U.S. patent application number 14/766401 was filed with the patent office on 2016-05-05 for methods of separating molecules.
The applicant listed for this patent is THE TRUSTEES OF PRINCETON UNIVERSITY. Invention is credited to Eric L. FIRST, Christodoulos A. FLOUDAS, M.M. Faruque HASAN.
Application Number | 20160121258 14/766401 |
Document ID | / |
Family ID | 51300109 |
Filed Date | 2016-05-05 |
United States Patent
Application |
20160121258 |
Kind Code |
A1 |
FIRST; Eric L. ; et
al. |
May 5, 2016 |
METHODS OF SEPARATING MOLECULES
Abstract
Disclosed herein are new methods, machines, processes, and
systems for separating molecules by determining better materials
and process optimization conditions. As a result of these advances,
this disclosure provides improved carbon dioxide capture, better
flue gas treatments, and more efficient methods of purifying gases
have been developed. Optimal sorbents can be obtained by using a
computational screening method that selects microporous structures
(e.g. zeolites and metal-organic frameworks) from a database of
materials with the greatest potential for cost-effective
separations. The disclosed methods are the first to consider both
the size and shape of the adsorbent material. This is also the
first disclosure to consider the process application and cost when
selecting which material to use.
Inventors: |
FIRST; Eric L.; (Princeton,
NJ) ; HASAN; M.M. Faruque; (Princeton, NJ) ;
FLOUDAS; Christodoulos A.; (Princeton, NJ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
THE TRUSTEES OF PRINCETON UNIVERSITY |
Princeton |
NJ |
US |
|
|
Family ID: |
51300109 |
Appl. No.: |
14/766401 |
Filed: |
February 5, 2014 |
PCT Filed: |
February 5, 2014 |
PCT NO: |
PCT/US14/14893 |
371 Date: |
August 6, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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61761436 |
Feb 6, 2013 |
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61765284 |
Feb 15, 2013 |
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61873940 |
Sep 5, 2013 |
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61889296 |
Oct 10, 2013 |
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61926561 |
Jan 13, 2014 |
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Current U.S.
Class: |
95/139 |
Current CPC
Class: |
B01D 2257/504 20130101;
Y02C 10/08 20130101; B01D 2257/80 20130101; Y02C 20/40 20200801;
B01D 53/26 20130101; B01D 53/04 20130101; B01D 2257/7025 20130101;
B01D 2253/108 20130101; B01D 2256/245 20130101; B01D 2257/102
20130101; Y02C 20/20 20130101; B01D 2253/116 20130101; B01D 53/047
20130101; B01D 2253/204 20130101; G06F 30/00 20200101 |
International
Class: |
B01D 53/04 20060101
B01D053/04; G06F 17/50 20060101 G06F017/50 |
Goverment Interests
STATEMENT REGARDING UNITED STATES GOVERNMENT FUNDING
[0002] This invention was made with government support under Grant
No. A0000994101 awarded by the University of Minnesota (University
of Minnesota Prime from the National Science Foundation Prime Award
No. EFRI-0937706); Grant No. CBET-1263165 awarded by the National
Science Foundation; and Government support under FA9550-11-C-0028
awarded by the DoD, Air Force Office of Scientific Research,
National Defense Science and Engineering Graduate (NDSEG)
Fellowship, 32 CFR 10 168a. The Government has certain rights in
the invention.
Claims
1. A method for separating molecules comprising: identifying
molecules in need of separation; identifying potential adsorbents
for separating the molecules; characterizing the pore structure of
the said potential adsorbents; minimizing the cost of carbon
dioxide capture and/or compression for potential adsorbents by
solving a mathematical model; ranking potential adsorbents based on
cost; treating the molecules in need of separation with a ranked
potential adsorbent.
2. The method of claim 1, wherein the molecules in need of
separating are chosen from hydrocarbons, nitrogen, oxygen, carbon
dioxide, and water.
3. The method of claim 2, wherein the molecules in need of
separating are chosen from CH.sub.4, CO.sub.2, N.sub.2, O.sub.2,
and H.sub.2O.
4. The method of claim 2, wherein the molecules in need of
separating are chosen from CH.sub.4, CO.sub.2, and N.sub.2.
5. The method of claim 1, comprising identifying minimum purity
standards.
6. The method of claim 1, comprising identifying minimum recovery
standards.
7. The method of claim 1, comprising ranking the potential
adsorbents according to shape and size.
8. The method of claim 1, comprising generating adsorption
isotherms for said potential adsorbents.
9. The method of claim 1, comprising calculating the adsorption
selectivity for said potential adsorbents.
10. The method of claim 1, comprising identifying process
conditions.
11. A method for selecting process conditions comprising:
minimizing the cost of carbon dioxide capture and/or compression
for a database of potential sorbents by solving a mathematical
model for process and material parameters.
12. The method of claim 11, wherein the process parameters include
one or more chosen from column length, adsorption pressure,
blowdown pressure, evacuation pressure, step duration for
adsorption, step duration for blowdown, and step duration for
evacuation.
13. The method of claim 12, wherein the process parameters include
all of the following: column length, adsorption pressure, blowdown
pressure, evacuation pressure, step duration for adsorption, step
duration for blowdown, and step duration for evacuation.
14. The method of claim 12, wherein the process parameters include
all of the following: column length, adsorption pressure,
evacuation pressure, step duration for adsorption, and step
duration for evacuation.
15. The method of claim 11, comprising selecting a process chosen
from pressure-swing adsorption, vacuum-swing adsorption,
temperature-swing adsorption, pressure-and-temperature-swing
adsorption, and vacuum-and-temperature-swing adsorption, simulated
moving bed adsorption, membrane-based separation, or any separation
process utilizing said microporous materials or their
derivatives.
16. The method of claim 11, wherein the database is filtered by one
or more material or process metrics.
17. The method of claim 16, wherein the material metrics are chosen
from limiting diameter, largest cavity diameter, accessible pore
volume, accessible surface area, shape selectivity, size
selectivity, pore selectivity, adsorption selectivity, permeation
selectivity, adsorption isotherms, diffusion coefficient,
permeability, minimum parasitic energy, and working capacity.
18. The method of claim 16, wherein the process metrics are chosen
from purity, recovery, energy penalty, and cost.
19. A molecular separation optimization system comprising: a
database of porous materials; a pore characterization means; a
separation process model; a means for minimizing the cost of a
model process; and a means for presenting the results to a system
user.
20. The system of claim 19, wherein the porous materials are chosen
from zeolites, metal-organic frameworks, zeolitic imidazolate
frameworks, silicates, aluminosilicates, titanosilicates, activated
carbons, carbon molecular sieves, and covalent-organic
frameworks.
21. (canceled)
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Provisional Patent
Application Nos. 61/926,561 (filed Jan. 13, 2014), 61/873,940
(Filed Sep. 5, 2013), 61/765,284 (filed Feb. 15, 2013), 61/761,436
(filed Feb. 6, 2013), and 61/889,296 (filed Oct. 19, 2013), the
contents of which are incorporated by reference in their
entirety.
BRIEF DESCRIPTION OF THE DRAWINGS
[0003] FIG. 1 shows a flow chart for an exemplary method of
separating gases by optimizing a mathematical model of a separation
process.
[0004] FIG. 2 shows a flow chart for an exemplary method of
separating carbon dioxide gas from methane gas.
[0005] FIG. 3 shows a flow chart for an exemplary method of
separating carbon dioxide gas from nitrogen gas.
[0006] FIG. 4 shows an exemplary gas separation process, applied to
methane purification.
[0007] FIG. 5 shows an exemplary pressure swing adsorption process
cycle configuration, applied to methane purification.
[0008] FIG. 6 shows an exemplary gas separation process, applied to
capturing carbon dioxide from flue gas.
[0009] FIG. 7 shows an exemplary pressure swing adsorption process
cycle configuration, applied to capturing carbon dioxide from flue
gas.
BACKGROUND
[0010] Separating mixtures of two or more molecular entities into
purified forms has challenged chemical engineers for centuries. The
field is constantly seeking new approaches and better means for
separating mixtures of molecules.
[0011] Every molecular separation involves the concentration of a
target molecule or molecules from a mixture of molecules.
Separation is the reverse of mixing, which requires a suitable
medium or material for separation, a driving force or energy to
achieve the specified separation, and a process to perform the
specified separation. Among the decisions that one needs to make
while designing an industrial separation, the following three are
especially critical: (i) which material to select from the universe
of potential materials, (ii) which process and which configuration
of the process to use that would give the best separation, and
(iii) which set or sets of operating conditions that the process
should use to achieve the best separation.
[0012] As processes for separating molecules have evolved, some
approaches have grown in complexity, requiring multiple steps and
machines. Previous separation methods only considered each of the
three above-listed strategies in isolation. By focusing only on one
area at a time, the interplay between strategies has been ignored
by the art. Such isolated studies have resulted in suboptimal
selection of materials, process configurations, and operating
conditions.
[0013] Selecting an appropriate material can be complicated because
not all molecules show equal affinity to adhere, absorb, adsorb,
desorb, or pass through a given material. Some molecules adsorb
more strongly onto the material surface than others, while some
molecules pass through a material more easily than others. Even the
groups of materials which have high internal surface areas and pore
volumes for adsorption-based separation, such as zeolites and metal
organic frameworks (MOFs), have hundreds and thousands of members
to select from. Furthermore, the selection of materials varies with
separation. Accordingly, a material appropriate for separating CO2
from power plant flue gases may not be appropriate for separating
CO2 from natural gas, or separating H2 from synthesis gas and so
on.
[0014] While material selection is central to any molecular
separation, it is equally important to select a process
configuration and optimize its performance. Many different
separation processes exist, which can be used to perform molecular
separation. The most widely used technologies include distillation,
absorption, adsorption and membrane-based processes. These
technologies are commercially implemented for different gas
separation applications. For instance, many amine-based chemical
absorption, solid sorbent-based pressure swing adsorption (PSA),
and polymeric material-based membrane processes are used in the
chemical and power industries to remove acid gases from natural
gas, flue gas, fuel gas and so on. Major sorbents for the
adsorption-based separation include microporous/mesoporous silica
or zeolites, activated carbonaceous materials and MOFs.
[0015] A separation process, either absorption, adsorption or
membrane-based process, can be designed in different modes and can
have different configurations. For instance, adsorption-based
separation offers three operational modes, namely Pressure Swing
Adsorption (PSA), Vacuum Swing Adsorption (VSA), and Temperature
Swing Adsorption (TSA). One major difference between the PSA and
VSA processes is the difference in their operating pressure levels.
The highest operating pressure in a VSA process is atmospheric,
while it can be more than atmospheric in a PSA process. The
performance of these two processes can be significantly different
for different feed compositions and flow rates, product
specifications, and adsorbents.
[0016] Technologies focusing on adsorption-based processes do not
consider material selection as an integral part of the
investigation, though alternative materials have the potential to
require less energy and cost, even for a fixed process type and
configuration. In fact, very few technologies consider
effectiveness of a material when used in a process. While
adsorption selectivity, equilibrium saturation capacity and minimum
parasitic energy are good screening metrics for identifying a
sorbent, the common fallibility of these metrics is that they are
all evaluated at equilibrium conditions. However, in practice, an
adsorption-based process often operates distantly from equilibrium.
The selection of a material depends on, among others, its
selectivity and affinity toward the target molecule, sorption
equilibrium and kinetics, regeneration and cost.
[0017] Transient breakthrough simulations of several highly
adsorption-selective zeolites and MOFs are used to identify
zeolites and MOFs which would exhibit large adsorption
selectivities for a given separation target. However, large
adsorption selectivity does not always guarantee the most
cost-effective separation. In many studies, the equilibrium
saturation capacities of the targeted molecules in different
materials are used to select the so-called "best" material for
adsorption. Some other technologies outline methods to calculate
the minimum parasitic energy required to separate a molecule (e.g.,
CO2 from flue gases) with an intention to screen materials. When
applied to an adsorption-based process, this metric is calculated
by taking into account the energy consumption due to heating, the
heat of desorption during regeneration, and associated operations.
These technologies do not consider the performance of materials
when used in actual process configurations.
[0018] In addition, the industrial scale deployment of
adsorption-based systems would require both the material and
process development. Therefore, identifying attainable process
configurations with realistic and optimum operational conditions
are crucial in evaluating a material's performance. Often it is the
case that a material shows great promise with high adsorption
capacity or very low theoretical parasitic energy or a high
adsorption selectivity, but when put in a real process cannot even
separate CO2 with the required purity and recovery. Among those
materials, which are able to attain the required purity and
recovery, some exhibit high energy penalty and process cost.
[0019] It is important to optimize the cost impact of a separation
process. To realize the full potential of a process, it is crucial
to optimize its performance. However, the rigorous optimization of
a complex separation process is challenging. For instance, the
adsorption-based processes such PSA and VSA are usually multi-step
and adsorbent-packed distributed processes that undergo a transient
state before reaching a cyclic steady state. PSA and VSA are cyclic
processes for which the performance varies with the column size,
cycle configuration, step durations and pressure levels in each
step. Adsorption-based process models include nonlinear algebraic
and partial differential equations (NAPDEs).
[0020] Contributions have been made for the optimization of PSA and
VSA processes. For instance, a mixed-integer nonlinear optimization
(MINLP) model with time averaged mass and energy balances has been
used for the design of a PSA process for the minimum annualized
cost. Some studies have proposed partial or full discretization of
the NAPDEs describing a PSA model. The resulting large-scale
nonlinear programming (NLP) model is usually solved using
commercial solvers. The efficacy of such approach has been
demonstrated for the air separation using rapid PSA and modified
PSA processes. Sequential quadratic programming (SQP)-based
approaches and direct optimization approaches have been also used
to optimize PSA processes. However, solving a detailed NAPDE model
for PSA/VSA optimization has remained as a challenge.
DETAILED DESCRIPTION
[0021] Advances in molecular separation have now been made.
Disclosed herein are new methods for separating molecules by
determining better materials and process optimization conditions.
Thanks to the disclosed advances, better carbon dioxide capture and
better flue gas treatments have been developed.
[0022] Advances in identifying sorbents for molecular separations
have now been made. For example, better sorbents can be obtained by
using a computational screening method that selects microporous
structures (e.g. zeolites and metal-organic frameworks) from a
database of materials with the greatest potential for
cost-effective separations. The disclosed methods are the first to
consider both the size and shape of the adsorbent material. This is
also the first disclosure to consider the process application,
process design, and process optimization when selecting which
material to use.
[0023] Screening microporous structures by both pore size and shape
has proven useful for identifying new microporous materials for
separating molecules. The disclosed method considers both the
material as well as the process, so it indicates both the
feasibility and performance of a material and the optimal process
parameters for performing the separation. The disclosed methods
consider several metrics, including process cost, when selecting
the best materials from large databases of possibilities through an
efficient screening procedure.
[0024] The disclosed pore characterization methods for zeolites and
metal-organic frameworks provide better information about the
geometry and topology of the porous networks, including a
three-dimensional visualization and quantitative data including
portals, channels, cages, connectivity, pore size distribution,
accessible volume, accessible surface area, largest cavity
diameter, and pore limiting diameter. (First, E. L., Gounaris, C.
E., Wei, J., and Floudas, C. A. Phys. Chem. Chem. Phys.,
13:17339-17358, 2011; First, E. L., Floudas, C. A. Micropor.
Mesopor. Mater., 165:32-39, 2013).
[0025] The shape-selective screening approach has applications for
both separations as well as catalysis applications, where the
selectivity data can be extended to reactants, products, and
transition state structures. The disclosed methods are demonstrated
for carbon capture, but the methodology is applicable to any
separation application, and can be combined with other process
models beyond pressure-swing adsorption (PSA) and vacuum-swing
adsorption (VSA).
[0026] The above methods provide the first holistic approach to
identifying the optimal sorbents for separation applications. Such
methods effectively combine material selection with process
optimization to generate a short list of candidate sorbents from a
large database of microporous materials.
[0027] The disclosed methods build on existing methods for
evaluating microporous materials for separation applications
(adsorption selectivity, Henry constant, working capacity, total
equilibrium capacity, and minimum parasitic energy), while also
introducing new metrics that are demonstrated to select good
candidates for cost-effective materials. One such metric is shape
selectivity, which is a measure of the degree to which the zeolite
can separate one molecule from another (or multiple others) based
on shape and size exclusion, i.e., "shape selectivity" and "size
selectivity".
[0028] Shape selectivity considers the hindrance to molecular
transport through the most dominant pathway of a microporous
structure. Shape selectivity emphasizes finding a material capable
of high throughput, where diffusion through the main pores is much
faster for one molecule compared to another, and may be
particularly appropriate for membrane or diffusion-limited
applications. (Gounaris, C. E., Floudas, C. A., and Wei, J. Chem.
Eng. Sci., 61:7933-7948, 2006; Gounaris, C. E., Wei, J., and
Floudas, C. A. Chem. Eng. Sci., 61:7949-7962, 2006; Gounaris, C.
E., Wei, J., Floudas, C. A., AIChE J., 56:611-632, 2009; First, E.
L., Gounaris, C. E., and Floudas, C. A. Langmuir, 29:5599-5608,
2013).
[0029] The disclosed methods are the first to utilize the metric of
size selectivity, which takes into account the entire distribution
of pore sizes. Size selectivity is a measure of relative difference
in accessible pore volume between two molecules. In adsorption
processes, side channels can play a key role, as molecules may fill
into smaller pores of a structure, making size selectivity
particularly appropriate. (Hasan, M. M. F., First, E. L., and
Floudas, C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013).
[0030] The methods of this disclosure apply the new metric of pore
selectivity, which combines the shape-based energetic calculations
of shape selectivity with pore accessibility calculations of size
selectivity. It is a measure of the energetically-weighted
accessibility of the pore system for one molecule compared to the
other. (First, E. L., Hasan, M. M. F., and Floudas, C. A.
Unpublished manuscript)
[0031] One advantage of the disclosed methods is that they combine
material selection with process optimization by calculating the
cost of the optimal process utilizing each material. This is
achieved via a detailed nonlinear algebraic and partial
differential equation (NAPDE)-based non-isothermal adsorption model
that describes the overall separation process. (Hasan, M. M. F.,
Baliban, R. C., Elia, J. A., and Floudas, C. A. Ind. Eng. Chem.
Res., 51:15665-15682, 2012; Hasan, M. M. F., First, E. L., and
Floudas, C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013). The
disclosed methods optimize the separation process based on major
independent variables, which may include but are not limited to
column length, adsorption pressure, blowdown pressure,
desorption/evacuation pressure, and the step durations for
adsorption, blowdown, and desorption/evacuation, to minimize the
total annualized cost subject to purity and recovery
constraints.
[0032] The methods of this disclosure leverage an efficient
Kriging-based grey-box optimization formulation. (Hasan, M. M. F.,
Baliban, R. C., Elia, J. A., and Floudas, C. A. Ind. Eng. Chem.
Res., 51:15665-15682, 2012; Hasan, M. M. F., First, E. L., and
Floudas, C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013). The
result is that we not only select cost-effective materials for a
separation application, but also simultaneously provide the optimal
process conditions.
[0033] One advantage of the above method is identifying new, better
materials for separating molecules. This disclosure provides new
sorbents. This disclosure provides new zeolites and metal-organic
framework (MOF) sorbents. This disclosure provides new methods for
using these sorbents in molecular separations. This disclosure
provides new methods of treating flue gases, including a new
dehydration method. This disclosure provides new methods for
purifying methane.
[0034] In one embodiment, the disclosed methods are used for
post-combustion carbon capture from power plant flue gases
(separation of CO2 from primarily N2). Disclosed are 13 zeolite
framework types with a process cost for carbon capture and
compression up to 150 bar that is lower than the process cost using
zeolite 13X, the most popular and commercially available zeolite
for this application. These framework types are: AHT, NAB, MVY,
ABW, AWO, WEI, VNI, TON, OFF, ITW, LTF, ERI, and MOZ. These new
sorbent materials provide better, more cost effective carbon
capture benefits than the state of the art zeolites.
[0035] We have also identified a number of novel sorbents for
methane purification (separation of CO2 from primarily CH4). For
example, we have identified 10 zeolite framework types that are
both feasible (meaning that the purity of the methane product is at
least 97% and at least 95% of the methane is recovered) and
cost-effective for some feed conditions. Eight of these zeolites
are feasible for all feed conditions in the range of 5%-50% CO2
content. The process cost for these zeolites includes the recovery
and compression of methane, and the capture and compression of
CO2.
[0036] This disclosure provides the following 10 new zeolite
framework types for separating carbon dioxide from methane: WEI,
AHT, AEN, ABW, APC, BIK, JBW, LTJ, MON, and NSI. The materials
consistently in the top 5 for each feed condition are WEI, AHT, and
AEN.
[0037] In one embodiment, this disclosure provides cost-effective
materials for adsorption-based separation of carbon dioxide (CO2)
from nitrogen (N2). The processes and compositions are useful for
capturing CO2 from flue gas. The applications include (but are not
limited to) separating CO2 from the following sources: coal-fired
power plants, natural gas-fired power plants, oil-fired power
plants, power plants that burn any carbonaceous fuels, agricultural
processing plants, ammonia plants, asphalt plants, cement plants,
refineries, natural gas processing plants, ethanol plants,
petrochemical plants, iron and steel plants, paper and wood plants,
sugar plants, and utility plants.
[0038] In one embodiment, this disclosure provides cost-effective
materials for adsorption-based separation of carbon dioxide (CO2)
from methane (CH4). The processes and compositions are useful for
purifying methane. Methane purification includes (but is not
limited to) purifying the following: natural gas, shale gas,
coalbed methane, enhanced oil recovery (EOR) gas, biogas, and
landfill gas.
[0039] The improved adsorbent materials were identified using a
novel computational framework that combines material screening and
process optimization. This in silico framework selects the most
cost-effective materials for a separation application from a
diverse range of feed conditions, including composition, pressure,
temperature, and flow rate. The selected materials minimize
investment and operating costs while satisfying stringent purity
and recovery constraints.
[0040] In one embodiment, the disclosed methods include the
following: geometric-level pore topology characterization via pore
characterization; unique metrics including shape, size, and pore
selectivities; atomistic-level molecular simulations on only a
subset of the original databases; and adsorption selectivity as a
screening stage rather than the final ranking.
[0041] In one embodiment, the process optimization portion of the
disclosed methods has advantages including the following: feed
dehydration to remove water, either pressure swing or vacuum swing
adsorption modes to achieve the optimal adsorption; CO2 capture
coupled with compression for sequestration; independently operating
multiple and identical adsorption columns; blowdown to an
intermediate pressure to increase CO2 purity.
[0042] In one embodiment, the process optimization portion of the
disclosed methods has advantages including the following: either
compression or expansion of the feed to achieve the optimal
adsorption; CO2 capture coupled with compression for sequestration;
independently operating multiple and identical adsorption columns;
and product compression and power integration between the feed
expander and the product compressor to minimize energy
consumption.
[0043] The disclosed methods provide the first disclosure of using
the above identified zeolites for carbon capture from flue gas
(separation of CO2 from N2) or methane purification (separation of
CO2 from methane). These zeolites perform these separations with
minimal cost.
[0044] In one embodiment, the disclosed methods include a new
material screening metric ("pore selectivity") to accommodate
molecules with a non-circular footprint.
[0045] In one embodiment, the disclosed methods include screening
criteria for filtering materials from a zeolite database.
[0046] In one embodiment, the disclosed methods include different
force field parameters for adsorption calculations.
[0047] In one embodiment, the disclosed methods include an improved
isotherm fitting algorithm. (Hasan, M. M. F., First, E. L., and
Floudas, C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013).
[0048] In one embodiment, the disclosed methods include dehydration
of the feed.
[0049] In one embodiment, the disclosed methods include process
choice, allowing pressure swing or vacuum swing adsorption
modes.
[0050] In one embodiment, the disclosed methods include process
choice, allowing feed expansion or compression.
[0051] In one embodiment, the disclosed methods include expansion
through an expansion turbine.
[0052] In one embodiment, the disclosed methods include selecting a
pressure reducing means.
[0053] In one embodiment, the disclosed methods include a tool for
determining the cost-effectiveness of using an expansion
turbine.
[0054] In one embodiment, the disclosed methods include a blowdown
step to an intermediate pressure to increase CO2 purity.
[0055] In one embodiment, the disclosed methods include process
conditions including two products (both CO2 and methane are
products) that are extracted from the adsorption column at
different steps in the cycle.
[0056] In one embodiment, the disclosed methods include conditions
wherein each product is compressed to a different pressure.
[0057] In one embodiment, the disclosed methods include maximum
operating pressure in the range of 1-60 bar.
[0058] In one embodiment, the disclosed methods include a means for
selecting cost-effective materials for carbon capture for a range
of feed conditions, including CO2 levels from 5% to 50%.
[0059] In one embodiment, the disclosed methods include a means for
selecting cost-effective materials for methane purification for a
range of feed conditions, including CO2 levels from 5% to 50%.
[0060] Disclosed herein is a method of separating molecules
comprising: [0061] identifying molecules in need of separation;
[0062] identifying potential adsorbents for separating the
molecules; [0063] characterizing the pore structure of the said
potential adsorbents; [0064] minimizing the cost of carbon dioxide
capture and/or compression for potential adsorbents by solving a
mathematical model; [0065] ranking potential adsorbents based on
cost; [0066] treating the molecules in need of separation with a
ranked potential adsorbent.
[0067] As used herein, the term "molecules in need of separation"
means two or more molecules that are present in a mixture such that
it is desired to separate the mixture into two or more portions of
different compositions such that the concentration of one or more
of the molecules is higher in one or more of the portions than it
is in the original mixture. In one embodiment, the molecules in
need of separating are two components of a binary mixture that are
desired to be separated into two portions such that one of the
molecules has a higher concentration in one of the portions than in
the original mixture.
[0068] As used herein, the term "potential adsorbents" means a set
of adsorbents that may or may not be able to perform a desired
separation for molecules in need of separation.
[0069] As used herein, the term "adsorbent" means a material
capable of adsorbing other molecules onto its surface. For example,
adsorbents may include zeolites, metal-organic frameworks, zeolitic
imidazolate frameworks, silicates, aluminosilicates,
titanosilicates, activated carbons, carbon molecular sieves, and
covalent-organic frameworks.
[0070] As used herein, the term "separating the molecules" means a
process by which a mixture containing molecules in need of
separation is separated into two or more portions of different
compositions such that the concentration of one or more of the
molecules is higher in one or more of the portions than it is in
the original mixture.
[0071] As used herein, the term "characterizing the pore structure"
means analysis of the crystal structure or other description of a
porous material to describe quantitatively or qualitatively the
pore structure of that material. In one embodiment, characterizing
the pore structure is the process by which the geometry and
topology of the pores of a porous material are described, and this
description is used to calculate derived quantities, such as pore
limiting diameter, largest cavity diameter, and other data.
[0072] As used herein, the term "minimizing the cost" means the
application of optimization with the objective of identifying the
lowest cost within specified limitations.
[0073] As used herein, the term "minimizing the cost of carbon
dioxide capture and/or compression" means minimizing the cost of a
process to separate carbon dioxide from a mixture of molecules and
compressing the carbon dioxide to increase its pressure.
[0074] As used herein, the term "treating the molecules" means a
process by which a mixture containing molecules in need of
separation is separated by putting the mixture into contact with an
adsorbent.
[0075] In one embodiment of the method, the molecules in need of
separating are chosen from hydrocarbons, nitrogen, oxygen, carbon
dioxide, and water.
[0076] As used herein, the term "hydrocarbons" means the group of
molecules with composition containing only carbon and hydrogen, as
well as derivatives of such molecules, including those additionally
containing oxygen or sulfur.
[0077] As used herein, the term "nitrogen" means a gas with the
molecular formula N2.
[0078] As used herein, the term "oxygen" means a gas with the
molecular formula O2.
[0079] As used herein, the term "carbon dioxide" means a gas with
the molecular formula CO2.
[0080] As used herein, the term "water" means a compound with the
molecular formula H2O.
[0081] In one embodiment of the method, the molecules in need of
separating are chosen from CH4, CO2, N2, O2, and H2O.
[0082] In one embodiment of the method, the molecules in need of
separating are chosen from CH4, CO2, and N2.
[0083] In one embodiment, the method of separating molecules
comprises identifying minimum purity standards.
[0084] As used herein, the term "minimum purity standards" means
the lowest acceptable concentration of a molecule of interest in a
mixture of molecules.
[0085] In one embodiment, the method of separating molecules
comprises identifying minimum recovery standards.
[0086] As used herein, the term "minimum recovery standards" means
the lowest acceptable amount of a molecule of interest that must be
present in the purified portion of an original mixture after
separation.
[0087] In one embodiment, the method of separating molecules
comprises ranking the potential adsorbents according to shape and
size.
[0088] As used herein, the term "ranking the potential adsorbents"
means a process of selecting and/or ordering a set of adsorbents
based on a metric.
[0089] In one embodiment, the method of separating molecules
comprises generating adsorption isotherms for said potential
adsorbents.
[0090] As used herein, the term "adsorption isotherms" means a
relationship between the equilibrium adsorption capacity and the
partial pressure or concentration of a molecule when it is adsorbed
onto the surface of an adsorbent at a given temperature.
[0091] In one embodiment, the method of separating molecules
comprises calculating the adsorption selectivity for said potential
adsorbents.
[0092] As used herein, the term "calculating the adsorption
selectivity" means a process to quantitatively assess and compare
the adsorption affinity of a molecule onto an adsorbent surface
relative to the adsorption affinity of another molecule onto the
same adsorbent surface.
[0093] In one embodiment, the method of separating molecules
comprises identifying process conditions.
[0094] Disclosed herein is a method for selecting process
conditions comprising: minimizing the cost of carbon dioxide
capture and/or compression for a database of potential sorbents by
solving a mathematical model for process and material
parameters.
[0095] As used herein, the term "database" means a collection of
information.
[0096] As used herein, the term "mathematical model" means a set of
mathematical expressions and/or equations intended to describe the
behavior of a system.
[0097] As used herein, the term "process parameters" means the
properties, actions, and/or operational decisions that affect a
process. In one embodiment of the method, the process parameters
include one or more chosen from: column length, adsorption
pressure, blowdown pressure, evacuation pressure, step duration for
adsorption, step duration for blowdown, and step duration for
evacuation.
[0098] As used herein, the term "material parameters" means the
physical and chemical properties associated with a material.
[0099] As used herein, the term "column" means a vessel containing
an adsorbent.
[0100] As used herein, the term "column length" means the length of
a column.
[0101] As used herein, the term "adsorption pressure" means the
pressure at which a mixture of molecules in need of separation
enters the column, some of which are retained within the adsorbent
while others pass through for a period of time.
[0102] As used herein, the term "blowdown pressure" means the
pressure at which the column is retained for a period of time to
purge some of the undesired molecules retained inside the
column.
[0103] As used herein, the term "evacuation pressure" means the
pressure at which the column is retained for a period of time to
purge some of the desired molecules retained inside the column.
[0104] As used herein, the term "step duration for adsorption"
means a period of time in which the column is maintained at the
adsorption pressure.
[0105] As used herein, the term "step duration for blowdown" means
a period of time in which the column is transitioning to and
maintained at the blowdown pressure.
[0106] As used herein, the term "step duration for evacuation"
means a period of time in which the column is transitioning to and
maintained at the evacuation pressure.
[0107] In one embodiment, the method for selecting process
conditions comprises selecting a process chosen from pressure-swing
adsorption, vacuum-swing adsorption, temperature-swing adsorption,
pressure-and-temperature-swing adsorption, and
vacuum-and-temperature-swing adsorption, simulated moving bed
adsorption, membrane-based separation, or any separation process
utilizing said microporous materials or their derivatives.
[0108] As used herein, the term "pressure-swing adsorption" means a
process by which a mixture of molecules separated by contacting it
with an adsorbent at one pressure and desorbing the adsorbed
molecules at another pressure.
[0109] As used herein, the term "vacuum-swing adsorption" means a
pressure-swing adsorption process in which the desorption occurs at
a pressure at or lower than atmospheric pressure.
[0110] As used herein, the term "temperature-swing adsorption"
means a process by which a mixture of molecules separated by
contacting it with an adsorbent at one temperature and desorbing
the adsorbed molecules at another temperature.
[0111] As used herein, the term "pressure-and-temperature-swing
adsorption" means a process by which a mixture of molecules
separated by contacting it with an adsorbent at one pressure and
temperature and desorbing the adsorbed molecules at another
pressure and temperature.
[0112] As used herein, the term "vacuum-and-temperature-swing
adsorption" means a pressure-and-temperature swing adsorption
process in which the desorption occurs at a pressure at or lower
than atmospheric pressure.
[0113] As used herein, the term "simulated moving bed adsorption"
means a process by which a mixture of molecules separated based on
concentration gradient and sequential switching of ports between
adsorbent beds.
[0114] As used herein, the term "membrane-based separation" means a
process by which a mixture of molecules separated using a
membrane.
[0115] In one embodiment of the method, the database is filtered by
one or more material or process metrics.
[0116] In one embodiment the method comprises choosing material
metrics from pore limiting diameter, largest cavity diameter,
accessible pore volume, accessible surface area, shape selectivity,
size selectivity, pore selectivity, adsorption selectivity,
permeation selectivity, adsorption isotherms, diffusion
coefficient, permeability, minimum parasitic energy, and working
capacity.
[0117] As used herein, the term "pore limiting diameter" means the
largest characteristic guest molecule size for which there is a
non-zero accessible adsorbent volume.
[0118] As used herein, the term "largest cavity diameter" means the
maximum of the pore size distribution for adsorbent pores.
[0119] As used herein, the term "accessible pore volume" means the
volume of pores of an adsorbent which is accessible to a guest
molecule.
[0120] As used herein, the term "accessible surface area" means the
surface area of pores of an adsorbent which is accessible to a
guest molecule.
[0121] As used herein, the term "selectivity" means capability of a
material to preferentially interact with one molecular species over
another.
[0122] As used herein, the term "shape selectivity" means
selectivity derived from a difference in molecular shape.
[0123] As used herein, the term "size selectivity" means
selectivity derived from a difference in molecular size.
[0124] As used herein, the term "pore selectivity" means
selectivity derived from a difference in molecular accessibility in
the pores.
[0125] As used herein, the term "adsorption selectivity" means
selectivity derived from a difference in adsorption.
[0126] As used herein, the term "permeation selectivity" means
selectivity derived from a difference in permeability.
[0127] As used herein, the term "diffusion coefficient" means a
constant which is defined as the ratio of the molar flux due to
molecular diffusion and the gradient in the concentration of the
molecule.
[0128] As used herein, the term "permeability" means the degree of
permeation of a molecule relative to the permeation of another
molecule through a membrane.
[0129] As used herein, the term "minimum parasitic energy" means
the minimum electric load imposed on a power plant when an
additional process is installed and operated. In one embodiment,
the minimum parasitic energy is the minimum electric load imposed
on a power plant by a carbon dioxide separation process.
[0130] As used herein, the term "working capacity" means the net
adsorption capacity of an adsorbent when separating a molecule from
a mixture of molecules in need of separation. In one embodiment,
the working capacity is the difference between the adsorption
capacity during adsorption and desorption.
[0131] In one embodiment, the method for selecting process
conditions comprises choosing process metrics from purity,
recovery, energy penalty, and cost.
[0132] As used herein, the term "purity" means the degree to which
a molecule is mixed or unmixed with other molecules in a given
mixture of molecules. In one embodiment, purity means the
concentration of a molecule present in a mixture of molecules.
[0133] As used herein, the term "recovery" means the amount of a
molecule of interest present in the purified portion of an original
mixture after separation.
[0134] As used herein, the term "energy penalty" means the energy
load imposed to a power plant by a separation process.
[0135] As used herein, the term "cost" means the expense (monetary,
energetic, or other resources) of constructing and/or operating a
process. In one embodiment, cost is the total monetary expense
incurred in the form of investment, operating, maintenance,
material and others. In one embodiment, cost is the energy penalty
required to operate the separation process.
[0136] Disclosed herein is a molecular separation optimization
system comprising: [0137] a database of porous materials; [0138] a
pore characterization means; [0139] a separation process model;
[0140] a means for minimizing the cost of a model process; and
[0141] a means for presenting the results to a system user.
[0142] In one embodiment of the molecular separation optimization
system, the porous materials are chosen from zeolites,
metal-organic frameworks, zeolitic imidazolate frameworks,
silicates, aluminosilicates, titanosilicates, germanosilicates,
activated carbons, and carbon molecular sieves.
[0143] As used herein, the term "zeolites" means an open
three-dimensional framework structure composed of
tetrahedrally-coordinated atoms ("T-atoms") connected with oxygen
atoms. Typically, the T-atoms include silicon and aluminum, but may
also include phosphorus, titanium, beryllium, germanium, and other
metals. The structure may include extra-framework cations, such as
hydrogen, sodium, potassium, barium, calcium, magnesium, iron,
gallium, germanium, and others. The zeolite may include defects,
such as the result of dealumination and desilication processes. The
zeolite may include adsorbed material, including water, gases, and
organic materials, such as the result of chemical vapor deposition,
chemical liquid deposition, coking, and adsorption processes. The
zeolite may include mesopores. The zeolite may be present in a
binder, such as to form a powder or pellet.
[0144] As used herein, the term "metal-organic frameworks" means a
compound composed of metal ions or clusters coordinated to organic
ligands, called linkers, to form a regular structure.
[0145] As used herein, the term "zeolitic imidazolate frameworks,
silicates" means metal organic frameworks composed of metal ions
tetrahedrally coordinated to imidazole ligands.
[0146] As used herein, the term "aluminosilicates" means a mineral
composed of aluminum, silicon, oxygen, and cations.
[0147] As used herein, the term "titanosilicates" means a mineral
composed of titanium, silicon, oxygen, and cations.
[0148] As used herein, the term "germanosilicates" means a mineral
composed of germanium, silicon, oxygen, and cations.
[0149] As used herein, the term "activated carbons" means carbon
processed to introduce pores.
[0150] As used herein, the term "carbon molecular sieves" means
carbon processed to introduce pores of a precise and uniform
size.
[0151] In one embodiment of the molecular separation optimization
system, the porous materials are chosen from zeolites and
metal-organic frameworks.
EXAMPLES
[0152] The following examples are illustrative only, and are not
intended to be limiting of the invention, as claimed.
Example 1
Process Optimization
[0153] Potential zeolites and metal-organic frameworks were
identified based on their pore sizes using ZEOMICS and MOFomics,
three-dimensional pore characterization methods. (First, E. L.,
Gounaris, C. E., Wei, J., and Floudas, C. A. Phys. Chem. Chem.
Phys., 13:17339-17358, 2011; First, E. L., Floudas, C. A. Micropor.
Mesopor. Mater., 165:32-39, 2013). The identified materials were
ranked based on shape selectivity and size selectivity. The top
structures were selected. Adsorption isotherms were generated for
those top structures. The Henry constants were calculated for those
top structures. Those top structures were further filtered based on
adsorption selectivity. For each sorbent on the short list of
remaining candidates, a PSA/VSA process was optimized (using the
algorithm depicted in FIG. 1) to obtain the minimum process cost,
and the corresponding purity, recovery and energy penalty, using a
detailed mathematical model. (Hasan, M. M. F., Baliban, R. C.,
Elia, J. A., and Floudas, C. A. Ind. Eng. Chem. Res.,
51:15665-15682, 2012; Hasan, M. M. F., First, E. L., and Floudas,
C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013). FIG. 3 shows
a flow chart representation of the material selection and process
optimization method.
Example 2
Carbon Capture from Power Plant Flue Gas
[0154] New, better zeolites for carbon capture from power plant
flue gases were identified by using the disclosed methods and
systems. A flow chart of the material screening and process
optimization method is shown in FIG. 3. The accessible volume,
accessible surface area, pore limiting diameter (PLD), and largest
cavity diameter (LCD) data were calculated for each of 199 silica
zeolite structures with pore characterizations from our database,
ZEOMICS. (First, E. L., Gounaris, C. E., Wei, J., and Floudas, C.
A. Phys. Chem. Chem. Phys., 13:17339-17358, 2011) Shape selectivity
was calculated for CO2 versus N2 for each material. (Gounaris, C.
E., Floudas, C. A., and Wei, J. Chem. Eng. Sci., 61:7933-7948,
2006; Gounaris, C. E., Wei, J., and Floudas, C. A. Chem. Eng. Sci.,
61:7949-7962, 2006; Gounaris, C. E., Wei, J., Floudas, C. A., AIChE
J., 56:611-632, 2009; First, E. L., Gounaris, C. E., and Floudas,
C. A. Langmuir, 29:5599-5608, 2013). Size selectivity was
calculated for CO2 versus N2 for each material. (Hasan, M. M. F.,
First, E. L., and Floudas, C. A. Phys. Chem. Chem. Phys.,
15:17601-17618, 2013).
[0155] In a screening process, zeolites with shape selectivity
greater than 0 or size selectivity greater than 0.15 were selected
for further consideration. CO2 and N2 adsorption isotherms were
generated for each of these structures at 25.degree. C. to
calculate adsorption selectivity. (Hasan, M. M. F., First, E. L.,
and Floudas, C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013).
Zeolites with adsorption selectivity less than 10 were filtered
out. CO2 and N2 adsorption isotherms at four additional
temperatures (50.degree. C., 75.degree. C., 100.degree. C., and
125.degree. C.) were calculated for the remaining structures, which
were fit to a dual-site Langmuir model.
[0156] The equilibrium performance of the selected zeolites was
evaluated by using a dual-site Langmuir model fitted with
equilibrium isotherm data generated using grand canonical Monte
Carlo (GCMC) simulations. (Hasan, M. M. F., First, E. L., and
Floudas, C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013).
[0157] To determine whether the transport into the solid phase is
controlled by micropore or macropore diffusion, the mass transfer
resistances in micropores and macropores were estimated and
compared at linear equilibrium.
[0158] The calculated micropore and macropore resistances suggested
that macropore resistance controls the rate of intraparticle mass
transfer, which in the case of zeolite-based CO2 capture, also
controls the inter-phase mass transfer. The mass transfer rate
between the gas and solid phases was attained by using a linear
driving force (LDF) model. (Hasan, M. M. F., Baliban, R. C., Elia,
J. A., and Floudas, C. A. Ind. Eng. Chem. Res., 51:15665-15682,
2012; Hasan, M. M. F., First, E. L., and Floudas, C. A. Phys. Chem.
Chem. Phys., 15:17601-17618, 2013).
Example 3
Capturing Carbon Dioxide from Flue Gas
[0159] To evaluate the performance of the top adsorption-selective
zeolites in an adsorption process, the following were used: (a) PSA
cycle model, (b) a process configuration model, and (c) a detailed
adsorption/desorption model for the process.
[0160] FIG. 7 shows four steps in a cycle along with their usual
pressure profiles. FIG. 6 shows a process diagram. Feed gas is used
in step 1 for pressurizing the bed and in step 2 for CO2 adsorption
at the adsorption pressure. In the forward blowdown step (step 3),
adsorbed N2 is purged by reducing the column pressure to an
intermediate pressure. In the last step, the adsorbed CO2 is
desorbed by further reducing the column pressure. Starting from an
initial bed condition, the process undergoes a transient state for
a number of cycles before reaching a cyclic steady state, which is
where the initial and final conditions for a cycle appear to be the
same. In this example, when the process is started with sorbent
saturated with N2, cyclic steady state is usually reached after
about 50 cycles.
Example 4
Configuration of a CO2 Capture Process
[0161] As shown in FIG. 6, the above 4-step PSA cycle (shown in
FIG. 7) can operate in either PSA or VSA mode. In PSA mode, feed
gas enters through inlet a where a compressor compresses the gas to
the adsorption pressure, while in VSA mode, an inlet is used to
feed the gas at atmospheric pressure. The feed is considered to be
a mixture of 14% CO2 and 86% N2 at 1 kmol/s. Multiple columns
packed with adsorbent zeolites are used, and the total number of
columns is calculated using the procedure outlined. (Hasan, M. M.
F., Baliban, R. C., Elia, J. A., and Floudas, C. A. Ind. Eng. Chem.
Res., 51:15665-15682, 2012; Hasan, M. M. F., First, E. L., and
Floudas, C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013).
Example 5
Separating Carbon Dioxide from Nitrogen
[0162] FIG. 7 shows a 4-step PSA cycle with corresponding pressure
profiles. FIG. 6 shows a process diagram. Each column has three
different outlets. One outlet is used to vent the non-adsorbed gas
during the adsorption step; a second outlet is used to purge mostly
N2 during the blowdown step; a third outlet is used to recover the
product CO2 during the evacuation step. A vacuum pump is placed at
an outlet to purge N2 out of the system. Similarly, a second vacuum
pump is placed at an outlet to extract CO2 at the lowest pressure.
Lastly, the extracted CO2 is compressed to send to the
sequestration site using a 6-stage compressor system with
interstage cooling.
[0163] A detailed nonlinear algebraic and partial differential
equation (NAPDE)-based non-isothermal adsorption model was used to
describe the overall PSA process. (Hasan, M. M. F., Baliban, R. C.,
Elia, J. A., and Floudas, C. A. Ind. Eng. Chem. Res.,
51:15665-15682, 2012; Hasan, M. M. F., First, E. L., and Floudas,
C. A. Phys. Chem. Chem. Phys., 15:17601-17618, 2013). The model was
used to evaluate a multi-component adsorption system in an
adsorbent-packed column with non-isothermal adsorption/desorption
including frictional pressure drop. Temperature and
pressure/velocity effects and heat transfer resistance across the
column wall were also evaluated.
Example 6
Optimizing the PSA Process for Carbon Capture
[0164] The disclosed methods were used to minimize the total
annualized cost of CO2 capture and compression using the 4-step PSA
process to obtain CO2 at 150 bar for storage. In this example, the
minimum purity and recovery were both set to be 90%. The NAPDE
model included seven major independent variables, namely column
length, adsorption pressure, blowdown pressure, evacuation
pressure, and the durations for adsorption, blowdown, and
evacuation.
[0165] The optimization method is depicted in FIG. 1. The following
process steps were performed: (i) solving the original NAPDE model
at several fixed conditions to generate input-output data
(samples), (ii) developing a Kriging-based surrogate model using
the samples, (iii) optimizing the surrogate model for subsequent
samplings, and (iv) repeating steps (ii) and (iii) until
convergence to an optimal solution. The PSA optimization was
performed for each selected zeolite generating a rank-ordered list
of cost-effective sorbents. Combinatorial optimization-based
techniques were applied for the simultaneous selection of materials
and processes for cost-effective separation.
Example 7
Separation of Carbon Dioxide from Methane
[0166] The material screening and process optimization method is
shown in FIG. 2. Candidate zeolites were identified for separating
CO2 from methane. Zeolites with shape selectivity greater than 0,
size selectivity greater than 0.1, or pore selectivity greater than
0.1 were selected for further consideration. For zeolites meeting
these requirements, CO2 and methane adsorption isotherms were
generated at 25.degree. C. to calculate adsorption selectivity.
Zeolites with adsorption selectivity less than 10 were filtered out
from further consideration. For the remaining structures, CO2 and
methane adsorption isotherms were constructed at four additional
temperatures (50.degree. C., 75.degree. C., 100.degree. C., and
125.degree. C.), which were fit to a dual-site Langmuir model.
[0167] A dual-site Langmuir model fitted with equilibrium isotherm
data generated using grand canonical Monte Carlo (GCMC) simulation
was used to evaluate the equilibrium performance of the selected
zeolites. To determine whether the transport into the solid phase
was controlled by micropore or macropore diffusion, the mass
transfer resistances in micropores and macropores at linear
equilibrium were evaluated.
[0168] The process diagram is depicted in FIG. 4. The feed can be
expanded or compressed to reach the optimal adsorption pressure.
One or multiple identical zeolite-packed adsorption columns were
used for adsorption. Since CO2 is selectively adsorbed over methane
in many zeolites, most of the methane fed into a column passed
through without being adsorbed. The clean methane was then
compressed to 60 bar to meet the specification for pipeline
transportation.
[0169] A desorption (evacuation) vacuum pump was used for column
regeneration. The desorption vacuum pump was placed at the feed-end
of a column to purge most of the residual CO2 and methane at
moderate or low vacuum. CO2 from the vacuum pump was compressed to
150 bar for sequestration by using a 6-stage compression train with
intercoolers and a pressure ratio of 2.3 at each stage.
[0170] The PSA process was optimized to minimize the total
annualized cost of CO2/methane separation and compression using the
3-step PSA process (illustrated in FIG. 5) to obtain methane at 60
bar for transportation and CO2 at 150 bar for transportation for
utilization or sequestration.
[0171] A NAPDE model using the following five independent variables
was used: column length, adsorption pressure, desorption pressure,
and the step durations for adsorption and desorption.
Example 8
Determining Conditions for Separating CO2 from a Flue Gas
Comprising a Mixture of CO2 and N2
[0172] From a database of microporous materials, potential zeolites
were identified based on their pore sizes using a three dimensional
characterization method. These materials were ranked based on shape
selectivity and size selectivity. Next, zeolites with highest
rankings from both lists of shape-selective and size-selective
materials were selected. Complete adsorption isotherms were
calculated for CO2 and N2 by using the crystal structures of the
selected materials. The Henry constants were calculated for these
materials. The materials were additionally screened based on
adsorption selectivity. Each selected zeolite was represented by
its isotherm model. For the zeolites meeting the cut-off criteria
for shape or size selectivity and adsorption selectivity, PSA/VSA
process was optimized to obtain the minimum capture and compression
cost and the corresponding purity, recovery and energy penalty
using a detailed mathematical model. The minimum cost of capture
and compression was used as the final metric to compare those
zeolites that can capture CO2 with at least 90% purity and 90%
recovery.
Example 9
Capturing CO2 from Coal-Fired Power Plant Flue Gas
[0173] In this example, the feed gas was composed of 15% H2O and
85% non-aqueous gases. Of the non-aqueous gases, 14% was CO2 and
86% was N2 and O2. The flow rate was 1 kmol/s.
[0174] Notably, the operating conditions remain the same for other
flow rates, except that the number of columns or number of trains
(identical process configurations operating in parallel) may
change. In all cases, feed dehydration is independent of
sorbent.
[0175] The following process conditions were used:
TABLE-US-00001 Unit Operating conditions Description Direct contact
Temp.: 55 .fwdarw. 35.degree. C. Removes water from gas cooler
mixture (up to 5.5%) TEG-absorber Temp. 35.degree. C., Removes
water from gas mixture (up to 0.1%) Heater Temp.: 73.degree. C.
Heats water-rich solvent Vacuum flash P: 0.04 bar Removes water
from solvent unit using vacuum flash Cooler Temp.: 65.degree. C.
Cools water-lean solvent
[0176] All sorbents utilized a pressurization step time of 20 s. In
each case, the pressurization step brought the column pressure from
the evacuation step pressure to the adsorption step pressure. All
sorbents used two adsorption columns. However, any number of
columns could be used by applying the disclosed optimization
methods.
TABLE-US-00002 Adsorp- Adsorp- Blow- Blow- Evac- Evac- tion tion
down down uation uation Column step step step step step step Zeo-
length pressure duration pressure duration pressure duration lite
(m) (bar) (s) (bar) (s) (bar) (s) AHT 1 2.01 33.73 0.65 49.26 0.03
74.45 NAB 1.08 5.86 20.26 0.61 35.83 0.05 68.59 MVY 1.03 1.94 23.66
0.38 39.43 0.01 82.2 ABW 1 2.34 31.88 0.48 50.77 0.02 69.97 AWO 1
2.2 50 0.35 55.13 0.02 100 WEI 1.03 1.91 20.47 0.39 43.32 0.01
80.74 VNI 1 3.32 24.79 0.59 63.06 0.02 79.91 TON 1 2.92 20 0.39
72.43 0.03 92.8 OFF 1 2.91 30.16 0.36 72.2 0.03 100 ITW 1 2.8 30.22
0.32 72.66 0.03 98.63 LTF 1 2.82 29.76 0.47 82.75 0.02 100 ERI 1
3.08 27.25 0.45 66.54 0.02 87.79 MOZ 1 1.67 28.73 0.29 74.22 0.01
100
[0177] The CO2 compression process is independent of sorbent. The
CO2 compression process is as follows:
TABLE-US-00003 Unit Operating conditions Description 6-stage
CO.sub.2 6 stages with intercoolers, each Compresses CO.sub.2
compression train having a pressure ratio of 2.33 up to 150 bar
Example 10
Purification of Natural Gas
[0178] In this example, the feed was a mixture of CH4 and CO2 at
0.1 kmol/s.
[0179] The same operating conditions can be used for other flow
rates, except that the number of columns or number of trains
(identical process configurations operating in parallel) may
change. Such changes could be recognized and applied by an ordinary
artisan using the disclosed methods.
[0180] In this example, all sorbents and conditions have
pressurization step time of 20 s. In this example, all sorbents and
conditions use a column length of 1 m.
[0181] The following conditions were applied to purifying
methane:
TABLE-US-00004 Number Adsorption Adsorption Desorption Desorption
of step step step step Zeolite columns pressure (bar) duration (s)
pressure (bar) duration (s) Feed is 5% CO2, 95% CH4 ABW 2 3 77.22
0.09 69.4 AHT 2 2.64 100 0.08 80 APC 2 3.74 87.67 0.1 80 WEI 2 3.42
61.24 0.1 52.93 AEN 2 2.63 83.28 0.07 80 BIK 2 2.52 100 0.07 80 JBW
2 2.75 100 0.08 80 LTJ 2 5 46.18 0.07 61.34 MON 2 3.26 100 0.09 80
NSI 2 4.24 70 0.01 80 Feed is 10% CO2, 90% CH4 WEI 2 5 54.78 0.1
68.11 ABW 2 2.92 70 0.08 80 AEN 2 2.91 70 0.08 72.25 AHT 2 4.01 40
0.1 46.34 APC 2 3.61 70 0.1 80 BIK 2 2.99 70 0.08 80 MON 2 3.24 70
0.1 80 JBW 2 3.35 70.27 0.08 80 Feed is 20% CO2, 80% CH4 AHT 2 5 40
0.1 56.33 WEI 2 3 40 0.09 55.74 AEN 2 3.62 70 0.09 79.08 APC 2 2.26
48.59 0.06 64.19 BIK 2 2.56 63.54 0.06 80 JBW 2 2.69 50.15 0.09
60.31 MON 2 2.27 70 0.07 80 ABW 2 1.99 40 0.05 42.86 Feed is 30%
CO2, 70% CH4 WEI 2 3.6 40 0.1 51.65 AEN 2 3 64.55 0.07 80 APC 2
1.97 41.13 0.06 60.04 AHT 1 3.61 47.9 0.1 127.78 JBW 2 2.6 44.75
0.08 60.94 MON 2 1.89 70 0.05 80 BIK 1 3 40 0.05 120.48 ABW 2 1.65
40 0.02 54.72 Feed is 40% CO2, 60% CH4 WEI 2 3 45.89 0.06 62.65 AHT
2 2.06 40 0.05 55.9 AEN 2 3 40 0.08 49.56 MON 1 3.08 40 0.07 150
APC 1 2.29 40 0.05 143.12 BIK 1 2.18 40 0.05 145.08 JBW 2 2.98
40.55 0.07 43.62 ABW 1 1.35 42.55 0.02 135.65 Feed is 50% CO2, 50%
CH4 WEI 2 4.5 40 0.1 57.41 AEN 1 2.9 40 0.07 135.08 MON 1 2.14 40
0.04 150 JBW 1 2.65 40 0.07 150 AHT 1 3 40 0.02 137.03 BIK 1 1.48
42.85 0.03 129.87 APC 1 1.69 40 0.04 80 ABW 1 1.25 41.14 0.01
150
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