 ≤ MW ≤ 480
-0.4 ≤ WLOGP ≤ 5.6
40 ≤ MR ≤ 130
20 ≤ atoms ≤ 70

None
Veber?

Veber (GSK) filter: implemented from
Veber DF. et al. 2002 J. Med. Chem.
Rotatable bonds ≤ 10
TPSA ≤ 140

0.0
Egan?

Egan (Pharmacia) filter: implemented from
Egan WJ. et al. 2000 J. Med. Chem.
WLOGP ≤ 5.88
TPSA ≤ 131.6

0.0
Muegge?

Muegge (Bayer) filter: implemented from
Muegge I. et al. 2001 J. Med. Chem.
200 ≤ MW ≤ 600
-2 ≤ XLOGP ≤ 5
TPSA ≤ 150
Num. rings ≤ 7
Num. carbon > 4
Num. heteroatoms > 1
Num. rotatable bonds ≤ 15
H-bond acc. ≤ 10
H-bond don. ≤ 5

1.0
Bioavailability Score?

Abbott Bioavailability Score: Probability of F > 10% in rat
implemented from
Martin YC. 2005 J. Med. Chem.

0.55

Medicinal Chemistry

PAINS?

Pan Assay Interference Structures: implemented from
Baell JB. & Holloway GA. 2010 J. Med. Chem.

0.0 alert
Brenk?

Structural Alert: implemented from
Brenk R. et al. 2008 ChemMedChem

2.0 alert: heavy_metal
Leadlikeness?

Leadlikeness: implemented from
Teague SJ. 1999 Angew. Chem. Int. Ed.
250 ≤ MW ≤ 350
XLOGP ≤ 3.5
Num. rotatable bonds ≤ 7

No; 1 violation:MW<1.0
Synthetic accessibility?

Synthetic accessibility score: from 1 (very easy) to 10 (very difficult)
based on 1024 fragmental contributions (FP2) modulated by size and complexity penaties,
trained on 12'782'590 molecules and tested on 40 external molecules (r2 = 0.94)

1.47

Application In Synthesis of [ 937-41-7 ]

* All experimental methods are cited from the reference, please refer to the original source for details. We do not guarantee the accuracy of the content in the reference.

  • Downstream synthetic route of [ 937-41-7 ]

[ 937-41-7 ] Synthesis Path-Downstream   1~1

  • 1
  • [ 19012-02-3 ]
  • [ 937-41-7 ]
  • phenyl (E)-3-(3-acetyl-1-methyl-1H-indol-2-yl)acrylate [ No CAS ]
 

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