Anton Paar USA Inc
Company Description
Anton Paar develops, produces and distributes highly accurate laboratory instruments and process measuring systems, and provides custom-tailored automation and robotic solutions. It is the world leader in the measurement of density, concentration and CO2 and in the field of rheometry. Anton Paar GmbH is owned by the charitable Santner Foundation
Chief Chromatographic Techniques Supported
ICP-OES
- ICP-AES
- Flash Chromatography
- Ion Chromatography
- HPLC
- Prep HPLC
- GC–MS
- ICP-MS
Markets Served
Anton Paar is the world market leader in the field of density measurement, the determination of dissolved CO2 and the analysis of materials' deformation and flow behavior. Customers of Anton Paar include the biggest international soft drink producers, breweries, petroleum-, food-, chemical-, pharmaceutical companies , and many more. Anton Paar is committed to long-term partnerships with our customers and employees as well as responsibility towards society in general.
Major Products/Services
The Multiwave PRO and the Multiwave GO are the champions of microwave-assisted sample preparation and extraction. With a broad range of rotors and accessories that enable acid digestion, leaching, solvent extraction, oxygen combustion, evaporation, and drying, these systems are ready for the most demanding applications.
Facility
Anton Paar USA is headquartered in Ashland, VA, with over 36,000 square feet of office, laboratory, and light industrial space designed to support and serve our U.S. customers.
Anton Paar USA, Inc.
10215 Timber Ridge Drive
Virginia, Ashland, VA 23005
TELEPHONE
(804) 550-1051
FAX
(804) 550-1057
info.us@anton-paar.com|~info.us@anton-paar.com/
WEB SITE
www.anton-paar.com|~www.anton-paar.com/
NUMBER OF EMPLOYEES
US: 160
Elsewhere: 2400
YEAR FOUNDED
1922
AI and Dual-Sensor Spectroscopy Supercharge Antibiotic Fermentation
June 30th 2025Researchers from Chinese universities have developed an AI-powered platform that combines near-infrared (NIR) and Raman spectroscopy for real-time monitoring and control of antibiotic production, boosting efficiency by over 30%.
Toward a Generalizable Model of Diffuse Reflectance in Particulate Systems
June 30th 2025This tutorial examines the modeling of diffuse reflectance (DR) in complex particulate samples, such as powders and granular solids. Traditional theoretical frameworks like empirical absorbance, Kubelka-Munk, radiative transfer theory (RTT), and the Hapke model are presented in standard and matrix notation where applicable. Their advantages and limitations are highlighted, particularly for heterogeneous particle size distributions and real-world variations in the optical properties of particulate samples. Hybrid and emerging computational strategies, including Monte Carlo methods, full-wave numerical solvers, and machine learning (ML) models, are evaluated for their potential to produce more generalizable prediction models.
