the last 5 years, there has been a noticeable uptake in the use of Hybrid Photon
Counting (CMOS and HPAD) detectors. The latter trend clearly points to this type of
detector being the technology of choice for the coming years, and the discussion
above indicates the effect that this will have on data quality.
The average collection temperature over the all the structures reported in the CSD
has gone down approximately 15 K over the last 10 years from 204 K in 2009 to
189 K in 2018, although the range of temperatures has increased slightly as more
experiments are performed to investigate the behaviour of materials under extreme
conditions. The increased use of cooling technologies, particularly those using liquid
nitrogen [45] to reduce thermal motion and possibly freeze out disorder, has
undoubtedly played a role in this decrease.
1.2.3 The High-Throughput Process
The previous sections have considered hardware developments and illustrated their
ability to provide very rapid and accurate data collection. However, these advances
cannot be harnessed without development of the appropriate software to drive the
process, manage it and deal with the output. Furthermore, to enable true highthroughput or optimum efficiency, this must happen in real-time in relation to the
data collection process. Computing hardware can now be configured to process at
high speed, and very powerful software can be written relatively easily, so it is not
surprising that there have been software developments that are commensurate with
the hardware improvements. Both national facilities and instrument manufacturers
have dedicated teams to develop software to support and develop the experiment
process, and this now involves functions beyond those of simply interfacing with the
instrument and processing raw data. In this review we will focus only on those, more
recent, aspects of software development that support higher-throughput data collection and the efficient operation of a facility, which predominantly falls into the
categories of screening and automation.
Screening
As noted elsewhere in this article, the range of chemistry research being undertaken
very often provides significant challenges for crystallography. Accordingly, samples
can be poor in quality/crystallinity, and often it is not possible to recrystallise or
grow better crystals. National facilities are generally more powerful than those
available locally, so it is very common for them to be used to tackle the tougher
problems that cannot be handled at home. Therefore, these facilities have become
highly specialised to deal with this type of sample. The challenge with these samples
is often the selection of the best possible crystal that will afford the best possible
dataset, and so an efficient quality screening process is critical.
Due to the diversity of chemical samples, there has been little development of
automated crystal growth, selection and mounting mechanisms in the way that
Leading Edge Chemical Crystallography Service Provision and Its Impact on. . .
85
Counting (CMOS and HPAD) detectors. The latter trend clearly points to this type of
detector being the technology of choice for the coming years, and the discussion
above indicates the effect that this will have on data quality.
The average collection temperature over the all the structures reported in the CSD
has gone down approximately 15 K over the last 10 years from 204 K in 2009 to
189 K in 2018, although the range of temperatures has increased slightly as more
experiments are performed to investigate the behaviour of materials under extreme
conditions. The increased use of cooling technologies, particularly those using liquid
nitrogen [45] to reduce thermal motion and possibly freeze out disorder, has
undoubtedly played a role in this decrease.
1.2.3 The High-Throughput Process
The previous sections have considered hardware developments and illustrated their
ability to provide very rapid and accurate data collection. However, these advances
cannot be harnessed without development of the appropriate software to drive the
process, manage it and deal with the output. Furthermore, to enable true highthroughput or optimum efficiency, this must happen in real-time in relation to the
data collection process. Computing hardware can now be configured to process at
high speed, and very powerful software can be written relatively easily, so it is not
surprising that there have been software developments that are commensurate with
the hardware improvements. Both national facilities and instrument manufacturers
have dedicated teams to develop software to support and develop the experiment
process, and this now involves functions beyond those of simply interfacing with the
instrument and processing raw data. In this review we will focus only on those, more
recent, aspects of software development that support higher-throughput data collection and the efficient operation of a facility, which predominantly falls into the
categories of screening and automation.
Screening
As noted elsewhere in this article, the range of chemistry research being undertaken
very often provides significant challenges for crystallography. Accordingly, samples
can be poor in quality/crystallinity, and often it is not possible to recrystallise or
grow better crystals. National facilities are generally more powerful than those
available locally, so it is very common for them to be used to tackle the tougher
problems that cannot be handled at home. Therefore, these facilities have become
highly specialised to deal with this type of sample. The challenge with these samples
is often the selection of the best possible crystal that will afford the best possible
dataset, and so an efficient quality screening process is critical.
Due to the diversity of chemical samples, there has been little development of
automated crystal growth, selection and mounting mechanisms in the way that
Leading Edge Chemical Crystallography Service Provision and Its Impact on. . .
85