Topics

Advances in Neutron Facilities, Instrumentation and Software

Developments in sources, instrumentation, sample environments and control software.
  

Hard Condensed Matter

Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged.
  

Soft Matter

Neutron studies of soft materials and related fields including in situ and in operando studies.  Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged.
    

Biology, Biophysics and Biotechnology

Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged.
       

Materials Chemistry and Energy

Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics.
         

Structural Materials and Engineering

Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others.
          

Neutron Physics

 Fundamental physical studies of the neutron and related areas.
            

Emerging Applications in Neutron Scattering: Machine Learning and Data Science

Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.
              

General Submissions

If your work doesn't fit in one of the topical sessions described above, feel free to make a general submission and we will help direct it to the subsession most closely aligned with your work.