Ci a ion: A shad, M.Y.; Ahmad, A.S.;
Mula ski, J.; Modzelewska, A.;
Jackowski, M.; Pawlak-K uczek, H.;
Niedzwiecki, L. Pionee ing he Fu u e:
A T ailblazing Re iew o he Fusion o
Compu a ional Fluid Dynamics and
Machine Lea ning Re olu ionizing
Plasma Ca alysis and Non-The mal
Plasma Reac o Design. Ca alys s 2024,
14, 40. h ps://doi.o g/10.3390/
ca al14010040
Academic Edi o s: Huijuan Wang,
Au o a San os and He Guo
Recei ed: 29 Sep embe 2023
Re ised: 14 Decembe 2023
Accep ed: 27 Decembe 2023
Published: 6 Janua y 2024
Copy igh : © 2024 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
ca alys s
Re iew
Pionee ing he Fu u e: A T ailblazing Re iew o he Fusion o
Compu a ional Fluid Dynamics and Machine Lea ning
Re olu ionizing Plasma Ca alysis and Non-The mal Plasma
Reac o Design
Muhammad Yousa A shad 1,2,* , Anam Suhail Ahmad 3, Jakub Mula ski 4, Aleksand a Modzelewska 5,
Ma eusz Jackowski 5, Halina Pawlak-K uczek 4and Lukasz Niedzwiecki 4,6,*
1Co po a e Sus ainabili y and Digi al Chemical Managemen , In e loop Limi ed, Faisalabad 38000, Pakis an
2School o Chemical Enginee ing, Uni e si y o Adelaide, Adelaide, SA 5005, Aus alia
3Hallibu on Wo ldwide, Hous on, TX 77032-3219, USA; [email p o ec ed]
4Depa men o Ene gy Con e sion Enginee ing, W ocław Uni e si y o Science and Technology,
Wyb. Wyspia´nskiego 27, 50-370 W ocław, Poland; jakub.mula ski@pw .edu.pl (J.M.);
halina.pawlak@pw .edu.pl (H.P.-K.)
5
Depa men o Mic o, Nano and Biop ocess Enginee ing, Facul y o Chemis y, W oclaw Uni e si y o Science
and Technology, No wida 4/6, 50-373 W oclaw, Poland; aleksand a.modzelewska@pw .edu.pl (A.M.);
ma eusz.jackowski@pw .edu.pl (M.J.)
6Ene gy Resea ch Cen e, Cen e o Ene gy and En i onmen al Technologies, VŠB—Technical Uni e si y o
Os a a, 17. Lis opadu 2172/15, 708-00 Os a a, Czech Republic
*Co espondence: [email p o ec ed] (M.Y.A.); lukasz.niedzwiecki@pw .edu.pl (L.N.)
Abs ac : The ad ancemen o plasma echnology is in ica ely linked wi h he u iliza ion o com-
pu a ional luid dynamics (CFD) models, which play a pi o al ole in he design and op imiza ion
o indus ial-scale plasma eac o s. This comp ehensi e compila ion encapsula es he e ol ing
landscape o plasma eac o design, encompassing luid dynamics, chemical kine ics, hea ans e ,
and adia ion ene gy. By employing di e se ools such as FLUENT, Py hon, MATLAB, and Abaqus,
CFD echniques un a el he complexi ies o u bulence, mul iphase low, and species anspo . The
spec um o plasma beha io equa ions, including ion and elec on densi ies, elec ic ields, and
ecombina ion eac ions, is p esen ed in a holis ic manne . The modeling o non- he mal plasma
eac o s, unde pinned by p ecise ma hema ical o mula ions and compu a ional s a egies, is u -
he empowe ed by he in eg a ion o machine lea ning algo i hms o p edic i e modeling and
op imiza ion. F om biomass gasi ica ion o in ica e chemical eac ions, his wo k unde sco es he
e sa ile po en ial o plasma hyb id modeling in eshaping a ious indus ial p ocesses. Wi hin
he sphe e o plasma ca alysis, modeling and simula ion me hodologies ha e pa ed he way o
ans o ma i e p og ess. Encompassing eac o con igu a ions, kine ic pa hways, hyd ogen p oduc-
ion, was e alo iza ion, and beyond, his compila ion o e s a pano amic iew o he mul i ace ed
dimensions o plasma ca alysis. Mic okine ic modeling and ca alys design eme ge as ocal poin s o
op imizing CO
2
con e sion, while he in ica e in e play be ween plasma and ca alys s illumina es
insigh s in o ammonia syn hesis, me hane e o ming, and hyd oca bon con e sion. Le e aging
neu al ne wo ks and ad anced modeling echniques enables p edic i e p owess in he op imiza ion
o plasma-ca aly ic p ocesses. The in eg a ion o plasma and ca alys s o di e se applica ions, om
was e alo iza ion o syngas p oduc ion and di ec CO
2
/CH
4
con e sion, exempli ies he wide-
eaching po en ial o plasma ca alysis in sus ainable p ac ices. Ul ima ely, his an hology unde sco es
he ans o ma i e in luence o modeling and simula ion in shaping he o e on o plasma-ca aly ic
p ocesses, os e ing inno a ion and sus ainable applica ions.
Keywo ds: plasma; non- he mal plasma eac o s; plasma ca alysis
Ca alys s 2024,14, 40. h ps://doi.o g/10.3390/ca al14010040 h ps://www.mdpi.com/jou nal/ca alys s
Ca alys s 2024,14, 40 2 o 24
1. In oduc ion
Recen de elopmen s in e ms o building sus ainable ene gy sys ems ha e led o a
signi ican inc ease in he ins alled powe o in e mi en enewable ene gy sou ces (sola
and wind). This has led o a misma ch be ween supply and demand. The e o e, no able
e o has ecen ly been di ec ed o imp o ing he lexibili y o powe sys ems, which
includes bo h inc easing he lexibili y o con ollable powe sou ces [
1
,
2
] and demand-
side managemen . Capaci y ma ke s ha e been c ea ed in ecen yea s in many coun ies,
including he Scandina ian coun ies [
3
,
4
], G ea B i ain [
5
,
6
], and Poland [
7
]. The lexibili y
o powe uni s can be inc eased h ough he use o plasma o suppo combus ion in powe
plan boile s [
8
–
10
]. Howe e , an equally good measu e o imp o e he lexibili y and
up ake o ene gy sys ems is inc easing demand ela i e o supply om in e mi en sou ces,
which is called demand-side managemen . Wi hin demand-side managemen , echnologies
called powe - o-X a e o pa icula in e es [
11
,
12
] since hey a e capable o u ilizing excess
elec ici y du ing low-demand pe iods and con e ing i o ma ke able p oduc s. The X
in powe - o-X s ands o a p oduc , and i could indica e hyd ogen (P H) [
12
], me hanol
(P M) [
12
], o ammonia (P A) [
12
]. The ad an age o his app oach is no only ha i esul s
in a new p oduc p oduced by using elec ici y pu chased a a ma ginal p ice bu also ha
i a oids he cu ailmen o in e mi en enewable ene gy sou ces a a ime o high supply
and low demand. In he long- e m, changing he ene gy g id in his di ec ion will esul
in highe sha es o enewable ene gy in he powe mix. In ecen yea s, inc eased in e es
has been shown in he applica ion o plasma o hyd ogen p oduc ion [
13
,
14
], he ca aly ic
syn hesis o ammonia [
15
–
18
], he me hana ion o CO
2
o syn he ic na u al gas [
19
,
20
],
he con e sion o CO
2
o alcohols [
21
], and he p oduc ion o nanoma e ials [
22
], o name
bu a ew applica ions. Since plasma is ypically cha ac e ized by i s as s a up [
23
–
26
],
plasma-based echnologies a e o pa icula in e es wi h espec o hei inc eased use in
he demand-side managemen o powe sys ems. Achie ing his equi es indus ial-scale
powe - o-X plasma solu ions [11].
Non- he mal plasma (NTP), which is in a non-equilib ium s a e wi h di e en em-
pe a u es o elec ons, ions, and neu ons [
27
], has been p o en e ec i e in many di e en
applica ions. Clo hiaux, Ko opchak, and Moo e demons a ed he possibili y o he de-
composi ion o he apo o phosphono luo idic acid me hyl-l,2,2- ime hylp opyl es e
using a silen discha ge plasma [
28
]. Dobslaw e al. [
29
] con i med he easibili y o using
non- he mal plasma o he emo al o ola ile o ganic compounds and odo aba emen
in o ganic was e ea men plan s. In ano he wo k, Dobslaw e al. [
30
] showed a syne gy
be ween a non- he mal plasma (dielec ic ba ie discha ge) and he subsequen bio ick-
ling il e . Ande sen e al. [
31
] p o ed ha NTP sys ems could be e ec i ely used o he
aba emen o odo nuisances. NTP could also be applied o wa e pu i ica ion [
32
] as
well as o disin ec ion and s e iliza ion pu poses [
32
,
33
]. Apa om decon amina ion,
NTP can also be e ec i ely used in was ewa e ea men plan s [34], p o iding a easible
means o dealing wi h haza dous chemicals [
35
]. Mo eo e , K am e al. [
36
] epo ed
ha NTP is capable o inducing damage o he cell su ace, which is c i ical in e ms o
medical applica ions, such as disin ec ion o ai o emo e mul id ug- esis an mic obes.
Dobslaw and Glocke [
37
] epo ed he 100% deg ada ion o CF
4
-con amina ed ai a an
indus ial scale using NTP. Helbich e al. [
38
] demons a ed he success ul use o NTP o
he ea men o emissions o s y ene and seconda y emissions o ge ms o med h ough
biological p ocesses, wi h he e iciencies o emo al o ola ile o ganic compounds, ge ms,
and s y ene anging be ween 96 and 98%. Byeon e al. [
39
] in es iga ed he emo al o
gaseous oluene and submic on ae osol pa icles using a dielec ic ba ie discha ge eac-
o and epo ed oluene emo al e iciencies anging be ween 29% and 46%, depending
on he applied ol age, equency, ups eam oluene concen a ion, and esidence ime.
None heless, cau ion is needed in such applica ions since he con e sion o oluene in NTP
could gene a e hea y a oma ic byp oduc s, such as phenyle hyne, indene, naph halene,
and acenaph hylene, as shown by Wnukowski and Mo o´n o mic owa e plasma [
40
].
NTP plasma has been used o a ious applica ions ela ed o gasi ica ion echnologies,
Ca alys s 2024,14, 40 3 o 24
especially conce ning gasi ica ion o was e [
41
] and emo al o a s om p oduce gas [
42
],
which is c i ical om he poin o iew o he main enance and unin e up ed ope a ion
o gasi ie s [
43
,
44
]. Wnukowski e al. [
45
] epo ed a con e sion e iciencies anging
be ween 19 and 100% o a mosphe ic mic owa e plasma p ocessing o p oduce gas om
gasi ica ion o sewage sludge. Kwon and Im [
46
] in es iga ed he easibili y o non- he mal
plasma gasi ica ion o a was e- o-ene gy powe plan wi h an in eg a ed plasma gasi i-
ca ion combined cycle. Pe o med exe gy analysis has shown ha in such sys ems, he
plasma gasi ica ion uni is he one ha con ibu es he mos o he o al exe gy loss [
46
].
Since plasma eac o s exe such a p o ound e ec on he o e all sys emic ene ge ic and
exe ge ic e iciency, i is c ucial o ha e he igh oolse o e icien design o such eac o s.
The ma ch o indus ial-scale plasma eac o s in o new on ie s hinges upon he
seamless in eg a ion o in ica e compu a ional luid dynamics (CFD) models, which ha e
eme ged as indispensable ools o augmen ing eac o design and op imiza ion [
47
,
48
].
Wi hin he mul i ace ed a ena o plasma gene a ion and i s mani old applica ions, a con lu-
ence o a iables o ms, encapsula ing he in icacies o luid dynamics, chemical kine ics,
hea ans e , and adia ion ene gy [
49
,
50
]. This in oduc ion se es as a beacon, illumina -
ing he p o ound signi icance o compu a ional simula ions in decoding he laby in hine
physical and chemical o ches a ion wi hin plasma eac o s. Es eemed so wa e ame-
wo ks, including FLUENT, Py hon, MATLAB, and Abaqus, se e as he e y sca old
upon which in ica e nume ical luid models a e wo en, acili a ing me iculous sc u iny
o phenomena as di e se as u bulence, mul iphase low, and he in ica e mig a ion o
species. Resea che s, h ough elen less inqui y, un eil he pi o al ole o mic okine ic
modeling and he op imiza ion o ca alys s in p opelling he engines o e icien CO
2
con e sion [51,52].
Agains his backd op, modeling me hodologies, such as he in ica e wea e o neu al
ne wo ks, eme ge as indispensable allies, o ecas ing and e ining he e icacy o plasma-
ca aly ic endea o s. The usion o plasma and ca alys s o bi h no el alo iza ion pa h-
ways, o ches a e syngas symphonies, and a ec he me amo phosis o CO
2
and CH
4
s ands as a es amen o he di e se po en ial o plasma ca alysis wi hin he annals o
sus ainable p ac ices.
The aim o his e iew is o summa ize he wo ks on modeling plasma and i s a ious
chemical enginee ing applica ions, hus p o iding an o e iew o he app oaches used o
modeling ca aly ic plasma p ocesses.
2. Modeling and Simula ion in Plasma Ca alysis: Insigh s, S a egies, and Applica ions
Recen in es iga ions unde sco e he pi o al signi icance o modeling and simula ion
in p opelling he on ie o plasma ca alysis esea ch. Nume ous schola ly a icles del e
in o he applica ion o luid models wi hin he ealm o plasma ca alysis, me iculously
emphasizing hei indispensable ole in elucida ing phenomena such as s eame p opa-
ga ion, plasma dynamics, and he in ica e in e play be ween plasma and ca alys [
53
–
55
].
S a egically op imizing plasma pa ame e s and adep ly managing he luxes o eac i e
species s and ou as pi o al ace s in he ealm o plasma ca alysis. Resea ch endea o s
le e age sophis ica ed modeling echniques o sc u inize and p o e s a egic app oaches
o ine- uning eac i e species wi hin plasma ca aly ic sys ems [56,57].
Inno a i ely na iga ing he landscape o modeling app oaches, his e iew me icu-
lously un eils a ans o ma i e ealm wi hin he a i icial neu al ne wo k (ANN) models
and mic o luidic chip-based plasma low chemis y echniques. Beyond con en ional
bounds, i del es in o cu ing-edge in es iga ions on su ace-induced e ec s and plasma-
ca aly ic me hane e o ming. Employing sophis ica ed luid modeling echniques, hese
dedica ed inqui ies yield p o ound insigh s in o he in ica e dynamics o gas-phase edis-
ibu ion e ec s and he nuanced in luence exe ed by ca alys su aces. Cumula i ely, his
schola ly syn hesis accen ua es he no el con ibu ions ha anscend adi ional bound-
a ies, unde sco ing he pa amoun signi icance o modeling and simula ion. Speci ically
ha nessed h ough luid models, his esea ch no only un a els he in icacies o plasma
Ca alys s 2024,14, 40 4 o 24
beha io bu also s ee s he p ecise con ol o eac i e species, p esen ing a pionee ing
bluep in o ine- uning plasma-ca aly ic eac o s ac oss di e se applica ions wi hin he
expansi e domain o plasma ca alysis [58–61].
2.1. Explo ing Modeling and Simula ion in Plasma Ca alysis o Ammonia Syn hesis: Insigh s
and Inno a ions
Resea ch in plasma ca alysis o ammonia syn hesis has been hea ily in luenced by
a ious modeling and simula ion echniques, which ha e played a i al ole in gaining
insigh s and op imizing he p ocess. A signi ican po ion o he li e a u e ocuses on mi-
c okine ic modeling and luid dynamics, seeking o explo e he con ibu ions o Eley–Rideal
eac ions in ammonia syn hesis unde plasma condi ions [
62
–
64
]. Mo eo e , esea che s
ha e combined kine ic modeling wi h expe imen al s udies in dielec ic ba ie discha ge
eac o s o be e unde s and he in ica e eac ion mechanisms [64,65].
Ano he key a ea o esea ch in plasma-ca aly ic ammonia syn hesis is he in es iga-
ion o plasma e ec s and eac ion mechanisms. S udies ha e del ed in o he in luence o
he ma e ial dielec ic cons an on plasma gene a ion wi hin ca alys po es, e ealing im-
po an conside a ions o plasma–ca alys in e ac ions [
55
]. Addi ionally, he enhancemen
o eac ion a es beyond he he modynamic equilib ium in plasma-ca alyzed ammonia
syn hesis has been s udied, opening up new possibili ies o mo e e icien ammonia
p oduc ion [66].
Fu he mo e, esea che s ha e explo ed he di ec con e sion o CO
2
and CH
4
in o
liquid chemicals using plasma ca alysis. Expe imen al s udies and simula ions ha e shown
p omising esul s in con e ing CO
2
and CH
4
in o aluable p oduc s [
67
]. Meanwhile,
o he wo ks ha e emphasized he impo ance o modeling plasma chemis y and eac o
design o op imize he e iciency o CO2con e sion h ough plasma ca alysis [68].
In he ealm o modeling echniques, a i icial neu al ne wo ks (ANNs) and deep
lea ning ha e been ha nessed o enhance plasma ca alysis. ANNs ha e p o en use ul
in p edic ing he pe o mance o ammonia syn hesis in plasma ca alysis, enabling be e
con ol and op imiza ion o he p ocessing [
69
]. Simila ly, deep lea ning echniques ha e
been explo ed in modeling pulsed discha ge plasma ca alysis, o e ing no el pe spec i es
o unde s anding and imp o ing plasma-ca aly ic eac ions [70].
The collec i e body o wo k p esen ed in hese a icles showcases he indispensable
signi icance o modeling and simula ion echniques, encompassing mic okine ic modeling,
luid dynamics, and a i icial neu al ne wo ks, in ad ancing plasma ca alysis o ammonia
syn hesis. The s udies shed ligh on plasma e ec s, eac ion mechanisms, and he con-
e sion o CO
2
and CH
4
, o e ing aluable insigh s in o he beha io o plasma-ca aly ic
sys ems and hei po en ial applica ions in sus ainable ammonia p oduc ion. As he ield o
plasma ca alysis con inues o e ol e, hese modeling app oaches will undoub edly play a
cen al ole in unlocking new ho izons o e icien and en i onmen ally iendly ammonia
syn hesis p ocesses.
2.2. Ad ancing Ammonia Syn hesis h ough Plasma Ca alysis: Un eiling Insigh s and
Inno a ions ia Modeling and Simula ion
Resea ch in plasma ca alysis has made ema kable p og ess in comp ehending ca alys
su aces, mic okine ic modeling, and eac ion mechanisms. The i s g oup o a icles places
emphasis on he signi icance o ca alys su aces and mic okine ic modeling in plasma
ca alysis. Wang e al. [
71
] in es iga e he ole o a Ni/Al
2
O
3
ca alys su ace in ammonia
syn hesis using plasma-enhanced ca alysis a nea - oom empe a u e. Thei u iliza ion o
densi y unc ional heo y (DFT) mic okine ic modeling yields aluable insigh s in o eac ion
mechanisms, highligh ing he ca alys su ace’s impo ance in achie ing e icien ammonia
syn hesis. Sun e al. [
72
] explo e plasma-ca aly ic ni ogen ixa ion and i s co ela ion wi h
ca alys mic oanalysis. Th ough chemical kine ics modeling, hey gain aluable insigh s
in o eac ion mechanisms and pe o mance, ocusing on he ole o a TiO2@5% GO ca alys .
The second g oup o a icles del es in o he complexi ies o plasma-ca aly ic eac ions,
wi h a pa icula ocus on plasma cha ac e is ics and hei in luence on eac ion mechanisms.
Ca alys s 2024,14, 40 5 o 24
Rouwenho s e al. [
73
] discuss he use o plasma-d i en ca alysis o g een ammonia
syn hesis using in e mi en elec ici y. The s udy explo es he in ica e na u e o plasma-
ca aly ic eac ions, hei e ec s on plasma cha ac e is ics, and low pa e ns, con ibu ing o
he de elopmen o sus ainable ammonia syn hesis me hods. Loende s e al. [
74
] p esen a
mic okine ic model o he pa ial oxida ion o me hane on P (111) su aces unde plasma
ca alysis. By in es iga ing he in luence o di e en plasma species on eac ion kine ics and
mechanisms, his s udy deepens ou unde s anding o plasma-ca aly ic p ocesses.
Collec i ely, hese a icles unde sco e he impo ance o ca alys su aces, mic okine ic
modeling, and he complexi ies o plasma-ca aly ic eac ions in ad ancing he ield o
plasma ca alysis. The applica ion o DFT mic okine ic modeling p o ides aluable insigh s
in o eac ion mechanisms and ca alys pe o mance, while in es iga ions in o plasma cha -
ac e is ics shed ligh on he in icacies o plasma-ca aly ic p ocesses. Such esea ch plays a
c i ical ole in op imizing plasma ca alysis and expanding i s applica ions in sus ainable
syn hesis and chemical ans o ma ions.
2.3. Un a eling Complexi ies: Modeling App oaches in Ad ancing Plasma Ca alysis
Unde s anding and E iciency
The ad ancemen s in plasma ca alysis ha e been ueled by he use o modeling
app oaches o un a el he in ica e in e ac ions be ween plasma and ca alys s. Zhang
e al. [
75
] employ a 2D implici PIC/MCC model o s udy plasma s eame p opaga ion
wi hin ca alys po es, emphasizing he signi icance o su ace cha ging du ing his p ocess.
By compa ing hei esul s wi h luid modeling p edic ions, he s udy sheds ligh on he
complexi ies o plasma–ca alys in e ac ions. Simila ly, Michielsen e al. [
76
] use model
calcula ions o enhance ou unde s anding o plasma ca alysis, speci ically CO
2
dissocia ion
in a packed-bed DBD eac o . Thei in es iga ion o he in luence o ope a ing pa ame e s,
pa icula ly in helium plasma, o e s us a be e g asp o he unde lying mechanisms.
Pan e al. [
77
] conduc nume ical simula ions and calcula ions based on global and luid
models, as well as densi y unc ional heo y (DFT), o in es iga e nanosecond-pulsed DBD
plasma-ca aly ic CH
4
d y e o ming. Thei s udy highligh s he syne gis ic e ec s be ween
plasma and ca alys s, p o iding aluable insigh s in o he eac ion dynamics and e iciency
o his e o ming p ocess. On he o he hand, Dou e al. [
78
] del e in o he syne gis ic
plasma-ca aly ic con e sion o CO
2
and CH
4
in o oxygena es. By in es iga ing he ole o
me allic cobal si es and oxygen acancies in his p ocess and demons a ing he p oduc ion
o CH
3
COOH h ough ecombina ion in a plasma simula ion, he s udy unco e s po en ial
pa hways o sus ainable oxygena e p oduc ion.
Collec i ely, hese a icles demons a e he signi icance o modeling app oaches in
unde s anding plasma–ca alys in e ac ions and speci ic plasma-ca aly ic p ocesses. The
s udies shed ligh on he in ica e mechanisms and syne gis ic e ec s ha occu du ing
plasma ca alysis, pa ing he way o i s mo e e icien and sus ainable applica ions.
2.4. Explo ing Mechanisms, Modeling, and Applica ions in he Realm o Plasma Ca alysis
The ield o plasma ca alysis is a ealm o explo a ion encompassing mechanisms,
modeling app oaches, and di e se applica ions. Resea che s ha e made signi ican con-
ibu ions o unco e ing he mechanisms and de eloping modeling aspec s o plasma
ca alysis. Mei e al. [
79
] del e in o he e o ming o CH
4
wi h CO
2
using a nanosecond-
pulsed DBD plasma, shedding ligh on he ole o he CH
4
/CO
2
a io and o al low in
p oduc dis ibu ion and he in ica e in e ac ion be ween eac i e plasma species and
ca alys s. Chawdhu y e al. [
80
] in es iga e a p omising plasma-ca aly ic app oach o
single-s ep me hane con e sion o oxygena es a oom empe a u e, u ilizing plasma chem-
ical kine ic modeling o highligh he ca aly ic acili a ion o he con e sion p ocess.
Speci ic applica ions and ad ancemen s in plasma ca alysis a e also subjec s o o-
cused esea ch. Van’ Vee e al. [
81
] explo e spa ially and empo ally non-uni o m plasmas,
pa icula ly mic o-discha ges in a packed bed plasma eac o , o gain insigh s in o plasma-
ca aly ic ammonia syn hesis. The s udy inco po a es low simula ions and plasma kine ics

Ca alys s 2024,14, 40 6 o 24
modeling, deepening ou unde s anding o mic o-discha ges’ beha io and hei ole in
ammonia syn hesis. Ong e al. [
82
] discuss he applica ion o mic owa e plasma echnology
o con e ing CO
2
in o high- alue p oduc s, emphasizing luid models and kine ic mod-
els o unde s and plasma beha io and highligh ing he po en ial o mic owa e plasma
ca alysis in alue-added chemical p oduc ion.
Collec i ely, hese a icles con ibu e o he ad ancemen o ou unde s anding o
plasma ca alysis. By p o iding aluable insigh s in o he unde lying mechanisms, model-
ing echniques, and po en ial applica ions o plasma-ca aly ic eac ions, hese s udies pa e
he way o op imizing and p og essing plasma ca alysis o a ious pu poses. The in es-
iga ion o speci ic eac ions, ope a ing pa ame e s, and spa ial– empo al cha ac e is ics
adds o ou knowledge base o plasma ca alysis, enabling i s po en ial implemen a ion in
sus ainable and inno a i e chemical p ocesses.
2.5. Explo ing he Landscape o Plasma Ca alysis: Models, Applica ions, and Challenges
The ield o plasma ca alysis is en iched by di e se esea ch, encompassing models,
applica ions, and challenges. In he ealm o modeling and simula ion, esea che s ha e
made signi ican con ibu ions. Cheng e al. [
83
] p esen a model o nanosecond-pulsed
plasma d y e o ming o na u al gas, inco po a ing low and mixing e ec s. Thei wo k
sheds ligh on he complexi ies o plasma-ca aly ic eac ions in his con ex . Cheng e al. [
84
]
in oduce a no el plasma syne gis ic ca alysis model based on compu a ional luid dynam-
ics (CFD), o examine CO p oduc ion pa hways and he in luence o ib a ionally exci ed
species, p o iding aluable insigh s in o eac ion mechanisms unde plasma condi ions.
Oskooei e al. [
85
] u ilize a CFD model o simula e he plasma-assis ed ca aly ic educ ion o
NOx, CO, and HC in diesel engine exhaus , con ibu ing o ou unde s anding o emission
con ol echnologies.
Speci ic applica ions and challenges in plasma ca alysis ha e also been a ocal poin o
esea ch. Li e al. [
57
] in es iga e me hane- o-me hanol con e sion using bo h he e oge-
neous ca alysis and plasma ca alysis, emphasizing con inuous low eac o s and ad anced
simula ion echniques, o e ing po en ial ou es o e icien me hanol p oduc ion. Zhang
e al. [
86
] del e in o he o ma ion o mic o-discha ges inside a mesopo ous ca alys in
dielec ic ba ie discha ge (DBD) plasmas using a 2D luid model, unco e ing in ica e
plasma–ca alys in e ac ions in con ined spaces. Fu e al. [
87
] c i ically e iew i al disin-
ec ion using non- he mal plasma and discuss he po en ial o he plasma ca alysis sys em,
showcasing he di e se applica ions o plasma ca alysis in di e en domains.
Ano he c ucial aspec o esea ch in ol es ca alys cha ac e iza ion and p ocess
op imiza ion in plasma ca alysis. Zhang e al. [
88
] explo e plasma-enhanced ca aly ic
ac i a ion o CO
2
in a modi ied gliding a c eac o , emphasizing he gas low ield and he
need o u he plasma modeling s udies o op imize he p ocess. Kaliyappan e al. [
89
]
in es iga e he impac o ma e ial p ope ies on he plasma-ca aly ic dissocia ion o CO
2
using a packed-bed DBD plasma eac o , con ibu ing o he de elopmen o e icien
ca alys s o CO
2
con e sion. Zhu e al. [
90
] s udy he hyb id plasma-ca aly ic emo al o
ace one o e CuO/
γ
-Al
2
O
3
ca alys s using a esponse su ace me hod, o e ing insigh s
in o op imizing he p ocess condi ions o e icien pollu an emo al.
Add essing challenges in ca aly ic modeling wi hin plasma en i onmen s is also
a key ocus. Viladegu e al. [
91
] discuss he cha ac e iza ion o ca aly ic p ocesses in
plasma wind unnels and highligh disc epancies be ween cu en ca aly ic models used in
compu a ional luid dynamics (CFD) and ac ual ca aly ic p ocesses. Thei wo k sheds ligh
on he complexi ies o ca aly ic p ocesses in plasma en i onmen s and highligh s he need
o imp o ed modeling echniques.
Toge he , hese a icles con ibu e signi ican ly o ou unde s anding and ad ancemen
o plasma ca alysis. They explo e di e se modeling app oaches, speci ic applica ions in
di e en domains, and he challenges aced in ca aly ic modeling wi hin plasma en i on-
men s. This comp ehensi e esea ch o e s aluable insigh s ha can pa e he way o
u u e ad ancemen s in he ield o plasma ca alysis.
Ca alys s 2024,14, 40 7 o 24
2.6. Un eiling he Mul i ace ed Landscape o Ad ancemen s in Plasma Ca alysis o
Sus ainable P ocesses
Resea ch in he ield o ad ancemen s in plasma ca alysis o sus ainable p ocesses
co e s a wide ange o opics, including modeling, insigh s in o eac ions, sys em ad-
ancemen s, and kine ic pa hways. Resea che s ha e emphasized he signi icance o
modeling and designing plasma-ca aly ic sys ems, wi h a ocus on mic okine ic modeling
and ca alys design o e icien CO
2
con e sion [
92
]. Ano he a ea o in e es is explo ing
ene gy-e icien pa hways o pulsed-plasma-ac i a ed ammonia syn hesis, aking in o
accoun eac o s uc u e, plasma dynamics, and mass low con ol [
93
]. Addi ionally,
s udies ha e p esen ed mic okine ic models o in es iga e he non-oxida i e coupling o
me hane o e speci ic ca alys s in non- he mal plasma eac o s, p o iding aluable insigh s
in o ca alys design o e icien plasma-ca aly ic p ocesses [94].
Insigh s in o speci ic plasma-ca aly ic eac ions ha e been a ocus o esea ch, as well.
Some a icles combine expe imen al measu emen s and plasma kine ic modeling o enhance
ou unde s anding o ammonia decomposi ion in speci ic plasma en i onmen s [
95
]. O he
s udies explo e he e ec s o speci ic p omo e s on plasma-assis ed d y e o ming o
me hane o e speci ic ca alys s [96].
Ad ancemen s in plasma-ca aly ic sys ems ha e been discussed in a ious a icles.
These include explo ing he applica ion o dielec ic ba ie discha ge non- he mal plasma
in he aba emen o ola ile o ganic compounds (VOCs), conside ing ca alys s, plasma–
ca alys syne gy, and luid modeling [
97
]. Cha ac e izing he plasma ca aly ic decom-
posi ion o me hane, ocusing on he ole o a omic oxygen, and p oposing concep ual
models o he mal ca alysis and plasma-induced eac ions ha e also been key a eas o
in e es [
98
]. Mo eo e , some s udies ha e e iewed he emo al o speci ic pollu an s om
exhaus gases using non- he mal plasma combined wi h ca alys s, highligh ing di e en
plasma–ca alys sys ems and he use o nume ical modeling [
99
]. Modeling and kine ic
pa hways in plasma-ca aly ic eac ions ha e been ho oughly explo ed, as well. Some a i-
cles discuss he modeling o exci ed species and hei ole in he kine ic pa hways o speci ic
eac ions using ze o-dimensional low eac o models [
100
]. The op imiza ion o plasma
ca alys s is a c i ical endea o in enhancing he e iciency o chemical p ocesses, in ol ing
a nuanced adjus men o key pa ame e s o maximize desi ed ou comes. Fo ins ance, he
modula ion o plasma powe and equency is me iculously calib a ed o in luence he
ene gy le els and eac i e species gene a ed du ing eac ions, di ec ly impac ing ca aly ic
ac i i y. Simila ly, ca e ul con ol o e gas composi ion and low a e is essen ial, as hese
ac o s dic a e eac ion pa hways and selec i i y. The su ace cha ac e is ics o he ca alys ,
including composi ion and mo phology, signi ican ly in luence i s ca aly ic pe o mance.
Fo example, ailo ing he mo phology o a ca alys o enhance i s su ace a ea can lead o
inc eased ac i e si es and imp o ed ca aly ic ac i i y. Addi ionally, empe a u e con ol,
acili a ed by e ec i e cooling sys ems, is c ucial in p e en ing undesi ed side eac ions
and main aining an en i onmen conduci e o op imal ca aly ic pe o mance [93,94,97].
Collec i ely, hese a icles con ibu e o he ad ancemen o plasma ca alysis o
sus ainable p ocesses by p o iding aluable insigh s in o modeling app oaches, eac ion
mechanisms, ca alys design, and he op imiza ion o plasma-ca aly ic sys ems. The di e se
ange o esea ch highligh s he mul i ace ed na u e o plasma ca alysis and i s po en ial
o a ious applica ions in sus ainable p ocesses.
2.7. Explo ing Modeling, Reac ions, Sys ems, and Kine ics in Plasma Ca alysis o
Sus ainable P ocesses
Resea ch in he ield o ad ancemen s in plasma ca alysis o sus ainable p ocesses
co e s a di e se ange o opics, including modeling, insigh s in o eac ions, sys em ad-
ancemen s, and kine ic pa hways. The i s g oup o a icles emphasizes he signi icance
o modeling and design in plasma-ca aly ic sys ems. Bogae s and Cen i [
92
] unde sco e
he impo ance o mic okine ic modeling and ca alys design o e icien CO
2
con e -
sion. Pou ali e al. [
94
] con ibu e wi h hei mic okine ic model by s udying he non-
Ca alys s 2024,14, 40 8 o 24
oxida i e coupling o me hane o e a Cu ca alys in a non- he mal plasma eac o , p o id-
ing aluable insigh s in o op imal modeling app oaches and ca alys design o e icien
plasma-ca aly ic p ocesses.
Ande sen e al. [
64
] combine expe imen al measu emen s wi h plasma kine ic mod-
eling o elucida e ammonia decomposi ion in a dielec ic ba ie discha ge plasma. Tu
and Whi ehead [
101
] in es iga e he syne gis ic e ec be ween plasma and ca alys s in
a mosphe ic dielec ic ba ie discha ge d y e o ming o me hane. Diao e al. [
96
] explo e
he e ec s o a
β
-Mo
2
C p omo e on plasma-assis ed d y e o ming o me hane o e Mo
2
C-
Ni/Al
2
O
3
ca alys s, u he con ibu ing o ou unde s anding o eac ion mechanisms and
he pi o al ole o ca alys s in plasma-ca aly ic eac ions.
Li e al. [
97
] explo e he applica ion o dielec ic ba ie discha ge non- he mal plasma
in VOC aba emen , conside ing ca alys s, plasma–ca alys syne gy, and luid modeling.
Li e al. [
98
] p o ide insigh s by cha ac e izing he plasma ca aly ic decomposi ion o
me hane, ocusing on he ole o a omic oxygen and p oposing a concep ual model o
he mal ca alysis and plasma-induced eac ions. Zhu e al. [
102
] e iew he emo al o
CH
4
and NOx om ma ine LNG engine exhaus using non- he mal plasma combined wi h
ca alys , highligh ing di e en plasma–ca alys sys ems and he use o nume ical modeling,
showcasing ad ancemen s in plasma-ca aly ic sys ems o di e se applica ions.
Mai e e al. [
100
] discuss he modeling o exci ed species and hei ole in he kine ic
pa hways o non-oxida i e coupling o me hane by dielec ic ba ie discha ge, p esen ing a
ze o-dimensional low eac o model, p o iding deepe insigh s in o eac ion mechanisms,
and ou lining he in luence o exci ed species on plasma-ca aly ic p ocesses.
2.8. Ad ancing Plasma-Assis ed Ca alysis: Explo ing Reac o s, Kine ics, Hyd ogen P oduc ion,
and Compu a ional Analyses
Resea ch in he ield o plasma-assis ed ca alysis has wi nessed ema kable ad ance-
men s in a ious aspec s, spanning eac o con igu a ions, kine ics modeling, hyd ogen
p oduc ion, compa a i e s udies, unknowns, and compu a ional analyses wi h model
alida ion. Schola s ha e explo ed di e en plasma eac o con igu a ions o achie e he
selec i e gene a ion o oxygena es om CO
2
and CH
4
, u ilizing heo e ical modeling o
comp ehend he unde lying p ocesses. Addi ionally, esea che s ha e in es iga ed he
in luence o p ocess pa ame e s and packing ma e ials on chemical equilib ium and kine ics
in plasma-based CO
2
con e sion, shedding ligh on ac o s a ec ing eac ion e iciency.
Mo eo e , hey ha e employed modeling echniques o un eil he eac ion mechanisms o
di e en plasma sou ces in CH4con e sion while also analyzing he impac o low a es.
The ocus hen shi ed o plasma-ca aly ic echnologies o hyd ogen p oduc ion.
Comp ehensi e models ha e been de eloped o unde s and hyd ogen p oduc ion om
alcohol e o ming using plasma and plasma-ca aly ic echnologies, in es iga ing he e ec s
o a ious p ocess pa ame e s on e iciency. Non- he mal a mosphe ic plasma eac o s
o hyd ogen p oduc ion om low-densi y polye hylene ha e been s udied, emphasizing
he mal– luid models o unde s and he luid low and he mal beha io wi hin he sys em.
Fu he mo e, compa a i e s udies and explo a ion o unknown ac o s in plasma ca al-
ysis ha e been ca ied ou . Schola s ha e conduc ed compa a i e s udies o non- he mal
plasma-assis ed e o ming echnologies, simula ing he ca aly ic e ec s o plasma, hus
con ibu ing o ou unde s anding o he ad an ages and limi a ions o di e en plasma-
assis ed p ocesses. Mo eo e , hey ha e analyzed known knowns, known unknowns,
and unknown unknowns in plasma ca alysis, u ilizing simpli ied kine ic models and gen-
e alized models o speci ic ca alys s, unde lining he impo ance o u he esea ch in
hese a eas.
In he ealm o compu a ional s udies and model alida ion in plasma-assis ed ca aly-
sis, esea che s ha e in es iga ed plasma-based d y e o ming ac oss di e en ime scales,
alida ing hei models by compa ing simula ion esul s wi h expe imen al da a, ensu ing
accu acy and eliabili y. In addi ion, s udies on enzyme-ca alyzed p ocesses o d ug ex ac-
Ca alys s 2024,14, 40 9 o 24
ion ha e u ilized plasma-limi ed low models o calcula e c i ical pa ame e s, p o iding
insigh s in o d ug me abolism and ex ac ion kine ics.
The ield o plasma-assis ed ca alysis has seen subs an ial g ow h ac oss mul iple
dimensions. The comp ehensi e esea ch on eac o con igu a ions, kine ics modeling,
hyd ogen p oduc ion, compa a i e s udies, unknowns, and compu a ional analyses has
signi ican ly en iched ou unde s anding o plasma-ca aly ic p ocesses, pa ing he way o
hei op imiza ion and applica ion in a ious indus ies and sus ainable echnologies.
2.9. Ad ancing he F on ie s o Plasma-Ca aly ic P ocesses: Insigh s ac oss Syngas P oduc ion,
Re o ming, Was e Valo iza ion, and Beyond
This sec ion c i ically engages wi h a disce nible gap in he exis ing li e a u e pe ain-
ing o he de iciency in me hane deg ada ion ia NTP, o e ing a me iculous examina ion
o his unde explo ed aspec . Posi ioned wi hin he b oade con ex o plasma-ca aly ic
p ocesses, he esea ch ex ends i s ocus ac oss an a ay o domains, encompassing syngas
p oduc ion, me hane e o ming, a e olu ion, was e alo iza ion, hyd oca bon e o ming,
ca bon dioxide dissocia ion, plasma-ca aly ic NOx p oduc ion, neu al ne wo k modeling,
ammonia syn hesis, and CO2/CH4con e sion.
Examining syngas p oduc ion om me hane oxida ion using non- he mal plasma
eac o s, his e iew c i ically app aises he ca aly ic ole o su aces and uni o m packings
in augmen ing he e iciency o plasma-based e o ming p ocesses. Fu he mo e, ou e iew
encompasses sc u iny o a e olu ion in plasma gasi ica ion p ocesses, placing emphasis
on he ca aly ic po en ial o he mal plasma o was e alo iza ion.
In eg al o he manusc ip ’s c i ical examina ion is he ole o modeling and simula ion
as impe a i e ools o unde s anding plasma-assis ed eac ions, pa icula ly in ca aly ic
pa ial oxida ion and NOx p oduc ion. This e iew assesses a ious in luencing ac o s,
including plasma cha ac e is ics, low pa e ns, and ca alys in e ac ions. Expanding i s
scope, his e iew del es in o plasma ca alysis in hyd oca bon e o ming, ca bon dioxide
dissocia ion, and he di ec con e sion o CO2and CH4in o aluable p oduc s.
The in eg a ion o neu al ne wo k modeling eme ges as a p omising ye sc u inized
a enue, p o iding p edic i e insigh s in o he pe o mance o plasma-ca aly ic p ocesses.
The manusc ip also c i ically e alua es in es iga ions in o ammonia syn hesis using gliding
a c plasma and he s a egic use o K-p omo e s in CO2/CH4con e sion.
By c i ically add essing he de iciency in me hane deg ada ion by NTP and subjec -
ing a ious ace s o plasma ca alysis o igo ous sc u iny, his manusc ip se es as a
specialized and pionee ing con ibu ion. I s c i ical analysis no only con ibu es o ou
comp ehensi e unde s anding o plasma-ca aly ic p ocesses bu also challenges and e ines
p e ailing pe spec i es, pa ing he way o mo e nuanced and impac ul ad ancemen s in
sus ainable and e icien chemical ans o ma ions wi hin his dynamic ield.
3. De elopmen and Applica ion o Compu a ional Fluid Dynamics Models o
Op imiza ion o Plasma Reac o s on an Indus ial Scale
Compu a ional luid dynamics s udies a e impo an o ad ancing eac o design and
op imiza ion a he indus ial scale. Plasma gene a ion and u iliza ion consis o physical
and chemical phenomena ex ensi ely in ol ing anspo phenomena o luids inside he
plasma eac o s. Tu bulence, hea ans e , adia ion ene gy, mul iphase low, luid in e ac-
ions, and homogenous and he e ogeneous phase eac ions a e o signi ican impo ance in
he domain o CFD s udies. Based on he key expe imen al esul s, a nume ical luid model
is usually de eloped o CFD s udies. O en, so wa e like FLUENT, Py hon, MATLAB,
and Abaqus a e used o CFD coding and simula ion. In s eady s a es, he Na ie –S okes
equa ion is applied in incomp essible luid condi ions and physical sub-models. Eddy
dissipa ion o species anspo is also s udied in colloquium wi h kine ic models o
gas-phase eac ion s udies. Some imes, in he CFD models, we u ilize buil -in unc ions,
while in e oneous design, and e alua e models o use -de ined unc ions [65,103].
Ca alys s 2024,14, 40 16 o 24
Ca alys s 2024, 14, x FOR PEER REVIEW 17 o 26
uni-elec ode dielec ic coa ing, mainly he mionic emissions, inc eases he elec on em-
pe a u es in compa ison o uncoa ed elec odes [104].
Figu e 3. Di e en modeling app oaches o modeling o plasma eac o s (based on [130]).
G aph esul s show he simula ed beha io o NTP DBD sys ems o unconside ed
a mosphe ic gas using kine ic heo y wi h mul iple eac ions in ol ing mainly impo an
cha ged species o he e olu ion o cha ged species in COMSOL and BOLTZMAN Sol e .
The empe a u e o ion-kine ic eac ions mos ly depends on he au oioniza ion p ocess.
Spa ial– empo al a ia ion in he plasma olume o ecombina i e ai kine ic eac ions
leads o mo e au oioniza ion o sa u a ion o ion-kine ic empe a u e. In one-dimensional
condi ions, adia ion and hea ans e s can be neglec ed, bu a g ea e -dimensional model
inco po a es he espec i e species densi ies based on he a o emen ioned.
Ul ima e Model
•Hie a chical Modeling o S udies In e -a omis ic
Po en ial
•Baseline o MD Simula ions & Adso ba e-Ca alys
Sys ems
•Usually, a iables a e a unc ion o ime and leng h
•Modeling Wi hou Ca alysis & Adiaba ic Reac o s
•Plug & Lamina Flow
•1-D & 2-D Models
•A omic Scale & Mesoscale Models
•No Side Reac ions & Su ace Reac ions
Densi y Func ional Theo y
•S udies ac i a ion ene gy
ba ie s, in e media es, and
ansi ion s a es
•Small- ime sys ems usually
nanoseconds o picoseconds
•Usually mo e han 100 species
in ol ed
•A omic scale
Kine ic Mon e Ca lo
Equa ions
•Ex ends imescale
• o highe leng h and magni ude
o collisions as compa ed o
Classical MD
•Usually de i ed a e cons an
•Reac ion da a is collec ed om a
da abase.
•A omic Scale
•KMC is usually cheape han
classical MD and DFT
Classical MD simula ions
•Hold la ge sys ems o species han DFT
sys ems
•Usually include compu a ional luid
dynamics
•A omic Scale
A i ical Neu al Ne wo k
•Usually o modeling and
op imizing s udies S udies
p oduc dis ibu ion Inc eases
selec i i y wi h ela i e
calcula ions
Mac oscale Plasma
•Usually o 0-D models
•Fo su ace eac ions
•Syne gis ic e ec s
•Reduced o ma ion o coke
•Ho spo s in he eac ion and
discha ge a eas
Figu e 3. Di e en modeling app oaches o modeling o plasma eac o s (based on [130]).
A hyb id mul i-model app oach has been used in he li e a u e o chemical kine ics,
which s udies he deg ada ion a es using a p ocess in ensi ica ion s a egy o o a ion wi h
con e sion (in COMSOL), he geome y o he elec ode, elec ic ield s eng h, elec os a ic
condi ions, elec ode su ace a ea, and eloci y calcula ions in a plasma eac o . The
T&T eac o u ilizes Gibbs ene gy wi h a iable pa ame e s such as empe a u e and
p essu e. The Na ie S okes equa ion and mass conse a ion equa ion can be used o
mul iple species and he gene a ion o a 3D model in COMSOL. The so wa e uses a buil -
in comp ehensi e nominal esidual me hod o i e a ion and con e gence o he model
and alida ion wi h expe imen al esul s. The deg ada ion a e o gasi ie p oduc gas
highligh s a s ong ela ionship be ween he decomposi ion a e wi h he elec ode ip and
he elec ic ield in ensi y in o a ional in ensi ied plasma eac o s [131,132].
3.6. Hyb id Modeling o Plasma T anspo and Chemical Kine ics: Combining PIC and Mon e
Ca lo App oaches wi h Densi y Func ional Theo y and Mechanis ic Modeling
Combining Mon e Ca lo and pa icle in cell (PIC) o anspo and chemical kine ics
o e s a hyb id me hod o modeling. The 1D model is easy o compu e due o he low
compu a ional e o equi ed and limi ed species, and since he eac ion unde s udy has a
uni o m composi ion wi h no conside a ion o anspo phenomena. In luid modeling,

Ca alys s 2024,14, 40 17 o 24
mass, ene gy, and momen um balance a e combined in he Bol zmann anspo equa ion,
ye mo e compu a ional ime is equi ed han in kine ic modeling. I p essu e condi ions a e
aken in o conside a ion, i.e., low-p essu e condi ions, he Mon e Ca lo equa ion wi h luid
models is u ilized o s udy he de ailed elec on beha io in he plasma egion, b inging
o h a hyb id luid model, and bounda y condi ions, a s icking coe icien , and wall eac-
ion p obabili ies mus be conside ed o su ace eac ions in dielec ic plasma eac o s. A
new concep o he quali a i e app oach, mechanis ic modeling, conside s ac i a ion ene -
gies and a eac ion a e coe icien based on i s p incipal modeling using ab ini io me hods
o MD simula ions. In addi ion o conside ing mul i-phase physical and chemis y calcu-
la ions, densi y unc ional heo y is p oposed. Due o he complex na u e o plasma and
mul iple by-p oduc s, his inco po a es di e en body ene gy calcula ions and con igu a-
ions o ind app op ia e and p obable eac ion mechanisms [
120
,
133
,
134
]. Ta componen s
(naph halene and phenol) a e subjec ed o deg ada ion simila o he deg ada ion o double
ca bon bonds and a oma ic ing compounds. Double bonds a e des oyed by ozone mainly
a 1,2 posi ions as he e hyl and hyd oxyl ac i a e u he des uc ion. Naph halene b eak-
down a 2,3 posi ions as he middle deploymen inc eases he des uc ion a e. Package
QCISSTD(T)/63-11 G (d, p) de e mines he ac i a ion ene gy o oluene, phenol, and naph-
halene as 49 kJ/mol, 48.84 kJ/mol, and 28.06 kJ/ mol, while he same package gi es he
equi ed A henius ac i a ion ene gy exp ession le els as k = 4.17
×
10
10
exp (
−
5476.4/T),
1.22
×
10
12
exp (
−
5634.7/T), and inally
2.24 ×1012 exp (−3742.8/T) (cm3·mole−1·s−1)
in
succession. The ozone deg ada ion a e cons an s o biomass compounds, in sequence, a e
he naph halene molecule > phenol molecule > oluene molecule [135].
3.7. Use o Machine Lea ning Algo i hms o Op imiza ion and P edic ion o Plasma Reac o
Pe o mance in Plasma Hyb id Modeling
Jus like adi ional plasma hyb id modeling, machine lea ning algo i hms a e used in
combina ion o op imiza ion and p edic ion s udies o eac o pe o mance. Naph halene
is subjec ed o e o ming in a gliding a c plasma eac o . The esul s o e o ming a e
analyzed in he a h ee-combina ion model comp ising SVM, DT, and AAN o a complex
p ocedu al unde s anding and hype -pa ame e uning mainly wi h gene ic algo i hms.
The esul s show g ea symme y be ween expe imen al and modeling wo k. S eam-
o-ca bon S/C and discha ge powe a e he mos in luen ial ac o s o con e sion and
ene gy e iciency, espec i ely. Va iables a e coupled o pe o mance calcula ions. Machine
lea ning modeling shows an op imized a con e sion o 67.2% o an ene gy e iciency o
7.8 g/kWh [135–137].
P edic ions a e some imes no easible o la ge ca bon and a e cu en ly no a ailable
in he li e a u e o plasma echnologies’ ad ancemen . Chang’s ANN model was de el-
oped a ou -expe imen al-pa ame e s udy, unde sco ing he e ec on oluene emo al. The
pa ame e s a e he discha ge powe , ini ial concen a ion, low a e, and ela i e humidi y.
ML algo i hms a e widely a ailable o p edic ion s udies in he chemical plasma p ocess,
wi h limi a ions and d awbacks. The mos app op ia e ML algo i hms a e supe ised
lea ning algo i hms o eg ession classi ica ion and p edic ion p oblems. ANN me hods
a e sel -adap ed, au onomously con igu ed, and con inuously lea ning. The only d awback
is he la ge da a se equi emen o he ANN me hod’s execu ions and a challenge is a oid-
ing o e i ing. Usually, in plasma, chemical p ocess da a se s a e small and con ined. This
e en ually leads o unce ain y in he an icipa ed esul s. SVR is designa ed o non-linea
and highe -o de eg essions [
138
]. I has a a e chance o o e i ing and so consumes
g ea e aining ime. In he o igina ed da a se , usually con aining noise, DT algo i hm
ans o ma ion ep esen s a ee isualiza ion o obus calcula ions and decisions. Da a
se con i ma ion and p ope ies do no a ec DT calcula ions, and no p ep ocessing is
equi ed. Only no malized dis ibu ion and s anda diza ion a e conduc ed. The esul s
a e usually o e i ed due o gene aliza ion. The only ad an age is he p ocessing o la ge
da a se s.
Ca alys s 2024,14, 40 18 o 24
Kine ic s udies a e no easible o a mul i-leng h-scale complex plasma p ocess, so
a powe ul machine lea ning ool is equi ed [
138
]. ML is equi ed o he p edic ion and
op imiza ion o la ge chemical p ocesses. In expe imen a ion, he e a e usually long cycles,
complica ed p ocedu es, and suscep ibili y o en i onmen al in e e ence, all o which
cos us ime and esou ces in seeking o ob ain eliable esul s. In addi ion, expe imen al
complexi y scales exponen ially wi h he numbe o a iables, es ic ing he numbe o
expe imen s and na owing he ange o p ocess pa ame e s. Plasma modeling is a help ul
me hod o unde s anding he plasma p ocess and building a chemical kine ic model o
p edic ing key eac ion da a, i.e., a e cons an , con e sion, and c oss-sec ion. The gene ic
algo i hm inds he op imal hype pa ame e o each ML algo i hm in ol ed, o enhance
adap abili y and p edic i e accu acy. KPI-based unde s anding has been de eloped o
ene gy e iciency and he con e sion o naph halene [110,139,140].
De e mining he eac ion key pe o mance (P) o a plasma in ol es a casual combi-
na ion o h ee algo i hms, whe e he equa ion is gi en as
P=PANN X W1+W2XPSVR +W3X PDT (0≤W1,≤W2≤W3≤1)(8)
The algo i hm’s weigh ed pa ame e s a e W
1
,W
2
, and W
3
o DT, SVM, and ANN,
while Pis he p edic ed alue’s esul s. The mean squa e e o e alua ion o mula is used
o e alua e he pe o mance o he ML model in e ms o op imiza ion o he ela i e
weigh s using a p ede ined exhaus ion me hod [136,141]
MSE =
n
∑
i=1
(Pi−RI)2(9)
A ou o al inle concen a ion se s o 1.1 g/Nm
3
, 1.4 g/Nm
3
, 1.7 g/Nm
3
, and
2.0 g/Nm3
, model p edic ed and expe imen al alues a e calcula ed o he con e sion (%).
The con e sion a e a ies a 87%, 72%, and 70% a he ou designa ed a es. A lowe
ini ial concen a ions, models and p edic ion alues a e g ea ly ela ed, while an inc ease
in he concen a ion c ea es a signi ican de ia ion be ween he wo alues. In he case o
discha ge powe (W) alues om 32 W o 77 W, he con e sion inc eases om 64% o 73%
a 1.7 g/Nm
3
concen a ion. A g ea cohe ence exis s be ween p edic ed and expe imen al
alues o S/C = 0 [114,136,141].
4. Conclusions
In conclusion, he syn hesis o hese obse a ions unde sco es he subs an ial ad-
ancemen s in plasma eac o design and ca aly ic p ocesses. The in eg a ion o modeling
and simula ion has played a pi o al ole in un a eling he in icacies o hese domains.
The in ica e in e play be ween plasma and ca alys s has been me iculously examined,
p o iding p o ound insigh s in o c i ical eac ions such as ammonia syn hesis, me hane
e o ming, and hyd oca bon con e sion. Mic okine ic modeling and ca alys op imiza ion
ha e eme ged as ins umen al componen s, highligh ing hei pi o al ole in d i ing e i-
cien CO
2
con e sion and os e ing sus ainable chemical p ocesses. The ongoing e olu ion
in oduces inno a i e modeling echniques, including neu al ne wo ks, wi h p edic i e
capabili ies ha signi ican ly enhance he p ecision o plasma-ca aly ic p ocesses. The
con e gence o plasma and ca alys s is expanding in i s applica ion scope o encompass
a eas such as was e u iliza ion and syngas p oduc ion. In his con ex , plasma ca alysis
s ands ou as a p omising app oach, spea heading en i onmen ally conscious solu ions and
ans o ma i e indus ial applica ions. As his ajec o y un olds, modeling and simula ion
will pe sis as in aluable ools, guiding us owa d he de elopmen o e icien , sus ainable,
and inno a i e plasma-ca aly ic p ocesses, he eby con ibu ing o a mo e en i onmen ally
iendly u u e g ounded in scien i ic igo and echnological inno a ion.
Au ho Con ibu ions: Concep ualiza ion, M.Y.A.; me hodology, M.Y.A., A.S.A. and M.J.; so wa e,
M.Y.A., A.S.A. and J.M.; o mal analysis, M.Y.A., A.M., A.S.A. and M.J.; in es iga ion, M.Y.A., A.S.A.
Ca alys s 2024,14, 40 19 o 24
and J.M.; esou ces, M.Y.A. and A.S.A.; w i ing—o iginal d a p epa a ion, M.Y.A., A.S.A., J.M. and
L.N.; w i ing— e iew and edi ing, M.Y.A., A.S.A., M.J., A.M., L.N. and H.P.-K.; isualiza ion, M.Y.A.,
A.S.A. and A.M.; supe ision, M.Y.A., J.M. and H.P.-K. All au ho s ha e ead and ag eed o he
published e sion o he manusc ip .
Funding: This esea ch ecei ed no ex e nal unding.
Da a A ailabili y S a emen : No new da a we e c ea ed.
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
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