Introduction to LaTeX
Learning LaTeX can be a daunting task, especially when you're teaching yourself and stuck consulting stack exchange for hours on end. To spare others some of those early growing pains, I've created a quick start guide, as well as a template. The template includes the main pieces that I have used time and time again in drafting papers and reports.
You'll need to install a tex previewer (it essentially is an editor in which you can code up your document, compile it and view the resulting pdf). I like TeXShop, but there are other options as well.
Some basic document structure: A tex file (the code that generates your document) has two main parts: the preamble (which is where you include packages, define shortcuts, set colors, set the document type and style, etc) and the main document, where the content of your document lives (this is all sandwiched between \begin{document} and \end{document}). You will also likely have a bibliography file as well (extension .bib), that will be used to generate your bibliography and organize references (there will be a separate post on this topic).
The building blocks:
Text: This is the most straight forward portion of the document. As long as you're between \begin{document} and \end{document}, you can enter text just like a standard word processor. It's worth noting that you can divide up your text into sections with \section{Name of Section}. This will automatically number/letter (depending on the style and type of document chosen in the preamble) the text of your section name and give it a unique font/size compared with the rest of the main body of text.
Tables: Tables come up quite a lot for me, so I've included a simple table as well as a more complex, nicer looking one in the template. The basic structure for a simple table is shown below. The 'table' environment (\begin{table} \end{table}) will allow you to label and caption the table, and the 'tabular' environment (\begin{tabular} \end{tabular}) is what actually generates the structure of the table. Next to \begin{tabular} is where you can define the number of columns, as well as their alignment (c = center, l = left, r = right). The vertical bar key can be used here to insert vertical lines between columns. You can also add additional (or less) space between columns here as well. Finally, inside the tabular environment, rows of your table are separated with '//' (this is a line break command) and columns are delineated with '&'. Always make sure that you have the same number of items in each row (i.e. same number of columns) as you do in your definition. Within the table, horizontal lines can be added using '\hline' (note: this is not the only way to achieve horizontal lines).
3. Figures: You will undoubtedly need to add images/plots/figures to your document and this is pretty straight forward. Similarly to the table example, you first generate the figure environment (\begin{figure} \end{figure}) which will label your figure and give it a caption (if you choose). Inside of this environment, you include an image using \includegraphics[<specify scale, height or width of the image here>]{<specify the path to the file relative to the location of your .tex file>}
4. Equations: For me, writing equations is the biggest selling point for LaTeX. Once you get used to coding up equations, this method is so much quicker than any other equation editor and looks orders of magnitude nicer too. The two main equation environments that I use are the 'equation' environment (\begin{equation} \end{equation}) and the align environment (\begin{align} \end{align}). The main difference between these two is that the align environment allows you to (as the name suggests) align lines of equations, using the '&' key. This is handy for making your equations look cleaner and more organized, or to display an equation that is too long for a single line. Both these environments will by default number your equations. If you do not want a number, you can either include \nonumber at the end of the equation, or, you can use the equation* or align* environments. You can also enter into 'math' mode inline in your document using $ <put your equation code here> $. Using $$ $$ will cause a line break and display like \begin{equation*} \end{equation*}.
To serve as a launching off point, here is a template with all the main building blocks that I tend to use regularly. I hope you find it to be helpful!
\documentclass[preprint, 12pt]{elsarticle}
\usepackage{chemfig,siunitx}
\usepackage{amssymb}
\usepackage{amsmath}
\usepackage{mathrsfs}
\usepackage[mathscr]{euscript}
\usepackage{float}
\usepackage{comment}
\usepackage{rotating}
\usepackage{subcaption}
\usepackage{multirow}
\usepackage{mathrsfs}
\usepackage{graphicx}
\usepackage{dcolumn}
\usepackage{bm}
\usepackage{upgreek}
\usepackage{xcolor}
\usepackage{pgf}
\usepackage{tikz}
\usepackage{pgfplots}
\pgfplotsset{compat=newest}
\usetikzlibrary{positioning}
\usetikzlibrary{calc}
\usetikzlibrary{intersections,backgrounds}
\usetikzlibrary{decorations.pathmorphing}
\usetikzlibrary{patterns}
\usetikzlibrary{arrows}
\usetikzlibrary{shapes}
\usetikzlibrary{arrows,automata}
\usetikzlibrary{positioning}
\usetikzlibrary{shadows.blur}
\usepackage{xcolor,stackengine}
\usetikzlibrary{matrix}
\usetikzlibrary{arrows.meta, positioning}
\fboxsep=-\fboxrule
\usepackage{pgfplots}
\usepackage[version=4]{mhchem}
\setcompoundsep{4em}
\usepackage{filecontents,pgfplots}
\usepackage{bm}
\usepackage{natbib}
\setcitestyle{sectionbib,square}
\usepackage[bottom]{footmisc}
\usepackage{booktabs,adjustbox}
\usepackage{booktabs}
\usepgfplotslibrary{fillbetween}
\usepackage[colorinlistoftodos, color=blue!20!white, bordercolor=gray,
textsize=tiny,textwidth=0.8in]{todonotes}
\pgfplotsset{%
every tick label/.append style = {font=\tiny},
every axis label/.append style = {font=\scriptsize}
}
\pgfplotsset{
legend image with text/.style={
legend image code/.code={%
\node[anchor=center] at (0.3cm,0cm) {#1};
}
},
}
%This puts line numbers... usually required by journal for reviews/revisions.
%\usepackage{lineno}
% \linenumbers
\journal{Renewable Energy}
\newcommand{\finalcells}[2]{%
\begingroup\sbox0{\begin{minipage}{3cm}\raggedright#1\end{minipage}}%
\sbox2{\begin{minipage}{3cm}\raggedright#2\end{minipage}}%
\xdef\finalheight{\the\dimexpr\ht0+\dp0+\smallskipamount\relax}%
\xdef\finalheightB{\the\dimexpr\ht2+\dp2+\smallskipamount\relax}%
\ifdim\finalheightB>\finalheight
\global\let\finalheight\finalheightB
\fi\endgroup
\begin{minipage}[t][\finalheight][t]{3cm}\raggedright#1\end{minipage}&
\begin{minipage}[t][\finalheight][t]{3cm}\raggedright#2\end{minipage}}
\begin{document}
\begin{frontmatter}
\title{Biomass pyrolysis in fully-developed turbulent riser flow}
\author{S. Beetham\fnref{label2}}
\fntext[label2]{snverner@umich.edu}
\author{J. Capecelatro}
\address{Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48105, USA}
\begin{abstract} This work presents a numerical study of biomass pyrolysis in turbulent riser flow. Eulerian--Lagrangian simulations of unbounded sedimenting gas-solid flows are performed to isolate the effects of particle clustering on the production of syngas and tar. This configuration provides a framework to resolve the relevant length- and time-scales associated with thermal, chemical and multiphase processes taking place in the fully-developed region of a circulating fluidized bed riser. A four-step kinetic scheme is employed to model the devolatilization of biomass particles and secondary cracking of tar. Two-way coupling between the phases leads to clusters of sand particles that generate and sustain gas-phase turbulence and transport biomass particles. Neglecting the heterogeneity caused by clusters was found to lead to a maximum over-prediction of syngas yield of 33\%. Further, it was found that two-dimensional simulations over-predict the level of clustering, resulting in an under-prediction of syngas and tar yields. \par
\end{abstract}
\begin{keyword}
multiphase \sep turbulence \sep biomass pyrolysis \sep Euler-Lagrange \sep CFD \sep riser
\end{keyword}
\end{frontmatter}
\enlargethispage{-2\baselineskip}
\section{Introduction\label{Intro}}
Biofuels generated from the pyrolytic upgrading of biomass are becoming a formidable alternative to fossil fuels, with the important benefits of sustainability, carbon neutrality and economic feasibility \cite{Brown2010,Mettler2012,Bridgwater2012,Farrell2006}. The catalytic upgrading of biomass solids (e.g. cellulose-based materials often originating from agricultural waste) to useful products such as syngas, typically occurs in the riser of a circulating fluidized bed reactor.
While such technologies show great promise in a laboratory setting, scale-up to commercial application remains a key hurdle~\cite{dudukovic2009frontiers}. A recurring challenge is the need to ensure optimal contact between the reacting flow and fluidized particles (e.g. catalysts and biomass). While there has been significant progress characterizing hydrodynamic interactions in particle-laden flows~\cite{balachandar2010turbulent}, much less is known about interphase heat and mass transfer.
\section{Methodology \label{Methodology}}
\subsection{System description}
The simulation configuration considered in the present study is designed to provide a model flow that captures key phenomenology in the reactor. We focus on what would be considered the fully-developed region of the riser. Assuming the flow is sufficiently far from the entrance, the two phases would evolve spatially upward without retaining memory of any entrance effects. If we further assume the simulation domain is far from the walls of the riser, and given that the flow equations are frame invariant, we can consider a temporally-developing frame of reference in an unbounded system. Focusing on the fully-developed region of the riser flow enables us to resolve a broader range of length- and time-scales associated with biomass pyrolysis than could otherwise be achieved. Further, the present configuration isolates the role of multiphase dynamics on production yield.
Very simple table:
\begin{table}
\centering
\begin{tabular}{c | c c c} %letters here specify how columns are justified, c = center, l = left, r = right then vertical bars (Shift + \ key) will set vertical lines between columns
Label 1 & Label 2 & Label 3 & Label 4 \\ % & symbol separates columns and \\ ends the line
\hline % This will put a horizontal line
A & B & C & D \\
E & F & G & H \\
\end{tabular}
\caption{This is a caption.}
\label{tab:table1}
\end{table}
\begin{table}
\begin{center}
\def~{\hphantom{0}}
\begin{tabular}{l l l l l l}
\toprule
\multicolumn{6}{c}{Physical properties}\\
\midrule
& & & \textit{biomass} & \textit{sand} & \textit{char} \\
\cmidrule{4-6}
$d_p$ &[$\upmu$m] & Particle diameter& 500 & 200 & \\
$\rho_p$ &[kg/m$^3$]& Particle density\cite{Brown2003} & 400 & 2649 & 2333 \\
$C_{p,p}$ &[J/kg K ] & Particle heat capacity\cite{Lathouwers2001} & 2300 & 800 & 1100 \\
$T_p^0$ &[K] & Initial particle temperature & 300 & 790 & \\
$\kappa_p$ &[J/m s K ] & Particle thermal conductivity\cite{Lathouwers2001} & 0.3 & 0.27 & 1 \\
\cmidrule{4-6}
& & &$N_2$ & \textit{tar} & \textit{syngas} \\
\cmidrule{4-6}
$\rho_g$ &[kg/m$^3$] & Fluid density & {EOS\footnotemark[1]} & {EOS\footnotemark[1]} & {EOS\footnotemark[1]}\\
$C_{p,g}$ &[J/kg K] & Fluid heat capacity\cite{Lathouwers2001} & 1121 & 2500 & 1100 \\
$T_g^0$ &[K] & Initial fluid temperature & 790 & -- & -- \\
$\kappa_g$ &[J/m s K] & Fluid thermal conductivity\cite{Lathouwers2001} & 5.63$\times10^{-2}$ & \multicolumn{2}{c}{2.57$\times10^{-2}$} \\
$\nu_{g}$ &[m$^2$/s] & Fluid kinematic viscosity & \cite{Lemmon2004} & \multicolumn{2}{c}{3$\times$10$^{-5}\rho_g$ \cite{Lathouwers2001}} \\
\midrule
\multicolumn{6}{c}{Dimensional parameters}\\
\midrule
& & & \textit{biomass} & \textit{sand} & \\
$\tau_p$ &[s] & Particle response time & 0.15 & 0.16 & \\
$\mathcal{L}$ &[m] & Cluster length & 0.004 & 0.005 & \\
$\mathcal{V}$ &[m/s]& Terminal velocity & 0.028 & 0.0297 \\
$\bm{g}$& [m/s$^2$]& Gravity & \multicolumn{2}{c}{$(-0.18, 0, 0)$ } &\\
\midrule
\multicolumn{6}{c}{Non-dimensional parameters}\\
\midrule
& & &\textit{biomass} & \textit{sand} & \\
$\langle \varepsilon_p \rangle$ & \multicolumn{2}{l}{\hspace{2em} Mean particle volume fraction}& 0.005 & 0.01 & \\
$N_p$& \multicolumn{2}{l}{\hspace{2em} Number of particles} & 17\;302 & 540\;710 & \\
$\Phi_m$& \multicolumn{2}{l}{\hspace{2em} Mass loading} & 4.74 & 62.8 & \\
Re & \multicolumn{2}{l}{\hspace{2em} Reynolds number} &1.46 & 1.74& \\
Fr& \multicolumn{2}{l}{\hspace{2em} Froude number} & 8.71 & 24.4 & \\
Ar& \multicolumn{2}{l}{\hspace{2em} Archimedes number} & 3.01 & 1.28 & \\
\bottomrule
\end{tabular}
\caption{Summary of relevant simulation parameters. [1] Equation of state for an ideal gas (Eq. \ref{eq:EOS}). Note all biomass quantities are given at the unreacted state (i.e. at $t=t^{\star}$).}
\label{tab:sim}
\end{center}
\end{table}
\subsection{Chemical kinetics}
During catalytic upgrading, biomass particles are decomposed into char, syngas and tar vapor. The tar vapor undergoes secondary cracking to form additional syngas. In the current study, this process is modeled by four irreversible, first-order reactions commonly used in the literature~\cite{Xue2011, Alberto2013}. A summary of the kinetic scheme is shown in Fig.~\ref{fig:kinetics}. Here, solid biomass is composed of three components: cellulose, hemicellulose and lignin. The biomass under consideration in this study is bagasse, the woody pulp bi-product resultant of the commercial processing of sugarcane. The species composition of bagasse is given as
\begin{equation}
{\rm Biomass} = \alpha {\rm Cellulose} + \beta {\rm Hemicellulose} + \gamma {\rm Lignin},
\end{equation}
where the initial composition is given by $(\alpha, \beta, \gamma) = (0.36, 0.47, 0.17)$~\cite{Xue2011}.
\begin{figure}
\centering
\schemestart
\small{virgin biomass (s)}
\arrow{->[$k_{1}$][\begin{footnotesize}$\Delta h_1 $\end{footnotesize} ]}
\small{active biomass (s)} \hspace{3em}
\arrow(ARc--){->[$k_2$][\begin{footnotesize}$\Delta h_2$\end{footnotesize}]}[45] \hspace{3em} \small{tar vapor (g)} \arrow{->[$k_4$][\begin{footnotesize}$\Delta h_4$\end{footnotesize} ]} \small{syngas (g)}
\arrow(@ARc--){->[\begin{footnotesize}$\Delta h_3$\end{footnotesize}][$k_3$]}[-45] \hspace{13em}\small{ $\nu$ char (s) \+ $(1-\nu)$ syngas(g) }
\schemestop \\
\caption{Kinetic scheme used in the present work. Solid biomass consists of cellulose, hemicellulose and lignin. The phase of each constituent is noted in parentheses. The heats of formation for each reaction are given by: $\Delta h_1 = 0$ \cite{DiBlasi1994}, $\Delta h_2 = 255$ kJ/kg \cite{Koufopanos1991}, $\Delta h_3 = -20$ kJ/kg \cite{Koufopanos1991}, and $\Delta h_4 = -42$ kJ/kg \cite{Curtis1988}.}
\label{fig:kinetics}
\end{figure}
Upon heating, virgin biomass is activated and then devolatized into char, tar and syngas. Char remains within the particle while tar and syngas are transferred to the gas phase. The mass rates of change for the species involved in the activation and devolatization of biomass particles are given by
\begin{align}
\frac{d m^v_{i}}{dt} &= -k_{1_i} m_{i}^v \label{Eq:dmdt_bio_virgin} \\
\frac{d m^a_{i}}{dt} &=k_{1_i}m_{i}^v -(k_{2_i}+ k_{3_i})m_{i}^a \label{Eq:dmdt_bio_active} \\
\frac{d m_{\text{char}}}{dt} &= \sum_i \nu_i k_{3_i}m_{i}^{a} \label{Eq:dmdt_char} \\
\frac{d m_{\text{tar}}}{dt} &= \sum_i k_{2_i} m_{i}^{a} \label{Eq:dmdt_tar} \\
\frac{d m_{\text{syn}}}{dt} &= \sum_i(1-\nu_i)k_{3_i}m_{i}^{a} \label{Eq:dmdt_syn}
\end{align}
where $i = c, h, l$ corresponds to the biomass species cellulose, hemicellulose and lignin and the superscripts $a$ and $v$ refer to activated and virgin biomass, respectively. Secondary cracking, as it is a homogeneous reaction in the gas phase, is solved exclusively on the Eulerian mesh.
Since the biomass particles are composed at any point in time of virgin biomass, active biomass and char, the previous equations allow for an expression for the total rate of mass change for a biomass particle to be written as
\begin{equation}
\frac{dm_{\text{bio}}}{dt} = \sum_i \frac{d m_i^v}{dt} + \sum_i\frac{d m_i^a}{dt} + \frac{d m_{\text{char}}}{dt} \label{Eq:dmdt_bio}.
\end{equation}
Reaction rates for the kinetics are dictated by the Arrhenius equation
\begin{equation}
k_i = A_i \exp [-E_i/RT_p] \label{eq:reactionRate}
\end{equation}
where $A_i$ is the pre-exponential factor, $E_i$ is the activation energy, $R$ is the gas constant, and $T_p$ is the particle temperature. These quantities are summarized in Table~\ref{tab:kinetics}. Chemical kinetics are treated on the scale of the particle, and as such the mass of each species contained within each particle is tracked, but the transport within the particle itself is not considered.
\begin{table}
\centering
\def~{\hphantom{0}}
\begin{tabular}{c | c c c c }
\hline
\hline
Constituent & Reaction & $\nu$ ($k_3$) & $A \; (\text{s}^{-1})$ & $E$ (MJ/kmol) \\
\hline
& $k_{1c}$ & - & 2.8 $\times$ 10$^{19}$ & 242.4 \\
Cellulose \cite{Bradbury1979} & $k_{2c}$ & - & 3.28 $\times$ 10$^{14}$ & 196.5 \\
& $k_{3c}$ & ($\nu_c$) 0.35 & 1.3 $\times$ 10$^{10}$ & 150.5 \\
\hline
& $k_{1h}$ & - & 2.1 $\times$ 10$^{16}$ & 186.7 \\
Hemicellulose \cite{Miller1997}& $k_{2h}$ & - & 8.75 $\times$ 10$^{15}$ & 202.4 \\
& $k_{3h}$ & ($\nu_h$) 0.60 & 2.6 $\times$ 10$^{11}$ & 145.7 \\
\hline
& $k_{1l}$ & - & 9.6 $\times$ 10$^{8}$ & 107.6 \\
Lignin\cite{Miller1997} & $k_{2l}$ & - & 1.5 $\times$ 10$^{9}$ & 143.8 \\
& $k_{3l}$ & ($\nu_l$) 0.75 & 7.7 $\times$ 10$^{6}$ & 111.4 \\
\hline
Tar \cite{Liden1988}& $k_4$ & - & 4.25 $\times$ 10$^{6}$ & 108.0 \\
\hline
\hline
\end{tabular}
\caption{Rate coefficients used in the Arrhenius reaction (\ref{eq:reactionRate}).}
\label{tab:kinetics}
\end{table}
\subsection{Gas-phase description \label{sec:gas}}
The gaseous phase initially consists of pure nitrogen and evolves into a mixture of nitrogen, gaseous tar and syngas. To enforce conservation of mass, momentum and energy in the presence of solid particles, we consider the volume-filtered Navier--Stokes equations~\cite{anderson1967fluid,capecelatro2013euler}. Conservation of mass is given by
\begin{equation}
\frac{\partial}{\partial t} ( \varepsilon_{g} \rho_{g}) + \nabla \cdot ( \varepsilon_{g} \rho_{g} \bm{u}_{g}) = \sum_{l=1}^2 \dot{\mathcal{M}}_{l} \label{Eq:cont}
\end{equation}
where $\bm{u}_{g} = [u_g, v_g, w_g]^{\text{T}}$ is the fluid velocity and ${\mathcal{M}}_{l}$ is the interphase mass source term, with $l = (\text{tar}, \text{syn})$, referring to the reactive species, tar and syngas, respectively. Conservation of momentum is given by
\begin{align}
\frac{\partial}{\partial t} ( \varepsilon_{g} \rho_{g} \bm{u}_{g}) + \nabla \cdot ( \varepsilon_{g} \rho_{g} \bm{u}_{g} \bm{u}_{g}) = \varepsilon_g \nabla \cdot \boldsymbol{\tau}_{g} + \varepsilon_{g} \rho_{g} \bm{g} + \mathcal{F} + \bm{F}_{\text{mfr}}
\end{align}
where $\mathcal{F}$ accounts for two-way coupling between the gas and solid phases, which will be made explicit in Sec.~\ref{sec:gas}. $\bm{F}_{\text{mfr}}$ is a source term used to ensure that the system maintains a constant mass flow rate in order to achieve a statistically stationary state. The viscous stress tensor is given by
\begin{equation}
\boldsymbol{\tau}_{g} = -p_g \mathbb{I} +\mu_{g}^*\left\lbrack \nabla \bm{u}_{g} + \nabla \bm{u}_{g}^{\text{T}} - \frac{2}{3} (\nabla \cdot \bm{u}_{g}) \mathbb{I}\right\rbrack,
\end{equation}
where $p_g$ is the gas-phase pressure, $\mathbb{I}$ is the identity matrix and $\mu_{g}^*$ is an effective viscosity accounting for enhanced dissipation at the particle scale, given by~\cite{gibilaro2007apparent}
\begin{equation}
\mu_{g}^* = \mu_{g} \varepsilon_{g}^{-2.8}.
\end{equation}
Figure~\ref{fig:CITvs0D} shows the evolution of Favre averaged temperature, syngas mass fraction and tar mass fraction. Here, Favre average quantities are defined as $\widetilde{ (\cdot) } = \langle \varepsilon_g\rho_g\left(\cdot\right)\rangle / \langle \varepsilon_g \rho_g\rangle$. To assess the role of heterogeneity caused by clusters on thermochemical conversion, comparisons are made against a zero-dimensional system that models a homogeneous flow under identical conditions. In this system, all spatial variations are neglected and variables are solved for as a function of time only. A single, stationary biomass particle is introduced at a starting temperature of 300 K into a hot volume of nitrogen such that the volume fraction $\langle \varepsilon_p \rangle$ is consistent with the three-dimensional simulation. As was done in the three-dimensional case, the mean gas-phase temperature is forced to remain constant at 790 K.
\begin{figure}
\centering
\begin{subfigure}[b]{0.325\textwidth}
\caption{Temperature [K]}
\includegraphics[width = \textwidth]{3DTCIT}
\end{subfigure}
\begin{subfigure}[b]{0.315\textwidth}
\caption{Syngas [-]}
\includegraphics[width = \textwidth]{3DSGCIT}
\end{subfigure}
\begin{subfigure}[b]{0.315\textwidth}
\caption{Tar [-]}
\includegraphics[width = \textwidth]{3DTARCIT}
\end{subfigure}
\caption{Evolution of the gas-phase temperature, syngas, and tar. Mean values for three-dimensional CIT (dashed purple lines) and a homogeneous (zero-dimensional) system under identical conditions (solid black lines). The shaded regions correspond to $\pm3$ times the standard deviation in CIT.}
\label{fig:CITvs0D}
\end{figure}
Three key observations can be made: (1) spatial variations present in CIT induce variations in gas-phase temperature (which are large at early times due to the discrepancy in initial temperature between biomass particles and their surroundings). (2) Variations also exist in the mass fractions of tar and syngas. At early times ($t\lessapprox4\tau_p$), syngas and tar are predominantly formed in clusters where the majority of biomass particles exist, despite the lower temperature in these regions. The species are then transported away from clusters, where secondary reactions occur. (3) Because the zero-dimensional model does not account for heterogeneity in spatial distribution, it over-predicts both tar and syngas formation. The typical residence time for cellulosic biomass in a circulating fluidized bed reactor is approximately 1 s, corresponding to $6.25\tau_p$. Figure~\ref{fig:CITvs0D} shows that the zero-dimensional model over-predicts both tar and syngas production when simulation time reaches standard residence time by 8.9\% and 13.0\%, respectively. It is notable that for residence times less than 1 s, the zero-dimensional model achieves a maximum over-prediction of 32.9\% for syngas yield at $(t-t^{\star})/\tau_p = 4.02$ (0.64 s). Maximum over-prediction in the yield of tar is 9.0\% occurring at $(t-t^{\star})/\tau_p = 4.63$ (0.74 s). This suggests that heterogeneity plays an especially important role in systems with short residence times, for instance flash pyrolysis.
\section*{References}
\bibliographystyle{unsrtnat}
\bibliography{pyrolysis}
\end{document}
\endinput
When starting out with LaTeX, you'll undoubtedly ask yourself, 'But isn't [insert text editor you usually use] so much quicker/easier/etc.?' Maybe it is right now, but with practice, typesetting with LaTeX is quicker and looks more polished (especially when creating documents with lots of equations). In fact, once you get the hang of coding in LaTeX, you'll realize how time-consuming the equation editor in ppt and word really was and how much more streamlined having control over all aspects of the typesetting is.
