In general, the best hardware will be: the latest generation of processors, 4GB RAM per core and an SSD.

Based on your budget, an older processor, 2GB of RAM per core and a standard hard drive may also be sufficient for running ADF jobs. Since floating-point performance is crucial for ADF, we do not recommend to use hyperthreading or use all Opteron logical cores (i.e. run one process per floating point unit).

Note that since chips are continuously improved, specific recommendations may change. As of early 2015, these configurations should give the best performance for ADF:

Desktop or laptop: a quad-core i7 processor from the latest generation, 16GB of RAM and an SSD (a fusion drive may also work).

High-end workstation or a cluster: a dual-CPU Xeon E5 setup with at least 2GB, but better 4GB, of RAM per core and an SSD. Using an SSD becomes more essential as the number of cores per node increases. For calculations on multiple nodes, get a fast interconnect (Infiniband).

The short answer is “yes”. Windows users and nonexpert users definitely need a Graphical User Interface to work productively with our software. But also experienced computational chemists will appreciate the convenience of setting up complicated calculations with suggested settings, and especially the output visualization. Without the GUI, you will miss a lot. For that reason, we’ve presented the standard prices of ADF and BAND including already one copy of the ADF-GUI (resp. BAND-GUI).

Yes, the integrated GUI works with all our software, however, you can only use it for the features that are licensed.

Example: You have removed the GUI from your ADF license and have now bought BAND with a GUI: You can only drive BAND through the GUI, not ADF. You have to pay the ADF-GUI license to unlock the ADF features of your GUI.

No, usually you don’t need the source code.
We collaborate with all major hardware vendors to port and optimize our code on the most popular platforms. The binaries work out-of-the-box in parallel with fast interconnects through included MPI libaries or with the native parallel libraries (MPT, POE). The binaries are also shipped with linked-in mkl libraries, and are thoroughly tested against a test set before they are released.
Should the latest binary for your system not be available, we are happy to help you port it to your platform. If you are an experienced system administrator you can also compile ADF yourself e.g. on an unusual supercomputing platform. In this case we do not charge you for using the source code.

Only when you want to modify the source code to use non-standard options and features do you need to purchase the source code. Changes in the compiler flags, which have been carefully optimized for performance and robustness, are not recommended and the use of different compiler flags is at your own risk.

Scientists interested in further developing the ADF suite should e-mail us to discuss a possible collaboration with SCM, including a discounted (source code) license.

Hyperthreading does not speed up your ADF calculations, so it is not recommended to enforce this (by using a license for more cores and setting NSCM to double the number of physical cores). For licensing purposes, we only count physical cores. So, for instance, a hexa core machine with hyperthreading counts as six cores.

The latest AMD architectures have only one floating point unit per two cores. It is thus recommended to run ADF only on half of the cores on these machines, and we try to license these machines accordingly.

By default ADF tries to use all physical cores. So no hyperthreading and half of the cores of some AMD architectures.
To change this behavior, you need to set the NSCM variable, either in the environment, in your submit script, or in the queue definition in ADFjobs.

E.g. running from the command line on Linux: export NSCM=4 will make ADF use 4 cores even if there are 2 or 8 physical cores.

Likewise in ADFJobs you can change your sequential queue Queue => Edit => Sequential
Enter the desired number of cores in the ‘Default Options:’ field. Since this is the default queue so if you run a job without specifying a queue or modifying the default field in ADFJobs, it will use your indicated number of cores.

Download the correct binary, usually the standard binary will do. Follow the quickstart guide and let us know at if you run into any problems.
You should be able to automatically download a demo license. If your machine is not on the internet, run

which should give you a LICENSE INVALID message and your machine info, which you should send to to request a demo license for your machine.

This error message (which might also tell you “Could not create lock file in /tmp/…”) is generated by XQuartz. It may be solved by reinstalling XQuartz.

If you have problems with running ADFGUI remotely with a recent development snapshot, have a look at the extensive remote GUI description in the (development version) documentation.

ADF2016 users on Mac OS X who update to XQuartz 2.7.9 will discover that they cannot use GLX applications remotely any more. This includes the ADFGUI. To solve, at this point in time: stick to the older version of XQuartz (2.7.8), or install the latest version (currently 2.7.11):

After installing they should run this command to enable GLX:

defaults write org.macosforge.xquartz.X11 enable_iglx -bool true

The ADF installer sets the necessary environment variables in the Windows registry and notifies Explorer, but sometimes the latter does not work. In that case if you try to pick up your automatic demo license, you get the error message about the SCMLICENSE not being set.

If you reboot your system, the SCMLICENSE variable should be properly set and with your credentials you can then automatically download your demo license.

If you have a valid username and password (your evaluation period is still active or you are a current ADF licensee), you should be able to download ADF with the provided password and username.

The browser could have cached the wrong password from a previous attempt. Try again with a private session. Make sure you don’t include any spaces, the username is usually 6 characters and the automatically generated password is exactly 8 characters. If you still have problems, contact us at with the username and password and the download link for the binary you tried to download.

MPI Application rank … exited before MPI_Finalize() with status …
is an error that could have occured for several reasons. Please contact with:

  • input (.run), output (.out), logifle (.log, error (.err) for your job
  • your operating system (Windows 32/64 bit, Linux (distribution), MacOS (version))
  • which version of ADF you downloaded

It is easy to have your local GUI to set up and monitor jobs as well as visualize results, while submitting jobs to remote queues.

A video shows how to set up remote queues on Windows.

There are some conditions that must be fulfilled however. The main condition is that you must be able to log on to the remote computer using ssh (or, on Windows, plink.exe) without being asked for any passwords or confirmations. The common way for this is using public key authentication and the ssh-agent. Detailed instructions for Windows users are available in the Readme.rtf document and in its PDF version DocInstallation_windows.pdf (both in the ADF installation folder). Unix/Linux users probably already know how to do this. The other condition is: ADF must be installed on the remote machine and the commands that set up relevant environment variables must be present in the shell profile file, for example ~/.profile.

Suppose you are able to log on to the remote machine and suppose the machine is called, and your login there is myname (of course you will use real values instead of these). The machine is a login node of a cluster and PBS is the batch system used on the cluster. Our experience shows that this is a very common configuration among ADF users.
Now we need to configure a new queue in ADFjobs. Let’s call the queue cluster_PBS. Use the menu command Queue->;New…->PBS. The template already supplies some default values but you may want to change them depending on the cluster policies.

First the easy parts: type cluster_PBS in the Queue Name field, for Remote host, myname for Remote user. The Remote job directory specifies a directory on the cluster where ADFjobs will place job files.

The Run command is probably what you will want to think about more thoroughly. In the template it contains

qsub -lnodes=2:ppn=2:infiniband -lwalltime=$options “$job”

You may have to change everything between qsub and “$job” on the line depending on how PBS is configured on the cluster. This will also determine the value for the Default Options entry.

In the template, the wall clock time is configurable per job but you may decide that it is better to have the number of nodes as an option. In this case the Run command will look as:

qsub -lnodes=$options:ppn=2:infiniband -lwalltime=100:00:00 “$job”

Of course you can add there other qsub command line switches that you would normally put in the script after #QSUB. So if you choose to “hard-code” the number of nodes and leave walltime configurable then you may want to name the queue something like cluster_PBS_2nodes. If you choose to hard-code the walltime and leave the number of nodes configurable then you may want to name the queue cluster_PBS_100hr or something like that so that you can distinguish it from other similar queues that differ from this one by the hard-coded value.

After you’ve finished configuring the queue, press Save and test that you can see the status of the queue by selecting menu Queue->Status. This will query the status for each queue defined in ADFjobs by running the command specified in the System status command field (remotely if necessary). If you do not get the queue status but something like “Connection refused” or “No more authentication methods left” then check the ssh connection to the remote computer.

Finally test your queue by running a Test job.

If everything works as you like, you may consider setting your new queue as the Default Queue in ADFjobs. Then using the Run command in ADFinput or in ADFjobs will automatically assign this new queue to your job, and run the job on the remote machine.

Common 64-bit binaries for the latest subreleases for Mac, Windows, and Linux can still be downloaded.

Contact us if you need a different subrelease or a different OS. A list of bugfixes for ADF2014 and available binaries is also available.

No, Gaussian-type orbitals can not be used in ADF, since ADF uses Slater Type Orbitals (STOs).

Slater orbitals are better from a theoretical point of view since they have the correct behavior near the nucleus (cusp) and the correct asymptotic long-range behavior. Consequently, typically fewer STOs than GTOs are needed to reach a certain level of accuracy, as discussed in this news item Slaters beat Gaussians and a paper benchmarking DFT methods for a catalytic reaction.

There is no silver bullet. Some general recommendations follow below, which are by no means definite. Please check the literature carefully and check the robustness of the results by using a large basis set eventually, if possible.

The nomenclature of the STO basis sets in ADF simple: D, T, and Q stand for double, triple, and quadruple, and (n)P stands for n polarization functions. For example the DZP basis stands for double zeta + 1 polarization function. Inner electrons of (atomic) fragments can be frozen during the molecular calculation, this is denoted with ‘small’, ‘medium’ or ‘large’, or by specifically specifying up to which shell the electrons are frozen.

There are also specialized basis sets, e.g. containing diffuse functions (“AUG”, for describing anions and diffuse excitations), even-tempered basis sets (“ET”, for describing core electron binding energies), and optimized for ESR A-tensor and NMR spin-spin coupling calculations (ZORA/jcpl). See also the documentation for more technical details and the basis set database in ADF.

The DZP basis set could be a good starting point, especially for geometry optimization. See also this paper looking at catalytic reactions. In general this basis it is expected to be slightly better than the often used 6-31G* basis set in codes which use Gaussian basis sets. The DZP basis defaults to TZP for transition metals. The frozen core approximation generally does not affect geometries much, but a too large frozen core can lead to inaccuracies.

For the most accurate predictions of spectroscopic properties the largest QZ4P basis is recommended, although often the TZ2P basis is already close to the basis set limit. Also, usually an all-electron basis set is necessary to properly describe properties related to inner electrons (NMR, EPR, X-ray absorption).

The tutorial on calculating UV/VIS spectra with ADF will get you started with the basics. For getting more accurate results, however, you need to consider the technical details used in TDDFT, such as basis set, exchange correlation functional, and other settings.

There are also faster approximate TDDFT methods available, such as TDDFTB (see tutorial), sTDDFT and TDDFT+TB.

You are advised to check the literature on which approaches are suitable for similar compounds. Here are some general recommendations on what could work well in ADF:
1) optimize your molecule. Scalar relativistic, TZP, small core (although a large frozen core could also work), and numerical quality ‘Normal’ would typically be quite accurate. As to the functional, a GGA perhaps with dispersion corrections could give very good results (e.g. PBE-D3(BJ)). GGAs are much faster in ADF and can yield better geometries than hybrids. Note that the dispersion interactions affect the geometry, and thereby indirectly the electronic structure, including excitations.

2) TDDFT calculation for UV/VIS. Scalar relativistic up to 4d-elements is usually sufficient. For heavier elements you may want to check the effect of spin-orbit coupling on the spectrum (see also highlight on conversion efficiency of solar cell dyes). You may want a larger basis set (e.g. TZ2P) and perhaps all-electron. Also a higher accuracy may be desirable (good, or excellent). As to the number of excitations, this depends a bit on the electronic ground state and which excitations you are interested in. You could start with 30 or so to see how much to the blue/UV will be covered. Finally the functional could play an important role. The asymptotically correct SAOP model potential is often used, since this is an accurate Kohn-Sham potential well suited to describe virtual orbitals (see publication by Baerends et al.). You could also try hybrids (e.g. B3LYP) or metahybrids (M06-2X). Range-separated hybrids (CAMY-B3LYP) are sometimes advised for excitations with long-range charge transfer character. SAOP calculations will be much faster in ADF than hybrids.

Further comments:

  • for symmetric systems, ALLOWEDONLY can reduce the computation time by excluding the excitations which are symmetry-forbidden
  • for very large systems you may consider trying out TD-DFTB in combination with filtering out the single orbital transitions with very low oscillator strength
  • vibronic fine structure may be included by calculating Franck-Condon Factors. Since this involves calculating excited state frequencies (numerically), the calculations can be very demanding for large systems

You can do COSMO calculations with ADF. The COntinuum SOlvation MOdel treats the solvent as a polarizable continuum. You can also use other solvation models (SM12, SCRF, 3D-RISM) or subsystem DFT (Frozen Density Embedding) to include environment effects.
COSMO-RS (Realistic Solvents) is for calculating thermodynamic properties of (mixed) fluids. It uses post-ADF results (sigma profiles) for determining interactions between species in the liquid phase. You will typically not need COSMO-RS if you want to include solvent effects in your DFT calculation, but some properties such as solvation free energies may be more accurately treated with COSMO-RS than with COSMO.

To speed up a molecular or periodic DFT calculation, inner electrons of atoms can be frozen. Note that this is not a pseudopotential: all electrons are still present, the cores are just frozen at their optimized atomic configuration. The effect on the equilibrium geometry and properties of valence electrons is usually small. For spectroscopic properties of core electrons, or electrons close to the nucleus, typically an all electron (AE) approach is necessary.

In the atomic database (you can browse $ADFHOME/atomicdata to see which basis sets are available) the AE basis sets are denoted as the element names, while the name is extended with the highest shell that is kept frozen for the frozen core basis sets.

small core: the smallest core available in the basis set database, for example:

  • Rh.3d: all 28 electrons up to 3d are frozen: [Ar]3d10. The valence orbitals are: 4s, 4p, 5s, 4d, 5p.
  • Au.4d: all 46 electrons up to 4d are frozen: [Kr]4d10. The valence orbitals are: 5s, 5p, 6s, 4f, 5d, 6p.

large core: the largest core available in the basis set database, for example:

  • Rh.4p: all 36 electrons up to 4p are frozen: [Kr]. The valence orbitals are: 5s,  4d, 5p.
  • Au.4f: all 60 electrons up to 4f are frozen, [Kr]4d104f14. The valence orbitals are: 5s, 5p, 5d, 6s, 6p.

Note that for some elements and basis sets there is just 1 core available (e.g. 1s for C), in which case all core options default to that specific frozen core.

When there are two options available (e.g. Rh.3d and Rh.4p), the medium core option typically defaults to the large core option. The use of medium core is therefore not recommend, we suggest to choose your specific basis set, either from the GUI in the basis set details panel, or by browsing the available basis sets and specifically defining the appropriate core.

Fragment files in ADF must be spin-restricted. So if you want to do an energy decomposition of a chemical bond made between fragments with unpaired electrons, you should start with restricted fragments.

You can then use FragOccupations to set the spin-α and spin-β occupations in the fragments and do an unrestricted bonding analysis.

Rather than using a restricted calculation for the fragment with unpaired electrons, which can lead to SCF convergence issues, you may consider an advanced trick as
discussed by Mariusz Mitoraj
. This involves running an unrestricted Kohn-Sham calculation on your fragment, which should converge more easily. You then copy the α-orbitals into a restricted fragment (set SCF=0) t21 file.

Note that in either of these approximations spatially identical orbitals for α and β will be used, although if you duplicate the α spatial orbitals from an unrestricted run you will likely include some spin-polarization of the frontier orbitals. If you want to use truly unrestricted fragments, you could consider EDA in BAND for 0D systems (see tutorial with 1D periodicity).

There is also an example for Bond Energy analysis on open-shell fragments.

No, when you do a spin-restricted calculation in ADF with an odd number of electrons, you do not get the energy expression that is used in ROKS. In ROKS, the spin-unrestricted energy is optimized with alpha orbitals restricted to have the same spatial form as the beta orbitals. In ADF using a restricted calculations with an odd number of electrons will just result in fractional occupations of the frontier orbital. The energy of this electronic configuration is not the same as in a ROKS calculation.

Unrestricted calculations (UKS) in ADF should lead to proper integer occupations of the alpha and beta electrons, which are treated independently and can have spatially different forms.

You can for certain types of calculations (energies, forces and Hessians for GGAs only).
You will need a Linux OS with an NVidia CUDA GPU that does double precision, see the documentation for more details.

ADF does not calculate total energies. It calculates difference energies with respect to fragment energies. By default, these are the spherical spin-restricted atoms. For this reason total energies from other programs cannot be compared to ADF directly. Only energy difference comparisons are meaningful. These are the only energies that play a role in chemistry of course.

If you do need the total energy, there is a workaround: calculate total energies of the atomic fragments and add them to the bonding energy.

Because the total energy of an atom is, by definition, the energy difference between the atom and the (nucleus+free electrons) system one can calculate it by calculating a single atom with the charge equal to the number of electrons. The ‘bonding energy’ of such an ‘atom’ will then be equal to negative of the total energy of the atomic fragment. Care should be taken to apply this trick to frozen-core fragments. In this case, it only makes sense to remove the valence electrons and leave the frozen core.

You need to subtract the bonding energies of the individual atoms from the bonding energy of the molecule.
Care must be taken to get the correct atomic reference state. Usually you will need to break the symmetry (otherwise spherical symmetry is used) and note that ADF can not perform restricted open-shell Kohn-Sham (ROKS) calculations. An example input for the triplet oxygen atom:

O 0.0 0.0 0.0
Type QZ4P
Core None
numericalquality good
hybrid B3LYP
charge 0 2
symmetry nosym
A 5 // 3
end input

There are a few options to aid SCF convergence:

  • modern SCF algorithms: A-DIIS is usually a good option, and is default since ADF2016. Alternative options are LISTi (with good scaling) and ARH (slower per SCF cycle). E-DIIS is similar to A-DIIS but slower
  • use the OCCUPATIONS key to specify occupation numbers
  • use electron SMEARING for systems with low HOMO-LUMO gap
  • use KEEPORBITALS to keep the same orbitals occupied after a certain number of steps

See the SCF troubleshooting section of the ADF manual and send us relevant input and output if you keep having problems.

There may be a few reasons why imaginary frequencies are found after geometry optimization:

  1. The optimization threshold is not strict enough for the molecule’s potential energy surface (PES). For example, if there are almost no-barrier rotational modes (e.g. methyl groups in some situations) or cyclopentane-like fragments then the PES in such cases may be almost flat. In this case, much more strict convergence criteria (and higher integration accuracy) may be necessary to get to the energy minimum.
  2.  Even with tight convergence criteria, one may get a small imaginary frequency due to numerical noise, which is always present in every calculation. In this case it may be useful to scan the normal mode corresponding to the imaginary frequency and recheck is the frequency is indeed imaginary by finite differences. The latter is done using the SCANFREQ keyword, which is enabled by default in the ADFinput GUI module.
  3. If the scan shows an imaginary frequency then it means that the preceeding geometry optimization converged to a saddle point. This may happen when optimization was started close to the saddle point without a good Hessian estimate. In such a case ADF did not make enough steps to get a good Hessian approximation and figure out that it has negative eigenvalue(s).

Yes, it is be possible to combine COSMO and TDDFT. This will modify the zeroth-order KS orbitals and their energies, which is usually the most important solvation effect. COSMO could also modify the first-order change in the KS potential. This effect has been implemented and will certainly be important in case of a high value for the dielectric constant. The response of the COSMO surface charges due to the TDDFT-induced modified charges may be switched off (NOCSMRSP), which is probably a better representation of the solvent response for instantaneous (de)excitation.

In the response part of the calculations, one can also use a different dielectric constant . The reason for using two different dielectric constants is that the electronic transition can be so fast that only the electronic component of the solvent dielectric can respond, i.e., one should use the optical part of the dielectric constant. This is typically referred to as non-equilibrium solvation. If one optimizes an excited state, the solvent dielectric has time to fully respond and the same dielectric constant should be used..

Yes. See the tutorial and documentation on excited state geometry optimizations.

Yes, this can be done numerically by distorting the structure along the normal modes.
First calculate the normal modes “q” with ADF. Then calculate the polarizability tensor by applying finite electric fields at the geometries q_o + dq and q_o – dq.
From this one can obtain, by double finite difference, the derivative of the polarizability w.r.t. a particular normal mode of interest. This should be less time-consuming then a regular Raman calculation as well.

The beta tensor can be obtained by using the input key RESPONSE, for example:


In order to obtain gamma, one should calculate beta in small electric fields. Such a field can be switched on by specifying, for example: EFIELD 0 0 0.001 for an electric field of 0.001 a.u. in the z-direction. The beta calculation needs to be repeated for different field directions. gamma_zzzz can be obtained from (for example): gamma_zzzz = beta_zzz (E=0.001 z) – beta_zzz (E=-0.001z) / (2 * 0.001)

Similar relations hold for other tensor components.

Recently, the group of Lasse Jensen has implemented damped quadratic and cubic response, which gives access to many  non-linear optical properties including two-photon absorption. These methods will become available in ADF2017.

For a spin restricted open-shell calculation, save TAPE21, and use the whole molecule as a fragment in a SR unrestricted calculation with the keywords:

iter 0

ADF wil use the fragment density coming from the spin-restricted calculation as start-up density in the unrestricted calculation. iter 0 means that only 1 scf-iteration will be performed with the use of the fragment density (one should use the same XC-potential in both calculations of course), such that the alpha-orbital energies remain degenerate with the beta-orbitals.

After a calculation with ADF, BAND, ReaxFF, DFTB etc you will have a result file (a .t21, .runkf, .rxkf, or .rkf file). These are binary files, and like all other binary files used by the ADF package they are written using the KF library. The data are organized in sections, and each section can contain variables (either real, integer, string or logical). They may be transported between different platforms, conversion is performed automatically when needed.

Not all data on the files are intended to be used directly by end users, the detailed meaning of many data items will not be clear to end users who do not have access to the source code. Preferably use the GUI utilities to visualize the results or scripting tools to get relevant results from a batch of calculations.

The KF Browser is a useful tool to browse through our binary files. The available data can be searched, copied as text and plotted as graphs. It can be  started from the GUI (SCM → KF Browser) or from the command line ($ADFBIN/kfbrowser filename). To see all raw data, switch to the Expert mode (File → Expert Mode in KF Browser).
adfreport is a command line tool to quickly access results from different result files (.t21, .runkf, .rkf, .rxkf) in a uniform manner. You can get any variable from a result file by key value, or you can use predefined report commands (like geometry, charges, energy, etc). Run with the -h flag to get help and a detailed description of all predefined commands).
Note: if you include the -h flag and a filename, you will get specific help for the contents of that file.
To use adfreport via the command line: $ADFBIN/adfreport [-h] filename
KF Utilities are a set of command line utilities to handle KF files.
pkf: print the table of contents
dmpkf: dump the contents of all or part of a KF file to an ASCII file
udmpkf: make a binary KF file out of a ASCII file (typically a dumped KF File)
cpkf: copy all or part of one KF file to another KF file, or remove data from a KF file.
KFReader: C routines to read binary KF files python interface for reading binary KF files (requires ADF installation).

A possible origin of this problem is that ADF symmetrizes the input coordinates of fragments which are nearly symmetric. As a consequence, the fragment coordinates can no longer be transformed to their position in the full calculation of the complex.

The workaround is to use SYMMETRY TOL=1.0e-10 in the calculation of the fragments, such that the coordinates in the fragments are not symmetrized.

This message shows that the numerical integration is not as accurate as required (currently tested only with spin-orbit calculations). You can force the calculation to continue using the ALLOW BADINTEGRALS input key. This will force the calculation to continue, but remember there are possible inaccuracies due to these integrals. You can probably increase the accuracy of the eta integrals by increasing the overall integration accuracy (using the integration key). One will then probably still get the BAD ETA INTEGRALS message, but this is relative to the required accuracy. One can check the accuracy (it is printed on output), and if the accuracy is good enough one can use the ALLOW BADINTEGRALS key to force the calculation to continue.

One of the reasons can be that the SCM_TMPDIR environment variable also contains non-ASCII characters and ADF cannot use it. The solution is to set the SCM_TMPDIR value to a path that does not contain non-ASCII characters, for example, C:\TMP:

  1. Right click on My Computer
  2. Select Properties item in the pop-up menu
  3. Click on the “Advanced” tab
  4. Click on the “Environment Variables” button
  5. In the upper half under “User variables for …”, click the New button
  6. Enter SCM_TMPDIR in the variable name and C:/TMP in the variable value field. Please note that the path in the variable value must not contain spaces. It is also advised to use forward slashes as a path separator instead of the backslash
  7. Make sure the C:\TMP directory exists and is writable by anyone
  8. Click on the Ok button in all windows to confirm your change
  9. If you use the GUI, restart it so the change takes effect

BAND does not calculate the total energy. Instead, it calculates the formation energy with respect to the spherically symmetric spin-restricted atoms. The reason is that this number is easier to determine accurately using numerical integration then the total energy.

The problem is that BAND is (internally) centralizing the atom positions with respect to the geometrical center of the structure. During this centralization an atom can be positioned on one side of the unit cell or the other. (the result for this individual calculation will be the same in both cases, but for a PEDA calculation that is not true) In your case, the centralization of the fragments and of the PEDA calculation gave results which cannot be transformed into one another by a simple translation.

The solution is to pre-centralize the whole system with respect to the geometrical center of the “bigger” fragment. (since this fragment usually gives this problem) E.g. if you study a surface-adsorbate interaction, you centralize the whole structure w.r.t. the geometrical center of the surface. In some cases the adsorbate fragment might be the reason of the problem. If so, we recommend redefining the unit cell so that the adsorbate is closer to the center of the unit cell than to any of the borders of the unit cell.

If this approach does not solve your problem please send us your input and output, so we can look into it.

The dimension of the text-book “density of states per unit cell” (DOS) is [1/energy].
What is plotted in the BAND-GUI is not the DOS, but a histogram of the DOS, which is a dimensionless quantity.
The “unit” of the y-axis is [number of states / unit cell].
Each data-point in the plotted DOS represents the number of states (per unit cell) in an energy interval DeltaE. The histogram bin-width DeltaE depends on the DOS input options “Energies”, “Min”, “Max”: DeltaE = (Max-Min)/Energies.
In case one really wants the “text-book” dos, one can set the Dos%IntegrateDeltaE option to “false”. The result will be a very wild function.

The negative values in the partial DOS are artifacts due to the fact that in a non-orthogonal basis set the definition of a “partial DOS” is somewhat arbitrary.
The partial DOS can be a useful tool for understanding the physics/chemistry of your system, but it’s strictly speaking not a “physical quantity”.

You do not need COSMO-RS to do ADF calculations with continuum solvation (see COSMO vs COSMO-RS FAQ). If you want to calculate thermodynamic properties like partition coefficients, VLE, solubilities, etc. you do need COSMO-RS. COSMO-RS usually also yields more accurate solvation free energies and pKa values than COSMO.

In principle, yes, but your are advised to rerun the COSMO calculation with ADF.

Since ADF uses a slightly different procedure (gas phase optimization followed by COSMO calculation with an infinite dielectric constant) as well as different technical settings (basis set, integration, surface charge generation), our COSMO-RS implementation has been reparametrized specifically for use with sigma profiles generated in that way. Therefore you are advised to follow the set procedure in ADF, easiest is to use the COSMO-RS preset in the ADF GUI.

See for details: C.C. Pye, T. Ziegler, E. van Lenthe, J.N. Louwen, An implementation of the conductor-like screening model of solvation within the Amsterdam density functional package. Part II. COSMO for real solvents, Can. J. Chem.87, 790 (2009)

If you do insist on using sigma profiles generated with the other programs with different defaults, you can use the cosmo2kf utility to convert the plain ascii cosmo files to our binary file format.

There are also scripting tools for COSMO-RS to facilitate screening solvent (combinations) for activities, partition coefficients, VLE, etc.

We have text files for the regular compounds and ionic liquids. If you install the databases you can also search on elemental composition. 

With ADF/DFTB we ship the following parameters:

  • Quasinano 2013: electronic parameters for H-Po, La, Th. Enabling electronic properties like band structures, DOS, UV/VIS, NEGF
  • Quasinano 2015: + repulsive parameters for H-Ca, Br. Enabling geometry optimization, IR spectra, MD.
  • Dresden parameters: C, H, O, N, P, S, Al, Si, Ti, Cu, Na, see $ADFHOME/atomicdata/DFTB/Dresden/README
  • parameters (see Readme or website for latest info). Encrypted parameters may also be evaluated during trial
  • Dispersion corrections available (Grimme’s D2 & D3(BJ), London, UFF)

Yes, with DFTB3 and either the Quasinano or the 3ob parameters sets. With other DFTB methods and parameter sets you can use D2, London (ULG) or UFF dispersion.

In ADFInput in the Details → Run script tab, you can change the MOPAC input file before submitting the calculation.
A list of MOPAC keywords (from

Keywords used in MOPAC2012

& Turn next line into keywords
+ Add another line of keywords
0SCF Read in data, then stop
1ELECTRON Print final one-electron matrix
1SCF Do one scf and then stop
ADD-H Add hydrogen atoms (intended for use with organic compounds)
A0 Input geometry is in atomic units
AIDER Read in ab-initio derivatives
AIGIN Geometry must be in gaussian format
AIGOUT In arc file, include ab-initio geometry
ALLBONDS Print final bond-order matrix, including bonds to hydrogen
ALLVEC Print all vectors (keywords vectors also needed)
ALT_A=A In PDB files with alternative atoms, select atoms A
ALT_R=A In PDB files with alternative residues, select residues A
ANGSTROMS Input geometry is in Angstroms
AUTOSYM Symmetry to be imposed automatically
AUX Output auxiliary information for use by other programs
AM1 Use the AM1 hamiltonian
BAR=n.nn reduce bar length by a maximum of n.nn%
BCC (Unique) Solid is body-centered cubic (used by BZ)
BFGS Optimize geometries using bfgs procedure
BIGCYCLES=n Do a maximum of n big steps
BIRADICAL System has two unpaired electrons
BONDS Print final bond-order matrix
BZ Generate a file for use by program BZ
CAMP Use Camp-King converger in SCF
CARTAB Print point-group character table
A multi-electron configuration interaction specified
CHAINS(text) In a protein, explicitely define the letters of chains.
CHECK Report possible faults in input geometry
CHARGE=n Charge on system = n (e.g. NH4 = +1)
CHARGES Print net charge on system, and all charges in the system
CHARST Print details of working in CHARST
CIS C.I. uses 1 electron excitations only
CISD C.I. uses 1 and electron excitations
CISDT C.I. uses 1, 2 and 3 electron excitations
COMPFG Print heat of formation calculated in COMPFG
COSCCH Add in COSMO charge corrections
COSWRT Write details of the solvent accessible surface to a file
CUTOFP=n.nn Madelung distance cutoff is n .nn Angstroms
CUTOFF=n.nn In MOZYME, the interatomic distance where the NDDO approximation stops
CYCLES=n Do a maximum of n steps
CVB In MOZYME. add and remove specific bonds to allow a Lewis or PDB structure.
DAMP=n.nn n MOZYME. damp SCF oscillations using a factor of n.nn
DATA=text Input data set is re-defined to text
DCART Print part of working in DCART
DDMAX=n.nn See EF code
DDMIN=n.nn Minimum trust radius in a EF/TS calculation
DEBUG Debug option turned on
DEBUG PULAY Print working in PULAY
DENOUT, DENOUTF Density matrix output
DENSITY Print final density matrix
DERI1 Print part of working in DERI1
DERI2 Print part of working in DERI2
DERITR Print part of working in DERIT
DERIV Print part of working in DERIV
DERNVO Print part of working in DERNVO
DFORCE Force calculation specified, also print force matrix.
DFP Use Davidson-Fletcher-Powell method to optimize geometries
DISEX=n.nn Distance for interactions in fine grid in COSMO
DISP Print the hydrogen bonding and dispersion contributions to the heat of formation
DMAX=n.nn Maximum stepsize in eigenvector following
DOUBLET Doublet state required
Dynamic reaction coordinate calculation
DUMP=nn.nn Write restart files every n seconds
ECHO Data are echoed back before calculation starts
EF Use ef routine for minimum search
EIGEN Print canonical eigenvectors instead of LMOs in MOZYME calculations
EIGS Print all eigenvalues in ITER
ENPART Partition energy into components
EPS=n.nn Dielectric constant in COSMO calculation
ESP Electrostatic potential calculation
ESPRST Restart of electrostatic potential
ESR Calculate RHF spin density
EXCITED Optimize first excited singlet state
EXTERNAL=name Read parameters off disk
FIELD=(n.nn,,l.ll) An external electric field is to be used
FILL=n In RHF open and closed shell, force M.O. n to be filled
FLEPO Print details of geometry optimization
FMAT Print details of working in FMAT
FOCK Print last Fock matrix
FREQCY Print symmetrized Hessian in a FORCE calculation
FORCE, FORCETS Calculate vibrational frequencies
GEO-OK Override some safety checks
GEO_REF=<text> Use native structure as reference
GNORM=n.nn Exit when gradient norm drops below n .n kcal/mol/Angstrom
GRADIENTS Print all gradients
GRAPH Generate unformatted file for graphics
GRAPHF Generate formatted file for graphics suitable for  Jmol and MOPETE.
HCORE Print all parameters used, the one-electron matrix, and two-electron integrals
HESSIAN Print Hessian from geometry optimization
HESS=n Options for calculating Hessian matrices in EF
Heat of formation takes priority in DRC
HTML Write a web-page for displaying and editing a protein
HYPERFINE Hyperfine coupling constants to be calculated
INT Make all coordinates internal coordinates
INVERT Reverse all optimization flags
IONIZE Do not use – use SITE=(IONIZE) instead
Intrinsic reaction coordinate calculation
ISOTOPE Force matrix written to disk (channel 9 )
ITER Print details of working in ITER
ITRY=nn Set limit of number of SCF iterations to n
IUPD=n Mode of Hessian update in eigenvector following
KINETIC=n.nnn Excess kinetic energy added to DRC calculation
KING Use Camp-King converger for SCF
LARGE Print expanded output
LBFGS Use the low-memory version of the BFGS optimizer
LET Override certain safety checks
LEWIS Print the Lewis structure
LINMIN Print details of line minimization
LOCALIZE Print localized orbitals.  These are also called Natural Bond Orbitals or NBO
LOCATE-TS Given reactants and products, locate the transition state connecting them
LOG Generate a log file
MECI Print details of MECI calculation
MERS=(n1,n2,n3) Keyword for BZ
METAL=(a[,b[,c[…]]]) Make specified atoms 100% ionic
MICROS=n Use specific microstates in the C.I.
MINMEP Minimize MEP minima in the plane defined
MMOK Use molecular mechanics correction to CONH bonds
MNDO Use the MNDO hamiltonian
MNDOD Use the MNDO-d hamiltonian
MODE=n In EF, follow Hessian mode no. n
MOL_QMMM Incorporate environmental effects in the QM/MM approach
MOLDAT Print details of working in MOLDAT
MOLSYM Print details of working in MOLSYM
MOPAC Use old MOPAC definition for 2nd and 3rd atoms
MOZYME Use the Localized Molecular Orbital method to speed up the SCF
MS=n In MECI, magnetic component of spin
MULLIK Print the Mulliken population analysis
N**2 In excited state COSMO calculations, set the value of N**2
NLLSQ Minimize gradients using NLLSQ
NOANCI Do not use analytical C.I. derivatives
NOGPU Do not use GPU acceleration
NOLOG Suppress log file trail, where possible
NOMM Do not use molecular mechanics correction to CONH bonds
NONET NONET state required
NONR Do not use Newton-Raphson method in EF
NOOPT, NOOPT-X Do not optimize the coordinates of all atoms of type X
NOREOR In symmetry work, use supplied orientation
NORESEQ Suppress the default re-sequencing of atoms to the PDB sequence
NOSWAP Do not allow atom swapping when GEO_REF is used
NOSYM Point-group symmetry set to C1
NOTHIEL Do not use Thiel’s FSTMIN technique
NOTXT Remove any text from atom symbols
NOXYZ Do not print Cartesian coordinates
NSPA=n Sets number of geometric segments in COSMO
NSURF Number of surfaces in an ESP calculation
OCTET Octet state required
OLDCAV In COSMO, use the old Solvent Accessible Surface calculation
OLDENS Read initial density matrix off disk
OLDFPC Use the old fundamental physical constants
OLDGEO Previous geometry to be used
OMIN=n.nn In TS, minimum allowed overlap of eigenvectors
OPEN(n1,n2) Open-shell UHF or RHF calculation requested
OPT, OPT-X Optimize the coordinates of all atoms of type X
P=n.nn An applied pressure of n.nn Newtons/m2 to be used
PDB Input geometry is in protein data bank format
PDB=(text) User defined chemical symbols in protein data base
PDBOUT Output geometry in pdb format
PECI C.I. involves paired excitations only
PI Resolve density matrix into σ, π, and δ components
pKa Print the pKa for ionizable hydrogen atoms attached to oxygen atoms
PL Monitor convergence of density matrix in ITER
PM3 Use the MNDO-PM3 Hamiltonian
PM6 Use the PM6 Hamiltonian
PM6-D3 Use the PM6 Hamiltonian with Grimme’s corrections for dispersion
PM6-DH+ Use the PM6 Hamiltonian with corrections for dispersion and hydrogen-bonding
PM6-DH2 Use the PM6 Hamiltonian with corrections for dispersion and hydrogen-bonding
PM6-DH2X Use PM6 with corrections for dispersion and hydrogen and halogen bonding
PM6-D3H4 Use PM6 with Řezáč and Hobza’s D3H4 correction
PM6-D3H4X Use PM6 with Brahmkshatriya, et al.’s D3H4X correction
PMEP Complete semiempirical MEP calculation
PM7 Use the PM7 Hamiltonian
PM7-TS Use the PM7-TS Hamiltonian (only for barrier heights)
PMEPR Complete semiempirical MEP in a plane to be defined
POINT=n Number of points in reaction path
POINT1=n Number of points in first direction in grid calculation
POINT2=n Number of points in second direction in grid calculation
POLAR Calculate first, second and third order polarizabilities
POTWRT In ESP, write out electrostatic potential to unit 21
POWSQ Print details of working in POWSQ
PRECISE Criteria to be increased by 100 times
PRESSURE Apply pressure or tension to a solid or polymer
PRNT=n Print details of geometry optimization in EF
PRTCHAR Print charges in ARC file
PRTINT Print interatomic distances
PRTMEP MEP contour data output to <filename>.mep
PRTXYZ Print Cartesian coordinates
PULAY Use Pulay’s converger to obtain a SCF
QMMM Incorporate environmental effects in the QM/MM approach
QPMEP Charges derived from Wang-Ford type AM1 MEP
QUARTET Quartet state required
QUINTET Quintet state required
RAPID In MOZYME geometry optimizations, only use atoms being optimized in the SCF
RECALC=n In EF, recalculate Hessian every n steps
RE-LOCAL, RE-LOCAL=n During and at end of MOZYME calculation, re-localize the LMOs
RELSCF Default SCF criterion multiplied by n
REORTHOG In MOZYME, re-orthogonalize LMO’s each 10 SCF calculations.
RESEQ Re-arrange the atoms to match the PDB convention
RESIDUES Label each atom in a polypeptide with the amino acid residue
RESTART Calculation restarted
RHF Use Restricted Hartree-Fock methods
RM1 Use the RM1 Hamiltonian
RMAX=n.nn In TS, maximum allowed ratio for energy change
RMIN=n.nn In TS, minimum allowed ratio for energy change
ROOT=n Root n to be optimized in a C.I. calculation
RSCAL In EF, scale p-RFO to trust radius
RSOLV=n.nn Effective radius of solvent in COSMO
SADDLE Optimize transition state
SCALE Scaling factor for van der waals distance in ESP
SCFCRT=n.nn Default SCF criterion replaced by the value supplied
SCINCR=n.nn Increment between layers in ESP
SEPTET Septet state required
SETPI In MOZYME, some π bonds are explicitly set by the user
SETUP Extra keywords to be read from setup file
SEXTET Sextet state required
SHIFT=n.nn a damping factor of n defined to start SCF
SHUT <file> Send a command to MOPAC to make a restart and density file, then stop.
SIGMA Minimize gradients using SIGMA
SINGLET Singlet state required
SITE=(text) Define ionization state of residues in proteins
SLOG=n.nn In BFGS optimization, use fixed step of length n .nn
SLOPE Multiplier used to scale MNDO charges
SMOOTH In a GRID calculation, remove artifacts caused by the order in which points are calculated
SNAP Increase precision of symmetry angles
SPARKLE Use sparkles instead of atoms with basis sets
SPIN Print final UHF spin matrix
START_RES(text) Define starting residue numbers in a protein, if different from the default
STATIC Calculate Polarizability using electric fields
STEP Step size in path
STEP1=n.nnn Step size n for first coordinate in grid calculation
STEP2=n.nnn Step size n for second coordinate in grid calculation
STO3G Deorthogonalize orbitals in STO-3G basis
SUPER Print superdelocalizabilities
SWAP This keyword is now obsolete, see NOSWAP
SYBYL Output a file for use by Tripos’s SYBYL program
SYMAVG Average symmetry equivalent ESP charges
SYMOIR Print characters of eigenvectors and print number of I.R.s
SYMTRZ Print details of working in subroutine SYMTRZ.
SYMMETRY Impose symmetry conditions
T=n[M,H,D] A time of n seconds requested
Perform a thermodynamics calculation
THREADS=n Set the number of threads to be used in parallelization to n
TIMES Print times of various stages
Time takes priority in DRC
The system is a transition state (used in thermodynamics calculation)
TRIPLET Triplet state required
TS Using EF routine for TS search
UHF Use the Unrestricted Hartree-Fock method
VDW(text) Van der waals radius for atoms in COSMO defined by user
VDWM(text) Van der waals radius for atoms in MOZYME defined by user
VECTORS Print final eigenvectors
VELOCITY Supply the initial velocity vector in a DRC calculation
WILLIAMS Use Williams surface
X-PRIORITY=n.nn Geometry changes take priority in DRC
XENO Allow non-standard residues in proteins to be labeled.
XYZ Do all geometric operations in Cartesian coordinates
Z=n Number of mers in a cluster

Besides facilitating building molecules, our GUI can also visualize the progress of geometry optimizations, MOPAC charges, and IR modes. Geometry optimization can also be done interactively, e.g. to pre-optimize your molecule or periodic system.

For COSMO-RS, DFTB, and ReaxFF, there is no separate pricing for the Graphical Interfaces, so it’s always included in the price and you can use these on all machines where the engine itself is licensed.

For ADF and BAND, a few experts still wish to use only the ADF (BAND) binaries, without the GUI. In that case, we can offer discounted prices (so prices remain the same for current users with a binary-only ADF or BAND license). Contact us for a price quote excluding GUI’s if desired.

Yes. For a bundle for x cores and y GUI copies, the license fee is 2 times the license for ADF on x cores with y copies of ADF-GUI. This bundle allows you to run ADF, BAND, DFTB, and ReaxFF on x cores. COSMO-RS calculations only run interactively through the GUI or the command line. The y copies of the integrated GUI are fully licensed for use with all modules. Academic users may also use MOPAC free of charge with the ADF modeling suite on all GUI-licensed machines. Ask us for a detailed price quote.

Not for a host-locked license. In such a case one should order an 8-core license, or select a 4-core machine to install ADF on.

You can start immediately. After we have received your informal purchase order confirmation, your signed license agreement, and your machine information, you will receive a temporary license until the invoice is paid.

In case of any type of license upgrade, we will only charge price differences and only for the remaining time period of the contract, thus making it easy and attractive to upgrade.

For multi-year licenses we can change the machine info once a year when we send a new license file for the next year. Certain exceptions are possible at SCM’s discretion.
You can of course always upgrade your license to include more CPUs.

Click on i next to Force field input in ReaxFF Input to see which force fields are included with ReaxFF. Alternatively, open $ADFHOME/atomicdata/ForceFields/ReaxFF/Readme, which also contains the original references and sometimes a short description. The list of currently available force field are available in the documentation.

You are strongly advised to check the original publications to see how the force field has been trained and to what type of systems it has been applied.

If no force field is available for your elements, check the literature or parametrize it yourself, see the other FAQs.

This is hard work, which takes quite a bit of training and experience. The ReaxFF parameters are typically trained against DFT data and parameters should be optimized for all atom types in your system. In principle, parameters are transferable across systems, but including additional atoms requires also to include new interactions with all new element combinations. This is not trivial.

The semi-automatic Metropolis Monte Carlo procedure by Iype et al. (J. Comp. Chem. 34, 1143) for ReaxFF parameter optimization, based on DFT calculations with ADF, is available in the ADF modeling suite 2014. Dr. Iype has a web presentation on how this works in practice. See also the hands-on 2-day workshop with an example on ReaxFF parameterization.

ReaxFF parameter optimization with genetic algorithms (Larsson et al., J. Comp. Chem. 34, 2178) is currently only possible if you recompile ADF/ReaxFF with the GA code from Prof. Hartke, but we are working on integrating this further into the ADF/ReaxFF code.

RxFF consulting offers consulting services for optimizing force field parameters for new materials.

In the GUI: build a ReaxFF input with these elements X, Y, and Z, and click on the folder icon next to Force field:. A list of force fields included in the ADF/ReaxFF distribution that contain these atom types will be shown. If force fields are available, consult the Readme (click ‘i’) to check the publication to make sure this is the force field for your application.

If no force field shows up in the list, no suitable force field is available in your distribution. Use google or web of knowledge to find out if a ReaxFF force field exists for your application. If it does, and the force field is printed in the supporting information, you can add the ReaxFF force field file (see FAQ) to the existing ones in the distribution.

Note that not all terms may be available for all element combinations. To get more insight in which force field terms are available, use the python ReaxFF force field checking tool: $ADFHOME/scripting/

You can find a description of the general structure of the force field file and the parameters from the original ReaxFF documentation.

We try to include as much information on the origin of parameters the ReaxFF manual as well as in the GUI help files.

Many published ReaxFF force fields are building upon a previous set of parameters, and so only the elements studied in that paper are being refined, and the other parameters are just kept in place. You could try to trace back the origin of some of these parameters by looking at the existing force fields and finding out where the same parameters for a particular element also appear. Any force field that has matching atomic parameters might have some information about the origins of the parameters in the corresponding publication or in the information in the force field description file.

However, you need to be careful by just combining and using elements / parameters from different force fields. See also the FAQ about ReaxFF parameter transferability. You should also be aware that certain bonded terms may not be available for a particular unpublished element and/or combination of elements, so you are strongly advised to check this with our ReaxFF force field checking tool: $ADFHOME/scripting/ The original ReaxFF documentation describes the general structure and correspondence of the columns with the parameters.

In general the parameters are quite transferable, but some forcefields were developed for specialized cases such as explosives research (high pressure). It is good practice to scan through the publication of the forcefield (you can find the information by clicking the “i” button behind the forcefield ) before using it extensively. It is also wise to do some testing simulations to see if your structures are not falling apart or folding into weird geometries.

This is most easily done from the GUI using the File → Export Trajectory As: option in ADFJobs. You can export as Gromacs, PDB trajectory, or xmol file. For the .gro export you will get an additional dialogue window where you can include the timestep and the velocities.

Alternatively, you can use the scripting tool adfreport, e.g. adfreport yourreaxff.rxkf -r gro-t0.00025 > yourreaxff.gro
The  options for adfreport in your ADF distribution are displayed if you type adfreport -h

During a non-reactive ReaxFF simulation the connection table is determined only once at the beginning of a simulation and is then kept fixed. Other than this the same ReaxFF procedure with the same forces and energy expressions is used. Therefore, if the system is far from equilibrium, or if the temperature is too high, bonds may still be broken or formed.

You can also think about simulating the system at zero Kelvin with a strong thermostat to try and get your system to the nearest local minimum without changing the bonds too much.

This depends on what parameters are available in the force field file. A ReaxFF force field consists of some generic parameters, a number of atomic parameters (1 set for every atom type), bond parameters (combination of 2 atom types), angle parameters (combination of 3 atom types), dihedral parameters (combination of 4 atom types) and possibly hydrogen bond parameters (see original ReaxFF documentation for more details).

If a force field has elements X, Y an Z it means that it contains atomic parameters for X, Y and Z. However, it does not necessarily contain all combinations of the bond/angle/dihedral parameters. For example, X-X, Y-Y, Z-Z, X-Y and X-Z might have bond parameters, but Y-Z could be left out. This means that Y and Z should not be used together in the simulation, as their interaction is not defined.

To get more insight in which terms are available in a ReaxFF force field, use the python ReaxFF force field checking tool: $ADFHOME/scripting/

ReaxFF consists of two parts: the program and the force field files:

– The ReaxFF program is an implementation of the ReaxFF forcefield equations (see the Required citations ReaxFF page for the original papers).
– The ReaxFF force field files contain the parameters needed by the force field equations when running your simulation, they consist of 5 or 6 parts (see original ReaxFF documentation for more details):
* generic parameters
* atom parameters (per element)
* atom pairs / bond parameters (combination of two elements)
* angle parameters (combination of three elements)
* dihedrals (combination of four elements)
* and sometimes hydrogen bonds (per element)

A ReaxFF force field is build using a training set (see other FAQs) and is usually targeted for a specific simulation and typically includes about 4 to 12 elements, as the number of parameters scales to the 4th power with the number of elements included. Because ReaxFF uses pair/angle/dihedral parameters, it is not possible to simply combine two forcefield files.

The ADF GUI can tell you if a force field is available for the elements in your simulation (see other FAQs), but it will not be able to tell if the force field is conditioned for your specific simulation type. For this you will have to check the publication of the force field (doi link is usually included in the Readme file or the first line of the force field file)

The ADF implementation of ReaxFF still takes the original format. If a publication has the parameters printed in the supporting information in native format, just copy that data and save it as a file, e.g. YourNewReaxFF.ff, in $ADFHOME/atomicdata/ForceFields/ReaxFF. Then you can start using that force field by selecting it in the GUI, by clicking other after you’ve clicked the folder icon next to Force field: in the input panel.

If the parameters are printed in tables in the manuscript, but not as a comprehensive SI file, you can still compile your own ReaxFF force field file from this data in the same original ReaxFF format.