HORIBA Scientific is the world-leading manufacturer of high performance spectroscopic instrumentation and photonics components. Our products offer unsurpassed sensitivity, precision, performance, and capabilities.
HORIBA Scientific offerings encompass Raman, fluorescence, elemental analysis, forensics, GDS, ICP, particle characterization, spectroscopic ellipsometry, sulfur-in-oil, water quality, XRF, and OEM spectrometers. We also provide components, custom and OEM solutions, and worldwide support.
Our global team is dedicated to providing researchers with the highest quality products and solutions by integrating and aligning HORIBA's core strengths of scientific research, development, applications, sales, service, and support.
Prominent acquired brands include Jobin Yvon, IBH, SPEX, Instruments S.A., ISA, Dilor, Sofie, SLM, Beta Scientific, Photon Technology, Inc. (PTI), and Optical Building Blocks (OBB).
HORIBA Scientific is part of the HORIBA Group, with manufacturing facilities in Edison, New Jersey, as well as in France and Japan. Sales, service, and applications facilities are located around the world.
HORIBA Scientific
3880 Park Avenue
Edison, NJ 08820
TELEPHONE
(732) 494-8660
FAX
(732) 549-5125
E-MAILinfo.sci@horiba.com
WEB SITEwww.horiba.com/scientific
NUMBER OF EMPLOYEES
700
Elsewhere: 5000
YEAR FOUNDED
1819
Best of the Week: SciX Award Interviews, Tip-Enhanced Raman Scattering
June 13th 2025Top articles published this week include an interview about aromatic–metal interactions, a tutorial article about the recent advancements in tip-enhanced Raman spectroscopy (TERS), and a news article about using shortwave and near-infrared (SWIR/NIR) spectral imaging in cultural heritage applications.
Hyperspectral Imaging for Walnut Quality Assessment and Shelf-Life Classification
June 12th 2025Researchers from Hebei University and Hebei University of Engineering have developed a hyperspectral imaging method combined with data fusion and machine learning to accurately and non-destructively assess walnut quality and classify storage periods.