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diff --git a/CITATION.cff b/CITATION.cff
@@ -22,34 +22,83 @@
 cff-version: 1.2.0
 type: software
 message: "Please cite the following article when referencing Celeritas in a publication."
-title: "Celeritas: Accelerating Geant4 with GPUs"
-abstract: >-
-  Celeritas [1] is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Luminosity Large Hadron Collider (HL-LHC) simulation) on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a GPU-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.3, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling integration of Celeritas into high energy physics (HEP) experimental frameworks such as CMSSW. On the Summit supercomputer, Celeritas performs EM physics between 6× and 32× faster using the machine’s Nvidia GPUs compared to using only CPUs. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.8–2.3× on GPU and 1.2× on CPU.
+title: "Celeritas"
+type: software
+license:
+ - Apache-2.0
+ - MIT
+authors:
+  - family-names: Johnson
+    given-names: Seth R.
+    orcid: "https://orcid.org/0000-0003-1504-8966"
+  - family-names: Lund
+    given-names: Amanda
+    orcid: "https://orcid.org/0000-0002-8316-0709"
+  - family-names: Jun
+    given-names: Soon Yung
+    orcid: "https://orcid.org/0000-0003-3370-6109"
+  - family-names: Tognini
+    given-names: Stefano
+    orcid: "https://orcid.org/0000-0001-9741-6608"
+  - family-names: Lima
+    given-names: Guilherme
+    orcid: "https://orcid.org/0000-0003-4585-0546"
+  - family-names: Canal
+    given-names: Philippe
+    orcid: "https://orcid.org/0000-0002-7748-7887"
+  - family-names: Morgan
+    given-names: Ben
+  - family-names: Evans
+    given-names: Tom
+    orcid: "https://orcid.org/0000-0001-5743-3788"
+  - family-names: Esseiva
+    given-names: Julien
+date-released: 2022
+url: https://doi.org/10.11578/dc.20221011.1
+identifiers:
+  - type: doi
+    value: 10.11578/dc.20221011.1
+keywords:
+  - monte carlo
+  - particle transport
+  - high energy physics
+  - detector simulation
+  - computational physics
+  - hep
+  - cuda
+  - hip
 preferred-citation:
   authors:
     - family-names: Johnson
       given-names: Seth R.
       orcid: "https://orcid.org/0000-0003-1504-8966"
     - family-names: Lund
       given-names: Amanda
+      orcid: "https://orcid.org/0000-0002-8316-0709"
     - family-names: Canal
       given-names: Philippe
+      orcid: "https://orcid.org/0000-0002-7748-7887"
     - family-names: Tognini
       given-names: Stefano C.
+      orcid: "https://orcid.org/0000-0001-9741-6608"
     - family-names: Esseiva
       given-names: Julien
     - family-names: Jun
       given-names: Soon Yung
+      orcid: "https://orcid.org/0000-0003-3370-6109"
     - family-names: Lima
       given-names: Guilherme
+      orcid: "https://orcid.org/0000-0003-4585-0546"
     - family-names: Biondo
       given-names: Elliott
     - family-names: Evans
       given-names: Thomas
+      orcid: "https://orcid.org/0000-0001-5743-3788"
     - family-names: Demarteau
       given-names: Marcel
     - family-names: Romano
       given-names: Paul
+      orcid: "https://orcid.org/0000-0002-1147-045X"
   title: "Celeritas: Accelerating Geant4 with GPUs"
   type: article
   publisher: "EPJ Web of Conferences"
@@ -59,3 +108,5 @@ preferred-citation:
   identifiers:
     - type: doi
       value: 10.1051/epjconf/202429511005
+  abstract: >-
+    Celeritas is a new Monte Carlo (MC) detector simulation code designed for computationally intensive applications (specifically, High Luminosity Large Hadron Collider (HL-LHC) simulation) on high-performance heterogeneous architectures. In the past two years Celeritas has advanced from prototyping a GPU-based single physics model in infinite medium to implementing a full set of electromagnetic (EM) physics processes in complex geometries. The current release of Celeritas, version 0.3, has incorporated full device-based navigation, an event loop in the presence of magnetic fields, and detector hit scoring. New functionality incorporates a scheduler to offload electromagnetic physics to the GPU within a Geant4-driven simulation, enabling integration of Celeritas into high energy physics (HEP) experimental frameworks such as CMSSW. On the Summit supercomputer, Celeritas performs EM physics between 6× and 32× faster using the machine’s Nvidia GPUs compared to using only CPUs. When running a multithreaded Geant4 ATLAS test beam application with full hadronic physics, using Celeritas to accelerate the EM physics results in an overall simulation speedup of 1.8–2.3× on GPU and 1.2× on CPU.
diff --git a/README.md b/README.md
@@ -124,17 +124,20 @@ details on coding in Celeritas, and [the administration guidelines][administrati
 | **doc**       | Code documentation and manual                         |
 | **example**   | Example applications and input files                  |
 | **external**  | Automatically fetched external CMake dependencies     |
-| **interface** | Wrapper interfaces to Celeritas library functions     |
 | **scripts**   | Development and continuous integration helper scripts |
 | **src**       | Library source code                                   |
 | **test**      | Unit tests                                            |
 
 # Citing Celeritas
 
-If using Celeritas in your work, we ask that you cite the code using its
-[DOECode](https://www.osti.gov/doecode/biblio/94866) registration:
+If using Celeritas in your work, we ask that you cite the following article:
 
-> Seth R. Johnson, Amanda Lund, Soon Yung Jun, Stefano Tognini, Guilherme Lima, Paul Romano, Philippe Canal, Ben Morgan, and Tom Evans. “Celeritas,” July 2022. https://doi.org/10.11578/dc.20221011.1.
+> Johnson, Seth R., Amanda Lund, Philippe Canal, Stefano C. Tognini, Julien Esseiva, Soon Yung Jun, Guilherme Lima, et al. 2024. “Celeritas: Accelerating Geant4 with GPUs.” EPJ Web of Conferences 295:11005. https://doi.org/10.1051/epjconf/202429511005.
+
+See also its [DOECode](https://www.osti.gov/doecode/biblio/94866) registration:
+
+> Johnson, Seth R., Amanda Lund, Soon Yung Jun, Stefano Tognini, Guilherme Lima, Philippe Canal, Ben Morgan, Tom Evans, and Julien Esseiva. 2022. “Celeritas.” https://doi.org/10.11578/dc.20221011.1.
 
 A continually evolving list of works authored by (or with content authored by)
-core team members is available in our [citation file](doc/_static/celeritas.bib).
+core team members is continually updated at [our publications page](https://github.com/celeritas-project/celeritas/blob/doc/gh-pages-base/publications.md)
+and displayed on [the official project web site](https://celeritas.ornl.gov/).