Gary W. Kramer

UV Laser Micromachining of Polymers for Microfluidic Applications

We have recently begun to explore the use of UV laser ablation micromachining to construct microfluidic devices in polymers. This technique can create microchannels rapidly and modify the resulting polymer surface in a single step. By ablating under different atmospheres, it is possible to alter both the surface chemistries and physical surface morphologies of the microchannels. We have employed electroosmotic flow measurements, chemical mapping, and optical microscopy to characterize the microfluidic devices. In addition, we have studied the parameters affecting the ablation, such as the laser wavelength, laser fluence, laser firing repetition rate, and the material being ablated.

Need for and Metrological Approaches Towards Standardization of Fluorescence Measurements from the View of National Metrology Institutes

The need for standardization in fluorescence measurements to improve quality assurance and to meet regulatory demands is addressed from the viewpoint of National Metrology Institutes (NMIs). Classes of fluorescence standards are defined, including instrument calibration standards for the determination and correction of instrument bias, application-specific standards based on commonly used fluorescent labels, and instrument validation standards for periodic checks of instrument performance. The need for each class of standard is addressed and on-going efforts by NMIs and others are described. Several certified reference materials (CRMs) that have recently been developed by NMIs are highlighted. These include spectral correction standards, developed independently by both NIST and BAM (Germany), and fluorescence intensity standards for flow cytometry, developed by NIST. In addition, future activities at both institutes are addressed such as the development of day-to-day intensity standards.

Documenting Laboratory Workflows Using the Analytical Information Markup Language

The Analytical Information Markup Language (AnIML) is a standardization effort of ASTM (formerly American Society for Testing and Materials) Subcommittee E13.15 on Analytical Data. AnIML provides an XML-based format for analytical data. It is designed specifically for spectroscopy and chromatography data, but is suitable for use with many different analytical measurement techniques. AnIML consists of a generic core structure that permits the storage of arbitrary analytical data. These include multi-dimensional data, name-value pairs, and hierarchies. The concept of technique definitions permits the formal specification of constraints for usage of the core. This way, a definition can prescribe how the data for specific measurement techniques should be captured in the data file. To address changing requirements, AnIML supports an extension concept that allows vendors or end users to specify additional data that should be stored for a technique. These extensions can also be formally documented so that they do not break compatibility with existing software. This article presents an overview of AnIML and demonstrates how AnIML can be used to record data from everyday experimental workflows in a laboratoryenvironment. Issues related to the usage of AnIML in regulated environments are also discussed, including the use of digital signatures and audit trail functionality to ensure data integrity.

Spectro ML-A Markup Language for Molecular Spectrometry Data

SpectroML is a markup language for molecular spectrometry data that can be used as a “web-aware” mechanism for instrument-to-instrument, instrument-to-application, and application-to-application data interchange and archiving. SpectroML was developed using XML (extensible mark up language), and its vocabulary was gleaned from the terminology, data dictionaries, and concepts embodied in existing standards, instrument software, and data interchange formats. Currently, we have created a SpectroML vocabulary, document type definition, schema, stylesheets, and some demonstration applications for UV-visible spectroscopy data; however, the structure and flexible data model embodied in SpectroML should make it easily adaptable to other spectroscopy techniques.

Automated Generation of AnIML Documents by Analytical Instruments

The scope of this project covers the storing of result data produced by generic laboratory devices during processing of analytical experiments, the data describing the examination methods, and the audit trail using the Analytical Information Markup Language (AnIML) standard. This project also considers the integration of generic devices in automated laboratory environments. AnIML is an upcoming ASTM standard format for recording analytical data and workflows with accompanying experimental metadata. Adapting this standard to existing instruments currently requires manual intervention. The goal of this project is to automate as many steps as possible in generating an AnIML document with all its essential information supplied directly by the analytical instrument. Software with such functionality could be integrated into analytical instruments or reside in firmware boxes hooked to the instruments. This would allow a smooth transition to the new standard even in complex existing environments. A set of prerequisites have to be fulfilled before the feasibility of this approach can be shown. The prototype application we describe here integrates the generic description of an instrument using the Laboratory Equipment Control Interface Specification, Object Management Group (LECIS OMG) Device Capability Dataset. Information about the devices commands and the devices data stream with its semantics can be found there. The experiments metadata are provided by the test order. In both cases, XML schemas contain the information syntax. Using this information, we developed a generic interface that maps the result stream semantically and then transforms it into an AnIML document without manual intervention. At this time, we have completed and tested a prototype implementation and are working to support the full functionality of both the LECIS OMG and the ASTM AnIML standards. (JALA 2006;11:247–53)

Molecular Spectrometry Data Interchange Applications for NIST's SpectroML

SpectroML, a markup language for ultraviolet-visible spectroscopy data, has been developed as a “Web-aware” mechanism for instrument-to-instrument, instrument-to-application, and application-to-application data interchange and archiving. This article documents the application of SpectroML to the interchange and archiving of measurement data from three spectrophotometers that are used in the NIST optical filter standards program. It describes how result data from the NIST national reference spectrophotometer and two commercial spectrophotometers are converted into SpectroML format and how SpectroML-formatted data and metadata are imported into the optical filter standards database.

Improving Interoperability by Incorporating UnitsML Into Markup Languages

Maintaining the integrity of analytical data over time is a challenge. Years ago, data were recorded on paper that was pasted directly into a laboratory notebook. The digital age has made maintaining the integrity of data harder. Nowadays, digitized analytical data are often separated from information about how the sample was collected and prepared for analysis and how the data were acquired. The data are stored on digital media, while the related information about the data may be written in a paper notebook or stored separately in other digital files. Sometimes the connection between this “scientific meta-data” and the analytical data is lost, rendering the spectrum or chromatogram useless. We have been working with ASTM Subcommittee E13.15 on Analytical Data to create the Analytical Information Markup Language or AnIML—a new way to interchange and store spectroscopy and chromatography data based on XML (Extensible Markup Language). XML is a language for describing what data are by enclosing them in computer-useable tags. Recording the units associated with the analytical data and metadata is an essential issue for any data representation scheme that must be addressed by all domain-specific markup languages. As scientific markup languages proliferate, it is very desirable to have a single scheme for handling units to facilitate moving information between different data domains. At NIST, we have been developing a general markup language just for units that we call UnitsML. This presentation will describe how UnitsML is used and how it is being incorporated into AnIML.

An inexpensive video signal multiplexer for multicamera machine vision in automated analytical laboratory systems

A computer-controlled multiplexer that selects one of up to eight video signal sources is described. The unit is used in conjunction with inexpensive charge-coupled-device video cameras, a frame grabber and computer interface, and commercially available image analysis software to detect events in an automated laboratory setup. The image processing software and the event-driven multiplexer software run under the Windows 3.1 operating system. The configuration presented here is an inexpensive alternative to systems that require more than one frame grabber in combination with multiple cameras or that use commercially available multiplexing frame grabbers.

The System Capability Dataset for Laboratory Automation System Integration

A System Capability Dataset (SCD) is a tool for stylizing the way the unique characteristics and attributes of an automation environment are represented in a systematic, computer-usable fashion. Device Capability Datasets (DCDs) that describe the characteristics and behaviors of the constituent devices in a system are central components of an SCD. However, an SCD is more than just the sum of its DCDs, since the SCD must contain information about the logical and physical dependencies and relationships of the all devices and other components in the system. By stylizing the idiosyncratic characteristics of devices, the capability dataset approach permits the construction of standard integration interfaces and can eliminate custom programming for devices, facilitate integrating different types of devices, and enable centralized control and error handling for laboratory automation systems.

The Device Capability Dataset: A Descriptive Approach to Laboratory Automation System Integration Standards

A Device Capability Dataset (DCD) describes the idiosyncratic characteristics of laboratory equipment, such as the equipments identity, physical dimensions, location, supported command set, generated events, input-output (I/O) ports, and other resources. The DCD concept provides a means for standardizing the interfacing of laboratory automation devices in a descriptive rather than a prescriptive manner.