diff --git a/src/polysolve/Utils.hpp b/src/polysolve/Utils.hpp
index fda3aa8..5f87f6c 100644
--- a/src/polysolve/Utils.hpp
+++ b/src/polysolve/Utils.hpp
@@ -61,48 +61,3 @@ namespace polysolve
     Eigen::SparseMatrix<double> sparse_identity(int rows, int cols);
 
 } // namespace polysolve
-
-namespace nlohmann
-{
-	template <typename T, int nrows, int ncols, int maxdim1, int maxdim2>
-	struct adl_serializer<Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2>>
-	{
-		static void to_json(json &j, const Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2> &matrix)
-		{
-			for (int row = 0; row < matrix.rows(); ++row)
-			{
-				json column = json::array();
-				for (int col = 0; col < matrix.cols(); ++col)
-				{
-					column.push_back(matrix(row, col));
-				}
-				j.push_back(column);
-			}
-		}
-
-		static void from_json(const json &j, Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2> &matrix)
-		{
-			using Scalar = typename Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2>::Scalar;
-			assert(j.size() > 0);
-			assert(nrows >= j.size() || nrows == -1);
-			assert(j.at(0).is_number() || ncols == -1 || ncols >= j.at(0).size());
-			
-			const int n_cols = j.at(0).is_number() ? 1 : j.at(0).size();
-			if (nrows == -1 || ncols == -1)
-				matrix.setZero(j.size(), n_cols);
-			
-			for (std::size_t row = 0; row < j.size(); ++row)
-			{
-				const auto& jrow = j.at(row);
-				if (jrow.is_number())
-					matrix(row) = jrow;
-				else
-					for (std::size_t col = 0; col < jrow.size(); ++col)
-					{
-						const auto& value = jrow.at(col);
-						matrix(row, col) = value.get<Scalar>();
-					}
-			}
-		}
-	};
-} // namespace nlohmann
\ No newline at end of file
diff --git a/src/polysolve/nonlinear/BoxConstraintSolver.cpp b/src/polysolve/nonlinear/BoxConstraintSolver.cpp
index d40c3f5..3dab2ac 100644
--- a/src/polysolve/nonlinear/BoxConstraintSolver.cpp
+++ b/src/polysolve/nonlinear/BoxConstraintSolver.cpp
@@ -7,6 +7,51 @@
 
 #include <fstream>
 
+namespace nlohmann
+{
+	template <typename T, int nrows, int ncols, int maxdim1, int maxdim2>
+	struct adl_serializer<Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2>>
+	{
+		static void to_json(json &j, const Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2> &matrix)
+		{
+			for (int row = 0; row < matrix.rows(); ++row)
+			{
+				json column = json::array();
+				for (int col = 0; col < matrix.cols(); ++col)
+				{
+					column.push_back(matrix(row, col));
+				}
+				j.push_back(column);
+			}
+		}
+
+		static void from_json(const json &j, Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2> &matrix)
+		{
+			using Scalar = typename Eigen::Matrix<T, nrows, ncols, Eigen::ColMajor, maxdim1, maxdim2>::Scalar;
+			assert(j.size() > 0);
+			assert(nrows >= j.size() || nrows == -1);
+			assert(j.at(0).is_number() || ncols == -1 || ncols >= j.at(0).size());
+			
+			const int n_cols = j.at(0).is_number() ? 1 : j.at(0).size();
+			if (nrows == -1 || ncols == -1)
+				matrix.setZero(j.size(), n_cols);
+			
+			for (std::size_t row = 0; row < j.size(); ++row)
+			{
+				const auto& jrow = j.at(row);
+				if (jrow.is_number())
+					matrix(row) = jrow;
+				else
+					for (std::size_t col = 0; col < jrow.size(); ++col)
+					{
+						const auto& value = jrow.at(col);
+						matrix(row, col) = value.get<Scalar>();
+					}
+			}
+		}
+	};
+} // namespace nlohmann
+
 namespace polysolve::nonlinear
 {